Ieee projects 2012 2013 - Parallal and Distributed Computing

Elysium Technologies Private Limited
Approved by ISO 9001:2008 and AICTE for SKP Training
Singapore | Madurai | Trichy | Coimbatore | Cochin | Kollam | Chennai
http://www.elysiumtechnologies.com, info@elysiumtechnologies.com

IEEE FINAL YEAR PROJECTS 2012 – 2013
Parallel and Distributed Computing
Corporate Office: Madurai
227-230, Church road, Anna nagar, Madurai – 625 020.
0452 – 4390702, 4392702, +9199447933980
Email: info@elysiumtechnologies.com, elysiumtechnologies@gmail.com
Website: www.elysiumtechnologies.com

Branch Office: Trichy
15, III Floor, SI Towers, Melapudur main road, Trichy – 620 001.
0431 – 4002234, +919790464324.
Email: trichy@elysiumtechnologies.com, elysium.trichy@gmail.com.

Branch Office: Coimbatore
577/4, DB Road, RS Puram, Opp to KFC, Coimbatore – 641 002.
+919677751577
Website: Elysiumtechnologies.com, Email: info@elysiumtechnologies.com

Branch Office: Kollam
Surya Complex, Vendor junction, Kollam – 691 010, Kerala.
0474 – 2723622, +919446505482.
Email: kerala@elysiumtechnologies.com.

Branch Office: Cochin
4th Floor, Anjali Complex, near south over bridge, Valanjambalam,
Cochin – 682 016, Kerala.
0484 – 6006002, +917736004002.

IEEE Final Year Projects 2012 |Student Projects | Parallel and Distributed Computing
Projects


Email: kerala@elysiumtechnologies.com, Website: www.elysiumtechnologies.com
PARALLEL AND DISTRIBUTED COMPUTING 2012 – 2013

EGC
A Cluster-on-a-Chip Architecture for High-Throughput Phylogeny Search
3201

In this paper, we describe an FPGA-based coprocessor architecture that performs a high-throughput branch-and-bound
search of the space of phylogenetic trees corresponding to the number of input taxa. Our coprocessor architecture is
designed to accelerate maximum-parsimony phylogeny reconstruction for gene-order and sequence data and is
amenable to both exhaustive and heuristic tree searches. Our architecture exposes coarse-grain parallelism by dividing
the search space among parallel processing elements (PEs) and each PE exposes fine-grain memory parallelism for
their lower-bound computation, the kernel computation performed by each PE. Inter-PE communication is performed
entirely on-chip. When using this coprocessor for maximum-parsimony reconstruction for gene-order data, our
coprocessor achieves a 40X improvement over software in search throughput, corresponding to a 14X end-to-end
application improvement when including all communication and systems overheads.

EGC A Framework for Routing Performance Analysis in Delay Tolerant Networks with
3202 Application to Non-Cooperative Networks

In this paper, we present a framework for analyzing routing performance in delay tolerant networks (DTNs). Differently
from previous work, our framework is aimed at characterizing the exact distribution of relevant performance metrics,
which is a substantial improvement over existing studies characterizing either the expected value of the metric, or an
asymptotic approximation of the actual distribution. In particular, the considered performance metrics are packet
delivery delay, and communication cost, expressed as number of copies of a packet circulating in the network at the
time of delivery. Our proposed framework is based on a characterization of the routing process as a stochastic coloring
process and can be applied to model performance of most stateless delay tolerant routing protocols, such as epidemic,
two-hops, and spray and wait. After introducing the framework, we present examples of its application to derive the
packet delivery delay and communication cost distribution of two such protocols, namely epidemic and two-hops
routing. Characterizing packet delivery delay and communication cost distribution is important to investigate
fundamental properties of delay tolerant networks. As an example, we show how packet delivery delay distribution can
be used to estimate how epidemic routing performance changes in presence of different degrees of node cooperation
within the network. More specifically, we consider fully cooperative, noncooperative, and probabilistic cooperative
scenarios, and derive nearly exact expressions of the packet delivery rate (PDR) under these scenarios based on our
proposed framework. The comparison of the obtained packet delivery rate estimation in the various cooperation
scenarios suggests that even a modest level of node cooperation (probabilistic cooperation with a low probability of
cooperation) is sufficient to achieve 2-fold performance improvement with respect to the most pessimistic scenario in
which all potential forwarders dr- - op packets.

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EGC
A Game-Theoretic Approach to the Formation of Clustered Overlay Networks
3203

In many large-scale content sharing applications, participants or nodes are connected with each other based on their
content or interests, thus forming clusters. In this paper, we model the formation of such clustered overlays as a
strategic game, where nodes determine their cluster membership with the goal of improving the recall of their queries.
We study the evolution of such overlays both theoretically and experimentally in terms of stability, optimality, load
balance, and the required overhead. We show that, in general, decisions made independently by each node using only
local information lead to overall cost-effective cluster configurations that are also dynamically adaptable to system
updates such as churn and query or content changes.

EGC A Novel Parallel Scan for Multicore Processors and Its Application in Sparse Matrix-
3204
Vector Multiplication

We present a novel parallel algorithm for computing the scan operations on x86 multicore processors. The existing best
known parallel scan for the same platform requires the number of processors to be a power of two. But this constraint is
removed from our proposed method. In the design of the algorithm architectural considerations for x86 multicore
processors are given so that the rate of cache misses is reduced and the cost of thread synchronization and
management is minimized. Results from tests made on a machine with dual-socket times quad-core Intel Xeon E5405
showed that the proposed solution outperformed the best known parallel reference. A novel approach to sparse matrix-
vector multiplication (SpMV) based on the proposed scan is then explained. The approach, unlike the existing ones that
make use of backward segmented operations, uses forward ones for more efficient caching. An implementation of the
proposed SpMV was tested against the SpMV in Intel's Math Kernel Library (MKL) and merits were found in the proposed
approach.

EGC A QoS Oriented Vertical Handoff Scheme for WiMAX/WLAN Overlay Networks
3205

Recently, a number of wireless communication technologies are migrating toward heterogeneous overlay networks. The
integration of Mobile WiMAX and WLAN seems to be a promising approach due to their homogeneous nature and
complementary characteristics. In this paper, we investigate several important issues for the interworking of Mobile
WiMAX and WLAN networks. We address a tightly coupled interworking architecture. Further, a seamless and proactive
vertical handoff scheme is designed based on the architecture with aims to provide always the best quality of service
(QoS) for users. Both the performance of applications and network conditions are considered in the handoff process.
Moreover, we derive evaluation algorithms to estimate the conditions of both WiMAX and WLAN networks in terms of
available bandwidth and packet delay. A simulation study has demonstrated that the proposed schemes can keep
stations always being best connected.

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EGC A Rendezvous-Based Approach Enabling Energy-Efficient Sensory Data Collection with
3206 Mobile Sinks

A large class of Wireless Sensor Networks (WSN) applications involves a set of isolated urban areas (e.g., urban parks
or building blocks) covered by sensor nodes (SNs) monitoring environmental parameters. Mobile sinks (MSs) mounted
upon urban vehicles with fixed trajectories (e.g., buses) provide the ideal infrastructure to effectively retrieve sensory
data from such isolated WSN fields. Existing approaches involve either single-hop transfer of data from SNs that lie
within the MS's range or heavy involvement of network periphery nodes in data retrieval, processing, buffering, and
delivering tasks. These nodes run the risk of rapid energy exhaustion resulting in loss of network connectivity and
decreased network lifetime. Our proposed protocol aims at minimizing the overall network overhead and energy
expenditure associated with the multihop data retrieval process while also ensuring balanced energy consumption
among SNs and prolonged network lifetime. This is achieved through building cluster structures consisted of member
nodes that route their measured data to their assigned cluster head (CH). CHs perform data filtering upon raw data
exploiting potential spatial-temporal data redundancy and forward the filtered information to appropriate end nodes with
sufficient residual energy, located in proximity to the MS's trajectory. Simulation results confirm the effectiveness of our
approach against as well as its performance gain over alternative methods.

EGC A Sequentially Consistent Multiprocessor Architecture for Out-of-Order Retirement of Instructions
3207

Out-of-order retirement of instructions has been shown to be an effective technique to increase the number of in-flight
instructions. This form of runtime scheduling can reduce pipeline stalls caused by head-of-line blocking effects in the
reorder buffer (ROB). Expanding the width of the instruction window can be highly beneficial to multiprocessors that
implement a strict memory model, especially when both loads and stores encounter long latencies due to cache misses,
and whose stalls must be overlapped with instruction execution to overcome the memory latencies. Based on the
Validation Buffer (VB) architecture (a previously proposed out-of-order retirement, checkpoint-free architecture for
single processors), this paper proposes a cost-effective, scalable, out-of-order retirement multiprocessor, capable of
enforcing sequential consistency without impacting the design of the memory hierarchy or interconnect. Our simulation
results indicate that utilizing a VB can speed up both relaxed and sequentially consistent in-order retirement in future
multiprocessor systems by between 3 and 20 percent, depending on the ROB
size.

EGC
A Survey and Evaluation of Topology-Agnostic Deterministic Routing Algorithms
3208

Most standard cluster interconnect technologies are flexible with respect to network topology. This has spawned a
substantial amount of research on topology-agnostic routing algorithms, which make no assumption about the network
structure, thus providing the flexibility needed to route on irregular networks. Actually, such an irregularity should be

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often interpreted as minor modifications of some regular interconnection pattern, such as those induced by faults. In
fact, topology-agnostic routing algorithms are also becoming increasingly useful for networks on chip (NoCs), where
faults may make the preferred 2D mesh topology irregular. Existing topology-agnostic routing algorithms were
developed for varying purposes, giving them different and not always comparable properties. Details are scattered
among many papers, each with distinct conditions, making comparison difficult. This paper presents a comprehensive
overview of the known topology-agnostic routing algorithms. We classify these algorithms by their most important
properties, and evaluate them consistently. This provides significant insight into the algorithms and their
appropriateness for different on- and off-chip environments.

EGC
3209
A Survey of Parallel Programming Models and Tools in the Multi and Many-Core Era

In this work, we present a survey of the different parallel programming models and tools available today with special
consideration to their suitability for high-performance computing. Thus, we review the shared and distributed memory
approaches, as well as the current heterogeneous parallel programming model. In addition, we analyze how the
partitioned global address space (PGAS) and hybrid parallel programming models are used to combine the advantages
of shared and distributed memory systems. The work is completed by considering languages with specific parallel
support and the distributed programming paradigm. In all cases, we present characteristics, strengths, and weaknesses.
The study shows that the availability of multi-core CPUs has given new impulse to the shared memory parallel
programming approach. In addition, we find that hybrid parallel programming is the current way of harnessing the
capabilities of computer clusters with multi-core nodes. On the other hand, heterogeneous programming is found to be
an increasingly popular paradigm, as a consequence of the availability of multi-core CPUs+GPUs systems. The use of
open industry standards like OpenMP, MPI, or OpenCL, as opposed to proprietary solutions, seems to be the way to
uniformize and extend the use of parallel programming models.

EGC
A Systematic Approach toward Automated Performance Analysis and Tuning
3210

High productivity is critical in harnessing the power of high-performance computing systems to solve science and
engineering problems. It is a challenge to bridge the gap between the hardware complexity and the software limitations.
Despite significant progress in programming language, compiler, and performance tools, tuning an application remains
largely a manual task, and is done mostly by experts. In this paper, we propose a systematic approach toward
automated performance analysis and tuning that we expect to improve the productivity of performance debugging
significantly. Our approach seeks to build a framework that facilitates the combination of expert knowledge, compiler
techniques, and performance research for performance diagnosis and solution discovery. With our framework, once a
diagnosis and tuning strategy has been developed, it can be stored in an open and extensible database and thus be
reused in the future. We demonstrate the effectiveness of our approach through the automated performance analysis
and tuning of two scientific applications. We show that the tuning process is highly automated, and the performance
improvement is significant.

Projects


EGC
A Transport-Friendly NIC for Multicore/Multiprocessor Systems
3211

Receive side scaling (RSS) is an NIC technology that provides the benefits of parallel receive processing in
multiprocessing environments. However, RSS lacks a critical data steering mechanism that would automatically steer
incoming network data to the same core on which its application thread resides. This absence causes inefficient cache
usage if an application thread is not running on the core on which RSS has scheduled the received traffic to be
processed and results in degraded performance. To remedy the RSS limitation, Intel's Ethernet Flow Director technology
has been introduced. However, our analysis shows that Flow Director can cause significant packet reordering. Packet
reordering causes various negative impacts in high-speed networks. We propose an NIC data steering mechanism to
remedy the RSS and Flow Director limitations. This data steering mechanism is mainly targeted at TCP. We term an NIC
with such a data steering mechanism “A Transport-Friendly NIC” (A-TFN). Experimental results have proven the
effectiveness of A-TFN in accelerating TCP/IP performance.

EGC A Two-Dimensional Low-Diameter Scalable On-Chip Network for Interconnecting Thousands of
3212 Cores

This paper introduces the Spidergon-Donut (SD) on-chip interconnection network for interconnecting 1,000 cores in
future MPSoCs and CMPs. Unlike the Spidergon network, the SD network which extends the Spidergon network into the
second dimension, significantly reduces the network diameter, well below the popular 2D Mesh and Torus networks for
one extra node degree and roughly 25 percent more links. A detailed construction of the SD network and a method to
reshuffle the SD network's nodes for layout onto the 2D plane, and simple one-to-one and broadcast routing algorithms
for the SD network are presented. The various configurations of the SD network are analyzed and compared including
detailed area and delay studies. To interconnect a thousand cores, the paper concludes that a hybrid version of the SD
network with smaller SD instances interconnected by a crossbar is a feasible low-diameter network topology for
interconnecting the cores of a thousand core system.

EGC Accelerating Matrix Operations with Improved Deeply Pipelined Vector Reduction
3213

Many scientific or engineering applications involve matrix operations, in which reduction of vectors is a common
operation. If the core operator of the reduction is deeply pipelined, which is usually the case, dependencies between the
input data elements cause data hazards. To tackle this problem, we propose a new reduction method with low latency
and high pipeline utilization. The performance of the proposed design is evaluated for both single data set and multiple
data set scenarios. Further, QR decomposition is used to demonstrate how the proposed method can accelerate its
execution. We implement the design on an FPGA and compare its results to other
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methods.

EGC Adaptive Forwarding Delay Control for VANET Data Aggregation
3214

In-network data aggregation is a useful technique to reduce redundant data and to improve communication efficiency.
Traditional data aggregation schemes for wireless sensor networks usually rely on a fixed routing structure to ensure
data can be aggregated at certain sensor nodes. However, they cannot be applied in highly mobile vehicular
environments. In this paper, we propose an adaptive forwarding delay control scheme, namely Catch-Up, which
dynamically changes the forwarding speed of nearby reports so that they have a better chance to meet each other and
be aggregated together. The Catch-Up scheme is designed based on a distributed learning algorithm. Each vehicle
learns from local observations and chooses a delay based on learning results. The simulation results demonstrate that
our scheme can efficiently reduce the number of redundant reports and achieve a good trade-off between delay and
communication overhead.

EGC
3215
Aho-Corasick String Matching on Shared -Memory Parallel Architectures

String matching requires a combination of (sometimes all) the following characteristics: high and/or predictable
performance, support for large data sets and flexibility of integration and customization. This paper compares several
software-based implementations of the Aho-Corasick algorithm for high-performance systems. We focus on the
matching of unknown inputs streamed from a single source, typical of security applications and difficult to manage
since the input cannot be preprocessed to obtain locality. We consider shared-memory architectures (Niagara 2, x86
multiprocessors, and Cray XMT) and distributed-memory architectures with homogeneous (InfiniBand cluster of x86
multicores) or heterogeneous processing elements (InfiniBand cluster of x86 multicores with NVIDIA Tesla C1060
GPUs). We describe how each solution achieves the objectives of supporting large dictionaries, sustaining high
performance, and enabling customization and flexibility using various data sets.

EGC
3216
An Efficient Adaptive Deadlock-Free Routing Algorithm for Torus Networks

A deadlock-free minimal routing algorithm called clue is first proposed for VCT (virtual cut-through)-switched tori. Only
two virtual channels are required. One channel is applied in the deadlock-free routing algorithm for the mesh
subnetwork based on a known base routing scheme, such as, negative-first or dimension-order routing. The other
channel is similar to an adaptive channel. This combination presents a novel fully adaptive minimal routing scheme
because the first channel does not supply routing paths for every source-destination pair. Other two algorithms named
flow controlled clue and wormhole clue are proposed. Flow controlled clue is proposed for VCT-switched tori, which is
fully adaptive minimal deadlock-free with no virtual channel. Each input port requires at least two buffers, each of which

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is able to keep a packet. A simple but well-designed flow control function is used in the proposed flow controlled clue
routing algorithm to avoid deadlocks. Wormhole clue is proposed for wormhole-switched tori. It is partially adaptive
because we add some constraints to the adaptive channels for deadlock avoidance. It is shown that clue and flow
controlled clue work better than the bubble flow control scheme under several popular traffic patterns in 3-dimensional
(3D) torus. In a wormhole-switched tori, the advantage of wormhole clue over Duato's protocol is also very
apparent.

EGC
An Efficient Approach for Mobile Asset Tracking Using Contexts
3217

Due to the heterogeneity involved in smart interconnected devices, cellular applications, and surrounding (GPS-aware)
environments there is a need to develop a realistic approach to track mobile assets. Current tracking systems are costly
and inefficient over wireless data transmission systems where cost is based on the rate of data being sent. Our aim is to
develop an efficient and improved geographical asset tracking solution and conserve valuable mobile resources by
dynamically adapting the tracking scheme by means of context-aware personalized route learning techniques. We intend
to perform this tracking by proactively monitoring the context information in a distributed, efficient, and scalable
fashion. Context profiles, which indicate the characteristics of a route based on environmental conditions, are utilized to
dynamically represent the values of the asset's properties. We designed and implemented an adaptive learning based
scheme that makes an optimized judgment of data transmission. This manuscript is complemented with theoretical and
practical evaluations that prove that significant costs can be saved and operational efficiency can be achieved.

EGC
EGC An Efficient Prediction-Based Routing in Disruption-Tolerant Networks
3218
3218

Routing is one of the most challenging, open problems in disruption-tolerant networks (DTNs) because of the short-lived
wireless connectivity environment. To deal with this issue, researchers have investigated routing based on the
prediction of future contacts, taking advantage of nodes' mobility history. However, most of the previous work focused
on the prediction of whether two nodes would have a contact, without considering the time of the contact. This paper
proposes predict and relay (PER), an efficient routing algorithm for DTNs, where nodes determine the probability
distribution of future contact times and choose a proper next-hop in order to improve the end-to-end delivery
probability. The algorithm is based on two observations: one is that nodes usually move around a set of well-visited
landmark points instead of moving randomly; the other is that node mobility behavior is semi-deterministic and could be
predicted once there is sufficient mobility history information. Specifically, our approach employs a time-homogeneous
semi-Markov process model that describes node mobility as transitions between landmarks. Then, we extend it to
handle the scenario where we consider the transition time between two landmarks. A simulation study shows that this
approach improves the delivery ratio and also reduces the delivery latency compared to traditional DTN routing
schemes.

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EGC
An Intelligent Task Allocation Scheme for Multihop Wireless Networks
3219

Emerging applications in Multihop Wireless Networks (MHWNs) require considerable processing power which often may
be beyond the capability of individual nodes. Parallel processing provides a promising solution, which partitions a
program into multiple small tasks and executes each task concurrently on independent nodes. However, multihop
wireless communication is inevitable in such networks and it could have an adverse effect on distributed processing. In
this paper, an adaptive intelligent task mapping together with a scheduling scheme based on a genetic algorithm is
proposed to provide real-time guarantees. This solution enables efficient parallel processing in a way that only possible
node collaborations with cost-effective communications are considered. Furthermore, in order to alleviate the power
scarcity of MHWN, a hybrid fitness function is derived and embedded in the algorithm to extend the overall network
lifetime via workload balancing among the collaborative nodes, while still ensuring the arbitrary application deadlines.
Simulation results show significant performance improvement in various testing environments over existing
mechanisms.

EGC
An MDP-Based Dynamic Optimization Methodology for Wireless Sensor Networks
3220

Wireless sensor networks (WSNs) are distributed systems that have proliferated across diverse application domains
(e.g., security/defense, health care, etc.). One commonality across all WSN domains is the need to meet application
requirements (i.e., lifetime, responsiveness, etc.) through domain specific sensor node design. Techniques such as
sensor node parameter tuning enable WSN designers to specialize tunable parameters (i.e., processor voltage and
frequency, sensing frequency, etc.) to meet these application requirements. However, given WSN domain diversity,
varying environmental situations (stimuli), and sensor node complexity, sensor node parameter tuning is a very
challenging task. In this paper, we propose an automated Markov Decision Process (MDP)-based methodology to
prescribe optimal sensor node operation (selection of values for tunable parameters such as processor voltage,
processor frequency, and sensing frequency) to meet application requirements and adapt to changing environmental
stimuli. Numerical results confirm the optimality of our proposed methodology and reveal that our methodology more
closely meets application requirements compared to other feasible policies.

EGC
3221
Analysis of Impact of TXOP Allocation on IEEE 802.11e EDCA under Variable Network Load

In this paper, we investigate the impact of transmission opportunity (TXOP), arbitration interframe space (AIFS), and
contention window on the performance of an IEEE 802.11e cluster with four traffic classes under Poisson frame arrivals.
We derive an analytical model of the cluster using queuing model of individual nodes, discrete time Markov chain, and
probabilistic modeling of the backoff process. The analytical model demonstrates the complex interaction between

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TXOP, on one side, and AIFS and contention window, on the other. We derive saturation and stability points for all traffic
classes and discuss their dependency on TXOP allocations. Our results indicate that use of nonzero TXOP parameter
under Poisson frame arrivals improves performance slightly by separating points of saturation and instability. More
substantial performance improvements should be expected by deploying TXOP differentiation under bursty traffic. Since
all traffic classes need to operate in stable, nonsaturated regime, this work has important implications for the design of
congestion control and admission control schemes in IEEE 802.11e clusters.

EGC
3222
ASM: Adaptive Voice Stream Multicast over Low-Power Wireless Networks

Low-power Wireless Networks (LWNs) have become increasingly available for mission-critical applications such as
security surveillance and disaster response. In particular, emerging low-power wireless audio platforms provide an
economical solution for ad hoc voice communication in emergency scenarios. In this paper, we develop a system called
Adaptive Stream Multicast (ASM) for voice communication over multihop LWNs. ASM is composed of several novel
components specially designed to deliver robust voice quality for multiple sinks in dynamic environments: 1) an
empirical model to automatically evaluate the voice quality perceived at sinks based on current network condition; 2) a
feedback-based Forward Error Correction (FEC) scheme where the source can adapt its coding redundancy ratio
dynamically in response to the voice quality variation at sinks; 3) a Tree-based Opportunistic Routing (TOR) protocol
that fully exploits the broadcast opportunities on a tree based on novel forwarder selection and coordination rules; and
4) a distributed admission control algorithm that ensures the voice quality guarantees when admitting new voice
streams. ASM has been implemented on a low-power hardware platform and extensively evaluated through experiments
on a test bed of 18 nodes. The experiment results show that ASM can achieve satisfactory multicast voice quality in
dynamic environments while incurring low-communication overhead.

EGC
Asymmetric Event-Driven Node Localization in Wireless Sensor Networks
3223

Localization of wireless sensor nodes has long been regarded as a problem that is difficult to solve, especially when
considering characteristics of real-world environments. This paper formally describes, designs, implements, and
evaluates a novel localization system called Spotlight. The system uses spatiotemporal properties of well-controlled
events in the network, light in this case, to obtain locations of sensor nodes. Performance of the system is evaluated
through deployments of Mica2 and XSM motes in an outdoor environment, where 20 cm localization error is achieved. A
2
sensor network consisting of any number of nodes deployed in a 2,500 m area can be localized in under 10 minutes.
Submeter localization error in an outdoor environment is made possible without equipping the wireless sensor nodes
with specialized ranging hardware.

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EGC
3224
Autonomic Placement of Mixed Batch and Transactional Workloads

To reduce the cost of infrastructure and electrical energy, enterprise datacenters consolidate workloads on the same
physical hardware. Often, these workloads comprise both transactional and long-running analytic computations. Such
consolidation brings new performance management challenges due to the intrinsically different nature of a
heterogeneous set of mixed workloads, ranging from scientific simulations to multitier transactional applications. The
fact that such different workloads have different natures imposes the need for new scheduling mechanisms to manage
collocated heterogeneous sets of applications, such as running a web application and a batch job on the same physical
server, with differentiated performance goals. In this paper, we present a technique that enables existing middleware to
fairly manage mixed workloads: long running jobs and transactional applications. Our technique permits collocation of
the workload types on the same physical hardware, and leverages virtualization control mechanisms to perform online
system reconfiguration. In our experiments, including simulations as well as a prototype system built on top of state-of-
the-art commercial middleware, we demonstrate that our technique maximizes mixed workload performance while
providing service differentiation based on high-level performance goals.

EGC
3225
Balancing Performance and Cost in CMP Interconnection Networks

This paper presents an innovative router design, called Rotary Router, which successfully addresses CMP
cost/performance constraints. The router structure is based on two independent rings, which force packets to circulate
either clockwise or counterclockwise, traveling through every port of the router. These two rings constitute a completely
decentralized arbitration scheme that enables a simple, but efficient way to connect every input port to every output
port. The proposed router is able to avoid network deadlock, livelock, and starvation without requiring data-path
modifications. The organization of the router permits the inclusion of throughput enhancement techniques without
significantly penalizing the implementation cost. In particular, the router performs adaptive routing, eliminates HOL
blocking, and carries out implicit congestion control using simple arbitration and buffering strategies. Additionally, the
proposal is capable of avoiding end-to-end deadlock at coherence protocol level with no physical or virtual resource
replication, while guaranteeing in-order packet delivery. This facilitates router management and improves storage
utilization. Using a comprehensive evaluation framework that includes full-system simulation and hardware description,
the proposal is compared with two representative router counterparts. The results obtained demonstrate the Rotary
Router's substantial performance and efficiency advantages.

EGC
3226
Balancing the Trade-Offs between Query Delay and Data Availability in MANETs

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In mobile ad hoc networks (MANETs), nodes move freely and link/node failures are common, which leads to frequent
network partitions. When a network partition occurs, mobile nodes in one partition are not able to access data hosted by
nodes in other partitions, and hence significantly degrade the performance of data access. To deal with this problem, we
apply data replication techniques. Existing data replication solutions in both wired or wireless networks aim at either
reducing the query delay or improving the data availability, but not both. As both metrics are important for mobile
nodes, we propose schemes to balance the trade-offs between data availability and query delay under different system
settings and requirements. Extensive simulation results show that the proposed schemes can achieve a balance
between these two metrics and provide satisfying system performance.

EGC BECAN: A Bandwidth-Efficient Cooperative Authentication Scheme for Filtering Injected False
3227 Data in Wireless Sensor Networks

Injecting false data attack is a well known serious threat to wireless sensor network, for which an adversary reports
bogus information to sink causing error decision at upper level and energy waste in en-route nodes. In this paper, we
propose a novel bandwidth-efficient cooperative authentication (BECAN) scheme for filtering injected false data. Based
on the random graph characteristics of sensor node deployment and the cooperative bit-compressed authentication
technique, the proposed BECAN scheme can save energy by early detecting and filtering the majority of injected false
data with minor extra overheads at the en-route nodes. In addition, only a very small fraction of injected false data needs
to be checked by the sink, which thus largely reduces the burden of the sink. Both theoretical and simulation results are
given to demonstrate the effectiveness of the proposed scheme in terms of high filtering probability and energy saving.

EGC
3228
BEES: Bio inspired backbone Selection in Wireless Sensor Networks

Sensor networks have their own distinguishing characteristics that set them apart from other types of networks. Several
techniques have been proposed in the literature to address some of the fundamental problems faced by a sensor
network design. Most of the proposed techniques attempt to solve one problem in isolation from the others; hence,
protocol designers have to face the same common challenges again and again. This, in turn, has a direct impact on the
complexity of the protocols and on energy consumption. Instead of using this approach, we propose BEES, a
lightweight bioinspired backbone construction protocol, that can help mitigate many of the typical challenges in sensor
networks by allowing the development of simpler network protocols. We show how BEES can help mitigate many of the
typical challenges inherent to sensor networks including sensor localization, clustering, and data aggregation among
others.

EGC BloomCast: Efficient and Effective Full-Text Retrieval in Unstructured P2P Networks
3229

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Efficient and effective full-text retrieval in unstructured peer-to-peer networks remains a challenge in the research
community. First, it is difficult, if not impossible, for unstructured P2P systems to effectively locate items with
guaranteed recall. Second, existing schemes to improve search success rate often rely on replicating a large number of
item replicas across the wide area network, incurring a large amount of communication and storage costs. In this paper,
we propose BloomCast, an efficient and effective full-text retrieval scheme, in unstructured P2P networks. By leveraging
a hybrid P2P protocol, BloomCast replicates the items uniformly at random across the P2P networks, achieving a
guaranteed recall at a communication cost of O(√N), where N is the size of the network. Furthermore, by casting Bloom
Filters instead of the raw documents across the network, BloomCast significantly reduces the communication and
storage costs for replication. We demonstrate the power of BloomCast design through both mathematical proof and
comprehensive simulations based on the query logs from a major commercial search engine and NIST TREC WT10G
data collection. Results show that BloomCast achieves an average query recall of 91 percent, which outperforms the
existing WP algorithm by 18 percent, while BloomCast greatly reduces the search latency for query processing by 57
percent.

EGC Bounding the Impact of Unbounded Attacks in Stabilization
3230

Self-stabilization is a versatile approach to fault-tolerance since it permits a distributed system to recover from any
transient fault that arbitrarily corrupts the contents of all memories in the system. Byzantine tolerance is an attractive
feature of distributed systems that permit to cope with arbitrary malicious behaviors. Combining these two properties
proved difficult: it is impossible to contain the spatial impact of Byzantine nodes in a self-stabilizing context for global
tasks such as tree orientation and tree construction. We present and illustrate a new concept of Byzantine containment
in stabilization. Our property, called Strong Stabilization enables to contain the impact of Byzantine nodes if they
actually perform too many Byzantine actions. We derive impossibility results for strong stabilization and present
strongly stabilizing protocols for tree orientation and tree construction that are optimal with respect to the number of
Byzantine nodes that can be tolerated in a self-stabilizing context.

EGC Capacity of Data Collection in Arbitrary Wireless Sensor Networks
3231

Data collection is a fundamental function provided by wireless sensor networks. How to efficiently collect sensing data
from all sensor nodes is critical to the performance of sensor networks. In this paper, we aim to understand the
theoretical limits of data collection in a TDMA-based sensor network in terms of possible and achievable maximum
capacity. Previously, the study of data collection capacity has concentrated on large-scale random networks. However,
in most of the practical sensor applications, the sensor network is not uniformly deployed and the number of sensors
may not be as huge as in theory. Therefore, it is necessary to study the capacity of data collection in an arbitrary
network. In this paper, we first derive the upper and lower bounds for data collection capacity in arbitrary networks

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under protocol interference and disk graph models. We show that a simple BFS tree-based method can lead to order-
optimal performance for any arbitrary sensor networks. We then study the capacity bounds of data collection under a
general graph model, where two nearby nodes may be unable to communicate due to barriers or path fading, and
discuss performance implications. Finally, we provide discussions on the design of data collection under a physical
interference model or a Gaussian channel model.

EGC
3232
Cashing in on the Cache in the Cloud

Over the past decades, caching has become the key technology used for bridging the performance gap across memory
hierarchies via temporal or spatial localities; in particular, the effect is prominent in disk storage systems. Applications
that involve heavy I/O activities, which are common in the cloud, probably benefit the most from caching. The use of
local volatile memory as cache might be a natural alternative, but many well-known restrictions, such as capacity and
the utilization of host machines, hinder its effective use. In addition to technical challenges, providing cache services in
clouds encounters a major practical issue (quality of service or service level agreement issue) of pricing. Currently,
(public) cloud users are limited to a small set of uniform and coarse-grained service offerings, such as High-Memory and
High-CPU in Amazon EC2. In this paper, we present the cache as a service (CaaS) model as an optional service to typical
infrastructure service offerings. Specifically, the cloud provider sets aside a large pool of memory that can be
dynamically partitioned and allocated to standard infrastructure services as disk cache. We first investigate the
feasibility of providing CaaS with the proof-of-concept elastic cache system (using dedicated remote memory servers)
built and validated on the actual system, and practical benefits of CaaS for both users and providers (i.e., performance
and profit, respectively) are thoroughly studied with a novel pricing scheme. Our CaaS model helps to leverage the
cloud economy greatly in that 1) the extra user cost for I/O performance gain is minimal if ever exists, and 2) the
provider's profit increases due to improvements in server consolidation resulting from that performance gain. Through
extensive experiments with eight resource allocation strategies, we demonstrate that our CaaS model can be a
promising cost-efficient solution for both users and providers.

EGC
3233
Communication-Aware Globally-Coordinated On-Chip Networks

With continued Moore's law scaling, multicore-based architectures are becoming the de facto design paradigm for
achieving low-cost and performance/power-efficient processing systems through effective exploitation of available
parallelism in software and hardware. A crucial subsystem within multicores is the on-chip interconnection network that
orchestrates high-bandwidth, low-latency, and low-power communication of data. Much previous work has focused on
improving the design of on-chip networks but without more fully taking into consideration the on-chip communication
behavior of application workloads that can be exploited by the network design. A significant portion of this paper
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analyzes and models on-chip network traffic characteristics of representative application workloads. Leveraged by this,
the notion of globally coordinated on-chip networks is proposed in which application communication behavior-captured
by traffic profiling-is utilized in the design and configuration of on-chip networks so as to support prevailing traffic flows
well, in a globally coordinated manner. This is applied to the design of a hybrid network consisting of a mesh augmented
with configurable multidrop (bus-like) spanning channels that serve as express paths for traffic flows benefiting from
them, according to the characterized traffic profile. Evaluations reveal that network latency and energy consumption for
a 64-core system running OpenMP benchmarks can be improved on average by 15 and 27 percent, respectively, with
globally coordinated on-chip networks.

EGC
3234
Consensus in Sparse, Mobile Ad Hoc Networks

Consensus is central to several applications including collaborative ones which a wireless ad hoc network can facilitate
for mobile users in terrains with no infrastructure support for communication. We solve the consensus problem in a
sparse network in which a node can at times have no other node in its wireless range and useful end-to-end connectivity
between nodes can just be a temporary feature that emerges at arbitrary intervals of time for any given node pair.
Efficient one-to-many dissemination, essential for consensus, now becomes a challenge; enough number of
destinations cannot deliver a multicast unless nodes retain the multicast message for exercising opportunistic
forwarding. Seeking to keep storage and bandwidth costs low, we propose two protocols. An eventually relinquishing
(◇ RC) protocol that does not store messages for long is used for attempting at consensus, and an eventually quiescent
(◇ QC) one that stops forwarding messages after a while is used for concluding consensus. Use of the ◇ RC protocol
poses additional challenges for consensus, when the fraction, f/n, of nodes that can crash is 1/4 ≤ f/n <; 1/2. Consensus
latency and packet overhead are measured through simulations and both decrease considerably even for a modest
increase in network density.

EGC Cost-Driven Scheduling of Grid Workflows Using Partial Critical Paths
3235

Recently, utility Grids have emerged as a new model of service provisioning in heterogeneous distributed systems. In
this model, users negotiate with service providers on their required Quality of Service and on the corresponding price to
reach a Service Level Agreement. One of the most challenging problems in utility Grids is workflow scheduling, i.e., the
problem of satisfying the QoS of the users as well as minimizing the cost of workflow execution. In this paper, we
propose a new QoS-based workflow scheduling algorithm based on a novel concept called Partial Critical Paths (PCP),
that tries to minimize the cost of workflow execution while meeting a user-defined deadline. The PCP algorithm has two
phases: in the deadline distribution phase it recursively assigns subdeadlines to the tasks on the partial critical paths
ending at previously assigned tasks, and in the planning phase it assigns the cheapest service to each task while
meeting its subdeadline. The simulation results show that the performance of the PCP algorithm is very promising.

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EGC
3236
Coverage and Connectivity in Duty-Cycled Wireless Sensor Networks for Event Monitoring

In duty-cycled wireless sensor networks (WSNs) for stochastic event monitoring, existing efforts are mainly
concentrated on energy-efficient scheduling of sensor nodes to guarantee the coverage performance, ignoring another
crucial issue of connectivity. The connectivity problem is extremely challenging in the duty-cycled WSNs due to the fact
that the link connections between nodes are transient thus unstable. In this paper, we propose a new kind of network,
partitioned synchronous network, to jointly address the coverage and connectivity problem. We analyze the coverage
and connectivity performances of partitioned synchronous network and compare them with those of existing
asynchronous network. We perform extensive simulations to demonstrate that the proposed partitioned synchronous
network has a better connectivity performance than that of asynchronous network, while coverage performances of two
types of networks are close.

EGC CSI: An Energy-Aware Cover-Sense-Inform Framework for k-Covered Wireless Sensor
3237 Networks

It is well known that sensor duty-cycling is an important mechanism that helps densely deployed wireless sensor
networks (WSNs) save energy. On the other hand, geographic forwarding is an efficient scheme for WSNs as it requires
maintaining only local topology information to forward data to their destination. Most of geographic forwarding
protocols assume that all sensors are always on (or active) during forwarding. However, such an assumption is
unrealistic for real-world applications where sensors are switched on or off (or inactive). In this paper, we describe our
cover-sense-inform (CSI) framework for k-covered WSNs, where each point in a sensor field is covered by at least k
active sensors. In CSI, k-coverage, sensor scheduling, and data forwarding are jointly considered. Based on our
previous work on connected k-coverage [3], we propose the first design of geographic forwarding protocols for duty-
cycled k-covered WSNs with and without data aggregation. Then, we evaluate the performance of our joint k-coverage
and geographic forwarding protocols and compare them to CCP [37], a k-Coverage Configuration Protocol, with a
geographic forwarding protocol on top of it, such as BVGF [36], which we have slightly updated in such a way that it
considers energy for a fair comparison. Simulation results show that our joint protocols outperform CCP+BVGF.

EGC
3238
Cut Detection in Wireless Sensor Networks

A wireless sensor network can get separated into multiple connected components due to the failure of some of its
nodes, which is called a “cut.” In this paper, we consider the problem of detecting cuts by the remaining nodes of a
wireless sensor network. We propose an algorithm that allows 1) every node to detect when the connectivity to a
specially designated node has been lost, and 2) one or more nodes (that are connected to the special node after the cut)
to detect the occurrence of the cut. The algorithm is distributed and asynchronous: every node needs to communicate
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with only those nodes that are within its communication range. The algorithm is based on the iterative computation of a
fictitious “electrical potential” of the nodes. The convergence rate of the underlying iterative scheme is independent of
the size and structure of the network. We demonstrate the effectiveness of the proposed algorithm through simulations
and a real hardware implementation.

EGC
3239
DCS: Distributed Asynchronous Clock Synchronization in Delay Tolerant Networks

In this paper, we propose a distributed asynchronous clock synchronization (DCS) protocol for Delay Tolerant Networks
(DTNs). Different from existing clock synchronization protocols, the proposed DCS protocol can achieve global clock
synchronization among mobile nodes within the network over asynchronous and intermittent connections with long
delays. Convergence of the clock values can be reached by compensating for clock errors using mutual relative clock
information that is propagated in the network by contacted nodes. The level of clock accuracy is depreciated with
respect to time in order to account for long delays between contact opportunities. Mathematical analysis and simulation
results for various network scenarios are presented to demonstrate the convergence and performance of the DCS
protocol. It is shown that the DCS protocol can achieve faster clock convergence speed and, as a result, reduces energy
cost by half for neighbor discovery.

EGC
3240
DDC: A Novel Scheme to Directly Decode the Collisions in UHF RFID Systems

RFID has been gaining popularity due to its variety of applications, such as inventory control and localization. One
important issue in RFID system is tag identification. In RFID systems, the tag randomly selects a slot to send a Random
Number (RN) packet to contend for identification. Collision happens when multiple tags select the same slot, which
makes the RN packet undecodable and thus reduces the channel utilization. In this paper, we redesign the RN pattern to
make the collided RNs decodable. By leveraging the collision slots, the system performance can be dramatically
enhanced. This novel scheme is called DDC, which is able to directly decode the collisions without exact knowledge of
collided RNs. In the DDC scheme, we modify the RN generator in RFID tag and add a collision decoding scheme for RFID
reader. We implement DDC in GNU Radio and USRP2 based testbed to verify its feasibility. Both theoretical analysis and
testbed experiment show that DDC achieves 40 percent tag read rate gain compared with traditional RFID protocol.

EGC
3241
Delegation-Based I/O Mechanism for High Performance Computing Systems

Massively parallel applications often require periodic data checkpointing for program restart and post-run data analysis.
Although high performance computing systems provide massive parallelism and computing power to fulfill the crucial
requirements of the scientific applications, the I/O tasks of high-end applications do not scale. Strict data consistency

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semantics adopted from traditional file systems are inadequate for homogeneous parallel computing platforms. For high
performance parallel applications independent I/O is critical, particularly if checkpointing data are dynamically created
or irregularly partitioned. In particular, parallel programs generating a large number of unrelated I/O accesses on large-
scale systems often face serious I/O serializations introduced by lock contention and conflicts at file system layer. As
these applications may not be able to utilize the I/O optimizations requiring process synchronization, they pose a great
challenge for parallel I/O architecture and software designs. We propose an I/O mechanism to bridge the gap between
scientific applications and parallel storage systems. A static file domain partitioning method is developed to align the I/O
requests and produce a client-server mapping that minimizes the file lock acquisition costs and eliminates the lock
contention. Our performance evaluations of production application I/O kernels demonstrate scalable performance and
achieve high I/O bandwidths.

EGC Determination of Wireless Networks Parameters through Parallel Hierarchical Support Vector
3242
Machines

We consider the problems of 1) estimating the physical locations of nodes in an indoor wireless network, and 2)
estimating the channel noise in a MIMO wireless network, since knowing these parameters are important to many tasks
of a wireless network such as network management, event detection, location-based service, and routing. A hierarchical
support vector machines (H-SVM) scheme is proposed with the following advantages. First, H-SVM offers an efficient
evaluation procedure in a distributed manner due to hierarchical structure. Second, H-SVM could determine these
parameters based only on simpler network information, e.g., the hop counts, without requiring particular ranging
hardware. Third, the exact mean and the variance of the estimation error introduced by H-SVM are derived which are
seldom addressed in previous works. Furthermore, we present a parallel learning algorithm to reduce the computation
time required for the proposed H-SVM. Thanks for the quicker matrix diagonization technique, our algorithm can reduce
the traditional SVM learning complexity from O(n3) to O(n2) where n is the training sample size. Finally, the simulation
results verify the validity and effectiveness for the proposed H-SVM with parallel learning algorithm.

EGC
3243
Distributed Diagnosis of Dynamic Events in Partitionable Arbitrary Topology Networks

This work introduces the Distributed Network Reachability (DNR) algorithm, a distributed system-level diagnosis
algorithm that allows every node of a partitionable arbitrary topology network to determine which portions of the
network are reachable and unreachable. DNR is the first distributed diagnosis algorithm that works in the presence of
network partitions and healings caused by dynamic fault and repair events. Both crash and timing faults are assumed,
and a faulty node is indistinguishable of a network partition. Every link is alternately tested by one of its adjacent nodes
at subsequent testing intervals. Upon the detection of a new event, the new diagnostic information is disseminated to
reachable nodes. New events can occur before the dissemination completes. Any time a new event is detected or
informed, a working node may compute the network reachability using local diagnostic information. The bounded

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correctness of DNR is proved, including the bounded diagnostic latency, bounded startup and accuracy. Simulation
results are presented for several random and regular topologies, showing the performance of the algorithm under highly
dynamic fault situations.

EGC
Distributed Evidence Propagation in Junction Trees on Clusters
3244

Evidence propagation is a major step in exact inference, a key problem in exploring probabilistic graphical models. In
this paper, we propose a novel approach for parallelizing evidence propagation in junction trees on clusters. Our
proposed method explores structural parallelism in a given junction tree. We decompose a junction tree into a set of
subtrees, each consisting of one or multiple leaf-root paths in the junction tree. In evidence propagation, we first
perform evidence collection in these subtrees concurrently. Then, the partially updated subtrees exchange data for
junction tree merging, so that all the cliques in the junction tree can be fully updated for evidence collection. Finally,
evidence distribution is performed in all the subtrees to complete evidence propagation. Since merging subtrees
requires communication across processors, we propose a technique called bitmap partitioning to explore the tradeoff
between bandwidth utilization efficiency and the overhead due to the startup latency of message passing. We
implemented the proposed method using Message Passing Interface (MPI) on a state-of-the-art Myrinet cluster
consisting of 128 processors. Compared with a baseline method, our technique results in improved scalability.

EGC
3245
Distributed Packet Buffers for High-Bandwidth Switches and Routers

High-speed routers rely on well-designed packet buffers that support multiple queues, provide large capacity and short
response times. Some researchers suggested combined SRAM/DRAM hierarchical buffer architectures to meet these
challenges. However, these architectures suffer from either large SRAM requirement or high time-complexity in the
memory management. In this paper, we present scalable, efficient, and novel distributed packet buffer architecture. Two
fundamental issues need to be addressed to make this architecture feasible: 1) how to minimize the overhead of an
individual packet buffer; and 2) how to design scalable packet buffers using independent buffer subsystems. We
address these issues by first designing an efficient compact buffer that reduces the SRAM size requirement by (k-1)/k.
Then, we introduce a feasible way of coordinating multiple subsystems with a load-balancing algorithm that maximizes
the overall system performance. Both theoretical analysis and experimental results demonstrate that our load-balancing
algorithm and the distributed packet buffer architecture can easily scale to meet the buffering needs of high bandwidth
links and satisfy the requirements of scale and support for multiple queues.

EGC Distributed Privacy-Preserving Access Control in Sensor Networks
3246

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The owner and users of a sensor network may be different, which necessitates privacy-preserving access control. On
the one hand, the network owner need enforce strict access control so that the sensed data are only accessible to users
willing to pay. On the other hand, users wish to protect their respective data access patterns whose disclosure may be
used against their interests. This paper presents {rm DP}^2{rm{AC}}, a Distributed Privacy-Preserving Access Control
scheme for sensor networks, which is the first work of its kind. Users in {rm DP}^2{rm{AC}} purchase tokens from the
network owner whereby to query data from sensor nodes which will reply only after validating the tokens. The use of
blind signatures in token generation ensures that tokens are publicly verifiable yet unlinkable to user identities, so
privacy-preserving access control is achieved. A central component in {rm DP}^2{rm{AC}} is to prevent malicious users
from reusing tokens, for which we propose a suite of distributed token reuse detection (DTRD) schemes without
involving the base station. These schemes share the essential idea that a sensor node checks with some other nodes
(called witnesses) whether a token has been used, but they differ in how the witnesses are chosen. We thoroughly
compare their performance with regard to TRD capability, communication overhead, storage overhead, and attack
resilience. The efficacy and efficiency of {rm DP}^2{rm{AC}} are confirmed by detailed performance evaluations.

EGC Distributed Throughput Optimization for ZigBee Cluster-Tree Networks
3247

ZigBee, a unique communication standard designed for low-rate wireless personal area networks, has extremely low
complexity, cost, and power consumption for wireless connectivity in inexpensive, portable, and mobile devices. Among
the well-known ZigBee topologies, ZigBee cluster-tree is especially suitable for low-power and low-cost wireless sensor
networks because it supports power saving operations and light-weight routing. In a constructed wireless sensor
network, the information about some area of interest may require further investigation such that more traffic will be
generated. However, the restricted routing of a ZigBee cluster-tree network may not be able to provide sufficient
bandwidth for the increased traffic load, so the additional information may not be delivered successfully. In this paper,
we present an adoptive-parent-based framework for a ZigBee cluster-tree network to increase bandwidth utilization
without generating any extra message exchange. To optimize the throughput in the framework, we model the process as
a vertex-constraint maximum flow problem, and develop a distributed algorithm that is fully compatible with the ZigBee
standard. The optimality and convergence property of the algorithm are proved theoretically. Finally, the results of
simulation experiments demonstrate the significant performance improvement achieved by the proposed framework and
algorithm over existing approaches.

EGC Distributed Uplink Power Control in Multiservice Wireless Networks via a Game Theoretic
3248
Approach with Convex Pricing

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In this paper, the problem of efficient distributed power control via convex pricing of users' transmission power in the
uplink of CDMA wireless networks supporting multiple services is addressed. Each user is associated with a nested
utility function, which appropriately represents his degree of satisfaction in relation to the expected trade-off between
his QoS-aware actual uplink throughput performance and the corresponding power consumption. Initially, a Multiservice
Uplink Power Control game (MSUPC) is formulated, where each user aims selfishly at maximizing his utility-based
performance under the imposed physical limitations and its unique Nash equilibrium point is determined. Then the
inefficiency of MSUPC game's Nash equilibrium is proven and a usage-based convex pricing policy of the transmission
power is introduced, which offers a more effective approach compared to the linear pricing schemes that have been
adopted in the literature. Consequently, a Multiservice Uplink Power Control game with Convex Pricing (MSUPC-CP) is
formulated and its unique Pareto optimal Nash equilibrium is determined. A distributed iterative algorithm for computing
MSUPC-CP game's equilibrium is proposed, while the overall approach's efficiency is illustrated via modeling and
simulation.

EGC
3249
DRAGON: Detection and Tracking of Dynamic Amorphous Events in Wireless Sensor Networks

Wireless sensor networks may be deployed in many applications to detect and track events of interest. Events can be
either point events with an exact location and constant shape, or region events which cover a large area and have
dynamic shapes. While both types of events have received attention, no event detection and tracking protocol in
existing wireless sensor network research is able to identify and track region events with dynamic identities, which arise
when events are created or destroyed through splitting and merging. In this paper, we propose DRAGON, an event
detection and tracking protocol which is able to handle all types of events including region events with dynamic
identities. DRAGON employs two physics metaphors: event center of mass, to give an approximate location to the event;
and node momentum, to guide the detection of event merges and splits. Both detailed theoretical analysis and extensive
performance studies of DRAGON's properties demonstrate that DRAGON's execution is distributed among the sensor
nodes, has low latency, is energy efficient, is able to run on a wide array of physical deployments, and has performance
which scales well with event size, speed, and count.

EGC
3250
Dynamic Beacon Mobility Scheduling for Sensor Localization

In mobile-beacon assisted sensor localization, beacon mobility scheduling aims to determine the best beacon trajectory
so that each sensor receives sufficient beacon signals and becomes localized with minimum delay. We propose a novel
DeteRministic dynamic bEAcon Mobility Scheduling (DREAMS) algorithm, without requiring any prior knowledge of the
sensory field. In this algorithm, the beacon trajectory is defined as the track of Depth-First Traversal (DFT) of the
network graph, thus deterministic. The mobile beacon performs DFT dynamically, under the instruction of nearby
sensors on the fly. It moves from sensor to sensor in an intelligent heuristic manner according to Received Signal
Strength (RSS)-based distance measurements. We prove that DREAMS guarantees full localization (every sensor is

Projects


localized) when the measurements are noise-free, and derive the upper bound of beacon total moving distance in this
case. Then, we suggest to apply node elimination and Local Minimum Spanning Tree (LMST) to shorten beacon tour and
reduce delay. Further, we extend DREAMS to multibeacon scenarios. Beacons with different coordinate systems
compete for localizing sensors. Loser beacons agree on winner beacons' coordinate system, and become cooperative in
subsequent localization. All sensors are finally localized in a commonly agreed coordinate systems. Through simulation
we show that DREAMS guarantees full localization even with noisy distance measurements. We evaluate its
performance on localization delay and communication overhead in comparison with a previously proposed static path-
based scheduling method.

EGC
3251
Dynamic Fractional Resource Scheduling versus Batch Scheduling

We propose a novel job scheduling approach for homogeneous cluster computing platforms. Its key feature is the use of
virtual machine technology to share fractional node resources in a precise and controlled manner. Other VM-based
scheduling approaches have focused primarily on technical issues or extensions to existing batch scheduling systems,
while we take a more aggressive approach and seek to find heuristics that maximize an objective metric correlated with
job performance. We derive absolute performance bounds and develop algorithms for the online nonclairvoyant version
of our scheduling problem. We further evaluate these algorithms in simulation against both synthetic and real-world
HPC workloads and compare our algorithms to standard batch scheduling approaches. We find that our approach
improves over batch scheduling by orders of magnitude in terms of job stretch, while leading to comparable or better
resource utilization. Our results demonstrate that virtualization technology coupled with lightweight online scheduling
strategies can afford dramatic improvements in performance for executing HPC workloads.

EGC EasyPDP: An Efficient Parallel Dynamic Programming Runtime System for Computational
3252 Biology

Dynamic programming (DP) is a popular and efficient technique in many scientific applications such as computational
biology. Nevertheless, its performance is limited due to the burgeoning volume of scientific data, and parallelism is
necessary and crucial to keep the computation time at acceptable levels. The intrinsically strong data dependency of
dynamic programming makes it difficult and error-prone for the programmer to write a correct and efficient parallel
program. Therefore, this paper builds a runtime system named EasyPDP aiming at parallelizing dynamic programming
algorithms on multicore and multiprocessor platforms. Under the concept of software reusability and complexity
reduction of parallel programming, a DAG Data Driven Model is proposed, which supports those applications with a
strong data interdependence relationship. Based on the model, EasyPDP runtime system is designed and implemented.
It automatically handles thread creation, dynamic data task allocation and scheduling, data partitioning, and fault
tolerance. Five frequently used DAG patterns from biological dynamic programming algorithms have been put into the
DAG pattern library of EasyPDP, so that the programmer can choose to use any of them according to his/her specific

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application. Besides, an ideal computing distribution model is proposed to discuss the optimal values for the
performance tuning arguments of EasyPDP. We evaluate the performance potential and fault tolerance feature of
EasyPDP in multicore system. We also compare EasyPDP with other methods such as Block-Cycle Wavefront (BCW).
The experimental results illustrate that EasyPDP system is fine and provides an efficient infrastructure for dynamic
programming algorithms.

EGC
3253
Efficient Communication Algorithms in Hexagonal Mesh Interconnection Networks

In this paper, we show that the hexagonal mesh networks developed in the early 1990s are a special case of the EJ
networks that have been considered more recently. Using a node addressing scheme based on the EJ number system,
we give a shortest path routing algorithm for hexagonal mesh networks. We also extend the known efficient one-to-all
broadcasting algorithm on hexagonal mesh networks to algorithms for one-to-one personalized broadcasting, all-to-all
broadcasting, and all-to-all personalized broadcasting algorithms. Their time complexity and optimality are analyzed.

EGC
Efficient Hardware Barrier Synchronization in Many-Core CMPs
3254

Traditional software-based barrier implementations for shared memory parallel machines tend to produce hotspots in
terms of memory and network contention as the number of processors increases. This could limit their applicability to
future many-core CMPs in which possibly several dozens of cores would need to be synchronized efficiently. In this
work, we develop GBarrier, a hardware-based barrier mechanism especially aimed at providing efficient barriers in
future many-core CMPs. Our proposal deploys a dedicated G-line-based network to allow for fast and efficient signaling
of barrier arrival and departure. Since GBarrier does not have any influence on the memory system, we avoid all
coherence activity and barrier-related network traffic that traditional approaches introduce and that restrict scalability.
Through detailed simulations of a 32-core CMP, we compare GBarrier against one of the most efficient software-based
barrier implementations for a set of kernels and scientific applications. Evaluation results show average reductions of 54
and 21 percent in execution time, 53 and 18 percent in network traffic, and also 76 and 31 percent in the energy-delay²
product metric for the full CMP when the kernels and scientific applications, respectively, are considered.

EGC
3255 Efficient Master/Worker Parallel Discrete Event Simulation on Meta computing Systems

The master/worker (MW) paradigm can be used as an approach to parallel discrete event simulation (PDES) on
metacomputing systems. MW PDES applications incur overheads not found in conventional PDES executions executing
on tightly coupled machines. We introduce four optimization techniques in MW PDES systems on public resource and
desktop grid infrastructures. Work unit caching, pipelined state updates, expedited message delivery, and adaptive work

Projects


unit scheduling mechanisms in the context of MW PDES are described. These optimizations provide significant
performance benefits when used in tandem. We present results showing that an optimized MW PDES system using
these techniques can exhibit performance comparable to a traditional PDES system for queueing network and particle
physics simulation applications while providing execution capability across metacomputing systems.

EGC Efficient Server Provisioning with Control for End-to-End Response Time Guarantee on
3256 Multitier Clusters

Dynamic virtual server provisioning is critical to quality-of-service assurance for multitier Internet applications. In this
paper, we address three important challenging problems. First, we propose an efficient server provisioning approach on
multitier clusters based on an end-to-end resource allocation optimization model. It is to minimize the number of virtual
servers allocated to the system while the average end-to-end response time guarantee is satisfied. Second, we design a
model-independent fuzzy controller for bounding an important performance metric, the 90th-percentile response time of
requests flowing through the multitier architecture. Third, to compensate for the latency due to the dynamic addition of
virtual servers, we design a self-tuning component that adaptively adjusts the output scaling factor of the fuzzy
controller according to the transient behavior of the end-to-end response time. Extensive simulation results, using two
representative customer behavior models in a typical three-tier web cluster, demonstrate that the provisioning approach
is able to significantly reduce the number of virtual servers allocated for the performance guarantee compared to an
existing representative approach. The approach integrated with the model-independent self-tuning fuzzy controller can
efficiently assure the average and the 90th-percentile end-to-end response time guarantees on multitier clusters.

EGC
3257
Embedded Transitive Closure Network for Runtime Deadlock Detection in Networks-on-Chip

Interconnection networks with adaptive routing are susceptible to deadlock, which could lead to performance
degradation or system failure. Detecting deadlocks at runtime is challenging because of their highly distributed
characteristics. In this paper, we present a deadlock detection method that utilizes runtime transitive closure (TC)
computation to discover the existence of deadlock-equivalence sets, which imply loops of requests in networks-on-chip
(NoCs). This detection scheme guarantees the discovery of all true deadlocks without false alarms in contrast with state-
of-the-art approximation and heuristic approaches. A distributed TC-network architecture, which couples with the NoC
infrastructure, is also presented to realize the detection mechanism efficiently. Detailed hardware realization
architectures and schematics are also discussed. Our results based on a cycle-accurate simulator demonstrate the
effectiveness of the proposed method. It drastically outperforms timing-based deadlock detection mechanisms by
eliminating false detections and, thus, reducing energy wastage in retransmission for various traffic scenarios including
real-world application. We found that timing-based methods may produce two orders of magnitude more deadlock
alarms than the TC-network method. Moreover, the implementations presented in this paper demonstrate that the
hardware overhead of TC-networks is insignificant.

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EGC
3258
Enabling Secure and Efficient Ranked Keyword Search over Outsourced Cloud Data

Cloud computing economically enables the paradigm of data service outsourcing. However, to protect data privacy,
sensitive cloud data have to be encrypted before outsourced to the commercial public cloud, which makes effective data
utilization service a very challenging task. Although traditional searchable encryption techniques allow users to securely
search over encrypted data through keywords, they support only Boolean search and are not yet sufficient to meet the
effective data utilization need that is inherently demanded by large number of users and huge amount of data files in
cloud. In this paper, we define and solve the problem of secure ranked keyword search over encrypted cloud data.
Ranked search greatly enhances system usability by enabling search result relevance ranking instead of sending
undifferentiated results, and further ensures the file retrieval accuracy. Specifically, we explore the statistical measure
approach, i.e., relevance score, from information retrieval to build a secure searchable index, and develop a one-to-many
order-preserving mapping technique to properly protect those sensitive score information. The resulting design is able
to facilitate efficient server-side ranking without losing keyword privacy. Thorough analysis shows that our proposed
solution enjoys “as-strong-as-possible” security guarantee compared to previous searchable encryption schemes, while
correctly realizing the goal of ranked keyword search. Extensive experimental results demonstrate the efficiency of the
proposed solution.

EGC Energy-Efficient Scheduling of Periodic Real-Time Tasks on Lightly Loaded Multicore
3259 Processors

For lightly loaded multicore processors that contain more processing cores than running tasks and have dynamic
voltage and frequency scaling capability, we address the energy-efficient scheduling of periodic real-time tasks. First,
we introduce two energy-saving techniques for the lightly loaded multicore processors: exploiting overabundant cores
for executing a task in parallel with a lower frequency and turning off power of rarely used cores. Next, we verify that if
the two introduced techniques are supported, then the problem of minimizing energy consumption of real-time tasks
while meeting their deadlines is NP-hard on a lightly loaded multicore processor. Finally, we propose a polynomial-time
scheduling scheme that provides a near minimum-energy feasible schedule. The difference of energy consumption
between the provided schedule and the minimum-energy schedule is limited. The scheme saves up to 64 percent of the
processing core energy consumed by the previous scheme that executes each task on a separate core.

EGC Energy-Efficient Topology Control in Cooperative Ad Hoc Networks
3260

Projects


Cooperative communication (CC) exploits space diversity through allowing multiple nodes cooperatively relay signals to
the receiver so that the combined signal at the receiver can be correctly decoded. Since CC can reduce the transmission
power and extend the transmission coverage, it has been considered in topology control protocols [1], [2]. However,
prior research on topology control with CC only focuses on maintaining the network connectivity, minimizing the
transmission power of each node, whereas ignores the energy efficiency of paths in constructed topologies. This may
cause inefficient routes and hurt the overall network performance in cooperative ad hoc networks. In this paper, to
address this problem, we introduce a new topology control problem: energy-efficient topology control problem with
cooperative communication, and propose two topology control algorithms to build cooperative energy spanners in
which the energy efficiency of individual paths are guaranteed. Both proposed algorithms can be performed in
distributed and localized fashion while maintaining the globally efficient paths. Simulation results confirm the nice
performance of all proposed algorithms.

EGC Equivalent Disk Allocations
3261

Declustering techniques reduce query response times through parallel I/O by distributing data among multiple devices.
Except for a few cases, it is not possible to find declustering schemes that are optimal for all spatial range queries. As a
result of this, most of the research on declustering have focused on finding schemes with low worst case additive error.
Number-theoretic declustering techniques provide low additive error and high threshold. In this paper, we investigate
equivalent disk allocations and focus on number-theoretic declustering. Most of the number-theoretic disk allocations
are equivalent and provide the same additive error and threshold. Investigation of equivalent allocations simplifies
schemes to find allocations with desirable properties. By keeping one of the equivalent disk allocations, we can reduce
the complexity of searching for good disk allocations under various criteria such as additive error and threshold. Using
proposed scheme, we were able to collect the most extensive experimental results on additive error and threshold in 2,
3, and 4 dimensions.

EGC
Exploiting Event-Level Parallelism for Parallel Network Simulation on Multicore Systems
3262

This paper proposes a parallel simulation methodology to speed up network simulations on modern multicore systems.
In this paper, we present the design and implementation of this approach and the performance speedups achieved
under various network conditions. This methodology provides two unique and important advantages: 1) one can readily
enjoy performance speedups without using an unfamiliar simulation language/library to rewrite his protocol module
code for parallel simulations, and 2) one can conduct parallel simulations in the same way as when he conducts
sequential simulations. We implemented this methodology and evaluated its performance speedups on the popular ns-2
network simulator. Our results show that this methodology is feasible and can provide satisfactory performance
speedups under high event load conditions on wired networks.

Projects

Ieee projects 2012 2013 - Parallal and Distributed Computing

Ieee projects 2012 2013 - Parallal and Distributed Computing

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Ieee projects 2012 2013 - Parallal and Distributed Computing