SlideShare une entreprise Scribd logo
1  sur  5
On Quality of Monitoring for Multi-channel Wireless Infrastructure
Networks
ABSTRACT:
Passive monitoring utilizing distributed wireless sniffers is an effective technique to monitor
activities in wireless infrastructure networks for fault diagnosis, resource management and
critical path analysis. In this paper, we introduce a quality of monitoring (QoM) metric defined
by the expected number of active users monitored, and investigate the problem of maximizing
QoM by judiciously assigning sniffers to channels based on the knowledge of user activities in
a multi-channel wireless network. Two types of capture models are considered. The user-centric
model assumes frame-level capturing capability of sniffers such that the activities of different
users can be distinguished while the sniffer-centric model only utilizes the binary channel
information (active or not) at a sniffer. For the user-centric model, we show that the implied
optimization problem is NP-hard, but a constant approximation ratio can be attained via
polynomial complexity algorithms. For the sniffer-centric model, we devise stochastic inference
schemes to transform the problem into the user-centric domain, where we are able to apply our
polynomial approximation algorithms. The effectiveness of our proposed schemes and
algorithms is further evaluated using both synthetic data as well as real-world traces from an
operational WLAN.
GLOBALSOFT TECHNOLOGIES
IEEE PROJECTS & SOFTWARE DEVELOPMENTS
IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE
BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS
CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401
Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmail.com
EXISTING SYSTEM:
There has been much work done on wireless monitoring from a system-level approach, in an
attempt to design complete systems, and address the interactions among the components of such
systems. The work uses AP, SNMP logs, and wired side traces to analyze WiFi traffic
characteristics.
DISADVANTAGES OF EXISTING SYSTEM:
 Ideally, a network administrator would want to perform network monitoring on all
channels simultaneously. However, multi-radio sniffers are known to be large and
expensive to deploy.
 The basic problem underlying all of our models can be cast as finding an assignment of
sniffers to channels so as to maximize the QoM.
 The problem of sniffer assignment, in an attempt to maximize the QoM metric, is further
complicated by the dynamics of real-life systems such as: 1) the user population changes
over time (churn), 2) activities of a single user is dynamic, and 3) connectivity between
users and sniffers may vary due to changes in channel conditions or mobility.
PROPOSED SYSTEM:
In this paper, we focus on designing algorithms that aim at maximizing the QoM metric with
different granularities of a priori knowledge. The usage patterns are assumed to be stationary
during the decision period. We make the following contributions toward the design of passive
monitoring systems for multi-channel wireless infrastructure networks. We provide a formal
model for evaluating the quality of monitoring. We study two categories of monitoring models
that differ in the information capturing capability of passive monitoring systems. For each of
these models we provide algorithms and methods that optimize the quality of monitoring. We
unravel interactions between the two monitoring models by devising two methods to convert
the sniffer-centric model to the user-centric domain by exploiting the stochastic properties of
underlying user processes
ADVANTAGES OF PROPOSED SYSTEM:
The first approach, Quantized Linear ICA (QLICA), estimates the hidden structure by applying
a quantization process on the outcome of the traditional ICA, while the second approach, Binary
ICA (BICA), decomposes the observation data into OR mixtures of hidden components and
recovers the underlying structure. Finally, an extensive evaluation study is carried out using
both synthetic data as well as real-world traces from an operational WLAN.
HARDWARE & SOFTWARE REQUIREMENTS:
HARDWARE REQUIREMENTS:
System : Pentium IV 2.4 GHz.
Hard Disk : 40 GB.
Floppy Drive : 1.44 Mb.
Monitor : 15 VGA Color.
Mouse : Logitech.
Ram : 512 MB.
SOFTWARE REQUIREMENTS:
Operating system : Windows XP Professional.
Coding Language : C#.NET
REFERENCE:
Huy Nguyen, Gabriel Scalosub and Rong Zheng,Senior Member, IEEE “On Quality of
Monitoring for Multi-channel Wireless Infrastructure Networks”- IEEE TRANSACTIONS
ON MOBILE COMPUTING, 2013.
CLOUING
DOMAIN: WIRELESS NETWORK PROJECTS

Contenu connexe

En vedette

Buta, Cecelia 1 23 15
Buta, Cecelia 1 23 15Buta, Cecelia 1 23 15
Buta, Cecelia 1 23 15Cecelia Butta
 
¿Que Es Un Troyano, Como Marcha? Infografia
¿Que Es Un Troyano, Como Marcha? Infografia
¿Que Es Un Troyano, Como Marcha? Infografia
¿Que Es Un Troyano, Como Marcha? Infografia comprarantiviruschrome75
 
Wilujeng sumping
Wilujeng sumpingWilujeng sumping
Wilujeng sumpingwierid
 
1С:Бухгалтерия 8.3
1С:Бухгалтерия 8.31С:Бухгалтерия 8.3
1С:Бухгалтерия 8.3Platansoft
 
Q3 functional report
Q3   functional reportQ3   functional report
Q3 functional report647435
 
JAVA 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementati...
JAVA 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementati...JAVA 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementati...
JAVA 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementati...IEEEGLOBALSOFTTECHNOLOGIES
 

En vedette (7)

Previous work
Previous workPrevious work
Previous work
 
Buta, Cecelia 1 23 15
Buta, Cecelia 1 23 15Buta, Cecelia 1 23 15
Buta, Cecelia 1 23 15
 
¿Que Es Un Troyano, Como Marcha? Infografia
¿Que Es Un Troyano, Como Marcha? Infografia
¿Que Es Un Troyano, Como Marcha? Infografia
¿Que Es Un Troyano, Como Marcha? Infografia
 
Wilujeng sumping
Wilujeng sumpingWilujeng sumping
Wilujeng sumping
 
1С:Бухгалтерия 8.3
1С:Бухгалтерия 8.31С:Бухгалтерия 8.3
1С:Бухгалтерия 8.3
 
Q3 functional report
Q3   functional reportQ3   functional report
Q3 functional report
 
JAVA 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementati...
JAVA 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementati...JAVA 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementati...
JAVA 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementati...
 

Plus de IEEEGLOBALSOFTTECHNOLOGIES

DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Vampire attacks draining life from w...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Vampire attacks draining life from w...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Vampire attacks draining life from w...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Vampire attacks draining life from w...IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT SSD a robust rf location fingerprint...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT SSD a robust rf location fingerprint...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT SSD a robust rf location fingerprint...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT SSD a robust rf location fingerprint...IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Privacy preserving distributed profi...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Privacy preserving distributed profi...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Privacy preserving distributed profi...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Privacy preserving distributed profi...IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Optimal multicast capacity and delay...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Optimal multicast capacity and delay...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Optimal multicast capacity and delay...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Optimal multicast capacity and delay...IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementa...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementa...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementa...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementa...IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Model based analysis of wireless sys...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Model based analysis of wireless sys...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Model based analysis of wireless sys...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Model based analysis of wireless sys...IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Mobile relay configuration in data i...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Mobile relay configuration in data i...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Mobile relay configuration in data i...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Mobile relay configuration in data i...IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Distributed cooperative caching in s...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Distributed cooperative caching in s...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Distributed cooperative caching in s...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Distributed cooperative caching in s...IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Delay optimal broadcast for multihop...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Delay optimal broadcast for multihop...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Delay optimal broadcast for multihop...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Delay optimal broadcast for multihop...IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Dcim distributed cache invalidation ...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Dcim distributed cache invalidation ...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Dcim distributed cache invalidation ...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Dcim distributed cache invalidation ...IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Cooperative packet delivery in hybri...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Cooperative packet delivery in hybri...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Cooperative packet delivery in hybri...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Cooperative packet delivery in hybri...IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Content sharing over smartphone base...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Content sharing over smartphone base...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Content sharing over smartphone base...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Content sharing over smartphone base...IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Community aware opportunistic routin...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Community aware opportunistic routin...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Community aware opportunistic routin...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Community aware opportunistic routin...IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Capacity of hybrid wireless mesh net...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Capacity of hybrid wireless mesh net...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Capacity of hybrid wireless mesh net...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Capacity of hybrid wireless mesh net...IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Adaptive position update for geograp...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Adaptive position update for geograp...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Adaptive position update for geograp...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Adaptive position update for geograp...IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT A scalable server architecture for m...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT A scalable server architecture for m...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT A scalable server architecture for m...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT A scalable server architecture for m...IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Scalable and secure sharing of person...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Scalable and secure sharing of person...DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Scalable and secure sharing of person...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Scalable and secure sharing of person...IEEEGLOBALSOFTTECHNOLOGIES
 
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Qos ranking prediction for cloud serv...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Qos ranking prediction for cloud serv...DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Qos ranking prediction for cloud serv...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Qos ranking prediction for cloud serv...IEEEGLOBALSOFTTECHNOLOGIES
 

Plus de IEEEGLOBALSOFTTECHNOLOGIES (20)

DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Vampire attacks draining life from w...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Vampire attacks draining life from w...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Vampire attacks draining life from w...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Vampire attacks draining life from w...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT SSD a robust rf location fingerprint...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT SSD a robust rf location fingerprint...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT SSD a robust rf location fingerprint...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT SSD a robust rf location fingerprint...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Privacy preserving distributed profi...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Privacy preserving distributed profi...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Privacy preserving distributed profi...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Privacy preserving distributed profi...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Optimal multicast capacity and delay...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Optimal multicast capacity and delay...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Optimal multicast capacity and delay...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Optimal multicast capacity and delay...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementa...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementa...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementa...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT On the real time hardware implementa...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Model based analysis of wireless sys...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Model based analysis of wireless sys...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Model based analysis of wireless sys...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Model based analysis of wireless sys...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Mobile relay configuration in data i...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Mobile relay configuration in data i...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Mobile relay configuration in data i...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Mobile relay configuration in data i...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Distributed cooperative caching in s...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Distributed cooperative caching in s...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Distributed cooperative caching in s...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Distributed cooperative caching in s...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Delay optimal broadcast for multihop...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Delay optimal broadcast for multihop...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Delay optimal broadcast for multihop...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Delay optimal broadcast for multihop...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Dcim distributed cache invalidation ...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Dcim distributed cache invalidation ...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Dcim distributed cache invalidation ...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Dcim distributed cache invalidation ...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Cooperative packet delivery in hybri...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Cooperative packet delivery in hybri...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Cooperative packet delivery in hybri...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Cooperative packet delivery in hybri...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Content sharing over smartphone base...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Content sharing over smartphone base...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Content sharing over smartphone base...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Content sharing over smartphone base...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Community aware opportunistic routin...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Community aware opportunistic routin...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Community aware opportunistic routin...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Community aware opportunistic routin...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Capacity of hybrid wireless mesh net...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Capacity of hybrid wireless mesh net...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Capacity of hybrid wireless mesh net...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Capacity of hybrid wireless mesh net...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Adaptive position update for geograp...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Adaptive position update for geograp...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Adaptive position update for geograp...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT Adaptive position update for geograp...
 
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT A scalable server architecture for m...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT A scalable server architecture for m...DOTNET 2013 IEEE MOBILECOMPUTING PROJECT A scalable server architecture for m...
DOTNET 2013 IEEE MOBILECOMPUTING PROJECT A scalable server architecture for m...
 
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
 
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Attribute based access to scalable me...
 
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Scalable and secure sharing of person...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Scalable and secure sharing of person...DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Scalable and secure sharing of person...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Scalable and secure sharing of person...
 
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Qos ranking prediction for cloud serv...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Qos ranking prediction for cloud serv...DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Qos ranking prediction for cloud serv...
DOTNET 2013 IEEE CLOUDCOMPUTING PROJECT Qos ranking prediction for cloud serv...
 

Dernier

#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024BookNet Canada
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdfhans926745
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024Results
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfEnterprise Knowledge
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024The Digital Insurer
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Servicegiselly40
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
 
Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitecturePixlogix Infotech
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Igalia
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonAnna Loughnan Colquhoun
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxMalak Abu Hammad
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationRadu Cotescu
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j
 
SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024Scott Keck-Warren
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Alan Dix
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slidespraypatel2
 

Dernier (20)

#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
#StandardsGoals for 2024: What’s new for BISAC - Tech Forum 2024
 
[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf[2024]Digital Global Overview Report 2024 Meltwater.pdf
[2024]Digital Global Overview Report 2024 Meltwater.pdf
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024
 
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdfThe Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
The Role of Taxonomy and Ontology in Semantic Layers - Heather Hedden.pdf
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
 
Understanding the Laravel MVC Architecture
Understanding the Laravel MVC ArchitectureUnderstanding the Laravel MVC Architecture
Understanding the Laravel MVC Architecture
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
Neo4j - How KGs are shaping the future of Generative AI at AWS Summit London ...
 
SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024SQL Database Design For Developers at php[tek] 2024
SQL Database Design For Developers at php[tek] 2024
 
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...Swan(sea) Song – personal research during my six years at Swansea ... and bey...
Swan(sea) Song – personal research during my six years at Swansea ... and bey...
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slides
 

JAVA 2013 IEEE MOBILECOMPUTING PROJECT On quality of monitoring for multi channel wireless infrastructure networks

  • 1. On Quality of Monitoring for Multi-channel Wireless Infrastructure Networks ABSTRACT: Passive monitoring utilizing distributed wireless sniffers is an effective technique to monitor activities in wireless infrastructure networks for fault diagnosis, resource management and critical path analysis. In this paper, we introduce a quality of monitoring (QoM) metric defined by the expected number of active users monitored, and investigate the problem of maximizing QoM by judiciously assigning sniffers to channels based on the knowledge of user activities in a multi-channel wireless network. Two types of capture models are considered. The user-centric model assumes frame-level capturing capability of sniffers such that the activities of different users can be distinguished while the sniffer-centric model only utilizes the binary channel information (active or not) at a sniffer. For the user-centric model, we show that the implied optimization problem is NP-hard, but a constant approximation ratio can be attained via polynomial complexity algorithms. For the sniffer-centric model, we devise stochastic inference schemes to transform the problem into the user-centric domain, where we are able to apply our polynomial approximation algorithms. The effectiveness of our proposed schemes and algorithms is further evaluated using both synthetic data as well as real-world traces from an operational WLAN. GLOBALSOFT TECHNOLOGIES IEEE PROJECTS & SOFTWARE DEVELOPMENTS IEEE FINAL YEAR PROJECTS|IEEE ENGINEERING PROJECTS|IEEE STUDENTS PROJECTS|IEEE BULK PROJECTS|BE/BTECH/ME/MTECH/MS/MCA PROJECTS|CSE/IT/ECE/EEE PROJECTS CELL: +91 98495 39085, +91 99662 35788, +91 98495 57908, +91 97014 40401 Visit: www.finalyearprojects.org Mail to:ieeefinalsemprojects@gmail.com
  • 2. EXISTING SYSTEM: There has been much work done on wireless monitoring from a system-level approach, in an attempt to design complete systems, and address the interactions among the components of such systems. The work uses AP, SNMP logs, and wired side traces to analyze WiFi traffic characteristics. DISADVANTAGES OF EXISTING SYSTEM:  Ideally, a network administrator would want to perform network monitoring on all channels simultaneously. However, multi-radio sniffers are known to be large and expensive to deploy.  The basic problem underlying all of our models can be cast as finding an assignment of sniffers to channels so as to maximize the QoM.  The problem of sniffer assignment, in an attempt to maximize the QoM metric, is further complicated by the dynamics of real-life systems such as: 1) the user population changes over time (churn), 2) activities of a single user is dynamic, and 3) connectivity between users and sniffers may vary due to changes in channel conditions or mobility. PROPOSED SYSTEM: In this paper, we focus on designing algorithms that aim at maximizing the QoM metric with different granularities of a priori knowledge. The usage patterns are assumed to be stationary during the decision period. We make the following contributions toward the design of passive monitoring systems for multi-channel wireless infrastructure networks. We provide a formal model for evaluating the quality of monitoring. We study two categories of monitoring models that differ in the information capturing capability of passive monitoring systems. For each of these models we provide algorithms and methods that optimize the quality of monitoring. We unravel interactions between the two monitoring models by devising two methods to convert the sniffer-centric model to the user-centric domain by exploiting the stochastic properties of underlying user processes
  • 3. ADVANTAGES OF PROPOSED SYSTEM: The first approach, Quantized Linear ICA (QLICA), estimates the hidden structure by applying a quantization process on the outcome of the traditional ICA, while the second approach, Binary ICA (BICA), decomposes the observation data into OR mixtures of hidden components and recovers the underlying structure. Finally, an extensive evaluation study is carried out using both synthetic data as well as real-world traces from an operational WLAN. HARDWARE & SOFTWARE REQUIREMENTS: HARDWARE REQUIREMENTS: System : Pentium IV 2.4 GHz. Hard Disk : 40 GB. Floppy Drive : 1.44 Mb. Monitor : 15 VGA Color. Mouse : Logitech. Ram : 512 MB. SOFTWARE REQUIREMENTS: Operating system : Windows XP Professional. Coding Language : C#.NET REFERENCE: Huy Nguyen, Gabriel Scalosub and Rong Zheng,Senior Member, IEEE “On Quality of Monitoring for Multi-channel Wireless Infrastructure Networks”- IEEE TRANSACTIONS ON MOBILE COMPUTING, 2013.
  • 4.