Fs2410401044

Heena Ahuja, Er. Jyoti Gupta / International Journal of Engineering Research and Applications
(IJERA) ISSN: 2248-9622 www.ijera.com
Vol. 2, Issue 4, July-August 2012, pp.1040-1044
Review of Vector-Based Forwarding Protocol for Underwater Sensor
Network

Heena Ahuja*, Er. Jyoti Gupta**
*Student, Department of ECE, MMU Mullana, Ambala, India
** Assistant Professor, ECE, MMU Mullana, Ambala, India

ABSTRACT
In this paper, we tackle one fundamental latency, node mobility (resulting in high network
problem in Underwater Sensor Networks (UWSNs): dynamics), high error probability, and three-dimensional
robust, scalable and energy efficient routing. network topology. These new features bring many
Underwater Sensor Networks (UWSNs) are challenges to the protocol design of UWSNs. In this paper,
significantly different from terrestrial sensor networks we tackle one fundamental problem in UWSNs: robust,
in the following aspects: low bandwidth, high latency, scalable, and energy efficient routing. The unique features
node mobility, high error probability, and 3- of UWSNs pose great challenges on its routing protocol
dimensional space. These new features bring many design and make many existing routing protocols for
challenges to the network protocol design of UWSNs. terrestrial networks unsuitable.
In this paper, we propose a novel routing protocol,
called vector-based forwarding (VBF), to provide
robust, scalable and energy efficient routing. VBF is 1.1 Unique Features of UWSNs
essentially a position-based routing approach: nodes UWSNs are significantly different from any terrestrial
close to the “vector" from the source to the destination sensor networks in terms of the following aspects:
will forward the message. In this way, only a small
fraction of the nodes are involved in routing. To 1.1.1 Low Bandwidth and High Latency in UWSNs:
improve the robustness, packets are forwarded in Acoustic channels (instead of RF channels) are used as the
redundant and interleaved paths. Further, a localized communication method since radio does not work well in
and distributed self-adaptation algorithm allows the water. The propagation speed of acoustic signals in water
nodes to reduce energy consumption by discarding is about 1.5 × 103 m/sec, which is five orders of magnitude
redundant packets.VBF performs well in dense lower than the radio propagation speed (3 × 108 m/sec).
networks. Moreover, the available bandwidth of underwater acoustic
channels is limited and dramatically depends on both
Keywords - Angle of arrival, energy, desirable factor, transmission range and frequency.
packets, protocol, self adaptation, vector.
1.1.2 UWSNs Are Highly Dynamic: The underwater
1. INTRODUCTION sensor networks we target are highly mobile networks
The Earth is a water planet. For decades, there where sensor nodes are not fixed and they will float with
have been significant interests in monitoring aquatic water currents. From empirical observations, underwater
environments for scientific exploration, commercial objects may move at the speed of 2-3 knots (or 3–6
exploitation and coastline protection. Highly precise, real- kilometers per hour) in a typical underwater condition.
time, and temporal spatial continuous aquatic environment This kind of mobility results in a highly dynamic network
monitoring systems are extremely important for various topology.
applications, such as oceanographic data collection,
pollution detection, and marine surveillance. However, 1.1.3 UWSNs Are Highly Error-Prone: Underwater
traditional techniques, such as remote telemetry and acoustic communication channels are significantly
sequential local sensing, cannot satisfy these high- affected by many factors such as signal attenuation, noise,
demanding application requirements. Recently, underwater multipath, Doppler spread, and even water temperature.
sensor networks have emerged as a very powerful All these factors cause high bit-error and delay variance.
technique for many applications for underwater Thus, communication links in UWSNs are highly error-
environment, including monitoring, measurement, prone.
surveillance and control [1].Compared with traditional
techniques in these application scenarios, underwater 1.1.4 UWSNs Are Three-Dimensional: UWSNs are
sensor networks enable people to perform underwater usually deployed in a three-dimensional space. This is
activities more accurately and timely in much wider areas. different from the 2-dimensional deployment of most
Even though underwater sensor networks terrestrial sensor networks. These characteristics of
(UWSNs) share some common properties with terrestrial UWSNs bring up many new challenges and make the
sensor networks, such as the large number of nodes and existing routing protocols for terrestrial sensor networks
the limited energy supplies, UWSNs are significantly unsuitable here. For UWSNs, the routing protocols should
different from terrestrial sensor networks in many aspects: be able to handle the node mobility and the unreliable
low bandwidth, high communication links with high energy efficiency.

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1.2 Routing Challenges in UWSNs relatively stable neighborhood to form the routing path. If
Same as in terrestrial sensor networks, saving energy is a applying these protocols in UWSNs, it would be costly to
major concern in UWSNs. At the same time, UWSN maintain and recover the frequently broken routing path
routing should be able to handle node mobility. This due to the node mobility. Geographic routing protocols,
requirement makes most existing energy-efficient routing which leverage the position information of each node to
protocols unsuitable for UWSNs. There are many routing determine the forwarding path, have been investigated
protocols proposed for terrestrial sensor networks, such as extensively for terrestrial wireless networks.
Directed Diffusion [2], and TTDD (Two-Tier Data
Dissemination) [3]. These protocols are mainly designed 2.2 Routing in Underwater Networks
for stationary networks. They usually employ query Much research work has been done in the last few years on
flooding as a powerful method to discover data delivery the routing protocols for underwater networks. The
paths. In UWSNs, however, most sensor nodes are mobile, challenges and state-of-art for the routing protocols in
and the “network topology” changes very rapidly even underwater networks have been discussed in detail in [9].
with small displacements. The frequent maintenance and A pioneering work is done in on the routing protocol for
recovery of forwarding paths is very expensive in high underwater networks. In this work, a central master node
dynamic networks, and even more expensive in dense 3- is used to probe the network topology and do the route
dimensional UWSNs. Thus, to provide scalable and establishment. The authors of [10] propose a centralized
efficient routing in UWSNs, we have to seek for new routing algorithm for delay sensitive application and a
solutions. In this paper, we investigate this challenging distributed routing algorithm for delay insensitive
routing problem in UWSNs, with scalability and energy applications in three-dimensional underwater networks. In
efficiency as the design objectives. Moreover, robustness [11], the authors propose a novel method to improve the
is also an important concern due to the high node failure efficiency of the flood-based routing protocol in
rate and error-prone channels in UWSNs. underwater sensor networks. An adaptive routing protocol
for under-water Delay Tolerant Networks (DTN) has been
1.2 Contributions proposed in [12], which divides the network into multiple
In this paper, we propose a novel routing protocol, called layers and every node adaptively finds its routes to the
vector-based forwarding (VBF), to address the routing upper layer according to its past memory. Different from
problem in UWSNs. VBF is robust, scalable and energy all the above work, our VBF takes advantages of the
efficient. It is essentially a location-based routing location information to form one or multiple routing pipes
approach. No state information is required on the sensor from the source to the destination. Multiple routes might
nodes and only a small fraction of the nodes are involved be used simultaneously in VBF to improve the reliability.
in routing. Moreover, in VBF, packets are forwarded along At the same time, the self-adaption algorithm in VBF can
redundant and interleaved paths from a source to a greatly improve the energy efficiency. Thus, our VBF can
destination, thus VBF is robust against packet loss and achieve a good balance between the reliability and energy
node failure. Further, we develop a localized and efficiency. In short, the routing protocols for UWSNs have
distributed self-adaptation algorithm to enhance the to address the node mobility issue at minimum energy
performance of VBF. The self-adaptation algorithm allows expenditure. However, existing routing protocols designed
nodes to weigh the benefit of forwarding packets and for land-based sensor networks can not satisfy this
thus reduce energy consumption by discarding low benefit requirement. When applied directly in the underwater
packets. We evaluate the performance of VBF through sensor network environment, these proposals become very
extensive simulations. Our experiment results show that expensive in terms of energy due to node mobility.
for networks with small or medium node mobility (1 m/s-3
m/s), VBF can effectively achieve the goals of robustness, 3 VECTOR BASED FORWARDING
energy efficiency, and high success of data delivery. PROTOCOL (VBF)
the introduction of the paper should explain the nature of In this section, we present our vector-based
the problem, previous work, purpose, and the contribution forwarding (VBF) protocol in detail.
of the paper. The contents of each section may be provided
to understand easily about the paper. 3.1 Overview of VBF
In sensor networks, energy constraint is a crucial factor
2 RELATED WORK since sensor nodes usually run on battery, and it is
In this section, we will review related work in impossible or difficult to recharge them in most
both terrestrial networks and underwater networks. application scenarios. In underwater sensor networks, in
addition to energy saving, the routing algorithms should be
2.1 Routing in Terrestrial Wireless Networks able to handle node mobility in an efficient way.
Energy efficiency has long been recognized as one of the
most important properties for terrestrial wireless networks.
Many energy efficient routing protocols such as Directed
Diffusion [4], Two-Tier Data Dissemination [5],
GRAdient [6], Rumor routing [7], and SPIN [8], which
aim for high energy efficiency, have been proposed in the
last few years for terrestrial wireless networks. These
protocols can achieve high energy efficiency in the
terrestrial networks. However, they depend on the

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field. The forwarding path is specified by the routing
vector from the sender to the target. Each packet also has a
RADIUS field, which is a pre-defined threshold used by
sensor nodes to determine if they are close enough to the
routing vector and eligible for packet forwarding. There
are two types of queries. One is location-dependent query.
In this case, the sink is interested in some specific area and
knows the location of the area. The other type is location
independent query, when the sink wants to know some
specific type of data regardless of its location. For
example, the sink wants to know if there exist abnormal
high temperatures in the network. Both of these two types
of queries can be routed effectively by VBF.

Fig. 1: A high level view of VBF for UWSNs. I) Query Forwarding: For location dependent queries,
the sink is interested in some specific area, so it issues an
Vector-Based Forwarding (VBF) protocol meets INTEREST query packet, which carries the coordinates of
these requirements successfully. We assume that each the sink and the target in the sink-based coordinate system,
node in VBF knows its position information, which is i.e., it has the information of SP and TP. This query is then
provided by some location algorithms [13]. If there is no directed to the targeted area following the pipe defined by
such localization service available, a sensor node can still SP and TP. For a location-independent query, the TP field
estimate its relative position to the forwarding node by of the INTEREST packet is invalid, and this query will be
measuring its distance to the forwarder and the angle of flooded to the target nodes. Upon receiving such query,
arrival (AOA) and strength of the signal by being armed the intended nodes can compute their locations in the sink-
with some hardware device. In this work, we assume that based coordinate system and then direct the subsequent
the position information can be calculated by measuring data packets to the sink.
the AOA and strength of the signal. In VBF, each packet
carries the positions of the sender, the target, and the II) Source-Initiated Query: In some application
forwarder (i.e., the node which transmits this packet). The scenarios, the source can initiate the query process. VBF
forwarding path is specified by the routing vector from the also supports such source initiated query. If a source
sender to the target. Upon receiving a packet, a node senses some events and wants to inform the sink, it first
computes its relative position to the forwarder. broadcasts a DATA READY packet. Upon receiving such
Recursively, all the nodes receiving the packet compute packets, each node computes its own position in the
their positions. If a node determines that it is sufficiently source-based coordinate system, updates the FP field, and
close to the routing vector (e.g., less than a predefined forwards the packet. Once the sink receives this packet, it
distance threshold), it puts its own computed position in calculates its position in the source-based coordinate
the packet and continues forwarding the packet; otherwise, system and transforms the position of the source into its
it simply discards the packet. In this way, all the packet own coordinate system. Then the sink can decide if it is
forwarders in the sensor network form a “routing pipe”. interested in such data. If so, it may send out an
The sensor nodes in this pipe are eligible for packet INTEREST packet to the area where the source resides.
forwarding, and those which are not close to the routing
vector (i.e., the axis of the pipe) do not forward. Fig.1 3.3 Handling Source Mobility
illustrates the basic idea of VBF. In the above figure, node Since the source node keeps moving, its location
S1 is the source, and node S0 is the sink. The routing vector calculated based on the old INTEREST packet might not
is specified by S1S0. Data packets are forwarded from S1 to be accurate any more. If no measure is taken to correct the
S0. Forwarders along the routing vector form a routing source location, the actual forwarding path might get far
pipe with a pre controlled radius (i.e., the distance away from the expected one; that is, the destination of the
threshold, denoted by W in this paper).As we can see, like data forwarding path most probably misses the sink. We
all other source routing protocols, VBF requires no state propose the following sink-assisted approach to solve this
information at each node. Therefore, it is scalable to the problem. The source keeps sending packets to the sink,
size of the network. Moreover, in VBF, only the nodes and the sink can utilize the source location information
along the forwarding path (specified by the routing vector) carried in the packets to determine if the source moves out
are involved in packet routing, thus saving the energy of of the targeted scope. For example, if the sink calculates
the network. its position as Pc = (xc, yc, zc) based on the coordinates of
the source, Psource = (xsource, ysource, zsource), and its real
3.2 The Basic VBF Protocol position is P = (x, y, z), then the sink can calculate the
VBF is a source routing protocol. Each packet relative position of the sink to the source as (δx, δy , δz) =
carries simple routing information. In a packet, there are (xc -xsource, yc - ysource, zc - zsource).Therefore, the real
three position fields, SP, TP and FP, i.e., the coordinates of position of the source is P’csource = (x - δx, y - δy , z - δz). By
the sender, the target and the forwarder. In order to handle comparing Psource and P’source, the sink can decide if the
node mobility, each packet contains a RANGE field. source moves out of the scope of the interested area. If so,
When a packet reaches the area specified by its TP, this the sink sends the SOURCE DENY packet to the source
packet is flooded in an area controlled by the RANGE

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using P’source. Once the source gets such packets, it stops Fig. 2: Desirableness Factor
sending data. At the same time, the sink initia The Algorithm we propose a self-adaptation algorithm
3.4 The Self-Adaptation Algorithm based on the concept of desirableness factor. This
In the basic VBF protocol, all the nodes close enough to algorithm aims to select the most desirable nodes as
the routing vector are qualified to forward packets. The forwarders. In this algorithm, when a node receives a
protocol is simple and introduces little computation packet, it first determines if it is close enough to the
overhead. However, when sensor nodes are densely routing vector. If yes, the node then holds the packet for a
deployed, VBF may involve too many nodes in data time period related to its desirableness factor. In other
forwarding, which in turn increases the energy words, each qualified node delays forwarding the packet
consumption. Thus, it is desirable to adjust the forwarding by a time interval T adaptation, which is calculated as
policy based on the node density. Due to the mobility of follows:
the nodes in the network, it is infeasible to determine the Tadaptation =p × Tdelay + R – d/v0 , (2)
global node density. On the other hand, it is inappropriate Where Tdelay is a pre-defined maximum delay, v0 is the
to measure the density at the transmission ends (i.e., the propagation speed of acoustic signals in water, i.e.,
sender and the target) because of the low propagation 1500m/s, and d is the distance between this node and the
speed of acoustic signals. We propose a self-adaptation forwarder. In the equation, the first term reflects the
algorithm for VBF to allow each node to estimate the waiting time based on the node’s desirableness factor: the
density in its neighborhood (based on local information) more desirable (i.e., the smaller the desirableness factor),
and forward packets adaptively. the less time to wait. The second term represents the
additional time needed for all the nodes in the forwarder’s
3.4.1 Desirableness Factor: transmission range to receive the acoustic signal from the
We introduce the notion of desirableness factor to measure forwarder. During the delayed time period T adaptation, if a
the “suitableness” of a node to forward packets. node receives duplicate packets from n other nodes, then
Definition 1: Given a routing vector S1S0, where S1 is the this node has to compute its desirableness factors relative
source and S0 is the sink, for forwarder F, the to these nodes, a1, . .. ,an, and the original forwarder, a0. If
desirableness factor, a, of a node A, is defined as min (a0, a1, . . . , an) < ac/2n, where c is a pre-defined initial
a=p/W + (R−d×cosθ)/R, (1) value of desirableness factor (0< c <3), then this node
where p is the projection of A to the routing vector S 1S0, d forwards the packet; otherwise, it discards the packet.
is the distance between node A and node F, and is the From Equation 2, we can see that the optimal node does
angle between vector FS0 and vector FA . R is the not defer forwarding packets in the self-adaptation
transmission range and W is the radius of the “routing algorithm. Thus, we have the following lemma.
pipe” (i.e., the distance threshold).Fig- 2 depict the various Lemma 1: If there exists an optimal path from the sender
parameters used in the definition of desirableness factor. to the target, i.e., each node in the path is the optimal node
From the definition, we see that for any node close enough for its upstream node, then the self-adaptation algorithm
to the routing vector, i.e., 0 < p < W, the desirableness selects this path and entails no delay.
factor of this node is in the range of [0, 3].
For a node, if its desirableness factor is large, it means that
either its projection to the routing vector is large or it is not
far away from the forwarder. In other words, it is not
desirable for this node to continue forwarding the packet.
On the other hand, if the desirableness factor of a node is
0, then this node is on both the routing vector and the edge
of the transmission range of the forwarder. We call this
node as the optimal node, and its position as the best
position. For any forwarder, there is at most one optimal
node and one best position. If the desirableness factor of a
node is close to 0, it means this node is close to the best
position.tes a new INTEREST query and finds a new
source. Fig. 3: VBF with self adaptation

An Example we illustrate VBF with self-adaptation in Fig.
3. In this figure, the forwarding path is specified as the
routing vector S1S0 from the source S1 to the sink S0. The
node F is the current forwarder. There are three nodes
namely, A, B and D in its transmission range. Node A has
the smallest desirableness factor among these nodes.
Therefore, A has the shortest delay time and sends out the
packet first. As shown in this figure, node B is most likely
to discard the packet because it is in the transmission range
of A and it has to re-evaluate the benefit to send the
packet. Node D is out of the transmission range of A;
therefore, it also forwards the packet.

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[3] C. Intanagonwiwat, R.Govindan, and D.Estrin.
4. SUMMARY Directed Diffusion: A Scalable and Roust
We have described the basic VBF routing Communication Paradigm for Sensor Networks. In
protocol and the self-adaptation algorithm. We can see that ACM International Conference on Mobile Computing
VBF addresses the mobility of nodes in the network and Networking (MOBICOM’00), Boston,
effectively. The positioning of nodes is performed locally Massachusetts, USA, August 2000.
[4] C. Intanagonwiwat, R.Govindan, and D. Estrin,
and no global synchronization required. VBF has no
“Directed diffusion: a scalable and roust
requirement for stable forward path. VBF is an energy
communication paradigm for sensor networks,” in
efficient and scalable protocol. 1) In VBF, no state Proceedings of the 6th Annual International
information is required for each node; therefore, it is Conference on Mobile Computing and Networking
scalable to the size of the network; 2) In VBF, only the (MOBICOM ’00), Boston, Mass, USA, August 2000.
nodes close to the routing vector are involved in packet [5] F. Ye, H. Luo, J. Cheng, S. Lu, and L. Zhang, “A two-
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delivery is not dependent on the stable neighborhood, but [6] F. Ye, G. Zhong, S. Lu, and L. Zhang, “GRAdient
on the node density. If there exists at least one path in the broadcast: a robust data delivery protocol for large
“routing pipe” specified by the routing vector, then the scale sensor networks,” ACM Wireless Networks, vol.
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and Applications(WSNA ’02), pp. 22–31, Atlanta, Ga,
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5. CONCLUSION [8] W. R. Heinzelman, J. Kulik, and H. Balakrishnan,
In this paper, we have proposed a vector-based “Adaptive protocols for information dissemination in
forwarding (VBF) protocol to address the routing wireless sensor networks,” in Proceedings of the 5th
challenges in UWSNs. VBF is scalable, robust and energy Annual ACM/IEEE International Conference
efficient: 1) Packets carry routing related information and onMobile Computing and Networking (MOBICOM
no state information is required at nodes. Thus, it is ’99), Seattle,Wash, USA, August 1999.
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6. FUTURE WORK [11] A. Goel, A. G. Kannan, I. Katz, and R. Bartos,
There are several directions in UWSNs worth “Improving efficiency of a flooding-based routing
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