This document summarizes a research paper on a virtual position-based routing protocol for wireless sensor networks. The protocol aims to address the "void routing problem" that occurs in geographic routing when a node has no neighbors that are closer to the destination. The proposed protocol maps node coordinates on the edges of voids to a virtual circle to transform the random network structure and allow greedy forwarding to continue. It divides the area around voids into three regions and applies different routing strategies in each region. Simulation results show the protocol achieves higher delivery rates, shorter paths, lower overhead and energy consumption compared to protocols using face routing to bypass voids.

1. Integrated Intelligent Research (IIR) International Journal of Business Intelligents
Volume: 05 Issue: 01 June 2016 Page No.65-68
ISSN: 2278-2400
65
Virtual Position based Olsr Protocol for Wireless
Sensor Networks
N. Sripathi 1
, M.Saveetha 2
1
PG scholar, Dept. of CS, Pavendhar Bharathidasan College of Engineering and Technology, Trichy, Tamilnadu, India.1
2
Assistant professor, Dept. of CS, Pavendhar Bharathidasan College of Engineering and Technology, Trichy, Tamilnadu, India.2
Email:nsripathi83@gmail.com1
,savi.sri.sv@gmail.com2
Abstract - In wireless sensor networks usually taken in routing
void problem in geographical routing in high control overhead
and transmission delay .The routing void protocol is proposed in
this paper is efficient bypassing void routing protocol. This
protocol based on virtual co-ordinates is to transform a structure
of random process in virtual circle .The circle are composed by
void edge in to by mapping of edge nodes. In this paper to used
the greedy forwarding algorithm. This algorithm can be process
on virtual circle. The virtual circle greedy forwarding failing on
routing void process. There are forwarding process are source to
destination. The proposed protocol as find the shortest path, long
transmission and High quality link maintenance.
Keywords: void routing, geographical, routing protocol.
I. INTRODUCTION
The wireless sensor networks fields one of the key technologies
is routing protocol. The sensor nodes are path depending on the
location information of routing geographic. The WSNs is large
scale wide application of geographic routing. The geographic
information is more efficient, high expansibility and low
influence. The sensor nodes are encountered of random
distribution from result. The greedy forwarding algorithm in
routing will fails, in such situation data transmission also fails.
The simple principle of greedy forwarding is low complexity.
The virtual circle to solve the routing void problem makes in
greedy forwarding algorithm. This algorithm works in
forwarding process. In this way of reduce overhead control
packet and energy consumption can be reduced. The existing
system OLSR protocol is nodes are banned from the selected
nodes in order to prevent the routing void. The transmission
information path between source and destination is achieved the
few hops. In each and every transmission is no need to full
information in hop.
A. Problem definitions
The sensor nodes are modeled by unit graph. The all nodes with
in communication ranges RC and nodes n are links in
bidirectional. Routing is an important issue that affects wireless
sensor networks. Geographic routing uses the physical location
as the node address. The source node determines the destination
address by looking it up from the location server or by
computing it using a hash function in a data-centric storage
scheme. The node usually forwards the packet to a neighbor
closer to the destination. This, however, may take the packet to a
dead-end node, that is, a node with no neighbor closer to the
destination. In GPSR and GFG routing, the FACE algorithm is
used on a planar graph to deal with the dead-end node problem.
In addition, GSR routing and a combination of the FACE
algorithm and the shortcut-based procedure are proposed to
improve routing efficiency. GSR routing builds a planar routing
sub graph, termed the Restricted Delaunay Graph (RDG), such
that a path exists whose distance, in terms of the Euclidean
distance or hop distance, in RDG is only the constant times to the
minimum distance between any pair of nodes. Geographic
routing protocols require nodes to have geographic information
that is obtained with difficulty in wireless sensor networks
because devices that operate via the geographic positioning
system (GPS) consume a large amount of power and do not work
indoors.Routing protocols based on virtual coordinates that
operate without the GPS assistance are proposed in wireless
sensor networks. Through an iterative procedure, a relaxation
algorithm assigns virtual coordinates to nodes that are close to
their physical locations, consuming, in the process, a great deal
of message broadcast overhead. In the distance between any two
nodes is first estimated by an all-pair, shortest-paths algorithm.
Subsequently, multidimensional scaling (MDS) is used to derive
node locations that fit the estimated distances. In seed nodes are
preprogrammed with their physical locations. Each node finds its
location by determining the shortest hop counts to seed nodes
and using the least square error method. In the locations of sensor
nodes are estimated by mobile robots that collect the signal
strength of the messages sent by sensors. However, these
methods do not guarantee packet delivery because the FACE
algorithm cannot be used to solve the dead-end node problem
due to the local error in the virtual coordinate assignment.
B. Void routing in geographic
The geographic routing is greedy forwarding adopted can be
interrupted due to radio coverage. The greedy algorithm in range
of communication causes of greedy forwarding failing. The
sensor nodes are tries to forward the one neighbor nodes to other
destination nodes. A routing void is encountered by nodes
doesn’t exist. In such situation greedy forwarding can be fails. As
show in Fig.1 node n, the packet tires to forward a destination
node d1.The node n2 is set of {n1, n3, n4} closer to the
destination d1. A routing void is encountered by node n5, tires to
packet forward to destination node d2.The packet can arrival the
d1 with paths of n5,n6,n7,d1 without routing problems.
II. RELATED WORKS

2. Integrated Intelligent Research (IIR) International Journal of Business Intelligents
Volume: 05 Issue: 01 June 2016 Page No.65-68
ISSN: 2278-2400
66
The structure component of every edge nodes are only two
neighbor nodes on the circle. The all edge nodes are around the
obstacle distance to point 0. R is a constant. The edge nodes are
locate on center point 0 and radius R. Many difficulties
associated with Virtual Coordinate System (VCS) based schemes
are attributable to lack of information about the physical
network. Layout information such as physical voids and relative
positions of sensor nodes with respect to X-Y directions are
absent. Even though VCS is based on connectivity, explicit
information on hop distances between pairs of nodes is not
available and difficult to estimate. Absence of connectivity
information, on the other hand, is the cause for many problems in
physical domain routing. Combining connectivity based
information in VCS and position or direction information in a
network essentially would combine the advantages of VCR and
GR schemes. However, this has to be done without inheriting the
need for accurate and costly node localization. Our approach is
based on the use of topology preserving maps, derived using
virtual coordinates alone, for geographic information instead of
physical locations. This way, we are able to combine the
advantages of physical and logical routing schemes without
inheriting their disadvantages. No such scheme is currently
available. Geographic-Logical Routing (GLR), transforms the set
of VCs to a set of Cartesian coordinates (2D topological
coordinates)and switches between Geographic Routing that use
Cartesian coordinates and Logical Routing that use virtual
coordinates to achieve higher routability. We demonstrate that
the topology maps are actually more useful than Geographic
maps for WSN routing as the topology coordinates more
accurately select the neighbor to forward the packet to than the
geographic coordinates.Traditional ad hoc routing protocols are
not a good fit for Wireless Sensor Networks (WSN) for the
following reasons. WSNS often require data dissemination
patterns that are not efficiently mapped to the unicast
connections assumed by ad hoc protocols. Further, nodes need to
maintain routing state specific to destinations of active routes;
this state may become invalid due to changes that are not near to
the node. Finally, because of the need to maintain non-local state,
this approach requires that the nodes have globally unique
identifiers. As a result, this approach is not ideal for WSNs
which favor routing protocols that support data-centric operation,
localized interactions and supporting arbitrary data-driven
dissemination with in-network processing. In contrast to
traditional ad hoc protocols. Geographical routing algorithms
provides attractive properties for WSNs. In these algorithms,
nodes exchange location information with their neighbors.
Packets addressed to a destination must provide its location. At
every intermediate hop, the subset of the neighbors that are
closer to the destination is called the forwarding set. Routing
simply forwards a packet to one of the nodes in the forwarding
set. This process is repeated greedily until the packet reaches the
destination. Thus, interactions are localized to location exchange
with direct neighbors and there is no need for global identifiers.
The main steps of entire process are
A. Void Detecting Phase
B. The main function of the void detecting phase is to
collect edge node information around the routing void
after the void is encountered.
B. Virtual Coordinate Mapping Phase
The virtual coordinate mapping phase is responsible for mapping
the edge node coordinates stored in the detecting packed to a
virtual circle, i.e., converting a structure composed of edge nodes
to the structure without routing void
.
Fig. No. 3 virtual coordinate mapping
C. Void Region Dividing Phase
The main function of the void region dividing phase is to divide
the surrounding area of the void into three different regions, in
which different routing strategies are applied. According to the
void position and the location of destination node of the packets,
the surrounding area of a void is divided into approaching region,
departing region and free region.
Fig. No. 3 Void region Diving phase
After implementing the three phases above, the edge nodes of
void contain two types of location information which are
geographic coordinates and virtual coordinates, and that
surrounding area of routing void has been divided into three
different regions according to the destination node.
III. PROPOSED SYSTEM
The proposed system also maintains the partial path information
of previous transmission. The link quality of with all the
neighbors is checked periodically and so the base station
communication is reduced. Like existing system, the optimal
routing path between the source and the destination is achieved
with fewest hops. No need of full hop information calculation for
each and every transmission. The proposed system aims to find
the shortest path, each individual hop usually has long
transmission distance with high quality link maintenance. In a
WSN, it is prohibitive to implement the table-driven shortest path
routing (SPR), which requires per-destination states maintained

3. Integrated Intelligent Research (IIR) International Journal of Business Intelligents
Volume: 05 Issue: 01 June 2016 Page No.65-68
ISSN: 2278-2400
67
by individual nodes. When the network scales to thousands of
nodes, the large size routing tables containing thousands of
entries may not be affordable to resource - constrained sensors.
The conflict between the large size network with a random
structure and the small routing table affordable to a sensor node
raises fundamental challenges to point-to-point routing in WSNs.
This project proposed an efficient bypassing void routing
protocol based on virtual coordinates. The basic idea of the
protocol is to transform a random structure composed of void
edges into a regular one by mapping edge nodes coordinates to a
virtual circle. By utilizing the virtual circle, the greedy
forwarding can be prevented from failing, so that there is no
routing void in forwarding process from source to destination
and control overhead can be reduced. Furthermore, the virtual
circle is beneficial to reduce average length of routing paths and
decrease transmission delay. The proposed protocol has higher
delivery ratio, shorter path length, less control packet overhead,
and energy consumption.It is believed that almost all the system
objectives that have been planned at the commencement of the
software development have been net with and the
implementation process of the project is completed. A trial run of
the system has been made and is giving good results the
procedures for processing is simple and regular order. The
application eliminates the difficulties in the existing system. It is
developed in a user-friendly manner. The application is very fast
and any transaction can be viewed or retaken at any level. Error
messages are given at each level of input of individual stages.
This software is very particular in reducing the difficulty in
analyzing the router algorithms. The application works well for
given tasks in network environment. Any node with .Net
framework installed can execute the application.After
implementing the three phases above, the edge nodes of void
contain two types of location information which are geographic
coordinates and virtual coordinates, and that surrounding area of
routing void has been divided into three different regions
according to the destination node. Discovery node restarts greedy
mode by utilizing the virtual coordinates, the packet stored in the
first phase is forwarded to relay nodes. In the greedy mode, the
ways to select relay node in three regions are different, but they
all use the greedy algorithm.
IV. SYSTEM DESIGN AND
IMPLEMENTATION
Fig. No. 3 Architecture Diagram
A. ENHANCED ROUTING PROTOCOLS
Along with existing system implementation, the proposed system
also maintains the partial path information of previous
transmission. The link quality of with all the neighbors is
checked periodically and so the base station communication is
reduced. Like existing system, the optimal routing path between
the source and the destination is achieved with fewest hops. No
need of full hop information calculation for each and every
transmission. The proposed system aims to find the shortest path,
each individual hop usually has long transmission distance with
high quality link maintenance.
B. PROTOCOL ANALYSIS
1) Routing Path Analysis:
According to the description of section III.B, after the
virtual coordinate mapping phase, the neighbors of the edge
nodes around the routing void receive the broadcasting messages.
These neighbor nodes have the opportunity to establish a short
path by utilizing the routing void information before void is
encountered. As shown in the node tries to send a packet to a
destination node. After sends the packet to by greedy algorithm,
a routing void is encountered at node.If face forwarding is
adopted to solve routing void problem,it is always activated at
the edge node
2) Control Overhead Analysis:
Assuming the length of control packet header in the greedy
algorithm is Lg, the lengths of detecting packet and distributing
packet in BVR-VCM are Lde and Ldi respectively, the edge node
number of routing void is Ns the average number of hops from
source to destination is hBVR-VCM. When n packets are sent, the
length of the control packet is (Lde + Ldi ) × Ns + Lg × hBVR-VCM
× n The average overhead of the control packet for each
packet is LBVR-VCM = (Lde + Ldi ) × Ns/n + Lg × hBVR-VCM
As shown in when the number of packets increases, the average
overhead is approximately equal that in greedy algorithm: LBVR-
VCM ≈ Lg × hBVR-VCM (9) Comparing with protocol based on face
forwarding, assuming the length of control packet header in the
greedy algorithm is L f , the proportion of the greedy algorithm is
g, and the average number of hops from source to destination is
hg. When n packets are sent, the length of control packet is (Lg ×
g + L f (1 − g)) × hg × n The average overhead of the control
packet for each packet is LFACE = (Lg × g + L f × (1 − g)) × hg
Since 0 < g < 1, L f > Lg, and hBVR-VCM ≤ hg learnt from section
IV.A, then Lg × hBVR-VCM ≤ Lg × hg < LFACE < L f × hg. For the
same fixed wireless sensor network, g is constant. In this
condition, no matter how many packets are send, LFACE is
constant, the value range of LFACE is . While LBVR-VCM decreases
as the increasing of the packets sent. So there exists a value
named nc, if n > nc, there is LBVR-VCM < LFACE, at this point the
control packet in BVR-VCM is always smaller than that in the
face forwarding protocol.

4. Integrated Intelligent Research (IIR) International Journal of Business Intelligents
Volume: 05 Issue: 01 June 2016 Page No.65-68
ISSN: 2278-2400
68
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