Modified GPSR Based Optimal Routing Algorithm for Reliable Communication in WSNs B.Shanmuga Raja1
N.Prabakaran1
V.R.Sarma Dhulipala2
Pervasive Computing Technologies Anna University of Technology Tiruchirappalli, Tamilnadu,
[email protected]
Pervasive Computing Technologies Anna University of Technology, Tiruchirappalli, Tamilnadu,
[email protected]
Asst.Professor, Dept of Physics, Anna University of Technology, Tiruchirappalli, Tamilnadu,
[email protected]
Abstract— Geographic routing is one of the most widely used routing strategies in large-scale wireless sensor networks (WSN). With location-based routing, small, cheap and resource constrained nodes can perform the routing function without the need of complex computations and large amount of memory space. In the traditional approach, nodes advertise their availability to update the routing table. We eliminate this to reduce energy consumption. We introduce Modified Greedy Perimeter Stateless Routing (GPSR) routing protocol for efficient communication among sensor nodes, which identifies optimal route based on energy utilization. The implementation of GPSR in sensor networks faces many challenges due to limited memory and battery energy on each node, frequent change of network topology and unreliable infrastructure. Our Modified-GPSR approach results in nearoptimal communication cost across the network. The simulation results prove that the energy and delay in minimized and substantially increases the network lifetime of sensor node. The proposed protocol outperforms the existing routing protocol for WSNs.
Implementation of GPSR must minimize the communication cost. In particular, we are interested in innetwork implementation strategies since routing all sensor data to a central server would incur prohibitive communication costs. In addition, load-balanced implementation strategies are highly desirable, because unbalanced strategies are likely to result in a much shorter network lifetime. Design of communication-efficient and load-balanced in-network implementations of join in sensor networks is particularly challenging due to limited memory available at each node and arbitrary network topologies.
Keywords- GPSR, WSN, Routing Protocol, Network Topology, Sensor nodes, Near-optimal communication
I.
INTRODUCTION
A wireless sensor network is composed of numerous nodes distributed over an area to collect information. The sensor nodes communicate among themselves through the wireless channel to self-organize into a multi-hop network and forward the collected data towards one or more base stations. Each node has one or more sensors, embedded processors and low-power radios, and is normally battery operated. Typically, these nodes coordinate to perform a common task. Low power capacities of sensor nodes result in very limited coverage and communication range compared to other mobile devices. Hence, to successfully cover the target area, sensor networks are composed of large number of nodes. Sensor networks are multi hop wireless networks formed by a large number of resourceconstrained sensor nodes. Each sensor node typically generates a stream of data items that are readings obtained from the sensing devices on the node. Motivated by the above , we develop efficient GPSR routing protocol, since each sensor node has limited battery energy and message communication is the main consumer of energy, distributed
Figure 1. Basic Architecture of Wireless Sensor Network.
II. GPSR Greedy Perimeter Stateless Routing, GPSR, is a efficient routing protocol for wireless sensor networks. Unlike other routing algorithms before it, which use graph-theoretic notions of shortest paths and transitive reachability to find routes, GPSR gives the correspondence between position and connectivity in a wireless sensor network, by using the geographic positions of nodes to make data packet forwarding decisions. GPSR uses greedy forwarding and perimeter forwarding techniques to forward data packets to nodes that are always closer to the target node. In regions of the network where such a greedy path does not exist.
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GPSR recovers by forwarding in perimeter mode, in which a packet traverses successively closer faces of a planar sub graph of the full radio network connectivity graph, until reaching a node closer to the destination, where greedy forwarding resumes. GPSR will allow the building of networks that cannot scale using prior routing algorithms for wired and wireless networks. Such classes of networks include Rooftop networks, Ad hoc networks, Sensor networks, Vehicular networks. GPSR protocol [6] is the earliest geographical routing protocols for Ad hoc networks which can also be used for WSN environment. The GPSR adapts a greedy forwarding strategy and perimeter forwarding strategy to route messages. It makes uses of a neighborhood beacon that sends a node’s identity and its position. However, instead of sending this beacon periodically and add to the network congestion, GPSR [6] piggybacks the neighborhood beacon on every message that is sent or forwarded by the node. Every node in GPSR has a neighborhood table of its own. We will show that geographic routing allows routers to be nearly stateless, and requires propagation of topology information for only a single hop: each node need only know its neighbors’ positions. The self-describing nature of position is the key to geography’s usefulness in routing. The position of a packet’s destination and positions of the candidate next hops are sufficient to make correct forwarding decisions, without any other topological information.
Figure 2. Greedy forwarding example. A is x’s closest neighbor to D.
GPSR is an algorithm which combines two different methods of routing. The first method is the Greedy Packet Forwarding method! This method will be used as long as possible, in some case till the Destination. But when the packet arrives on a node, where the node can't find with the Greedy Packet Forwarding a next node, nearer to the destination, and then will be used the second algorithm, the Perimeter forwarding. On the GPSR Protocol, all node of the network has a local table, in which all neighbour of the node is listed by name (ID) and position. A proactive Broadcast refreshes this table of each node in a regular time interval. The source node gives the packet a destination address. This address will not be changed by any node who forwards the packet. In the header of the GPSR Packets are many more data.
III. MODIFIED GPSR The proposed routing scheme is based on the fact that the energy consumed to send a message to a distant node is greater than the energy needed for a short range transmission. GPSR protocol [12] is extended using aggregation node or head set node. Aggregation node is responsible for Transmitting messages to the distant base station and routing is decided using the respective head set members. The head set is decided on a routine basis with reference to the energy level of the signal received to the base station at the time of reception of “Data packets”.
Figure 3. Perimeter forwarding by Right hand rule.
At one time, only one member of the head set is active and the remaining head set Members are in sleep mode. The task of transmission to the base station is uniformly distributed among all the head set members similar to LEACH protocol. Each cluster has a head set that consists of several virtual cluster heads. The operation on this network involves two process, selection of headsets for the clusters and members of head set transmits data to the base station. Each member of a head set becomes a cluster head once during an epoch depending on their battery power level. At the start, a set of cluster heads are chosen on random basis. These cluster heads send a short advertisement broadcast message. The sensor nodes receive the advertisements and choose their cluster heads based on the signal strengths of the advertisement messages.
Figure 4. Modified GPSR
Each sensor node sends an acknowledgment message to its cluster head. Moreover, the cluster heads choose a set of associates based on the signal analysis of the acknowledgments. A head-set has both cluster head and the associates. The head set, which is responsible to send Messages to the base station, is chosen for each time based on the energy level of the signal received to the base station. The non-cluster head nodes collect the sensor data and transmit the data to the cluster head, in their allotted time slots. The cluster head node must keep its radio turned on to receive the data from the nodes in the cluster. The associate Members of the head set remain in the sleep mode and do not receive any messages. After, some predetermined time interval, the next associate becomes a cluster head and the current cluster head becomes a passive head set member.
given number of cluster heads. The cluster heads broadcast messages to all the sensors in their neighborhood .Then the sensors receive messages from one or more cluster heads and choose their cluster head using the received signal strength. Later, the sensors transmit their decision to their corresponding cluster head. Finally, the cluster heads receive messages from their sensor nodes and remember their corresponding nodes. Energy consumption of each node during data transfer varies with respect to the distance from their respective head sets and head set to the base station via other nodes involved in the network. When the clusters are being formed by the network, head sets are also allocated to decide the optimal number of clusters. Cluster is being optimized based on the energy level consumption in the network. Head set size and energy consumption are directly proportional to each other, such that the head set size optimization in turn decides the power consumption of the network. Once the cluster is being decided with their respective headsets then the source and destination is being decided from the base station. The network is being monitored from the base station to have entire control over it. The “hello packet” is sent from the source to the destination by means of partial flooding using the right hand rule. The flooded packet is being tracked by the base station to form the routing table, to decide the optimal route with respect to energy consumption, shortest path and less delay. The optimal route decision is based on the shortest delay path and less energy consumption in the network as shown in flowchart represented in. The routing table is used to decide the path for the transmission of data in the network. The processed information reaches the base station where the signal is being efficiently used to monitor the physical changes the environment. IV. RESULTS AND DISCUSSION A WSN is simulated with 50 nodes to 500 nodes, each 50 node difference. The source node and target node are assumed. The source node transmits the “Data Packets” to all nearby nodes through right hand flooding technique (Perimeter Forwarding). The flooding data packets are tracked and a routing table is found through right hand flooding techniques, data reachablity is at the base station.
Figure 5. Flowchart of the Modified algorithm
For a sensor network of n nodes, the optimal number of clusters is given as k. All nodes are assumed to be at the same energy level at the beginning. The amount of consumed energy is same for all the clusters. At the start of the election phase, the base station randomly selects a
Figure 6. Optimum path length for various node densities.
Different path to deliver the packet is found through right hand flooding techniques, data reachablity is ensured and a routing table is formed with all the successful routes to target node. Once the routing table is formed, the optimal route is selected based on packet delivery delay, less energy consumption and number of hops. Fig .6 illustrates the variation in optimum number of nodes with respect to the path length variation from 50 to 500 nodes. As the graph shows, more number of nodes would lead to less path length, which in turn consumes less power in the network. The node sizes are randomly changed because of the consideration of both power and time taken for a packet to reach the target node. By using number of hops and delay in each wireless sensor node the time factor has been calculated. The path length decreases when number of nodes are highly similarly the path length will increase when using few number of nodes. Fig. 7 demonstrates the energy consumption with respect to number of nodes .as expected, the energy consumption is reduced when there are optimized number of nodes. Moreover, when more of nodes are used the energy consumption is lower because single cluster head will consume more energy to transmit signal to the base station in wireless sensor network. If the head-set size increases then the energy consumption will automatically decreases as shown in the Fig[7]. Even if the head-set size increasing more than the optimized value energy consumption is ensured and a routing table is formed with all the successful routes to target node. The optimal route is selected based on packet delivery delay, less energy consumption and number of hops.
Figure 8. Comparison of MGPSR with GPSR.
The above figure shows comparative results of GPSR and Modified GPSR in terms of parameters such as Throughput, Energy and Path length. Throughput and Energy consumption of network in MGPSR proves to be more efficient than the Greedy Perimeter Stateless Routing. Due to the minimum path length required by nodes in MGPSR to transmit data, communication will be faster than GPSR V.
CONCLUSION
Our Modified GPSR protocol is implemented on mobile wireless sensor networks. Modified GPSR algorithm has been simulated on different topologies in mobile networks, and a location based routing algorithm that could route packets in a scalable and effective manner has been built. Modified GPSR algorithm provides energy efficient routing protocol with the ability to route data from event tracking node (source) to event requesting node (destination) and assures reliable delivery of packets. Due to large amount of data generated in the network, assortment of efficient routes can have great impact on the life time of sensor network. Furthermore, it is accounted that Modified GPSR produces good performance in routing path lengths compared to existing protocols. Decreased hop counts from source node to the destination implies more power efficiency and less delay in sensor networks. REFERENCES [1]
[2] Figure 7. Energy Consumption in various node density
The figure shows that energy consumption is reduced when the head-set size is increased. From the above figure, it is implied that for a network which consists of 500 more nodes, the optimum range of energy that are consumed are decreases. It is inferred, as the number of cluster increases the energy consumption will decreases.
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