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Energy Efficeient Interference Aware Multipath Routing Protocol in WMSN

Jayashree Agrakhed Department of CSE

P. D. A. Engineering College Gulbarga, India

jayashreeptl@yahoo.com

G. S. Biradar Department of ECE

P. D. A, Engineering College Gulbarga, India

gsbiradar@yahoo.com

V. D. Mytri Principal

G. N. D. Engineering College Bidar, India

vithalmytri@gmail.com

Abstract—Automated information gathering in military, industrial, environmental and surveillance applications which requires improved QoS guarantees as well as high reliability is well supported with Wireless Multimedia Sensor Networks (WMSNs). In this paper, we propose a more reliable energy efficient multi-path routing scheme for multimedia-traffic. The proposed protocol quickly chooses partial disjoint paths in case of node failure to minimize routing overhead. Hence increases the reliability of the packets reaching the destination with minimum delay. Extensive simulations are carried out to show that proposed protocol achieves an efficient tradeoff among reliability, energy consumption and end to end delay. It provides higher packet delivery ratios and lower routing overheads compared to the Maximally Radio disjoint Multipath Routing (MR2) and Hop Count Multipath routing (HCMR) protocols.

Keywords-WSN ,WMSN ,Multipath Routing,QoS parameters

I. INTRODUCTION The emergence of Wireless Multimedia Sensor Networks

(WMSNs) has enhanced the performance of many of the existing applications of WSN such as surveillance applications, disaster relief, homeland security, proactive health care, smart homes, intrusion detection, and target tracking. Reliable environment monitoring is important in a variety of commercial and military application such as in security system to detect intrusions and to monitor the machines for fault detection and diagnosis where the acoustic, seismic and video sensors can be used. The authors of [1-3] discussed various routing techniques considering unique characteristics of sensor networks. The multimedia applications requires addressing additional challenges for energy-efficient multimedia processing, optimal routing and path selection, audio/video rate adaptation to meet the dynamic network topology and application specific QoS guarantees such as end-to-end delay, packet delivery ratio, data rates etc. The WSNs often subject to high failure rate due to environmental noise and obstacles, nodes may die due to battery depletion, environmental changes or malicious destruction. In such environment, reliable and energy efficient data delivery is crucial because sensor nodes operated with limited battery power and error prone wireless channels. In traditional WSNs, faults may either keep occurring at high frequencies, or stop occurring after certain moment in time [4]. The high-frequency fault occurrences have a more serious impact on WMSNs than traditional WSNs, because of huge volume of video or audio stream. The problem of path breaks due to node failure leads to additional routing overhead to find the

additional paths, which reduces the energy of the nodes and affects the network lifetime. Routing protocols must be designed to achieve fault tolerance in the presence of individual node failure keeping energy consumption at minimum. Earlier works using single path routing used flooding to route around failed nodes. Such flooding can adversely impact the lifetime of the energy constrained sensor network. Multipath routing is one way of improving the reliability of the transmitted information. While Multipath routing may be used for various other reasons such as load balancing, congestion avoidance, to reduce the frequency of route inquiries and to achieve a lower overall routing overhead, our objective is to primarily design a Multipath routing framework for providing enhanced robustness to node failures. We choose reliability and energy efficiency as two most important design goals of protocol.

The remainder of the paper is organized as follows. In Section II related work is reviewed. The proposed protocol is presented in section III. In section IV the proposed scheme is compared to other approaches from the literature with the help of simulated results. Conclusions are given in section V.

II. RELATED WORK Multipath routing can reduce the necessity for route updates, balance the traffic load, improves usage of limited energy of sensor nodes. In [5] the authors proposed Classical node-disjoint multipath and a novel braided multipath that consists of partially disjoint alternate paths to show the energy/resilience tradeoffs of these mechanisms for both independent and geographically-correlated failures. In [6], authors propose a novel approach called Label-based Multipath Routing (LMR) which can efficiently find a disjoint or segmented backup path to provide protection to the working path than compared to the disjoint or braided multipath methods. Disjointness [7] allows for a more balanced traffic in the network; however it does not deal with interference. In [8] a totally disjoint multipath routing in multihop wireless networks is presented which provides evaluation of the throughput in a multipath routing strategy considering the impact of interference. The Radio disjoint multi-path routing in MANET is discussed in [9] with an approach to choose multiple paths to be used simultaneously, reducing the effect of interference between nodes as far as possible. In order to measure the interference level of a node, the authors considered a mechanism to measure the load of a node in terms of a parameter to measure the packets transmitted or received by

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the node itself and to measure all packets heard from the others in the vicinity. Author of [10] presented a Maximally Radio-Disjoint Multipath Routing (MR2) for WMSNs to address the problem of interfering paths. In wireless communications, severe performance degradation can result from interference during data transmissions. Only a few works have actually considered the effect of interference in Multipath routing. It is observed that their is an urgent need to develop routing protocols which are more energy efficient, reliable and have better control on the QoS requirements of multimedia data. In this paper we have proposed a routing protocol to improve energy efficiency and reliability using Multipath routing while taking into consideration the impact of interference. The inter-path interference in a single channel is considered. We have considered single source-Destination pair and intra-session interference. Interference awareness and energy saving are achieved by switching a subset of sensor nodes in a passive state in which they do not take part in the routing process. This helps to maximize the network lifetime.

III. PROPOSED PROTOCOL We have considered the Multipath based approach to find quick alternate paths for the data to ensure end to end transmission in case of node failure due to energy consumption. The proposed protocol is compared with MR2 and Hop Count Multipath Routing (HCMR) protocols. HCMR don’t consider the interference and chooses path with best hop count.The rediscovery process in MR2 adds up to routing overhead and wastes the energy. In order to build paths, proposed protocol follows the main ideas behind existing AODV routing algorithm. The proposed Energy Efficient Interference Aware Multipath Routing (EEIAMR) protocol works as follows:

ALGORITHM: EEIAMR Step1: For each node find neighboring nodes

The sink broadcasts messages to create Neighbor Node (NN) table at each node to maintain the addresses of all the nodes that are able to communicate with the node directly without using relay node during topology setup.

Step2: Find paths from source node

When the source detects an event or has the data to transmit and if there is no route to destination established yet, it will start the route request procedure. Source node sends the route requests only to the neighbor nodes in NN table. Every intermediate node forwards the request only to the neighbor that is closer to sink node than oneself and farther from the source node and route discovery continued until sink is reached. Since it restricts flooding only to neighbors in the table, this reduces the communication overhead which is more if route discovery flooded to the whole network. Based on minimum hop count a best path is chosen from source to sink. Since the paths are formed only when required, it reduces the overhead of sensor node.

Step3: Data transmission

Once the multiple paths are discovered, source node chooses best path for data transmission. Only one path is chosen for data forwarding. To forward the data, each selected sensor node only needs to know about its neighboring node and do not need to maintain the whole path information. A node with large residual energy and farthest from the previous one is selected as the next intermediate hop.

Step4: Find alternate path

The data is sent only on one path initially. While transmission if any of the nodes on the primary path have less residual energy then partially disjoint path based on the NN table information is selected to route the traffic. As it has built multiple partial disjoint paths from source to sink, overhead of additional route discoveries is reduced in case of path failures due to node/link failure. For any node during data transmission, if next hop node becomes unavailable due to less energy, path fails. Each node finds the alternate paths checking their neighbors from the NN table to recover quickly from route breaks without initiating a new route discovery phase once again. The previous node of the failed one will attempt to find another available neighbor node as the next hop node. Reducing the effect of interference between nodes as far as possible gives the radio disjoint paths. For this failed node is put into passive state which prevents lower energy nodes to participate in the route and reduces the interference. From the new selected neighbor node again forwarding principle is executed and it may rejoin the primary path which in turn reduces the path length.

IV. SIMULATION SETUP The effectiveness of the proposed work is judged through simulation in NS-2 Network Simulator [11]. In this we implemented the interference un-aware HCMR and interference-aware MR2 protocols, and the proposed EEIAMR protocol. In all the implemented schemes the quality of metric used is path length - number of hop length from the source to the sink. In simulations, a square sensor field of size 1000 x 1000 m2 is considered where given number of N2 of static sensor nodes ranging from 49 to 625 are deployed in a randomized grid. The sink is located at the upper right corner (coordinates 1000, 1000) and a given transmitting sources are selected randomly. The transmission radio range is set for all nodes as 1500/N and thus giving mean node degree of 8. We assume that each node knows the position of sink node. A Constant Bit Rate (CBR) traffic flow is generated between source and destination to simulate video streams. The data packet size is of 100 bytes with packet interval set to 0.005s. The control packet size is assumed as 10 bytes. Simulations are repeated for several times to evaluate the performance of the system.

A. Energy model

The initial energy of all the nodes assumed as 10 joules. All the sensors are assumed to have same processing capability. For communication, we adopted the radio model of [12]. To transmit a k-bit message a distance ‘d ’, the consumed energy is given by

, (1)

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To receive a k-bit message, a sensor consumes the energy

(2)

Where is the dissipated energy by the radio to run the transmitter or the receiver circuitry and is the required energy by the transmit amplifier.

B. Simulatiion parameters

The Table I shows the parameters that are considered for the simulation.

TABLE I. SIMULATION PARAMETERS

Parameter Name Value Channel Type Channel/WirelessChannel Radio-Propagation model

Propagation/TwoRayGround

Network interface type

Phy/WirelessPhy

Mac Type Mac/802_11 Interface Queue Type

Queue/DropTail/PriQueue

Link Layer Type LL Antenna model Antenna/OmniAntenna Grid Size 1000X1000 Initial Energy 10 joules Nodes Status Static Nodes Number 49 to 625

C. Performance parameters

We have evaluated the performance according to the following metrics and compared with an interference-unaware HCMR and interference-aware MR2 protocols.

• Mean number of built paths: It is defined as the mean number of paths built.

• Mean Delay: It is defined as the average time between the moment a data packet is sent by a data source and the moment the sink receives the data packet.

• Overall consumed energy per message: It is defined as the overall consumed energy per message to reach the sink.

• Load Fairness: Load fairness ( ) is calculated in terms of the number of messages processed by the sensors involved in the routing process. We used commonly used formula for the load fairness as shown in equation (3)

��� ∑ ∑ (3) Where is the number of messages processed by the node ‘i ’ and ‘ n ’ is the number of nodes involved in the routing process.

D. Simulation results In this section the performance of proposed routing scheme is compared with the MR2 and HCMR protocols.

Figure 1. Total number of built paths

Figure 2. End to End Delay

The total number of built paths as a function of number of nodes is presented in Fig. 1 for the protocols MR2, HCMR and the proposed EEIAMR protocol. We can see that the EEIAMR is able to build less number of paths than compared to MR2 and HCMR. In case of HCMR, more number of sensors will involve due to the lack of interference awareness. Hence it leads to the more number of built paths from 6 to 8. In MR2 built paths are in the range of 2 to 4 and the number of non- interfering paths decreases as the network size increases. In comparison with the HCMR and MR2, the EEIAMR involves restricted numbers of sensors in the routing process due to interference awareness, which not only reduces the length of the path but also the number of paths built. The number of paths built remains constant for the proposed protocol even if the network size is increased. Thus the proposed protocol outperforms the other two protocols.

Fig. 2 shows variations of end-to-end delay as the number of nodes increases. It is assumed that delay is equivalent to total hop count delays. Since EEIAMR uses shorter path lengths with restricted number of sensors involvement in the routing process, the delay for the data to reach the sink will decrease. This behavior is more noticeable when the number of nodes increases.

Fig. 3 shows routing overhead for the three approaches as a function of number of nodes. If routing overhead is large, more energy is wasted in processing the route request packets which affects the overall network lifetime. As the HCMR has built many paths initially, there is less additional routing overhead compared to others. If active path fails in MR2, it floods another series of request messages to build additional paths, costing extra

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routing overhead which causes energy loss of sensors and hence loss of the packets. The EEIAMR introduces less routing overhead using short alternate paths with less number of nodes and hence less energy consumption as compared to MR2 where full alternate paths are built with more nodes involved. Longer paths have a more chance of having route breaks since one link/node failure on the path results in route invalidation.

Fig. 4 shows energy consumption of the sensors involved in the routing process. It is observed that there is lower node energy consumption of proposed EEIAMR over the other schemes. In HCMR path length is large due to more number of sensors involved increasing the overall energy consumption. The use of full alternate paths and extra routing overhead due to incremental approach of MR2 leads to more energy consumption compared to EEIAMR as it uses short alternate paths and also as the network size is increased the path length becomes even small and reduces the energy consumption.

Figure 3. Overall Routing Overhead

Figure 4. Overall consumed Energy per Message

Figure 5. Load Fairness

Figure 5 shows load fairness among sensors involved in the routing process. A better distribution of energy consumption is achieved in EEIAMR and it is close to the optimal value which is one. Probability that a given node consumes all of its energy before other ones decreases and improves the network lifetime.

V. CONCLUSION

Wireless multimedia sensor networks have a wide range of potential applications which strengthen the human interaction with the physical environment. The introductions of video and imaging sensors have posed additional challenges along with severe energy constraint of sensor nodes. Video and imaging data transmission requires both energy and QoS aware routing in order to ensure efficient usage of the sensors and effective access to the gathered measurements. We have considered Multipath routing with interference awareness in WMSNs using the available energy of the nodes to reduce routing overhead. The proposed protocol routes the traffic through alternate disjoint path when there are lower energy nodes on the primary path to distribute energy consumption overall network. This maximizes the network lifetime. Simulation results have demonstrated the effectiveness of our approach compared to MR2 and HCMR protocol.

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