International Journal of Advanced Research in Computer Science and Software Engineering

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1 ISSN: X International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: Energy Optimization Routing Techniques In Wireless Sensor Networks G. Nivetha Asst. Prof, Department of ECE, Anna University of Technology, Tamilnadu, India Abstract - Wireless sensor network (WSN) is a wireless network consists of base station and hundreds to thousands of small sensor nodes with sensing, computation, and wireless communications capabilities. Each sensor collects data from the monitored area and routes data back to the base station or sink. These sensor nodes have some constraints due to their limited energy, storage capacity and computing power. A primary goal in the design of wireless sensor networks is its lifetime maximization, constrained by the energy capacity of batteries. Routing protocols are in charge of discovering and maintaining the routes in the network. Many routing, power management, and data dissemination protocols have been specifically designed for WSNs where energy awareness is an essential design issue. Routing protocols in WSNs might differ depending on the application and network architecture. Overall, the routing techniques are classified into three categories based on the underlying network structure: flat, hierarchical and location-based routing. Clustering or hierarchical routing is introduced to WSNs because of its network scalability, energy-saving attributes and network topology stabilities. In Cluster routing, sensors are divided into groups called clusters, with each cluster electing one node as the head of the cluster, so that sensors communicate information only to cluster heads and then the cluster heads communicate the aggregated information to the processing center, may save energy. Thus, creation of clusters and assigning special tasks to cluster heads can greatly contribute to overall system scalability, lifetime, and energy efficiency. This paper surveys the different clustering algorithms for WSN. Keywords - Clustering, energy, efficiency, scalability, hierarchical 1. INTRODUCTION Recent advances in miniaturization and low-power design have led to the development of small-sized battery operated sensors that are capable of detecting ambient conditions in the environment surrounding them and then transform these measurements into signals that can be processed to reveal some characteristics about phenomena located in the area around these sensors. A large number of these sensors can be networked in many applications that require unattended operations, hence producing a wireless sensor network (WSN) [4]. WSNs have profound effects on military and civil applications such as target field imaging, intrusion detection, weather monitoring, security and tactical surveillance, distributed computing, detecting ambient conditions such as temperature, movement, sound, light, or the presence of certain objects, inventory control, and disaster management [1].Deployment of a sensor network in these applications can be in random fashion or manual. Creating a network of these sensors can assist rescue operations by locating survivors, identifying risky areas, and making the rescue team more aware of the overall situation in a disaster area [2] [3].. A sensor node typically consists of four basic components: a sensing unit, a processing unit, a communication unit, and a power unit, which is shown in Fig. 1.1 [12] [23]. The sensing unit usually consists of one or more sensors and analog to digital converters (ADCs). Sensor nodes sense or measure physical data of the area to be monitored. The continual analog signal sensed by the sensors is digitized by an analog-to-digital converter and sent to the processing unit. The processing unit usually consists of a microcontroller or microprocessor with memory, which provides intelligent control to the sensor node. The communication unit consists of a short - range radio for performing data transmission and reception over a radio channel. The power unit consists of a battery for supplying power to drive all other components in the system [4]. Sensor nodes are usually scattered in a sensor field, this is an area where the sensor nodes are deployed. Sensor nodes coordinate among themselves to produce high-quality information about the physical environment. Each of these scattered sensor nodes has the capability to collect and route data either to other sensors or back to an external BS(s). A BS may be a fixed or mobile node capable of connecting the 2012, IJARCSSE All Rights Reserved Page 344

2 sensor network to an existing communications infrastructure or to the internet where a user can have access to the reported data. One of the advantages of wireless sensor networks (WSNs) is their ability to operate unattended in harsh environments in which contemporary human-in aggregation in a hierarchical manner is widely used for prolonging the network lifetime. Data aggregation can eliminate data redundancy and reduce the communication load. Since large numbers of sensor nodes are densely deployed, neighbor nodes may be very close to each other. Hence, multihop communication in sensor networks is expected to consume less power than the traditional single hop communication. Sensor nodes carry limited, generally irreplaceable, power sources [18]. Sensor networks contain too much data for an end-user to process. Therefore, automated methods of combining or aggregating the data into a smaller set of meaningful information are required [7]. II. ROUTING IN WSN Routing protocols are in charge of discovering and maintaining the routes in the network. Many routing, power management, and data dissemination protocols have been Fig. 1 The components of Sensor node specifically designed for WSNs. In general, routing in WSNs can be divided into flat-based routing, location-based -the-loop monitoring schemes are risky, inefficient and routing and hierarchical-based routing, depending on the sometimes infeasible [6]. Therefore, sensors are expected to network structure [4] [5] [8] [14]. In flat-based protocols, all be deployed randomly in the area of interest by a relatively nodes are typically assigned equal roles or functionality. uncontrolled means, e.g. dropped by a helicopter, and to Location-based protocols utilize the position information to collectively form a network in an ad-hoc manner [4]. Given relay the data to the desired regions rather than the whole. the vast area to be covered, the short lifespan of the batteryoperated Hierarchical protocols aim at clustering the nodes so that sensors and the possibility of having damaged cluster heads can do some aggregation and reduction of data nodes during deployment, large population of sensors are in order to save energy than flat and location based routing expected in most WSNs applications. It is envisioned that [6] [7]. In a hierarchical or cluster based routing, sensors hundreds or even thousands of sensor nodes will be are divided into groups called clusters, with each cluster involved. Designing and operating such large size network electing one node as the head of the cluster, so that sensors would require scalable architectural and management communicate information only to cluster heads and then the strategies. In addition, sensors in such environments are cluster heads communicate with the base station [11]. As energy constrained and their batteries cannot be recharged. shown in Figure : 2, each cluster is managed by a special Therefore, designing energy-aware algorithms becomes an node or leader, called cluster head (CH), which is important factor for extending the lifetime of the sensors. responsible for coordinating the data transmission activities Therefore, while traditional networks aim to achieve high of all sensors in its clump.the creation of clusters and quality of service (QoS) provisions, sensor network assigning special tasks to cluster heads can greatly protocols must focus primarily on power conservation. They contribute to overall system scalability, lifetime, and energy must have inbuilt tradeoff mechanisms that give the end efficiency [6] [11]. Hierarchical routing is an efficient way user the option of prolonging network lifetime at the cost of to lower energy consumption within a cluster, performing lower throughput or higher transmission delay. Due to the data aggregation and fusion in order to decrease the number high density, multiple nodes may generate and transmit of transmitted messages to the BS. Besides achieving redundant data about the same event to the sink node, energy efficiency, clustering reduces channel contention and causing unnecessary energy consumption and hence a packet a collision, resulting in better network throughput significant reduction in network lifetime [19]. For a sensor under high load.clustering has been shown to improve node, energy consumption includes three parts: data sensing, network lifetime, a primary metric for evaluating the data processing, and data transmission/reception, amongst performance of a sensor network. In addition to supporting which, the energy consumed for communication is the most network scalability, clustering has numerous advantages. It critical. In addition to helping avoid information overload, can localize the route set up within the cluster and thus data aggregation, also known as data fusion, can combine reduce the size of the routing table stored in the individual several unreliable data measurements to produce a more node [6]. Clustering can also conserve communication accurate signal by enhancing the common signal and bandwidth since it limits the scope of inter-cluster reducing the uncorrelated noise [11]. Data gathering is a interactions to CHs and avoids redundant typical operation in many WSN applications, and data 2012, IJARCSSE All Rights Reserved Page 345

3 exchange of messages among sensor nodes [15] [22]. Moreover, clustering can stabilize the network topology at the level of sensors and thus cuts on topology maintenance overhead. The CH can also implement (CH) nodes compress data arriving from nodes that belong to the respective cluster, and send an aggregated packet to the base station in order to reduce the amount of information that must be transmitted to the base station. LEACH uses a TDMA/CDMA MAC [4] to reduce inter-cluster and intracluster collisions. However, data collection is centralized and is performed periodically. Therefore, this protocol is most appropriate when there is a need for constant monitoring by the sensor network. A user may not need all the data immediately. Hence, periodic data transmissions are unnecessary which may drain the limited energy of the sensor nodes. After a given interval of time, a randomized rotation of the role of the CH is conducted so that uniform energy dissipation in the sensor network is obtained. Fig 2: Clustering in WSN optimized management strategies to further enhance the network operation and prolong the battery life of the individual sensors and the network lifetime. A CH can schedule activities in the cluster so that nodes can switch to the low-power sleep mode most of the time and reduce the rate of energy consumption. Since a network is characterized by its limited wireless channel bandwidth, it would be beneficial if the amount of data transmitted to the sink can be reduced. Using clustering, the network appears smaller and more stable. The information, generated from neighboring sensor nodes, is often redundant and highly correlated, so data aggregation by each cluster head conserves communication bandwidth as well. Moreover, the ability to use different power levels in the inter - cluster and intra cluster communication reduces the interferences and the collisions in the network resulting in a better throughput. Clustering is a challenging task. CHs often lose more energy compared to regular nodes. It is necessary to perform reclustering periodically in order to select energy-abundant nodes to serve as CHs, thus distributing the load uniformly on all the nodes. Clustering mechanisms are helpful to reduce data latency and increase network lifetime [10] [13]. The next section paper surveys the different clustering algorithms for WSN. III. ENERGY-EFFICIENT CLUSTER BASED ROUTING TECHNIQUES 3.2. Power-Efficient Gathering in Sensor Information (PEGASIS) In [20], Lindsey proposed an enhancement over the LEACH protocol was proposed. The protocol, called Power-Efficient Gathering in Sensor Information Systems (PEGASIS), is a near optimal chain-based protocol. The basic idea of the protocol is that in order to extend network lifetime, nodes need only communicate with their closest neighbors, and they take turns in communicating with the BS [16] [21]. When the round of all nodes communicating with the BS ends, a new round starts, and so on. This reduces the power required to transmit data per round as the power draining is spread uniformly over all nodes. Hence, PEGASIS has two main objectives. Fig. 3 : Chaining in PEGASIS First, increase the lifetime of each node by using collaboration techniques.second,allow only local coordination between nodes that are close together so that the bandwidth consumed in communication is reduced. Unlike LEACH, [7] [19] [20] PEGASIS avoids cluster formation and uses only one node in a chain to transmit to the BS instead of multiple nodes. To locate the to all neighboring nodes and then adjusts the signal strength so that only one node can be heard. The chain in PEGASIS will consist of those nodes that are closest to each other and form a path to the BS as shown in Figure:3. The aggregated form of the data will be sent to the BS by any node in the chain and the nodes in the chain will take turns sending to the BS. The chain construction is performed in a greedy fashion. Simulation results showed that PEGASIS is able to increase the lifetime of the network to twice that under the LEACH protocol [22]. Such performance gain is achieved 3.1 Low Energy Adaptive Clustering Hierarchy (LEACH) A hierarchical clustering algorithm for sensor networks, called Low Energy Adaptive Clustering Hierarchy LEACH [4] [7] [9] [17] [19] is a cluster-based protocol, which includes distributed cluster formation. LEACH randomly selects a few sensor nodes as cluster heads (CHs) and rotates this role to evenly distribute the energy load among the sensors in the network. In LEACH, the cluster head 2012, IJARCSSE All Rights Reserved Page 346

4 through the elimination of the overhead caused by the dynamic cluster formation in LEACH, and decreasing the number of transmissions and reception by using data aggregation. Although the clustering overhead is avoided, PEGASIS still requires dynamic topology adjustment since a sensor node needs to know about the energy status of its neighbors in order to know where to route its data. Such topology adjustment can introduce significant overhead, especially for highly utilized networks. Moreover, PEGASIS assumes that each sensor node is able to communicate with the BS directly. In practical cases, sensor nodes use multihop communication to reach the BS. Also, PEGASIS assumes that all nodes maintain a complete database of the location of all other nodes in the network. In addition, PEGASIS assumes that all sensor nodes have the same level of energy and are likely to die at the same time. Note also that PEGASIS introduces an excessive delay for distant nodes on the chain. In addition, the single leader can become a bottleneck. Finally, although in most scenarios sensors will be fixed or immobile as assumed in PEGASIS, some sensors may be allowed to move and hence affect the protocol functionality. An extension to PEGASIS, called Hierarchical PEGASIS, was introduced in [2] with the objective of decreasing the delay incurred for packets during transmission to the BS. For this purpose, simultaneous transmissions of data are studied in order to avoid collisions through approaches that incorporate signal coding and spatial transmissions. In the latter, only spatially separated nodes are allowed to transmit at the same time. The chainbased protocol with CDMA-capable node constructs a chain of nodes that forms a tree like hierarchy, and each selected node at a particular level transmits data to a node in the upper level of the hierarchy. This method ensures data transmitting in parallel and reduces delay significantly. Such a hierarchical extension has been shown to perform better than the regular PEGASIS scheme by a factor of about 60. dissipation and prevents that the nodes chosen as CHs do not die quickly. HEEP has two essential phases: the initialization phase that forms chained clusters, and elects CHs, and transmission phases where collected data is transmitted. Since transmission distances are reduced, the total rounds of transmission are imperatively improved. Fig. 4 Chains cluster organization in HEEP 3.4 Power Efficient and Adaptive Clustering Hierarchy (PEACH). In [25] Sangho Yi, proposed a PEACH protocol for WSNs to minimize the energy consumption of each node, and maximize the network lifetime. In PEACH, cluster formation is performed by using overhearing characteristics of wireless communication to support adaptive multi-level clustering and avoid additional overheads. In WSNs, overhearing a node can recognize the source and the destination of packets transmitted by the neighbor nodes. PEACH is applicable in both locationsunaware and location-aware wireless sensor networks. PEACH is designed to operate on probabilistic routing protocols, in order to provide an adaptive multi-level clustering. PEACH is generally more scalable and efficient to the various circumstances than the existing clustering protocols of the wireless sensor networks The PEACH can significantly save energy consumption of each node, prolong the network lifetime, and are less affected by the distribution of sensor nodes compared with other clustering protocols. 3.3 Hybrid Energy Efficiency Protocol (HEEP) HEEP applies PEGASIS principle inside clusters. In HEEP, a chain of nodes in a same cluster is constructed with their closest neighbors and to improve energy [24] dissipation. Nodes communicate only not directly with the CH. Each CH sends the collected data within the cluster to the BS through CHs neighbors, using multi - hop techniques, which limits power consumption. Data aggregation of each node in a chain reduces the amount of exchanging data between nodes and their CH, to preserve node energy reserves. IV. CONCLUSION Figure:4 shows the node organization within clusters. N0 transmits its data to its close neighbor N1; N1 fuses the data Clustering protocol enables sensor nodes to reduce with its own and sends it to another neighbor, until reaching data packets by data aggregation in wireless sensor CH which transmits it to the BS. Hence, in this new networks. The wireless communication cost is decreased by organization (chains clustering), the transmission distances the reduction of the data packets, and the clustering and the number of nodes communicating with CH is protocols improve the lifetime and the energy consumption reduced. That implies better energy saving and prolongs of the networks. In this paper, we presented a survey on an CHs lifetime. HEEP uses the concept of the random rotation energy efficient cluster based routing protocols, in which of the CH roles proposed by LEACH, which controls energy PEACH has no overhead on cluster head selection and 2012, IJARCSSE All Rights Reserved Page 347

5 forms adaptive multi-level clustering PEACH significantly improves the lifetime and the energy consumption of the wireless sensor networks compared with other clustering protocols. REFERENCES [1] I. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, "A survey on sensor networks," IEEE Communications Magazine, Vol: 40 Issue: 8, pp , August 2002 [2] I.F. Akyildiz et al., Wireless sensor networks: a survey, in Elsevier Computer Networks,Vol: 38, pp , 2002 [3] Jennifer Yick, Biswanath Mukherjee, Dipak Ghosal, Wireless sensor network survey, in Elsevier Computer Networks, Vol: 52 pp , 2008 [4] Jamal N. Al-Karaki, Ahmed E. Kamal, Routing Techniques in Wireless Sensor Networks: A Survey, IEEE Wireless Communications, Vol 11, pp.6 28, December 2004 [5] K. Akkaya and M. Younis, "A Survey of Routing Protocols in Wireless Sensor Networks, in the Elsevier Ad Hoc Network Journal, Vol. 3/3,pp , 2005 [6] A. Abbasi, M. Younis, A survey on clustering algorithms for wireless sensor networks, in Elsevier Computer Networks Computer Communications, vol. 30, pp , October [7] W. Heinzelman, A. Chandrakasan and H. Balakrishnan, "Energy-Efficient Communication Protocol for Wireless Mi-crosensor Networks," Proceedings of the 33rd Hawaii International Conference on System Sciences (HICSS '00), January [8] Luis Javier García Villalba, Ana Lucila Sandoval Orozco, Alicia Triviño Cabrera and Cláudia Jacy Barenco Abbas, Routing Protocols in Wireless Sensor Networks, Int.Journal of Sensors,Vol.9,pp [9] Jalil Jabari lotf, Mehran Hosseinzadeh, Rasim M. Alguliev, Hierarchical routing in wireless sensor networks: a survey Proceedings of IEEE International Conference on Computer Engineering and Technology, Vol.3, [10] Congfeng Jiang,Daomin Yuan,Yinghui Zhao, Towards Clustering Algorithms in Wireless Sensor Networks-A Survey, Proceedings of IEEE Communications Society WCNC 2009 proceedings [11] O. Younis, M. Krunz, S. Ramasubramanian, Node clustering in wireless sensor networks: recent developments and deployment challenges, IEEE Network, vol. 20, pp , May [12] Giuseppe Anastasi, Marco Conti, Mario Di Francesco, Andrea Passarella, Energy conservation in wireless sensor networks: A survey, in Eleseiver Ad Hoc Networks,pp ,2009 [13] Seema Bandyopadhyay and Edward J. Coyle, An Energy Efficient Hierarchical Clustering Algorithm for Wireless Sensor Networks, Proceedings of IEEE INFOCOM 2003 [14] Debnath Bhattacharyya 1, Tai-Hoon Kim 1, * and Subhajit Pal, A Comparative Study of Wireless Sensor Networks and Their Routing Protocols, in International.Journal of Sensors,pp ,2010 [15] Sanjeev Saini1, Ram Sewak Singh2 & V. K. Gupta, Analysis of Energy Efficient Routing Protocols in Wireless Sensor Networks, International Journal of Computer Science & Communication, Vol. 1, No. 1, pp , June 2010 [16] Rajni Meelu & Rohit Anand, Performance Evaluation of Cluster-based Routing Protocols used in Heterogeneous Wireless Sensor Networks, International Journal of Information Technology and Knowledge Management, Vol. 4, pp [17] Rajesh Krishnan, David Starobinski, Efficient clustering algorithms for self-organizing wireless sensor networks, in Elsevier Ad Hoc Networks,Vol. 4 (2006) pp [18] Jae-Hwan Chang, and Leandros Tassiulas, Maximum Lifetime Routing in WirelessSensor Networks, IEEE/ACM Transactions on Networking, Vol. 12, August 2004 [19] Ming Liu, Jiannong Cao, Guihai Chen and Xiaomin Wang, An Energy-Aware Routing Protocol in Wireless Sensor Networks, in International.Journal of Sensors, vol.9, pp ,2009 [20] Lindsey, S.; Raghavendra, C. PEGASIS: Power- Efficient gathering in sensor information systems. In Proceeding of IEEE Aerospace Conference, Vol 3, pp ,2009 [21] Shio Kumar Singh 1, M P Singh 2, and D K Singh, Routing Protocols in Wireless Sensor Networks A Survey, International Journal of Computer Science & Engineering Survey (IJCSES),,vol.1, Issue.No.2, November 2010 [22] Shio Kumar Singh, M P Singh, D K Singh, A Survey of Energy-Efficient Hierarchical Cluster-Based Routing in Wireless Sensor Networks, International Journal. of Advanced Networking and Applications,,Vol. 02, Issue. 02, pp , 2010 [23] Jun Zheng, Abbas Jamalipour, Wireless sensor Networks A networking Perspective, Published by John Wiley & Sons, Inc., Hoboken, New Jersey. Copyright 2009 by Institute of Electrical and Electronics Engineers. All rights reserved [24] Djallel Eddine Boubiche and Azeddine Bilami, HEEP (Hybrid Energy Efficiency Protocol) based on chain clustering, International Journal on Sensor Networks, vol. 10,2010 [25] Sangho Yi, Junyoung Heo, Yookun Cho, Jiman Hong, PEACH: Power-efficient and adaptive clustering hierarchy protocol for wireless sensor networks, in Elseiver Computer Communications, vol. 30 pp , , IJARCSSE All Rights Reserved Page 348