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20320130406029

  1. 1. International Journal of Advanced Research ADVANCED RESEARCH IN ENGINEERING INTERNATIONAL JOURNAL OF in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME AND TECHNOLOGY (IJARET) ISSN 0976 - 6480 (Print) ISSN 0976 - 6499 (Online) Volume 4, Issue 7, November - December 2013, pp. 247-257 © IAEME: www.iaeme.com/ijaret.asp Journal Impact Factor (2013): 5.8376 (Calculated by GISI) www.jifactor.com IJARET ©IAEME OPTIMIZATION OF CLUSTERING TECHNIQUES USING ENERGY THRESHOLDS IN WIRELESS SENSOR NETWORKS Gaurang Raval1, Abhinav Shah2, Madhuri Bhavsar3 1 Associate professor, Department of Computer Science and Engineering, Nirma University, Ahmedabad, Gujarat 382481, India 2 Department of Computer Science and Engineering, Nirma University, Ahmedabad, Gujarat 382481, India 3 Sr. Associate professor, Department of Computer Science and Engineering, Nirma University, Ahmedabad, Gujarat 382481, India ABSTRACT A wireless sensor network consists of a large number of tiny devices having low-power transceivers that can be an effective tool for gathering data from a particular or variety of environments. Collected data determining the characteristics of particular environment is sent to the data processing center called base station. As sensor nodes have limited resources, the path for communication between sensor node and base station should be chosen such that total energy consumed along that path is minimized. Sensor nodes are grouped into clusters for high scalability and better data aggregation. Clusters create hierarchical WSNs which incorporate efficient utilization of limited resources of sensor nodes. In this paper a cluster-head election technique is implemented that optimizes network lifetime with reduced energy consumption. LEACH and LEACH-C are the popular clustering protocol and they provide energy efficient routing. As these protocols are defacto standard for clustering techniques the focus has been on optimizing LEACH-C protocol to achieve better network lifetime energy consumption. Several optimizations were implemented for LEACH-C protocol which includes a different clusterhead selection technique than LEACH-C. It selects optimal number of clusterheads in each round and also forms better clusters. Hence it consumes less energy and enhances network lifetime. Keywords: Clustering, Energy Threshold, LEACH-C, Wireless Sensor Network. 247
  2. 2. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME 1. INTRODUCTION Wireless Sensor networks consist of hundreds of thousands of low power multi-functional sensor nodes, operating in an unattended environment, with limited computation and sensing capabilities. Sensor nodes are equipped with small batteries with low power capacities. Recent advances in sensor development have resulted in the wide use of Wireless Sensor Net-works (WSNs) for remotely monitoring tasks. WSNs are used for physical environment monitoring, security surveillance, military applications, among others. WSNs are consisting of large number of nodes that work together to accomplish a data gathering task. Sensors communicate with each other to relay messages from the network to the Sink, which is the entity interested in monitoring the subject of interest. A sensor node has limited sensing, computing/storing and transmitting capabilities. Each sensor node is capable of sensing, processing, transmission, mobilizer, position finding system, and power units. Sensor nodes coordinate among themselves to generate information about the physical environment. WSNs are distributed, self-organizing systems. They rely on significant numbers of sensor nodes. Self-organizing feature of wireless sensor networks is challenging because of limitation of the bandwidth and energy resources available in these networks. Sensor nodes are typically battery powered devices. Sometimes failure of node from network will fail entire sensor network. The radio is the most power-consuming module of a sensor node. To preserve energy, the nodes should use low duty cycling, i.e. they turn their radios off but are still able to sense the environment. Once the event of interest is sensed, the node turns its radio on. In-network data processing (such as data aggregation, fusion, filtering, etc.) reduces the number of messages to be sent to the Sink, thus preserving energy. Data gathered by all nodes are correlated in WSNs, end user requires only a particular value like there is fire in particular area or not. For that it is required to process data locally. Aggregation techniques are used to perform this operation. Aggregation of data reduces size of data being propagated to the base station. This aggregated data is transmitted to the end user. Low Energy Adaptive Clustering Hierarchy (LEACH) protocol and LEACH-Centralized protocol are the most popular clustering protocol with efficient aggregation provision. Although these are de facto standards for clustering in WSN it suffers from certain drawbacks, this paper points out the drawbacks and suggests the improvements for the same. Section 2 describes LEACH and LEACH-C in detail. In section 3 problems in these protocols are discussed and in section 5 implementation and simulation details are discussed followed by conclusion and future work in section 6. 2. RELATED WORK LEACH is an application specific self organizing, adaptive clustering wireless sensor network protocol. It monitors environment to gather information from environment. In LEACH, the nodes are organizing themselves into clusters, a group of nodes, in which nodes having high energy act as cluster-head. All other non-cluster-head nodes sense the environment and sends gathered data to the cluster head. Cluster-head node performs aggregation on data received from non-cluster-head nodes and it sends the aggregated data to the end user, base station. Continuous role of a node as cluster head will result in declining energy status of the node, after some time it may be of no use. So it is required to change cluster-head periodically. In LEACH, cluster-head is not fixed throughout the network lifetime. LEACH uses randomized rotation of cluster-head position among the sensors to balance the energy usage across the network [2]. In this way, the energy load of being cluster-head is evenly distributed among the nodes. LEACH operates into rounds. Each round begins with a set-up phase followed by steady-state phase. In set-up phase, clusters are formed and cluster-head selection is done while in steady-state phase data is transferred from non-cluster-head nodes to the clusterhead node and then to the base station. The operation of LEACH is shown in Fig. 1 [2]. 248
  3. 3. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME Figure 1: Time line showing LEACH operation 2.1 Setup phase 1. Cluster head election: In LEACH, there is no centralized control. There should be certain number of clusters during each round. Energy load should be evenly distributed among all the nodes. Nodes begin with equal energy, so that there are no overly-utilized nodes in the network. Each sensor elects itself to be a cluster-head at beginning of round r+1 with probability Pi(t). Pi(t) is chosen such that the expected number of nodes for this round is k. Thus if there are N nodes in the network, the number of cluster-head. #of CHs = ∑࢔ ࡼ࢏ ‫ כ‬૚ ൌ ࢑ ࢏ୀ૚ (1) Ensuring that all nodes are cluster heads the same number of times requires each node to be a cluster head once in N/K rounds on average. If Ci(t) is the indicator function determining whether or not node has been a cluster head in the most recent ( r mod (N/K)) rounds (i.e. ,zero if node has been a cluster head and one otherwise), then each node should choose to become a cluster head at round with probability. Pi(t) = ࡺ ቐࡺିࡷ‫כ‬ቀࢇ࢓࢕ࢊ ቁ ࡺ ࡷ : ࢉ࢏ ሺ࢚ሻ ൌ ૚ ૙: ࢉ࢏ሺ࢚ሻ ൌ ૙ (2) Therefore, only nodes that have not already been cluster heads recently, and which presumably have more energy available than nodes that have recently performed this energy intensive function, may become cluster heads at round r+1. 2. Cluster formation Technique: When cluster head are decided, all the cluster head nodes must inform all the other nodes in the network that they have chosen this role for the current round. For this, each cluster head node broadcasts an advertisement message using a non persistent (CSMAcarrier sense multiple access) MAC protocol. Each non-cluster head node determines its cluster for this round by choosing the cluster head that requires the minimum communication energy, based on the received signal strength of the advertisement from each cluster head. The cluster head advertisement heard with the largest signal strength is the cluster head. And it requires the minimum amount of energy to communicate with. All the non cluster head nodes must inform their cluster head that they are member of that cluster. To do this each node transmits a join-request message (Join- REQ) back to the chosen cluster head using a non persistent CSMA MAC protocol. The cluster heads in LEACH act as local control centers to coordinate the data transmissions in their 249
  4. 4. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME cluster. The cluster head node sets up a TDMA schedule and transmits this schedule to the nodes in the cluster. This ensures that there are no collisions among data messages and also allows the radio components of each non-cluster head node to be turned off at all times except during their transmit time, thus reducing the energy consumed by the individual sensors. After the TDMA schedule is known by all nodes in the cluster, the set-up phase is complete and the steady-state operation (data transmission) can begin. 2.2 Steady state phase Typically in this phase data communication takes place by dividing its operation into frames, where nodes send their data to the cluster head in their given time slot. The duration of each slot is constant, so the time to send a frame of data depends on the number of nodes in the cluster. All non cluster head nodes remain in sleep state until its allocated transmission time. The cluster head must be awake to receive all the data from the nodes in the cluster. Once the cluster head receives all the data, it performs data aggregation and reduces the uncorrelated noise among the signals. The cluster head node sends the resultant data to the BS. BS may be located far away and the data messages are large, energy consumption for this transmission is high. A fixed spreading code and CSMA is used to send data from the cluster head nodes to the BS. 2.3 LEACH-C (LEACH-Centralized) LEACH protocol offers no guarantee about the placement and/or number of cluster head nodes. However, using a central control algorithm to form the clusters may produce better clusters. This is the basis for LEACH-centralized (LEACHC) protocol which uses a centralized clustering algorithm. It is divided into phases as LEACH: setup phase and steady state phase. It uses the same steady-state protocol as LEACH. In the set-up phase of LEACH-C, at start of each round all nodes send their current location and energy level to the BS. To evenly distribute energy load among all the nodes in the network, the BS computes the average node energy, and nodes having energy below this average cannot be cluster heads f or the current round. Using the remaining nodes as possible cluster heads, the BS finds clusters using the simulated annealing algorithm [16]. This algorithm attempts to minimize the amount of energy for the non-cluster head nodes to transmit their data to the cluster head, by minimizing the total sum of squared distances between all the non-cluster head nodes and the closest cluster head. At each iteration, the next state, which consists of a set of nodes in C’, is determined from the current state, the set of nodes in C, by randomly perturbing the x and y coordinates of the nodes c in C to get new coordinates x’ and y’. The nodes that have location closest to (x’, y’) become the new set of cluster head nodes c’ that make up set C’. Given the current state at iteration k, represented by the set of cluster head nodes C with cost f(C), the new state, represented by the set of cluster-head nodes C’ with cost f(C’), will become the current state with probability [1]: fሺ࢞ሻ ൌ ൝ࢋ ష൫ࢌሺࢉ′ሻషࢌሺࢉሻ൯ :ࢌሺࢉ′ሻஹࢌሺࢉሻ ࢻ࢑ ૚: ࢌሺࢉ′ሻ ൒ ࢌሺࢉሻ (3) Where αk is the control parameter and f( ) represents the cost function defined by ૛ f (C) = ∑࢔ ࢓࢏࢔ୀ૚ ࢊ ሺ࢏, ࢉሻ (4) Where d(i,c) in equation 4 is the distance between node i and node c. the parameter k must be chosen to be increasing with k to ensure that the algorithm converges. However if k increases too quickly, the system will get stuck in local minima. On the other hand, if k increases too slowly, the 250
  5. 5. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME system will take every long time to converge. The BS broadcasts a message that contains the cluster head ID for each node, once the cluster heads and associated Clusters are found. If a nodes cluster head ID matches its own ID, the node is a cluster head; otherwise, the node determines its TDMA slot for data transmission and goes to sleep until it is time to transmit data. The steady-state phase of LEACH-C is same as that of LEACH. 3. PROBLEMS LEACH-C suffers from some of the problems. In the beginning of each and every round all the alive nodes sends their energy and location to the base station. As the base station is located far away than the field where sensor nodes are distributed, it is most energy consuming transmission. In setup phase there are high congestion/collisions due to large number of nodes transmitting simultaneously. In the beginning of each round all nodes directly communicates with base station that it most energy consuming communication as shown in Fig 2. Fig 2: Energy consumption during simulation (150 nodes)[1] In LEACH-C All nodes do not succeed in transmitting locations/energy due to collisions, creating node isolations. It was observed after simulating LEACH-C with various data sets that 3040 % nodes do not succeed in transmitting their data to base station due to collisions or distance problems. It is also difficult to conclude that nodes energy is drained out or it is a transmission loss. Probing every node for this information is not feasible. Also in LEACH-C the choice for eligible nodes is limited as it is considering the nodes having residual energy more than the average network energy. Due to this the cluster head election process is little biased towards residual energy but it neglects the distance aspects while selecting clusters due to limited choices. LEACH and LEACH-C both shows performance variation when both are tried on random data sets where each set contains randomly deployed nodes. 251
  6. 6. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME 4. OUR APPROACH In LEACH-C protocol, at start of each round all nodes sends their energy and location to the far away located base station. Location of static node is fixed throughout the lifetime. So at start of first round, all nodes send their energy and location to the base station. But after completion of first round, in second and following rounds static nodes will not send their location to the base station as we assume that the nodes will be stationary. With this energy consumption of static nodes can be reduced and also can improve network lifetime. As in the beginning every nodes energy is assumed to be same, in the first round every node is only sending location while from next round onwards every node sends only its energy to base station. The advantage of not sending location is proved in as follows. For example desired No of clusters are 5%. Simulation time is 3600sec and each round time 20sec, around 180 rounds. If there are N nodes in the network, it is required to send N messages to the BS in each round, that will cost (No of rounds(R)*N). But for stationary nodes if we send its location only once then we can reduce communication cost by (R-1) * N, reducing setup overhead. base station will retain co-ordinates of nodes received in first round throughout the algorithm lifetime. Another improvement is setting an energy threshold for the round, RD_THR. This threshold is decided by estimating the approximate energy required by a cluster member during a round where it transmits data to clusterhead during its TDMA slot in a frame. This threshold is used for sending the energy to the base station. If any node goes below this threshold, that node will not send its energy to the base station. If base station does not receive energy of a particular node it will only consider it for cluster formation but not clusterhead. This node(s) will send sensed data to the cluster head but will not take participation in becoming cluster head. Remaining steps are performed same as LEACH-C protocol. Another threshold used is clusterhead selection threshold, CH_THR. BS will not consider nodes with energy below CH_THR for CH election. If current residual energy of node is less than threshold energy (0.5% of initial), node will be out of CH election process. BS will consider location of that node to form cluster but it will not consider this node as CH candidate. BS will not use average node energy during clustering, instead it will use CH-THR. The approximate CH_THR calculation is shown below, 1. CH_THR = 0.5% of initial energy (2 J) 2. 0.5% of initial energy = 0.005 * 2 J = 0.01 J 3. 1 Round = 6 Frames, 1 Frame = 10 Nodes TDMA slots, considering average 10 nodes in cluster with a network of around 50 nodes. 4. 1 Packet size = (500 data bytes ) = 4000 bits 5. Total energy required to survive one round as CH is, 4000 bits * 10 nodes * 6 frames * 50 nJ/bit = 0.012 J The CH_THR will change as the network size changes and it will be refined linearly with the network size and base station will keep discarding nodes having energy below CH_THR. Due to this change in clustering method large number of eligible nodes are considered which shows that our method is not biased towards residual energy but also considers distance factor equally while clustering. Because of this the clustering process results in uniform clusterhead creation with respect to distance. 5. SIMULATION AND ANALYSIS These approaches were implemented in NS-2 simulator. To have a fair comparison same simulation settings were considered for all the simulations. A 100 m x100 m field was assumed for node distribution with different number of nodes. 252
  7. 7. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME Parameter TABLE 1: Simulation Parameters value Node distribution (0,0) to (100,100) BS location (50,175) No. of Nodes Initial Node Energy 50,100,150,200 (Randomly distributed 5 sets for each) 2J Simulation Time 3600s Desired No. of cluster- 5% heads First LEACH-C and modified LEACH-C protocol were simulated using various scenarios. And then simulations were carried out using 50,100, 150, 200 number of nodes for threshold based modified LEACH-C protocol. Simulation results are shown in graphs and are also analyzed. Fig. 3 and Fig. 4 show energy consumption in joules of all nodes during simulation with 150 and 200 nodes respectively. It compares total energy consumed during simulation of LEACH, LEACH-C and modified LEACH-C protocol. In this simulation the non-cluster head nodes are not sending their location information to the base station in every round, but only during the first round. Also the clustering is based on CH_THR value. This graph indicates that modified LEACH-C has reduced energy consumption compared to LEACH and LEACH-C protocol. The energy usage is less in modified protocol because the number of message transmissions are less from nodes to base station and also it results in less collisions at the base station during setup phase. Also the clustering results in uniform distribution of clusterheads due to larger choice in clusterheads selection. Fig 3: Energy consumption during simulation (150 nodes) 253
  8. 8. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME Fig 4: Energy consumption during simulation (200 nodes) Fig. 5 and Fig. 6 compares nodes alive with time for different node scenarios for modified LEACH-C and LEACH-C and LEACH. It shows that LEACH and LEACH-C suffers from performance problem when presented with random data sets for various network sizes The spikes in the Fig.5 and Fig. 6 for LEACH and LEACH-C is due to inconsistent behavior of these protocols for random data sets. Our approach smoothens the performance of the protocol. This is due to less collisions during the setup phase as nodes refrain from sending location during every round as well as due to uniform clustering. Also more nodes are alive compared to LEACH and LEACH-C with the suggested improvements using thresholds. Fig 5: No. of nodes alive (150 nodes) 254
  9. 9. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME Fig 6: No. of nodes alive (200 nodes) Fig.7 compares the data received at base station during the simulations. It can be seen that throughput of our approach is very close to that of LEACH-C with improved energy usage and nodes alive count. Fig 7: Data received at BS 255
  10. 10. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME 6. CONCLUSION AND FUTURE WORK In this paper certain improvements are suggested over the original LEACH-C protocol. Avoiding unnecessary direct transmission from cluster members to base stations improves the network lifetime. Also a dual threshold was used for member selection and cluster head selection using estimated energy requirements for survival during the round. After implementation of proposed improvements through simulations and analysis of the same it can be concluded that suggested improvements brings in certain advantages and proves more efficient in terms of energy consumption, network lifetime and gives similar throughput. Hybrid protocol may be used to avoid initial energy transmissions/collisions and to avoid node isolations. Direct broadcast from member nodes to base stations can be completely avoided. REFERENCES [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] W. Heinzelman, Application-specific protocol architectures for wireless networks, Ph.D. dissertstion, Mass. Inst. Technol., Cambridge, 2000. Wendi B. Heinzelman,, Anantha P. Chandrakasan,Hari Balakrishnan, An ApplicationSpecific Protocol Architecture for Wireless Microsensor Networks. Wendi Beth Heinzelman , Application Specific Protocol Architectures for Wireless Networks ,B.S., Cornell University,M.S., Massachusetts Institute of Technology. D. J. Dechene , A. El Jardali , M. Luccini , and A. Sauer, A Survey of Clustering Algorithms for Wireless Sensor Networks , Department of Electrical and Computer Engineering The University Of Western Ontario London, Ontario, Canada. Seema Bandyopadhyay, Edward J. Coyle , An Energy Efficient Hierarchical Clustering Algorithm for Wireless Sensor Networks, School of Electrical and Computer Engineering Purdue University West Lafayette, IN, USA. Vinay Kumar, Sanjeev Jain , Sudarshan Tiwari, Energy Efficient Clustering Algorithms in Wireless Sensor Networks: A Survey, Dept. of ECE, Motilal Nehru National Institute of technology Allahabad , Uttar Pradesh, India-211004. K.Ramesh , Dr. K.Somasundaram A COMPARATIVE STUDY OF CLUSTERHEAD SELECTION ALGORITHMS IN WIRELESS SENSOR NETWORKS , Dept of ECE, Nandha Engineering College, Erode. Shilpa Chauhan , Dr. Sona Malhotra, Yogesh Chauhan, A Survey of Hierarchical Routing Protolols in Wireless Sensor Network , UIET, Kurukhsetra. EZZATI ABDELLAH, SAID BENALLA, Abderrahim BENI HSSANE , Moulay Lahcen HASNAOUI, Advanced Low Energy Adaptive Clustering Hierarchy, Dpartement mathmatique et Informatique Facult des Sciences et Techniques Settat, Morocco. Ki Young Jang, Kyung Tae Kim, Hee Yong Youn, An Energy Efficient Routing Scheme for Wireless Sensor Networks , School of Information and Communication Engineering Sungkyunkwan University, 440-746, Suwon, Korea. Rab Nawaz, Kashif Bilal, Mehtab Afzal , An Improved Energy Efficient Cluster Based Routing Protocol for Wireless Sensor Networks ,Department of Computer Science COMSATS Institute of Information Technology, Abbottabad, Pakistan. Mr.Soumen Chatterjee 2.Mr.Mohan Singh, A Centralized Energy- Efficient Routing Protocol for Wireless Sensor Networks ,Electrical and Electronics Department,Terii,Kurukshetra13611. G. Santhosh Kumar, Vinu Paul M V , K. Poulose Jacob, Mobility Metric based LEACHMobile Protocol , Department of Computer Science, Cochin University of Science and Technology Cochin 682 022, Kerala, INDIA. 256
  11. 11. International Journal of Advanced Research in Engineering and Technology (IJARET), ISSN 0976 – 6480(Print), ISSN 0976 – 6499(Online) Volume 4, Issue 7, November – December (2013), © IAEME [14] Mu Tong, Minghao Tang, LEACH-B:An Improved LEACH Protocol for Wireless Sensor Network , College of Information Science and Technology Donghua University Shanghai, China. [15] Bai Chen, Yaxiao Zhang , Yuxian Li , Xiaochen Hao , Yan Fang, A Clustering Algorithm of Cluster-head Optimization for Wireless Sensor Networks Based on Energy, Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China. [16] T. Murata and H. Ishibuchi, Performance evaluation of genetic algorithms for flowshop scheduling problems, Proc. 1st IEEE Conf. Evolutionary Computation, vol. 2, pp. 812817, June 1994. [17] Rashid M. Awadi, Rawya Y. Rizk, Mohamed I. Habib and Amira A. M. Elsonbaty, “An Efficient Cluster Head Selection Scheme for Dynamic Sleep Time in Wireless Sensor Network”, International Journal of Electronics and Communication Engineering & Technology (IJECET), Volume 4, Issue 6, 2013, pp. 1 - 13, ISSN Print: 0976- 6464, ISSN Online: 0976 –6472. [18] Yogesh V Patil, Pratik Gite and Sanjay Thakur, “Automatic Cluster Formation and Assigning Address for Wireless Sensor Network”, International Journal of Computer Engineering & Technology (IJCET), Volume 4, Issue 4, 2013, pp. 116 - 121, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375. [19] Mohanaradhya, Sumithra Devi K A and Andhe Dharani, “Distance Based Cluster Head Section in Sensor Networks for Efficient Energy Utilization”, International Journal of Advanced Research in Engineering & Technology (IJARET), Volume 4, Issue 1, 2013, pp. 50 - 58, ISSN Print: 0976-6480, ISSN Online: 0976-6499. [20] Preetee K. Karmore, Supriya S. Thombre and Gaurishankar L. Girhe, “Review on Operating Systems and Routing Protocols for Wireless Sensor Networks”, International Journal of Computer Engineering & Technology (IJCET), Volume 4, Issue 3, 2013, pp. 331 - 339, ISSN Print: 0976 – 6367, ISSN Online: 0976 – 6375. 257

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