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Cluster based wireless sensor network routings ieee
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Cluster based wireless sensor network routings ieee

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    Cluster based wireless sensor network routings ieee Cluster based wireless sensor network routings ieee Presentation Transcript

    • Cluster Based Wireless Sensor Network Routings using Artificial Bee Colony Algorithm Dervis Karaboga1, Selcuk Okdem2, and Celal Ozturk3 Erciyes University, Engineering Faculty, Kayseri, Turkey This paper appears in:Autonomous and Intelligent Systems (AIS), 2010 International Conference on artificial bee colony algorithm , custer based routing , wireless sensor networks Reporter NILAMADHAB MISHRA D0121008 & 978-1-4244-7107-2/10/$26.00 ©2010 IEEE. All rights reserved.
    • Contents• Aim• Concept• Artificial Bee colony algorithm• Hierarchical WSNs clustering and proposed approach• Simulation results• Conclusion 2
    • Aim• In this paper, the authors propose an innovative hierarchical clustering approach for wireless sensor networks to minimize energy consumption of the network using Artificial Bee Colony Algorithm which is a new swarm based heuristic algorithm.• A protocol is presented using Artificial Bee Colony Algorithm, which tries to provide optimum cluster organization in order to minimize energy consumption.• In cluster based networks, the selection of cluster heads and its members is an essential process which affects energy consumption.• Simulation results demonstrate that the proposed approach provides promising solutions for the wireless sensor networks. 3
    • Contents• Aim• Concept• Artificial Bee colony algorithm• Hierarchical WSNs clustering and proposed approach• Simulation results• Conclusion 4
    • Concept• The sensor devices collect data from physical environment, process it using aggregating techniques to get overall local data, and send final data to an external base station.• Flooding / gossiping is a basic method to transform data from a sensor node to the base station. In flooding, data is scattered by all the nodes as well as the base station. To broadcast data to all over the network consumes much energy and bandwidth.• Clustering is one of the routing design methodologies used to effectively manage network energy and to apply aggregation techniques in the network.• Data aggregation and fusion is simply used in the hierarchical WSNs in order to decrease the number of transmitted messages to the base station to minimize energy consumption and bandwidth utilization. 5
    • Concept• LEACH (Low-Energy Adaptive Clustering Hierarchy), HEED (Hybrid Energy Efficient Distributed Clustering ) and CLUDDA( Clustered Diffusion with Dynamic Data Aggregation) are the popular hierarchical routing methods which use data aggregation process. Although they offers good methodologies for implementation, yet create some bottlenecks.• So the authors propose a novel clustering method using Artificial Bee Colony (ABC) algorithm to preserve network energy and to get more performance in cluster based WSNs.• The algorithm shows superior performance against other well known optimization techniques. 6
    • Contents• Aim• Concept• Artificial Bee colony algorithm• Hierarchical WSNs clustering and proposed approach• Simulation results• Conclusion 7
    • Artificial Bee colony algorithm• It is a new swarm intelligence method inspired by intelligent foraging behavior of honey bees.• In ABC algorithm the colony of artificial bees is formed of three bee groups: employed bees, onlooker(observer) bees and scout(spy) bees. 8
    • Artificial Bee colony algorithm• It is assumed that there is only one artificial employed bee for each food source. In other words, the number of employed bees in the colony is equal to the number of food sources around the hive.• Employed bees go to their food source and come back to hive and dance on this area. The employed bee whose food source has been abandoned becomes a scout and starts to search for finding a new food source.• Onlookers watch the dance of employed bees and choose food sources depending on dances.• The main steps of the algorithm are given below:Initial food sources are produced for all employed beesREPEAT – Each employed bee goes to a food source in her memory and determines a neighbor source, then evaluates its nectar(juice) amount and dances in the hive – Each onlooker watches the dance of employed bees and chooses one of their sources depending on the dances, and then goes to that source. After choosing a neighbor around that, she evaluates its nectar amount. – Abandoned(uncontrolled) food sources are determined and are replaced with the new food sources discovered by scouts. – The best food source found so far is registered.UNTIL (requirements are met) 9
    • Artificial Bee colony algorithm• In ABC, a population based algorithm, the position of a food source represents a possible solution to the optimization problem and the nectar amount of a food source corresponds to the quality (fitness) of the associated solution. The number of the employed bees is equal to the number of solutions in the population.• There are three control parameters in the ABC:• the first one is the number of food sources which is equal to the number of employed or onlooker bees (SN).• second one is the value of limit parameter.• third one is the maximum cycle number (MCN).• At the first step, a randomly distributed initial population (food source positions) is generated. After initialization, the population is subjected to repeat the cycles of the search processes of the employed, onlooker, and scout bees, respectively. 10
    • Artificial Bee colony algorithmGenerate initial population xi; i=1...SNEvaluate the population Set cycle to 1 Repeat FOR each employed beeProduce new solutions Calculate the fitnessApply the greedy selection process FOR each onlooker bee Choose a solution xi depending on pi Produce new solutions vi Calculate the fitness Apply the greedy selection processIf there is an Abandoned solution for the scout, thenreplace it with a new solution produced Memorize the best solution so far Assign cycle = cycle + 1Until cycle = MCN Abandoned --- uncontrolled 11
    • Contents• Aim• Concept• Artificial Bee colony algorithm• Hierarchical WSNs clustering and proposed approach• Simulation results• Conclusion 12
    • Hierarchical WSNs clustering and proposed approach• LEACH protocol is already proposed to maximize the network lifetime by assigning different roles to the nodes. In this protocol, network is spited into clusters and cluster heads are chosen randomly in definite time intervals.• Cluster heads are responsible for collecting information inside the clusters and sending this information to the base. While nodes inside the clusters communicate in a small region, they consume low energy and cluster heads consumes more energy due to the communication with remote base station.• Since the role of cluster head in the clusters distributed randomly in each tour, the energy consumption for each node is equalized.• some disadvantages are in question??• First, all the nodes in network should have the ability of communication with the base.• 2nd , the distances to cluster heads from the member nodes as well as to base station from cluster heads are not taken into account.• Hence due to the both disadvantages in LEACH ,more n/w energy may be consumed.(problem) 13
    • Hierarchical WSNs clustering and proposed approach• The authors of LEACH algorithm further solved this problem by distributing the cluster heads uniformly, but the network assumed in this study requires node positioning systems like GPS, which cause the system to be more expensive, on sensor nodes. Also, GPS systems require additional energy consumption and needs large size of hardware.• So the authors of this paper proposed a low cost solutions to the existing problem by introducing the implementations of ABC algorithm. The proposed algorithm consists of two main phases.(WSNCABC-wireless sensor network clustering using artificial bee colony)• 1.setup phase Each node sends the calculated distances to the base station. Base station selects the cluster heads at each round using ABC algorithm. Once the base station declares the cluster heads to the network , then each node sends a request membership massage to the nearest cluster head. The cluster head after getting the request membership massage ,forms the initial network configuration and declares the formulation of cluster structure. 14
    • Hierarchical WSNs clustering and proposed approach• 2.Data gathering phase Cluster members sense the physical data from environment and store in their individual buffer. Then cluster head gathers sensed data from member nodes one by one using TDMA MAC protocol over a single channel and aggregates those data. Now the cluster head is ready to send the gathered and aggregated data to the base station. Centralized WSN application 15
    • Contents• Aim• Concept• Artificial Bee colony algorithm• Hierarchical WSNs clustering and proposed approach• Simulation results• Conclusion 16
    • Simulation results• Here the authors evaluate the performance of "Wireless Sensor Network Clustering using Artificial Bee Algorithm" (WSNCABC) via simulations, and compare it to basic transmission algorithm (direct communication) and a popular hierarchical routing method named "Low Energy Adaptive Clustering Hierarchy" (LEACH).• It is assumed that every node has a capability of communicating with sensor nodes in the network region as well as the base station.• In the simulations the same settings and assumptions are used for both LEACH and WSNCABC algorithms to be able to make a reliable comparisons.• In order to verify the success of the proposed approach, direct communication method and LEACH were used to make the comparisons. 17
    • Simulation results• In left figure, a network of 100 nodes is randomly deployed on an area of 500x500 m2, and base station is placed at the point of X=250 m, Y=575 m. Cluster heads are selected using LEACH algorithm(shown in squares), and members of the clusters are displayed with different markers.• In right Fig, a network of 100 nodes is randomly deployed on the same area, and cluster heads are chosen using ABC algorithm with the configuration described before. The cluster heads are uniformly selected providing that clusters have approximately equal sized of regions. 18
    • Simulation results• Demonstrates the residual energy of the network versus total received items.• it is seen that normalized residual energy of the network decreases as the number of received items increase in time, and the network using WSNCABC algorithm provides more performance by receiving 1.7 times more message items than the network using LEACH Algorithm when network energy is depleted by 50%. 19
    • Simulation results• It shows that WSNCABC algorithm clearly improves network lifetime over other two algorithms by spending less energy.• It also be observed that while the network is in more communication, bigger number of rounds implies the nodes have more energy in the network with WSNCABC algorithm. 20
    • Contents• Aim• Concept• Artificial Bee colony algorithm• Hierarchical WSNs clustering and proposed approach• Simulation results• Conclusion 21
    • Conclusion• This paper proposed a new approach for hierarchical WSN routing operations having aim to minimize the energy consumption of the network , that can be accomplished by using Artificial Bee Colony Algorithm so as to obtain optimum clusters with minimum energy consumption for communication.• The implementation of ABC algorithm to the clustering problem in WSNs is the first study in the literature.• Simulation outputs show that WSNCABC algorithm outperforms over direct transmission and LEACH Algorithm.• Hence ABC algorithm seems to be a promising solution for successful operations in cluster based WSNs. Thank You! 22