Cluster Based Energy Efficient and Fault Tolerant n-Coverage in Wireless Sensor Network

Coverage conservation and extend the network lifetime are the primary issues in wireless sensor networks. Due to the large variety of applications, coverage is focus to a wide range of interpretations. The applications necessitate that each point in the area is observed by only one sensor while other applications may require that each point is enclosed by at least sensors (n>1) to achieve fault tolerance. Sensor scheduling activities in existing Transparent and nonTransparent relay modes (T-NT) Mobile Multi-Hop relay networks fails to guarantee area coverage with minimal energy consumption and fault tolerance. To overcome these issues, Cluster based Energy Competent ncoverage scheme called (CEC ncoverage scheme) to ensure the full coverage of a monitored area while saving energy. CEC n-coverage scheme uses a novel sensor scheduling scheme based on the n-density and the remaining energy of each sensor to determine the state of all the deployed sensors to be either active or sleep as well as the state durations. Hence, it is attractive to trigger a minimum number of sensors that are able to ensure coverage area and turn off some redundant sensors to save energy and therefore extend network lifetime. In addition, decisive a smallest amount of active sensors based on the degree coverage required and its level. A variety of numerical parameters are computed using ns2 simulator on existing (T-NT) Mobile Multi-Hop relay networks and CEC n-coverage scheme. Simulation results showed that CEC n-coverage scheme in wireless sensor network provides better performance in terms of the energy efficiency, 6.61% reduced fault tolerant in terms of seconds and the percentage of active sensors to guarantee the area coverage compared to exiting algorithm. Keywords—Wireless Sensor network, Mobile Multi-Hop relay networks, n-coverage, Cluster based Energy Competent, Transparent and nonTransparent relay modes, Fault Tolerant, sensor scheduling.

[1]  Ivan Stojmenovic,et al.  Computing Localized Power-Efficient Data Aggregation Trees for Sensor Networks , 2011, IEEE Transactions on Parallel and Distributed Systems.

[2]  Feng Xia,et al.  Energy Efficient Ant Colony Algorithms for Data Aggregation in Wireless Sensor Networks , 2011, J. Comput. Syst. Sci..

[3]  Hazarath Munaga,et al.  A Fault Tolerant Trajectory Clustering (FTTC) for selecting cluster heads inWireless Sensor Networks , 2011, ArXiv.

[4]  Sanghyun Ahn,et al.  Designing the tree-based relaying network in wireless sensor networks , 2010 .

[5]  Guoliang Xing,et al.  Mobile Relay Configuration in Data-Intensive Wireless Sensor Networks , 2009, IEEE Transactions on Mobile Computing.

[6]  N. Nagarajan,et al.  Analysis of Transparent and non-Transparent relay modes in IEEE 802.16j Mobile Multi-Hop relay networks , 2012 .

[7]  Djamel Djenouri,et al.  Traffic-Differentiation-Based Modular QoS Localized Routing for Wireless Sensor Networks , 2011, IEEE Transactions on Mobile Computing.

[8]  Wei Wei,et al.  Fault-tolerant monitor placement for out-of-band wireless sensor network monitoring , 2012, Ad Hoc Networks.

[9]  Floriano De Rango,et al.  Link-Stability and Energy Aware Routing Protocol in Distributed Wireless Networks , 2012, IEEE Transactions on Parallel and Distributed Systems.

[10]  Lokesh Kumar Sharma,et al.  Connectivity and Coverage Preserving Schemes for Surveillance Applications in WSN , 2012 .

[11]  Cunqing Hua,et al.  Optimal Routing and Data Aggregation for Maximizing Lifetime of Wireless Sensor Networks , 2008, IEEE/ACM Transactions on Networking.

[12]  Kun Yang,et al.  Multi-objective K-connected Deployment and Power Assignment in WSNs using a problem-specific constrained evolutionary algorithm based on decomposition , 2011, Comput. Commun..

[13]  Ali Broumandnia,et al.  Node Placement and Coverage in Asymmetrical Area , 2012 .