Survivable Self-Organization for Prolonged Lifetime in Wireless Sensor Networks
More often than not, wireless sensor networks (WSNs) are deployed in adverse environments, where failures of sensor nodes and disruption of connectivity are regular phenomena. Therefore, the organization or clustering of WSNs needs to be survivable to the changing situations. On the other hand, ener...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Hindawi - SAGE Publishing
2011-05-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2011/257156 |
| _version_ | 1797762624214007808 |
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| author | Mohammad M. Hasan Jason P. Jue |
| author_facet | Mohammad M. Hasan Jason P. Jue |
| author_sort | Mohammad M. Hasan |
| collection | DOAJ |
| description | More often than not, wireless sensor networks (WSNs) are deployed in adverse environments, where failures of sensor nodes and disruption of connectivity are regular phenomena. Therefore, the organization or clustering of WSNs needs to be survivable to the changing situations. On the other hand, energy efficiency in WSNs remains the main concern to achieve a longer network lifetime. In this work, we associate survivability and energy efficiency with the clustering of WSNs and show that such a proactive scheme can actually increase the lifetime. We present an easy-to-implement method named DED (distributed, energy-efficient, and dual-homed clustering) which provides robustness for WSNs without relying on the redundancy of dedicated sensors, that is, without depending on node density. DED uses the information already gathered during the clustering process to determine backup routes from sources to observers, thus incurring low message overhead. It does not make any assumptions about network dimension, node capacity, or location awareness and terminates in a constant number of iterations. The correctness of the algorithm is proved analytically. Simulation results comparing with contemporary approaches demonstrate that our approach is effective both in providing survivability and in prolonging the network lifetime. |
| first_indexed | 2024-03-12T19:30:04Z |
| format | Article |
| id | doaj.art-e32e52ac721f4218b63ae443531b54a4 |
| institution | Directory Open Access Journal |
| issn | 1550-1477 |
| language | English |
| last_indexed | 2024-03-12T19:30:04Z |
| publishDate | 2011-05-01 |
| publisher | Hindawi - SAGE Publishing |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj.art-e32e52ac721f4218b63ae443531b54a42023-08-02T04:39:04ZengHindawi - SAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772011-05-01710.1155/2011/257156257156Survivable Self-Organization for Prolonged Lifetime in Wireless Sensor NetworksMohammad M. Hasan0Jason P. Jue1 Department of Math and Computer Science, Elizabeth City State University, Elizabeth City, NC 27909, USA Department of Computer Science, The University of Texas at Dallas, Richardson, TX 75083-0688, USAMore often than not, wireless sensor networks (WSNs) are deployed in adverse environments, where failures of sensor nodes and disruption of connectivity are regular phenomena. Therefore, the organization or clustering of WSNs needs to be survivable to the changing situations. On the other hand, energy efficiency in WSNs remains the main concern to achieve a longer network lifetime. In this work, we associate survivability and energy efficiency with the clustering of WSNs and show that such a proactive scheme can actually increase the lifetime. We present an easy-to-implement method named DED (distributed, energy-efficient, and dual-homed clustering) which provides robustness for WSNs without relying on the redundancy of dedicated sensors, that is, without depending on node density. DED uses the information already gathered during the clustering process to determine backup routes from sources to observers, thus incurring low message overhead. It does not make any assumptions about network dimension, node capacity, or location awareness and terminates in a constant number of iterations. The correctness of the algorithm is proved analytically. Simulation results comparing with contemporary approaches demonstrate that our approach is effective both in providing survivability and in prolonging the network lifetime.https://doi.org/10.1155/2011/257156 |
| spellingShingle | Mohammad M. Hasan Jason P. Jue Survivable Self-Organization for Prolonged Lifetime in Wireless Sensor Networks International Journal of Distributed Sensor Networks |
| title | Survivable Self-Organization for Prolonged Lifetime in Wireless Sensor Networks |
| title_full | Survivable Self-Organization for Prolonged Lifetime in Wireless Sensor Networks |
| title_fullStr | Survivable Self-Organization for Prolonged Lifetime in Wireless Sensor Networks |
| title_full_unstemmed | Survivable Self-Organization for Prolonged Lifetime in Wireless Sensor Networks |
| title_short | Survivable Self-Organization for Prolonged Lifetime in Wireless Sensor Networks |
| title_sort | survivable self organization for prolonged lifetime in wireless sensor networks |
| url | https://doi.org/10.1155/2011/257156 |
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