Open Access Open Access  Restricted Access Subscription Access
Open Access Open Access Open Access  Restricted Access Restricted Access Subscription Access

Maximize The Lifetime of Sensor Network by Load Balancing Using Tree Topology


Affiliations
1 Department of Information Technology, Walchand College of Engineering, India
     

   Subscribe/Renew Journal


In many wireless sensor networks due to the limited energy of sensor nodes energy conservation is one of the most important challenges. To enhance the lifetime of the network emphasis is given to design energy efficient routing algorithms. In WSN, sensor nodes which are nearer to the base station having a task of collecting data for the entire area and send to the base station. This node has an additional load and depletes its energy faster. This paper addresses the problem of lifetime maximization by load balancing. This paper proposes energy efficient load balanced data collection algorithm considering different network parameter (e.g., density, degree). In this method, Data collection tree topology is built at the sink node. Performance of the proposed algorithm is evaluated by considering various parameters like topology, availability of resources and the energy utilization of nodes in different paths of the tree, which may vary and ultimately impacts the overall network lifetime. Sensor nodes are switched from their original path to other based on the load and it reduces communication overhead.

Keywords

Load Balancing, Energy Efficiency, Data Collection Tree, Convergence Time.
Subscription Login to verify subscription
User
Notifications
Font Size

  • I.F. Akyildiz, W. Su, Y. Sankarasubramaniam and E. Cayirci, “Wireless Sensor Networks: A Survey”, Computer Networks, Vol. 38, No. 4, pp. 393-422, 2002.
  • G. Anastasi, M. Conti, M. Di Francesco and A. Passarella, “Energy Conservation in Wireless Sensor Networks: A Survey”, Ad Hoc Networks, Vol. 7, No. 3, pp. 537-568, 2009.
  • G. A1nastasi, M. Conti and M. Di Francesco, “Extending the Lifetime of Wireless Sensor Network through Adaptive Sleep”, IEEE Transactions on Industrial Informatics, Vol.5, No. 3, pp. 351-365, 2009.
  • Antoni Morell et al., “Data Aggregation and Principal Component Analysis in WSNs”, IEEE Transactions on Wireless Communications, Vol. 15, No. 6, pp. 3908-3919, 2015.
  • S. Toumpis and S. Gitzenis, “Load Balancing in Wireless Sensor Networks using Kirchhoff’s Voltage Law”, Proceedings of IEEE INFOCOM, pp. 1656-1664, 2009.
  • J. Liang, J. Wang, J. Cao, J. Chen and M. Lu, “An Efficient Algorithm for Constructing Maximum lifetime Tree for Data Gathering Without Aggregation in Wireless Sensor Networks”, Proceedings of IEEE INFOCOM, pp. 1-5, 2010.
  • Y. Liu, Y. He, M. Le, J. Wang, K. Liu, and L. Mo, “Does Wireless Sensor Network Scale? A Measurement Study on Green Orbs”, IEEE Transactions on Parallel and Distributed Systems, Vol. 24, No. 10, pp. 873-881, 2011.
  • A. Willig, “Recent and Emerging Topics in Wireless Industrial Communications : A Selection”, IEEE Transactions on Industrial Informatics, Vol. 4, No. 2, pp. 102-124, 2008.
  • Debraj De and Sajal K. Das, “SREE-Tree: Self-Reorganizing Energy-Efficient Tree Topology Management in Sensor Networks”, Proceedings of International Conference on Sustainable Internet and ICT for Sustainability, pp. 113-119, 2015.
  • Yunxia Chen and Qing Zhao, “On the Lifetime of Wireless Sensor Networks”, IEEE Communications Letters, Vol. 9, No. 11, pp. 976-978, 2005.
  • H. Dai and R. Han, “A Node-Centric Load Balancing Algorithm for Wireless Sensor Networks”, Proceedings of IEEE Global Telecommunications Conference, pp. 548-552, 2003.
  • Y. Wu, Z. Mao, S. Fahmy, S. Member and N.B. Shroff, “Constructing Maximum-Lifetime Data-Gathering Forests in Sensor Networks”, IEEE/ACM Transactions on Networking, Vol. 18, No. 5, pp. 1571-1584, 2010.
  • Y. Wang, Y. Wang, H. Tan and F.C.M. Lau, “Maximizing Network Lifetime Online by Localized Probabilistic Load Balancing”, Proceedings of International Conference on Ad-hoc, Mobile, and Wireless Networks, pp. 332-345, 2011.
  • D. Luo, X. Zhu, X. Wu and G. Chen, “Maximizing Lifetime for the Shortest Path Aggregation Tree in Wireless Sensor Networks”, Proceedings of IEEE INFOCOM, pp. 1566-1574, 2011.
  • S.K.A. Imon, A. Khan, M. Di Francesco and S.K. Das, “Energy-Efficient Randomized Switching for Maximizing Lifetime in Tree-based Wireless Sensor Networks”, IEEE/ACM Transactions on Networking, Vol. 23, No. 5, pp. 1401-1415, 2015.
  • U. Monaco, F. Cuomo, T. Melodia, F. Ricciato and M. Borghini, “Understanding Optimal Data Gathering in the Energy and Latency Domains of a Wireless Sensor Network”, Computer Networks, Vol. 50, No. 18, pp. 3564-3584, 2006.
  • Q. Zhao and M. Gurusamy, “Lifetime Maximization for Connected Target Coverage in Wireless Sensor Networks”, IEEE/ACM Transactions on Networking, Vol. 16, No. 6, pp. 1378-1391, 2008.
  • Z. Wang, E. Bulut and B. Szymanski, “Energy Efficient Collision Aware Multipath Routing for Wireless Sensor Networks”, Proceedings of IEEE International Conference on Communications, pp. 1-5, 2009.
  • Ozlem Durmaz Incel, Amitabha Ghosh, Bhaskar Krishnamachari and Krishnakant Chintalapudi, “Fast Data Collection in Tree-Based Wireless Sensor Networks”, IEEE Transactions on Mobile Computing, Vol. 11, No. 1, pp. 86-99, 2012.
  • H.O. Tan and I. Korpeoglu, “Power Efficient data Gathering and Aggregation in Wireless Sensor Networks”, ACM SIGMOD Record, Vol. 32, No. 4, pp. 66-71, 2003.

Abstract Views: 257

PDF Views: 5




  • Maximize The Lifetime of Sensor Network by Load Balancing Using Tree Topology

Abstract Views: 257  |  PDF Views: 5

Authors

S. S. Patil
Department of Information Technology, Walchand College of Engineering, India
B. S. Shetty
Department of Information Technology, Walchand College of Engineering, India

Abstract


In many wireless sensor networks due to the limited energy of sensor nodes energy conservation is one of the most important challenges. To enhance the lifetime of the network emphasis is given to design energy efficient routing algorithms. In WSN, sensor nodes which are nearer to the base station having a task of collecting data for the entire area and send to the base station. This node has an additional load and depletes its energy faster. This paper addresses the problem of lifetime maximization by load balancing. This paper proposes energy efficient load balanced data collection algorithm considering different network parameter (e.g., density, degree). In this method, Data collection tree topology is built at the sink node. Performance of the proposed algorithm is evaluated by considering various parameters like topology, availability of resources and the energy utilization of nodes in different paths of the tree, which may vary and ultimately impacts the overall network lifetime. Sensor nodes are switched from their original path to other based on the load and it reduces communication overhead.

Keywords


Load Balancing, Energy Efficiency, Data Collection Tree, Convergence Time.

References