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Hybrid data gathering scheme in wireless sensor networks

Mitra S. K., Chakraborty A., Naskar M. K.

Journal of Applied Computer Science

2011

Vol. 19, nr 2

73-88

For time-sensitive applications from a remote wireless sensor network, demands to design an efficient routing scheme that can enhance network lifetime and also offer an optimized performance in energy efficiency and reduced delay. In this paper, we propose an improved clustered-hop data gathering scheme which is a amalgamation of clustering and nearest neighborhood selection of the sensor nodes in each hop. The cluster heads and the super leader are altered every round for ensuring an uniformly distributed energy consumption among all the nodes. We have implemented the proposed scheme in nesC and performed simulations in TOSSIM. Successful packet transmission rates have also been analyzed using the interference-model. Compared with the existing popular schemes such as PEGASIS, BINARY, LBEERA and SHORT, our scheme offers an improved "energy delay" performance and has the capability to achieve a very good symmetry among different performance metrics.

DHS: A Data Handover Scheme for Lifetime Enhancement of Wireless Sensor Networks

Bhattacharyya A., Seetharam A., Naskar M. K.

Journal of Applied Computer Science

2008

Vol. 16, nr 2

23-41

Wireless sensor nodes must function in an energy-efficient manner in order to enhance network lifetime. In this paper we propose a Data Handover Scheme (DHS) which enhances the performance of several hierarchical routing protocols in terms of network lifetime. The base station being located at variable distances from the individual nodes, in spite of randomization and chain formation, each node actually dissipates a different amount of energy during its turn of transmission to the base station. DHS eliminates this energy difference by data handover in specific cycles through suitable node pairing and partner swapping. Extensive simulations show that LEACH with DHS performs 16.66% better than LEACH alone, PEGASIS with DHS shows 12.93% improvement over PEGASIS alone and binary model with DHS performs 15% better than the binary model alone considering network lifetime. A generalized mean transfer scheme is devised for large scale networks with significant (0.2–16%) lifetime increment. Furthermore PEGASIS with DHS shows that it attains almost a near optimal solution for the number of cycles endured by the network. As far as our knowledge goes, we are the first ones to address the problem of variable node distances from the Base Station and variable internodal distances.