Applied Mathematics & Information Sciences

Author Country (or Countries)



Data gathering in wireless sensor network (WSN) has attracted a lot of attention in research. Data gathering can be done with or without aggregation, depending on the degree of correlation among the source data. In this paper, we study the problem of data gathering without aggregation, aiming to conserving the energy of sensor nodes so as to maximize the network lifetime. We model the problem as one of finding a min-max-weight spanning tree (MMWST), which is shown to be NP-complete. In MMWST, the maximum weight of the nodes is minimized. The weight of a node in the tree equals the ratio of the number of the node’s descendants to the node’s energy. We propose a W(logn/loglogn)-approximation centralized algorithm MITT to construct MMWST without requiring node location information. Moreover, in order to enable MITT to be used in large-scale networks, a new solution that employs the clustering technique is proposed. To the best of our knowledge, MITT is the first algorithm that constructs MMWST in wireless sensor networks. Theoretical analyses and simulation results show that MITT can achieve longer network lifetime than existing data gathering algorithms.

Suggested Reviewers