EEMC: An energy-efficient multi-level clustering algorithm for large-scale wireless sensor networks Wireless sensor networks can be used to collect environmental data from the interested area using multi-hop communication. As sensor networks have limited and non-rechargeable energy resources, energy efficiency is a very important issue in designing the topology, which affects the lifetime of sensor networks greatly. In this paper, the energy consumption is modeled and compared under the flat scheme and the clustering scheme, respectively. Motivated by the analysis, we propose an energy-efficient multi-level clustering algorithm called EEMC, which is designed to achieve minimum energy consumption in sensor networks. The cluster head election scheme is also considered in EEMC. EEMC terminates in O$(log log N)$ iterations given $N$ nodes. When the path loss exponent is 2, EEMC also achieves minimum latency. We focus on the case where sink node is remotely located and sensor nodes are stationary. Simulation results demonstrate that our proposed algorithm is effective in prolonging the network lifetime of a large-scale network, as well as low latency and moderate overhead across the network.

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