An Energy-Efficient Unequal Clustering Algorithm Using ‘Sierpinski Triangle’ for WSNs

Abstract

Maximizing the nodes lifetime is one of the major issues in the wireless sensor networks (WSNs). Clustering algorithms represent the most well-known solution for optimizing the total consumed energy of WSNs. In clustered WSNs, each sensor is able to supervise an event and send information to its cluster head (CH) which aggregates and transmits data to the base station (BS) through other CHs in the network. This scenario causes the `hot spots' problem where closer CHs to the BS tend to die earlier because of the heavy relay data. Unequal clustering algorithms have tried to solve this problem and control the size of each cluster in the network. In this paper, we proposed a new unequal clustering algorithm called energy degree distance unequal clustering algorithm (EDDUCA) aiming to balance energy consumption and maximize the network lifetime. EDDUCA uses the `Sierpinski triangle' method in order to devide network into unequal clusters. The obtained results indicate that EDDUCA can effectively balance the energy consumption and therefore can lengthen the network lifetime.