LUCA: An Energy-efficient Unequal Clustering Algorithm Using Location Information for Wireless Sensor Networks

Abstract

Over the last several years, various clustering algorithms for wireless sensor networks have been proposed to prolong network lifetime. Most clustering algorithms provide an equal cluster size using node's ID, degree and etc. However, many of these algorithms heuristically determine the cluster size, even though the cluster size significantly affects the energy consumption of the entire network. In this paper, we present a theoretical model and propose a simple clustering algorithm called Location-based Unequal Clustering Algorithm (LUCA), where each cluster has a different cluster size based on its location information which is the distance between a cluster head and a sink. In LUCA, in order to minimize the energy consumption of entire network, a cluster has a larger cluster size as increasing distance from the sink. Simulation results show that LUCA achieves better performance than conventional equal clustering algorithm for energy efficiency.

FDMG: Fault detection method by using genetic algorithm in clustered wireless sensor networks

“…The efficiency of the proposed method was evaluated and compared with Lee [16] and Chen [15] algorithms in terms of detection accuracy and false alarm rate parameters. Whereas DA was defined as the ratio of the number of detected faulty nodes to the total number of faulty nodes, FAR was defined as the ratio of the number of fault-free nodes that are detected as faulty node to the total number of fault-free nodes [22].…”

“…This algorithm only detects permanent faults while transient faults are ignored although these types of faults may occur in most of the sensor nodes. Lee et al [16] proposed a distributed fault detection algorithm for wireless sensor networks which is simple and highly accurate in detecting faulty nodes. This approach used time redundancy for increasing the tolerance of transient faults.…”

“…The disadvantage of this algorithm is that it is not able to detect common mode failures. As mentioned above, most fault detection algorithms [6,[16][17][18][19][20] in WSNs compare their own sensed data with the data of neighbor nodes. If their data is similar to at least half of the data sensed by neighbors, the cited sensor will be considered as fault-free.…”

Energy-Efficient Unequal Chain Length Clustering for Wireless Sensor Networks in Smart Cities

“…Many clustering protocols [14][15][16]18] and unequal clustering protocols [20][21][22][23][24] have been suggested to minimize the energy consumption of WSNs.…”

“…UCA [23], location-based unequal clustering algorithm, is another unequal clustering algorithm where each cluster head has a different cluster size based on its distance to the base station. LUCA forms a cluster which has a smaller cluster size as the distance to the base station decreases.…”