An improved adaptive weighted clustering algorithm based on time interval grade in Mobile Ad Hoc networks

Mobile Ad Hoc Networks (MANETs) are self-configuring dynamic networks of mobile devices connected by wireless links without any fixed infrastructure or centralized administration. In order to achieve stable clusters, the cluster-heads (CHs) maintaining the cluster should be stable with minimum re-affiliation times and number of changes on CHs, with maximal throughput of the clustering formation and maintenance. An improved adaptive weighted clustering algorithm based on time interval grade (IATIGWCA) in MANETs is proposed. Each node can be assigned an adaptive role and set its status value through their Hello messages in the formation procedure of clusters, and an appropriate CH of a cluster is elected by the calculation the total weight which comprising four factors: degree difference, average Euclidean distance, average relative speed and consumed battery power. In the maintenance procedure of clusters, the duration of clustering maintenance is set to 2 grades which are Little Time Slot and Big Time Slot in order to improve the efficiency of clustering and decrease the times of computation of the total weight of every node. The simulation results show that the selection of numbers of CHs and numbers of clusters in the stage of the formation of clusters is an optimal solution which brings higher throughput, less re-affiliation times, less number of changes on CHs and longer residence time of cluster in IATIGWCA than LID and WCA.