Clustering for networks of moving objects

Abstract

This chapter presents the problem of clustering of moving objects in ad hoc wireless networks. The networks of moving objects include networks of flying objects, networks of cars and other vehicles, networks of people moving in the cities, and networks of robots sensing the environment or performing coordinated actions. Clustering of such objects increases the scalability of the network and improves efficiency, enabling the objects to simplify the communication with their peers. Clustering of static network objects has been analysed in great detail in the literature. While most of the clustering algorithms and protocols are applicable in the networks of moving objects, there are specific challenges produced by the mobility. This document will present a rich body of currently available scholarly work on clustering for moving objects, focusing on the case when all network nodes (both clusterheads and cluster members) are moving. Most of the research works presented in this Chapter aim to predict the movement of the networked nodes, or to measure the relative mobility between the nodes, in order to optimise the processes of clusterhead election and cluster maintenance.