Two-level mapping to mitigate congestion in machine to machine (M2M) cloud

This work focuses on mitigation of the network congestion in a Machine to Machine (M2M) cloud. Since the inception of M2M cloud communication technology, the number of M2M devices has radically increased. This has consequently increased the overall traffic of the network which, in turn, makes the entire network congestion prone. The work assumes an underlying clustered network topology of the M2M devices. We propose a hierarchical congestion control scheme in which we distinctly manage the network traffic by a two-level mapping - i) from the cluster heads (CHs) to the sink nodes and ii) from the sink nodes to the cloud gateways. To ensure "fairness", the mapping is based on the Theory of Social Choice. Results are demonstrated at the end which provide fair allocation of CHs to sink nodes and sink nodes to cloud gateways.