Multi-constrained Max-Min Fair Resource Allocation in Multi-channel Wireless Sensor Networks

Recent rich applications for the Internet of Things are demanding large bandwidth for communication which can cause congestion within multi-hop wireless sensor and ad hoc networks (WSANs). The capacity of the WSANs can be enhanced by using dual radios that allow concurrent use of multiple available wireless channels. It is a desirable feature that the enhanced capacity can be shared in a max-min fair manner by all existent flows in such multi-channel WSANs. In this paper, we propose a distributed resource allocation solution that achieves max-min fairness among multiple flows in multi-channel WSANs based on hybrid channel assignment. We find that the existence of two different types of enhanced network constraints in hybrid channel assignment-based multi-channel wireless networks leads to a new multi-constraint max-min resource allocation problem. We model the new max-min problem in the network utility maximization framework, with a particular focus on how to deal with resource prices induced by multi-constraints and adjust flow rates in response to the prices in a max-min fair manner. We present extensive simulation results to demonstrate the performance of the proposed distributed solution. We also discuss the trade-off between network throughput and fairness that exist in multi-channel WSANs.