Temporal-aware rate allocation in mission-oriented WSNs with sum-rate demand guarantee

Conventional resource allocation schemes for single-purpose WSNs are unable to capture the dynamicity of network and/or application specifications. This compels us to design mechanisms that support multi-purpose mission-oriented WSNs, where several missions with different characteristics coexist in an integrated WSN. The paper aims to propose an efficient temporal-aware resource allocation mechanism for mission-oriented WSNs. Furthermore, our design supports minimum sum-rate demand guarantee for active sessions of each mission. We use contention graph notion to analytically model the interference in our underlying WSN. Moreover, in-network processing operators play important role in our design scheme. Using a time-variant mission-oriented WSN model, we formulate our resource allocation problem as a dynamic network utility maximization problem, which aims to maximize a hybrid mix of an aggregated objective function of missions’ utilities and energy consumption, considering capacity, interference and sum-rate demand constraints. Finally, using dual decomposition method, we solve the problem and propose a distributed temporal-aware algorithm called TARC-SD that optimally allocates the shared bandwidth to the sources. The conducted experiments indicate that the TARC-SD algorithm achieves higher network utilization and wider feasible scenarios compared to conventional time-invariant schemes.