Heuristic Algorithm for Resource Allocation in an Internet of Battle Things

Internet of Things has been experiencing unprecedented deployment from the civilian to the military ones like the Internet of battle Things (IoBT). Different from the civilian applications, the presence of various electronic countermeasures (ECM) in IoBT would destroy the infrastructure of a network, making the mobile edge computing (MEC) with quality of service (QoS) guaranteed in such a resource-limited IoBT more challenging. To improve the QoS of mobile users under an ECM environment, we address the optimization scheme in an MEC network with heterogeneous edge servers, considering that the connections in a network might be destroyed and therefore switch to the other connections for data transmission due to ECM. Mathematically, we characterize the optimization of wireless resource allocation as a mixed-integer nonlinear problem to maximize the relative improvement in task computation time and energy consumption. We decompose the original problem into a few suboptimization problems and propose a heuristic algorithm that can achieve a suboptimal solution in polynomial time by solving this NP-hard problem. The analytic results show that our proposed scheme can save task computation time and energy consumption over traditional approaches under an ECM environment.