A load balancing scheme for sensing and analytics on a mobile edge computing network
Chen‐Khong Tham, Rajarshi Chattopadhyay · 2017
The processing time of real-time sensing, data analytics and other applications is an important performance metric. When the application is being executed on a distributed system, the load balancing scheme among processing nodes significantly affects the total processing time of the application. We consider a load balancing scheme for distributed computing at the edge of the network. In the edge model considered, a group of nodes, either mobile or static, with processing and sensing capabilities, are connected to each other over a wireless ad-hoc network. Load balancing among edge nodes is formulated as a min-max optimization problem, with the objective of minimizing the overall processing time of the application while still satisfying the wireless channel capacity and link contention constraints. We use an aggregate utility method to convert the min-max problem into a convex optimization problem. The obtained constrained convex optimization problem is then relaxed with Lagrangian dual decomposition and solved with gradient descent. This form of the formulation can be implemented in a fully distributed manner among the edge nodes, which is consistent with the decentralized nature of edge networks. However, the convergence of this scheme may be slow. We further propose a heuristic algorithm which achieves fast convergence. Our simulation results show that it can give near-optimal performance most of the time.