Surveillance-Aware Uplink Scheduling for Cellular Networks

Abstract

Most scheduling algorithms in the literature for cellular networks are concerned with throughput, fairness, or cost optimization. Recently, however, wireless surveillance in cellular networks has become increasingly important, and more and more institutions and companies have adopted commercial cellular surveillance cameras due to their low installation cost and the wide network coverage. In this paper, therefore, we first explore the resource allocation problem for a multi-camera surveillance system in cellular networks. We minimize the number of allocated resource blocks (RBs) while simultaneously ensuring the coverage requirement for the surveillance system in cellular networks. Specifically, we first describe our system model and then formulate the Camera Set Resource Allocation Problem (CSRAP). Next, we prove that the problem is NP-hard and inapproximable within ln n, where n is the number of surveillance targets. To solve the problem, we propose an approximation algorithm for the general case of CSRAP and then we find the optimal solutions of three deployments of cameras in the Manhattan Street Network to find the intrinsic characteristics of camera selections. The simulation results, based on two real surveillance maps and synthetic datasets, show that the number of allocated RBs can be effectively reduced compared to the existing approach for cellular networks.