Scheduling for Multi-Camera Surveillance in LTE Networks

TL;DR

This paper addresses resource allocation for multi-camera surveillance in LTE networks, proposing algorithms to minimize resource blocks while ensuring coverage, and demonstrating effectiveness through simulations.

Contribution

It formulates the CSRAP problem, proves its NP-hardness, and introduces optimal and approximation algorithms for efficient resource allocation in LTE surveillance.

Findings

Significant reduction in resource blocks compared to existing methods

Proposed algorithms effectively guarantee surveillance coverage

Simulation results validate the approach's efficiency

Abstract

Wireless surveillance in cellular networks has become increasingly important, while commercial LTE surveillance cameras are also available nowadays. Nevertheless, most scheduling algorithms in the literature are throughput, fairness, or profit-based approaches, which are not suitable for wireless surveillance. In this paper, therefore, we explore the resource allocation problem for a multi-camera surveillance system in 3GPP Long Term Evolution (LTE) uplink (UL) networks. We minimize the number of allocated resource blocks (RBs) while guaranteeing the coverage requirement for surveillance systems in LTE UL networks. Specifically, we formulate the Camera Set Resource Allocation Problem (CSRAP) and prove that the problem is NP-Hard. We then propose an Integer Linear Programming formulation for general cases to find the optimal solution. Moreover, we present a baseline algorithm and devise an approximation algorithm to solve the problem. Simulation results based on a real surveillance map and synthetic datasets manifest that the number of allocated RBs can be effectively reduced compared to the existing approach for LTE networks.