Uplink Scheduling for LTE Video Surveillance Systems

TL;DR

This paper addresses optimizing LTE-based video surveillance by selecting cameras and allocating resources to maximize system performance while ensuring coverage, introducing a heuristic and dynamic adjustment methods.

Contribution

It proposes a novel heuristic and dynamic adjustment approach for resource allocation in LTE video surveillance systems, enhancing performance and coverage.

Findings

Improved camera selection and resource allocation strategies.

Enhanced system performance with dynamic adjustments.

Effective coverage of all monitored objects.

Abstract

Due to the proliferation of applications for the Internet of Things, an increasing number of machine to machine (M2M) devices are being deployed. In particular, one of the M2M applications, video surveillance, has been widely discussed. Long Term Evolution (LTE), which can provide a high rate of data transmission and wide range of coverage, is a promising standard to serve as an M2M video surveillance system. In this paper, we studied a performance maximization problem in an LTE video surveillance system. Given a set of objects and a set of cameras, each camera has its own performance grade and its own coverage. The goal is to maximize the performance of the system by allocating limited resources to cameras while all objects should be monitored by the selected cameras. We propose a heuristic method to select the cameras and allocate resources to them to solve the problem. Moreover, to reduce the load of the LTE system, a dynamic adjustment method is also proposed.