Dynamic Resource Allocation for Event Processing in Surveillance Systems

Abstract

Allocating computing resources to different tasks of surveillance systems has always been a big challenge. The problem becomes complicated when it requires dealing with real-time computation and decision making as the system cannot afford of processing all sensory feeds and execute computationally expensive algorithms. In multi-modal surveillance systems, real-time event detection and understanding of a situation is crucial. So, the proper use of computing resources is necessary to control and manage an area of surveillance. This paper introduces a dynamic task scheduling technique considering available computing resources and real-time requirement according to the current surveillance context. The task scheduler determines the importance of each sensor with respect to its observation and surrounding context. The scheduler dynamically allocates CPU clock to data streams of each sensor so that it can minimize event detection time from the time of its occurrence. The simulation results reveal that the task scheduler can offer proper resource utilization which is valuable for surveillance systems.