Resource Allocation for Service Composition in Cloud-based Video Surveillance Platform

Abstract

Resource allocation play an important role in service composition for cloud-based video surveillance platform. In this platform, the utilization of computational resources is managed through accessing various services from Virtual Machine (VM) resources. A single service accessed from VMs running inside such a cloud platform may not cater the application demands of all surveillance users. Services require to be modeled as a value added composite service. In order to provide such a composite service to the customer, VM resources need to be utilized optimally so that QoS requirements is fulfilled. In order to optimize the VM resource allocation, we have used linear programming approach as well as heuristics. The simulation results show that our approach outperforms the existing VM allocation schemes in a cloud-based video surveillance environment, in terms of cost and response time.