Energy-Aware Service Orchestration Based on Temporal Reconfigurable Architecture

Abstract

Cloud computing is by far the most cost-effective technology for hosting Internet-scale services and applications. It becomes a valuable contributor and cost-saver for companies with the introduction of orchestration platforms as a Service (OaaS) to perform the services that support a variety of business processes such as BPEL. In this paper we will investigate three issues i) exploiting the minimum of resources to execute a maximum number of processes, ii) preventing possible overload to the server, and iii) minimizing the dynamic energy consumption which becomes one of the main challenges for large-scale computing, such as in cloud data center. As a solution for these challenges we propose a temporal partitioning based on dynamic reconfiguration approach. Our work aims to reduce the dynamic energy consumption. The proposed approach is based on two main steps: 1) Estimate the energy consumption of BPEL processes 2) Temporal and dynamic partitioning of BPEL process based on reconfigurable architecture in order to minimize overall energy consumption on each BPEL process at run time.