Modeling and Analyzing Adaptive Energy Consumption for Service Composition

Abstract

Abstract-In this paper, Petri nets are used to model the different components of service composition, and form the energy consumption model of service composition based on the relationship between components, Agent is also introduced in the energy consumption management process. Then, an adaptive energy consumption strategy are proposed to dynamically ensure that service composition can get the lowest energy consumption. The operational semantics and related theories of Petri nets help establish the correctness of our proposed method. We have also performed two simulations to evaluate our proposed approach. Results show that it can help reveal the structural and behavioral characteristics of energy consumption in service composition.Index Terms-Service composition, Agent, Petri nets, energy consumption I. INTRODUCTION Service composition provides a mechanism for distributed software integration, which primarily concerns the requests of users that cannot be satisfied by any available service [1]. This increased usage of service composition, together with the increasing energy costs [2]. The energy management is highly complex. First, energy consumption is inherently complicated due to the scale, heterogeneity, and concurrent user services that share a common set of service. Second, the operating environment of service composition is dynamic, it is difficult to plan energy consumption schema at design time. When service composition starts to execute, composition can not achieve the goal because of wrong design of composition or can not meet the required energy consumption. The failure will result in a waste of computing resources and increase energy consumption. Therefore, it requires that energy consumption management of service composition must have a certain adaptive ability, which means that service composition can dynamically select the service, in order to complete its execution successfully and meet the required energy consumption.Contributions. This paper investigates how to model and analyze the energy consumption of service composition based on user requirements. Below summarizes our main contributions: (1) Petri nets [3] are used to model different components of service composition. Agent[4] is introduced in the energy consumption management process. (2) We evaluate the energy consumption of service composition from the operational level(in addition to service, component, connector and Agent). Based on the model, we propose an adaptive energy consumption strategy to dynamically ensure that service composition can get the lowest energy consumption. (3) The operational