Simulation of Configurable Resource Allocation for Cloud-Based Business Processes

Abstract

Cloud computing has enabled provisioning of scalable and virtualized resources to organizations in an ubiquitous and on-demand manner. Likewise, configurable process modeling has enabled organizations to reuse their existing knowledge by sharing a reference process model between different tenants that can be customized according to specific needs. Nevertheless, there are some limitations in this context, (i) it is not costeffective to make use of real cloud infrastructure such as, Amazon EC2 for experimenting and analyzing the deployment of the best process variant, (ii) frequent changes in the configurations during experimentation using a real cloud setup involves various manual adjustments which is a time-consuming task, (iii) certain conditions prevailing in the internet-based cloud environments are beyond the control of the practitioners involved in such analysis. Thus, making use of simulation environments is one of the good alternative for testing and analyzing the best process variants with optimal resource allocation. Building upon our previous work, we propose in this paper, (i) a unified description model that allows the representation of process activities along with their possible cloud resource allocation alternatives, (ii) a methodology for simulating a configurable process along with its cloud resource consumption, and (iii) an extension of CloudSim framework in order to realize the simulation of the configurable resource allocation for the cloud-based business processes.

Efficient Resource Allocation in Fog Computing Using QTCS Model

“…Fog computing technology is used for deployment of real time applications in IoT. Suri et al [24] introduced the resource provisioning scheme by considering acceptable intensity levels. The existing problems are rectified through Virtual Machine-Physical Mapping.…”