Assessment of In-Cloud Enterprise Resource Planning System Performed in a Virtual Cluster

Abstract

This paper introduces a high-performed high-availability in-cloud enterprise resources planning (in-cloud ERP) which has deployed in the virtual machine cluster. The proposed approach can resolve the crucial problems of ERP failure due to unexpected downtime and failover between physical hosts in enterprises, causing operation termination and hence data loss. Besides, the proposed one together with the access control authentication and network security is capable of preventing intrusion hacked and/or malicious attack via internet. Regarding system assessment, cost-performance (C-P) ratio, a remarkable cost effectiveness evaluation, has been applied to several remarkable ERP systems. As a result, C-P ratio evaluated from the experiments shows that the proposed approach outperforms two well-known benchmark ERP systems, namely, in-house ECC 6.0 and in-cloud ByDesign.

Integrated High-Performance Platform for Fast Query Response in Big Data with Hive, Impala, and SparkSQL: A Performance Evaluation

“…In Figure 3, a cloud computing system capable of high performance, high availability, and high scalability is established for big data processing [18] where the layout shows a server farm at the top layer and storage farm at the bottom layer. As for virtualization in a cloud, a KVM-based virtual machine management (VMM) or hypervisor called Proxmox Virtual Environment (PVE) [19] is employed to deploy a cluster of virtual machines (VMs).…”

“…In order to evaluate the performance of the several approaches proposed in this paper, the performance index (PI) [27] was derived from first measuring an average access time in any specified environment with a variety of commands for a certain approach using Equation (1), next calculating weighted average access time in any specified environment with various data size in the files using Equation ( 2), then inducing a normalized performance index according to all of environments among the approaches using Equation (3), and finally resulting in the performance index according to different tests using Equation (4). In these equations, the subscript s indicates the index of the testing SQL command, the subscript i denotes the index of the testing file, j denotes the index of the testing environment, and k denotes the index of the testing approach.…”