Exploiting Cloud Computing and Web Services to Achieve Data Consistency, Availability, and Partition Tolerance in the Large-Scale Pervasive Systems
Dublin Core
Title
Exploiting Cloud Computing and Web Services to Achieve Data Consistency, Availability, and Partition Tolerance in the Large-Scale Pervasive Systems
Subject
CAP properties
cloud computing
data replication
distributed systems
pervasive information systems
web services
Description
This article presents a new comprehensive approach to realize a sufficient trade-off between the CAP properties (i.e., consistency, availability, and partition tolerance) in the large-scale pervasive information systems. To achieve these critical properties, the capabilities of both cloud computing and web services were exploited in developing the components of the proposed approach. These components include a cloud-based replication architecture for ensuring high data availability and achieving partition tolerance, a web services-based middleware for maintaining the eventual consistency, and a data caching scheme to enable the mobile computing elements to conduct update transactions during the disconnection periods. The evaluation of the performance aspects revealed that the proposed approach is able to achieve a load balance, lower propagation delay, and higher cache hit ratio, as compared to other baseline approaches.
Creator
Fadelelmoula, Ashraf Ahmed
Source
International Journal of Interactive Mobile Technologies (iJIM); Vol. 15 No. 15 (2021); pp. 74-102
1865-7923
Publisher
International Association of Online Engineering (IAOE), Vienna, Austria
Date
2021-08-11
Rights
Copyright (c) 2021 Ashraf Ahmed Fadelelmoula
Relation
Format
application/pdf
Language
eng
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Identifier
Citation
Ashraf Fadelelmoula Ahmed, Exploiting Cloud Computing and Web Services to Achieve Data Consistency, Availability, and Partition Tolerance in the Large-Scale Pervasive Systems, International Association of Online Engineering (IAOE), Vienna, Austria, 2021, accessed November 7, 2024, https://igi.indrastra.com/items/show/2012