Cognitive Agent Based Data Synchronization in Ubiquitous Networks

Abstract

In the recent past, some research works are focused on the design and management of ubiquitous networks (UNs) in terms of performance metrics like routing, computation overhead, latency, and security. Nowadays, data synchronization is one of the most challenging tasks in UNs to ensure the data consistency between the nodes or devices and servers. In this work, the authors present an overview of the UNs, including issues and challenges, cognitive agents, synchronization algorithms, and proposed data synchronization model using cognitive agents. This review article classifies some of the data synchronization algorithms into four categories named: synchronization based on the message digest; timestamp based synchronization; synchronization based on scalability performance; and delta synchronization with their relative performance. This article also compares synchronization algorithms against data synchronization in terms of accuracy, efficiency, scalability, consistency, and control overheads. The authors provide the model of cognitive agent-based data synchronization in UNs, which ensures the network performance in terms of reliability, energy efficient, accuracy, scalable, fault tolerant, and QoS based data synchronization algorithms using cognitive agents.