Delay sensitive data routing optimization using rendezvous agents in wireless sensor networks with mobile sink. Issue 5 (28th May 2021)

• Record Type: Journal Article
• Authors: Venkateswarlu, V. T.; Naganjaneyulu, P. V.; Rao, D. N.
• Is Part Of: International journal of computers and applications. Volume 43:Issue 5(2021)
• Page Start: 445
• Page End: 452
• Publication Date: 2021-05-28
• Subjects: Rendezvous points -- mobile sink -- delay sensitive data -- sensor networks -- fault tolerant; Computers -- Periodicals; Computer software -- Periodicals; Computer networks -- Periodicals; Multimedia systems -- Periodicals; Internet -- Periodicals; World Wide Web -- Periodicals; Minicomputers -- Periodicals; Microcomputers -- Periodicals; 004.05
• DOI: 10.1080/1206212X.2019.1576326
• Languages: English
• ISSNs: 1206-212X

Abstract

Abstract : The method of data collection and transmission of delay sensitive data often relies on mobile sink in wireless sensor networks. This is either by transmitting directly to the mobile sink if the mobile sink is in the reachable range of the sensor that is intended to send the data, or by using the route established by the hop level sensors between the sensors that are intended to send the data and the mobile sink. The constraint of this strategy can portray as the energy consumption due to the suboptimal methods of routing between source sensor and mobile sink and the fault intolerance in data collection and transmission sequence. Hence, it is obvious to conclude that the significant contributions required about the design of optimal data collection and transmitting strategies for energy efficient and fault tolerant delay sensitive data transmission in wireless sensor networks with mobile sink. According to the context of these objectives stated, this manuscript portrayed a 'Delay Sensitive Data Routing Optimization using Rendezvous Agents' for energy efficient and fault tolerant delay sensitive data transmission in wireless sensor networks with mobile sink. The significance of the proposal was evaluated by experimental study using network simulation. Performance of the proposal is scaled by comparing the proposed model with the other contemporary model built under similar objectives. The traditional metrics are in use to compare and scale the performance of the proposal with the contemporary model.