A Robust IOT-Cloud IaaS for Data Availability within Minimum Latency

A Robust IOT-Cloud IaaS for Data Availability within Minimum Latency

Sarra Hammoudi, Saad Harous, Zibouda Aliouat
Copyright: © 2019 |Pages: 17
DOI: 10.4018/IJSITA.2019100102
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Abstract

Sensors in Internet of Things generate a huge amount of data. The massive volume of the captured data is stored on cloud servers. Over time, the unbalanced load servers prevent better resource utilization. It also increases the input and the output response time. Hence, applying load balancing techniques is very important to achieve efficient system performance. Ensuring the critical data availability in such dynamic systems is very essential. In this article, the authors propose ROBUST for ensuring data availability mechanism and a fault-tolerance architecture. ROBUST also realises load balancing among servers within minimum latency, by avoiding the problem of the overloaded sites and unbalanced use of the resources on the servers. Comparing the response time using the ROBUST and Load Balancing in the Cloud Using Specialization (LBCS), ROBUST architecture has given satisfactory results in terms of critical data latency. Compared with LBCS, ROBUST gains 42% critical data recovery from a primary server and 45% when searching for duplicated critical data. The authors implemented the system using the JADE platform.
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Background

The following section discusses the algorithms and the related works that ensure the reliability of cloud computing. It also defines the main approaches and techniques that are applied to the architecture presented in this paper.

The authors in (Sidhu & Kinger, 2013), discussed the importance of Load Balancing (LB) technique to improve the system’s performance. The load balancing algorithms and metrics are detailed in the article to facilitate the unbalanced load servers problem solving. To highlight the importance of load balancing, a major goal is recognized and explored.

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