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

S. Hammoudi, S. Harous, Z. Aliouat
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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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在最小延迟内实现数据可用性的强大IOT-Cloud IaaS
物联网中的传感器会产生大量的数据。捕获的大量数据存储在云服务器上。随着时间的推移,负载不平衡的服务器会妨碍更好的资源利用。它还增加了输入和输出响应时间。因此,应用负载平衡技术对于实现高效的系统性能非常重要。在这种动态系统中确保关键数据的可用性是非常重要的。在本文中,作者提出了用于确保数据可用性的鲁棒机制和容错架构。鲁棒还通过避免站点过载和服务器上资源使用不平衡的问题,在最小的延迟内实现服务器之间的负载平衡。通过比较使用鲁棒架构和使用专门化云中的负载平衡(LBCS)的响应时间,鲁棒架构在关键数据延迟方面给出了令人满意的结果。与LBCS相比,ROBUST从主服务器恢复关键数据的效率提高了42%,在搜索重复的关键数据时提高了45%。作者利用JADE平台实现了该系统。
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