延迟最小化和负载平衡的雾计算

W. Akram, Z. Najar, A. Sarwar, Iraq Ahmad Reshi
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引用次数: 1

摘要

云被用于以非常高的速率存储和处理数据。此外,这个世界上几乎每个人都在使用云。然而,问题出现了,数据中心没有很好地定位。数据通过各种链路到达云,因此会产生更多的延迟。所以这个世界现在正在进入迷雾之中。雾计算为我们提供了处理更靠近物联网设备的数据的能力。在过去的十年中,物联网设备一直在快速增长,导致每天产生大量的数据。为了处理这种不断增长的数据,需要高效的算法来减少云上的负载,并以更快、更精确的方式给出结果。处理应该在雾节点上完成,以处理这个问题。本文采用一种新颖的技术来研究雾节点的负载均衡,在不同的雾节点之间分配负载,使得每个雾节点都不会空闲,而其他雾节点则需要时间来处理数据。
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Fog Computing for Delay Minimization and Load Balancing
Cloud is used to store and process data at a very high rate. Moreover, nearly everyone in this world is using the cloud. However, the problem arises that the data centers are not positioned well. The data reach the cloud by passing through the various links, due to which more delays occur. So this world is now moving into fog. Fog computing provides us the capability to process data nearer to the IoT devices. During the past decade, IoT devices have been growing rapidly, resulting in the production of a tremendous amount of data every day. For the processing of this ever-growing data, efficient algorithms are required to reduce the load on the cloud and give the results in a faster and more precise manner. The processing should be done on the fog node to handle this issue. In this paper, the authors study load balancing on fog nodes with a novel technique so that they distribute the load among different fog nodes so that none of the fog nodes remains idle while other takes time for processing the data.
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