Fog Load Balancing Broker (FLBB)

Mandeep Kaur, Rajinder Sandhu, R. Mohana
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引用次数: 2

Abstract

For efficient and timely execution of an IoT job allocation of an appropriate set of resources throughout its life span is significant. Initial allocation of resources is done through job scheduling techniques and for managing the resources during the execution load balancing techniques are implemented. Load Balancing in distributed systems is as important as is Job Scheduling. Modern systems are technically capable to place job requests on the most appropriate set of resources at the beginning of the execution process. But in distributed environments resources behave dynamically and the status of busy, available, or free resources keeps on changing very frequently. In such conditions single time allocation of resources to a job request, till the end of execution cannot be sufficient. For efficient utilization of available resources, timely execution, and efficient delivery of response resource allocations must be revised during the life span of a job request. This paper proposes a load balancing solution that takes care of the changing states of resources in the fog environments and relocates the job request from one environment to another wherever is found beneficial. The proposed framework performs its task in two steps: first checks if the relocation is feasible or not and second to select a job for relocation and shift it to some other environment. This framework is specifically designed for fog environments where load balancing is a pivot point for effective and efficient resource utilization, bandwidth and to achieve the desired quality of service (QoS).
雾负载平衡代理(FLBB)
为了高效及时地执行物联网作业,在其整个生命周期内分配一组适当的资源非常重要。资源的初始分配是通过作业调度技术完成的,为了在执行期间管理资源,实现了负载平衡技术。分布式系统中的负载平衡和作业调度一样重要。现代系统在技术上能够在执行过程开始时将作业请求放在最合适的资源集上。但在分布式环境中,资源的行为是动态的,繁忙、可用或空闲资源的状态不断变化,非常频繁。在这种情况下,单次为作业请求分配资源,直到执行结束是不够的。为了有效地利用可用资源,必须在作业请求的生命周期内修改响应资源分配的及时执行和有效交付。本文提出了一种负载平衡解决方案,该解决方案考虑了雾环境中资源状态的变化,并将作业请求从一个环境重新定位到另一个环境中。所提出的框架分两步完成任务:首先检查迁移是否可行,其次选择一个工作进行迁移并将其转移到其他环境。这个框架是专门为雾环境设计的,在雾环境中,负载平衡是有效和高效的资源利用、带宽和实现所需服务质量(QoS)的枢纽点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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