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Time and energy-efficient hybrid job scheduling scheme for mobile cloud computing empowered wireless sensor networks

机译:移动云计算的时间和节能混合作业调度方案赋权无线传感器网络

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摘要

The rapid growth of emerging sensory data processing and delivery application poses a significant challenge to researchers due to the WSN's resource limitations. To minimise the WSN's job processing time, highly resourceful cloud computing technology has become a potential solution. To minimise the WSNs battery usage and job execution time, the development of a proper job scheduling scheme has emerged as a potential research challenge for cloud empowered WSN's by taking into account different job and resource characteristics. In this paper, we propose a time and energy-efficient hybrid job scheduling scheme for WSNs job execution that not only assigns sensor-cloud resources but also network timeslot resources. We present an analytical model and compare our proposed scheme's performance with traditional contention and reservation-based scheme. Our experimental results demonstrate that the proposed scheme supersedes the state of the art up to approximately 28.05% in the metric of schedule length.
机译:由于WSN的资源限制,新兴感官数据处理和交付应用程序的快速增长对研究人员构成了重大挑战。为了最大限度地减少WSN的工作处理时间,高度智慧的云计算技术已成为潜在的解决方案。为了最大限度地减少WSNS电池使用和作业执行时间,通过考虑不同的工作和资源特征,云授权的潜在研究挑战是云的潜在研究挑战。在本文中,我们提出了一个时间和节能的混合作业调度方案,用于WSNS作业执行,不仅为传感器云资源分配了网络时隙资源。我们提出了一个分析模型,并将我们的拟议计划与基于传统争用和预订的计划进行了比较。我们的实验结果表明,所提出的方案在规程长度的公制中取代了最新的状态至约28.05%。

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