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Multithread Optimal Offloading Strategy Based on Cloud and Edge Collaboration

机译:基于云和边缘协作的多线程优化卸载策略

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To make full use of the resources of multi-core CPU and improve the system performance, most processors adopt multithreaded technology. However, how to achieve the energy-efficient offloading strategy for multithreaded computing remains an open problem. In this paper, we provide a collaborative cloud and edge computing offloading strategy to reduce energy consumption. Firstly, we formulate a joint optimizing offloading decision and computation resource allocation problem. Then, we design a collaborative cloud and edge computing search offloading (CCESO) algorithm. Based on this, the energy consumption minimization problem of a single thread application is transformed into a convex optimization problem through the time allocation strategy to achieve the optimal solution of the objective function. Secondly, for multithreaded applications, the cooperation scheme and offloading strategy between multi-thread are given to reduce the energy consumption of multithreaded. Experimental data show that the proposed collaborative cloud and edge computing offloading strategy can effectively reduce energy consumption.
机译:为了充分利用多核CPU的资源并提高系统性能,大多数处理器都采用了多线程技术。然而,如何实现多线程计算的节能卸载策略仍然是一个悬而未决的问题。在本文中,我们提供了一种协作式云和边缘计算卸载策略来减少能耗。首先,我们提出了联合优化卸载决策和计算资源分配问题。然后,我们设计了一种协作式云和边缘计算搜索卸载(CCESO)算法。基于此,通过时间分配策略将单线程应用的能耗最小化问题转化为凸优化问题,以实现目标函数的最优解。其次,针对多线程应用,提出了多线程之间的协作方案和卸载策略,以减少多线程的能耗。实验数据表明,提出的协同云和边缘计算卸载策略可以有效降低能耗。

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