Multiuser Joint Task Offloading and Resource Optimization in Proximate Clouds
Multiuser Joint Task Offloading and Resource Optimization in Proximate Clouds
复制标题
邻近云中的多用户联合任务卸载和资源优化
DOI：
10.1109/tvt.2016.2593486
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发表时间：
2017-04-01
影响因子：
6.8
通讯作者：
Zhang, Ping
中科院分区：
文献类型：
--
作者：
Lyu, Xinchen;Tian, Hui;Zhang, Ping
邻近云计算支持移动设备上的计算密集型应用程序，提供丰富的用户体验。然而，远程资源瓶颈限制了卸载的可扩展性，需要优化卸载决策和资源利用率。为此，在本文中，我们利用移动设备功能和用户偏好的可变性。我们的系统效用指标是基于任务完成时间和移动设备的能耗来衡量体验质量 (QoE)。我们提出了一种启发式卸载决策算法（HODA），该算法是半分布式的，联合优化卸载决策以及通信和计算资源，以最大化系统效用。我们的主要贡献是将问题简化为子模最大化问题，并通过将其分解为两个子问题来证明其 NP 难度：1）通过拟凸和凸优化解决的通信和计算资源优化，以及 2）通过子模集函数优化解决的卸载决策。 HODA 将寻找局部最优值的复杂性降低到 <inline-formula> <tex-math notation="LaTeX">$O(K^{3})$</tex-math></inline-formula>，其中 <inline-formula> <tex-math notation="LaTeX">$K$</tex-math></inline-formula> 是移动用户的数量。仿真结果表明 HODA 的平均性能与最优值相差 5% 以内。与其他解决方案相比，随着用户数量的增加，HODA 的性能明显优越。
Proximate cloud computing enables computationally intensive applications on mobile devices, providing a rich user experience. However, remote resource bottlenecks limit the scalability of offloading, requiring optimization of the offloading decision and resource utilization. To this end, in this paper, we leverage the variability in capabilities of mobile devices and user preferences. Our system utility metric is a measure of quality of experience (QoE) based on task completion time and energy consumption of a mobile device. We propose a heuristic offloading decision algorithm (HODA), which is semidistributed and jointly optimizes the offloading decision, and communication and computation resources to maximize system utility. Our main contribution is to reduce the problem to a submodular maximization problem and prove its NP-hardness by decomposing it into two subproblems: 1) optimization of communication and computation resources solved by quasiconvex and convex optimization and 2) offloading decision solved by submodular set function optimization. HODA reduces the complexity of finding the local optimum to <inline-formula> <tex-math notation="LaTeX">$O(K^{3})$</tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">$K$</tex-math></inline-formula> is the number of mobile users. Simulation results show that HODA performs within 5% of the optimal on average. Compared with other solutions, HODA's performance is significantly superior as the number of users increases.