On the Optimality of Task Offloading in Mobile Edge Computing Environments
On the Optimality of Task Offloading in Mobile Edge Computing Environments
复制标题
DOI：
10.1109/globecom38437.2019.9014081
复制
发表时间：
2019-12
期刊：
影响因子：
--
通讯作者：
Ibrahim A. Alghamdi;C. Anagnostopoulos;D. Pezaros
中科院分区：
文献类型：
--
作者：
Ibrahim A. Alghamdi;C. Anagnostopoulos;D. Pezaros
移动边缘计算(MEC)是为提高用户应用的服务质量而出现的新的计算范式。MEC面临的一个挑战是计算(任务/数据)卸载，其目标是增强移动设备的能力，以应对新的应用需求。计算分流面临着何时何地分流数据以执行计算(分析)任务的挑战。本文采用最优停止理论的原理，建立了两个时间最优的序贯决策模型，解决了这一问题。使用真实世界的数据集，与基线、确定性和随机模型进行比较，提供了性能评估。结果表明，我们的方法在单用户和竞争用户场景中优化了此类决策。
Mobile Edge Computing (MEC) has emerged as new computing paradigm to improve the QoS of users' applications. A challenge in MEC is computation (task/data) offloading, whose goal is to enhance the mobile devices' capabilities to face the requirements of new applications. Computation offloading faces the challenges of where and when to offload data to perform computing (analytics) tasks. In this paper, we tackle this problem by adopting the principles of Optimal Stopping Theory contributing with two time-optimized sequential decision making models. A performance evaluation is provided using real world data sets compared with baseline deterministic and stochastic models. The results show that our approach optimizes such decision in single user and competitive users scenarios.