论文标题
手机边缘计算中的同行卸载，并保证最差的响应时间
Peer Offloading in Mobile Edge Computing with Worst-Case Response Time Guarantees
论文作者
论文摘要
移动边缘计算（MEC）是一个新的范式，可在网络边缘提供云计算服务。为了通过有限的计算资源实现更好的性能，已经提出了合作边缘服务器之间的同伴卸载（例如，启用了启用MEC的基站），以作为处理计算任务的爆发和空间不平衡到达的有效技术。尽管文献中已经考虑了同伴卸载政策的各种绩效指标，但最糟糕的响应时间是实时应用程序中常见的服务质量（QoS）要求，但受到关注的关注要少得多。为了填补空白，我们根据随机到达模型制定了同行卸载问题，并针对有和没有事先了解任务到达率的情况的情况提出了两种在线算法。我们的目标是在能源消耗和最坏情况响应时间的限制下最大程度地提高时间平均吞吐量的效用。理论分析和数值结果都表明，我们的算法能够产生接近最佳性能。
Mobile edge computing (MEC) is a new paradigm that provides cloud computing services at the edge of networks. To achieve better performance with limited computing resources, peer offloading between cooperative edge servers (e.g. MEC- enabled base stations) has been proposed as an effective technique to handle bursty and spatially imbalanced arrival of computation tasks. While various performance metrics of peer offloading policies have been considered in the literatures, the worst-case response time, a common Quality of Service(QoS) requirement in real-time applications, yet receives much less attention. To fill the gap, we formulate the peer offloading problem based on a stochastic arrival model and propose two online algorithms for cases with and without prior knowledge of task arrival rate. Our goal is to maximize the utility function of time-average throughput under constraints of energy consumption and worst-case response time. Both theoretical analysis and numerical results show that our algorithms are able to produce close to optimal performance.
