Abstract
As more and more compute-intensive and delay-sensitive applications are deployed on smart mobile devices, mobile edge computing is considered an effective way to solve the limited computing ability of smart mobile devices (SMDs). At present, latency has become the most critical indicator of the quality of service (QoS), and more and more studies focus on this aspect. Unlike previous work, our work fully takes into account the limited storage and computing ability of edge servers. To effectively reduce the delay of SMDs and improve QoS, we propose a Delay Control Strategy Joint Service Caching and Task Offloading (DCS-OCTO) in a three-tier mobile edge computing (MEC) system consist of multi-user, multi-edge server and remote cloud servers. Some of the key challenges include service heterogeneity, unknown system dynamics, spatial demand coupling, and decentralized coordination. In particular, a very compelling but rarely studied issue is the dynamic service caching in the three-tier MEC system. The DCS-OCTO strategy is proposed based on Lyapunov optimization and Gibbs sampling. It works online without requiring prior information and achieves provable near-optimal performance. Finally, simulation results show that the strategy effectively reduces the overall system delay while ensuring low energy consumption.
Highlights
Nowadays, with the rapid development of the internet of things (IoT) and wireless technology, more and more smart mobile devices (SMDs) are showing explosive growth [1], [2]
In the SMDs-access points (AP)-remote servers three-layer mobile edge computing (MEC) system, under considering the storage space and computing capabilities of the MEC servers, we study the problem of minimizing system latency under the guarantee of energy consumption constraint of joint service caching and task offloading
Based on the Lyapunov optimization theory and Gibbs sampling, we developed a DCS-OCTO algorithm
Summary
With the rapid development of the internet of things (IoT) and wireless technology, more and more smart mobile devices (SMDs) are showing explosive growth [1], [2]. Remote cloud computing resources are usually deployed in large data centers far from most users This will cause SMD to have a longer delay and higher energy consumption during the offloading process [5]. In the SMDs-APs-remote servers three-layer MEC system, under considering the storage space and computing capabilities of the MEC servers, we study the problem of minimizing system latency under the guarantee of energy consumption constraint of joint service caching and task offloading. This problem is formulated as a mixed-integer nonlinear optimization problem. Considering the system delay and energy consumption from the perspective of APs storage space and energy consumption constraint, and the superiority of the algorithm is verified
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