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Collaborative Content Caching and Task Offloading in Multi-Access Edge Computing
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AI
DOI：10.1109/TVT.2022.3222596.png)
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Abstract
En 中文
Mobile augmented reality (MAR) applications are gaining popularity. There are significant challenges in handling the latency-sensitive and computation-intensive tasks generated by MAR applications on mobile devices. The emergence of mobile edge computing (MEC) provides a new idea to improve the computing capability of resource-constrained mobile terminals. In this paper, we study the task offloading and cache placement of MAR tasks in multi-MEC server cooperation system. The problem of the task offloading and cache placement is formulated to maximize the hit ratio and minimize the service latency under the constraints of MEC server's computing resources and cache space. To solve this problem, we propose a task offloading and cache placement (MOTOCP) algorithm based on multi-objective artificial bee colony. Pareto optimal relation is introduced in the optimization process to find the optimal solution. Extensive evaluation verifies that our proposed algorithm has better performance.
Keywords:
Task analysis
Servers
Bandwidth
Augmented reality
Wearable computers
Symbols
Smart phones
Cache placement
Task offloading
Edge computing
MAR
Journal
IF:
7.1
Papers:
1.8W
Citations:
6.6W