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Value-driven Cache Replacement Strategy in Mobile Edge Computing

机译:移动边缘计算中的值驱动缓存替换策略

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The mobile edge computing greatly reduces the transmission delay by offloading computing job to the base station, which is closer to the user. It solves the problem of high delay in cloud computing. Since the edge server has limited resources, improving the efficiency of computation offloading becomes a problem that needs to be addressed. Considering the data is reusable, it is a feasible solution to use the cache to improve the efficiency of computation offloading. In order to make the cache better serve the computation offloading process, we must design a reasonable cache replacement strategy. The traditional cache replacement strategy only considers the cache hit ratio, but ignores the cache value. It is not applicable to the edge computing process. In this paper, a new cache replacement strategy is proposed for the cache replacement problem in mobile edge computing, which is more suitable for computation offloading process. First, we define the cache value based on the priority of computing job. Then, we define the problem of maximizing the cache value in mobile edge computing as a multiobjective optimization problem. Finally, in order to find a suitable Pareto solution, we propose a cache replacement strategy based on the ideal point method. The experimental results show that the proposed algorithm results are significantly better than the existing competitive cache replacement methods.
机译:移动边缘计算通过将计算作业卸载到基站而大大降低了传输延迟,该基站更靠近用户。它解决了云计算的高延迟问题。由于边缘服务器具有有限的资源,提高计算卸载效率成为需要寻址的问题。考虑到数据是可重用的,它是使用缓存来提高计算卸载效率的可行解决方案。为了使缓存更好地服务于计算卸载过程,必须设计合理的缓存替换策略。传统的缓存替换策略仅考虑缓存命中率,但忽略缓存值。它不适用于边缘计算过程。在本文中,提出了一种新的缓存替换策略,用于移动边缘计算中的缓存替换问题,这更适合计算卸载过程。首先,我们根据计算作业的优先级来定义高速缓存值。然后,我们定义了将移动边缘计算中的高速缓存值最大化作为多目标优化问题的问题。最后,为了找到合适的帕累托解决方案,我们提出了一种基于理想点方法的缓存替换策略。实验结果表明,该算法结果明显优于现有的竞争缓存替换方法。

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