Performance Enhancement of Cache Consistency Mechanism in Mobile Computing Environment

In the context of mobile computing, the cache memory technique turns out to be the most widely used and the most effective solution to improve several quantities, namely: (1) the bandwidth consumption, (2) the information availability, and (3) the node latency. particularly in the Internet of Things (IoT) environment, where objects have limited storage and computing capacities. However, this solution may cause some cache management issues, specifically data consistency and data replacement. In this paper, we strive to assess the relationship between the consistency mechanism’s performance and the implemented replacement strategy and determine whether they are correlated or not. Afterward, we focus on improving the caching consistency mechanism’s performance based on the Time To Live principle (TTL) using the IoT-Data lifetime and the data Variable-TTL. Therefore, two based-TTL consistency mechanisms were implemented and evaluated using three replacement strategies: LFU (Least Frequently Used), LRU (Least Recently Used), and LFRU (Least Frequently Recently Used). The simulation experiments show that the consistency mechanism performance strongly depends on the implemented replacement strategy, which can significantly improve the performance, particularly in terms of data availability and end-user latency. In addition, the relative frequency and the variable-TTL considerably improve the wireless mobile caching performance.