Collaborative Online Caching with Freshness in the Internet of Things

In this paper, a Collaborative Online Caching Algorithm with Freshness is proposed to solve the data caching problem in the Internet of Things (IoT) among multiple small base stations (SBSs). In this algorithm, the ability of SBSs to cooperate with each other is related to three factors: the number of coordinated connections each SBS establishes with other SBSs, the distance between SBSs, and the number of served users in the coverage area of each SBS. On the basis of cooperative caching strategy, this algorithm considers online settings and introduces the term of "freshness" in the IoT to restrict the real-time degree of files cached in SBS, and on the premise that the freshness of files meets the user's expectation, an optimization model is constructed to minimize the total cost paid by SBSs. We express the problem as an Integer Linear Program and prove its NP-completeness by mapping method of set covering problem, so that we can obtain the best scheme for SBSs to cache files. In addition, due to the limited cache capacity, we have improved the Least Recently Used Replacement Policy (LRU) to update cached files by combining freshness and the frequency each file has been requested. Finally, we calculate the time complexity of the algorithm. The simulation results manifest that, compared with the caching strategy without considering freshness, the algorithm in this paper greatly improves user satisfaction with a little increase in total costs.