Energy-Efficient Cache Localization in Device-to-Device Network - Prerna, Duvya (TIET, 2019)
Last few years has seen one of the most important challenges for smart devices that is resource allocation. This has been a major bottleneck as there have been advancements in the cellular technology, especially 5G. With the increase in the enormous amount of number of users, there has been an increase in the demand of services and content within fraction of seconds. This has increased the burden on the network with respect to QoS and QoE to the end users and service providers. Caching the most popular contents on the user’s equipments (UE’s) can solve the problems because contents will be nearer to the users and can be shared using Device-to-Device (D2D) communication without the involvement of the core network. Motivated by this fact, in this thesis we present an extensive survey on the present caching techniques for D2D communication in 5G. Further, we present a model to address the problem of cache location decision. First, we find form a network of users using Matlab. Then we create dataset for predicting the cache locations in a network. Further, we predict the location where the user caches the most accessed content using machine learning classification models. The classification models used are decision tree and random forest. We compare the results obtained from decision tree and random forest classification model. On comparison we observe that the random forest model considering the trust factor between the users has higher accuracy. Then we use iFogSim simulator, to simulate the sending and receiving of contents in the network in a Software Defined Network environment. The metrics used for evaluating the simulations are access delay and energy consumption of the user’s equipment (UE’s). On analyzing the obtained result from simulation, we observe that the access delay is maximum at the users end when the sharing is with the gateway and energy consumption of the UE’s is also the maximum when the contents are accessed from the gateway.
Keywords: Cache Locations; D2D; IoT