PROJECT TITLE :

Cost-Optimal Caching for D2D Networks With User Mobility: Modeling, Analysis, and Computational Approaches - 2018

ABSTRACT:

Caching well-liked files at the user equipments (UEs) provides an efficient way to alleviate the burden of the backhaul networks. Usually, popularity-based mostly caching is not a system-wide optimal strategy, particularly for user mobility situations. Motivated by this observation, we have a tendency to think about optimal caching with the presence of mobility. A cost-optimal caching downside (COCP) for device-to-device (D2D) networks is modeled, in which the impact of user mobility, cache size, and total range of encoded segments are all taken under consideration. The hardness of the matter is proved via a reduction from the satisfiability drawback. Next, a lower-bounding function of the target function is derived. By the operate, an approximation of COCP (ACOCP) achieving linearization is obtained, that features two benefits. First, the ACOCP approach will use an off-the-shelf integer linear programming algorithm to get the global optimal resolution, and it can effectively deliver solutions for little-scale and medium-scale system scenarios. Second, and a lot of importantly, based on the ACOCP approach, one can derive a lower certain of world optimum of COCP, thus enabling performance benchmarking of any sub-optimal algorithm. To tackle large scenarios with low complexity, we have a tendency to 1st prove that the optimal caching placement of one user, giving other users' caching placements, will be derived in polynomial time. Then, primarily based on this proof, a mobility aware multi-user algorithm is developed. Simulation results verify the effectivenesses of the 2 approaches by comparing them to the lower sure of world optimum and typical caching algorithms.