Research On Proactive Storage At Caching-Enable Base Stations

With the rapid development of mobile network,the traditional mobile communication industry is facing severe challenge of the limited network bandwidth.Storing the popular data in small base stations is an effective solution to reduce the traffic load on the backhaul link and increase network bandwidth utilization,which is base station proactive storage.Since the distance between the base station and the user is short,the data can be transmitted efficiently.The key problem of the proactive storage at base stations in cellular networks is the data storage and distribution.Most of the current research of base station proactive storage considered the transmission cost,the storage or the energy efficiency of the data but little research studied on user fairness.In fact,user fairness is also very important.In this thesis,we research on proactive storage at caching-enable base stations,and consider the fairness in the storage allocation scheme.The specific work is as follows:(1)We propose a maximum fairness storage allocation scheme(MFSA)to tackle the unfair resource allocation issue in edge caching.First,we model the fairness problem of the proactive storage.Specifically,we use random linear network coding to store the content in the base station,and we maximize the fairness index of storage allocation under the limitation of total storage and transmission cost.Then we design the genetic algorithm to solve the problem.In order to simplify genetic operations,we use matrix coding.We also use the penalty function method to transform constrained optimization into unconstrained optimization and use simulated annealing to accelerate the convergence rate of the algorithms.Finally,the problem is solved by using the designed genetic algorithm.The experimental data show that compared with the storage scheme of the comparative papers,our storage scheme has improvement in fairness,the fairness index increased by 15.70%,17.10% and 16.20% when the total storage limit is 3000,4000,5000 and increased by 12.51%,15.10%,20.54% and 21.20%when the transmission cost limit is 50,60,70,80.(2)We propose a MOEA/D based multi-objective storage caching scheme that optimizes total storage,total transmission cost and user fairness at the same time.First,we study the MOEA/D algorithm based on multi-object decomposition.According to the algorithm and the application requirements of base station storage,we define three associated optimization objectives and establish the constraint conditions.Then we design the MOEA/D algorithm to solve this problem.We simplifiy the algorithm by vectorizing the matrix of the evolutionary algorithm in the MOEA/D,and we introduce the simulated annealing into the penalty function to ensure the evolutionary direction of the population.Finally,we use the designed MOEA/D algorithm to solve the problem and a set of optimal solutions are obtained.Comparing the optimal solution with the weight vector,we found that we can set objectives by adjusting the weight vector,which provides different choices for the actual application scenario.In addition,the convergence of the algorithm is analyzed by the fixed weight vector.Through the analysis of the two aggregation methods,we found that in this thesis,the Tchebycheff aggregation method based MOEA/D algorithm is more suitable.