Ali A.S.Mahmoud K.R.Naguib K.M.Department of ElectronicsCommunications and ComputersFaculty of EngineeringHelwan UniversityCairoEgypt; National Telecommunications Regulatory AuthorityMinistry of Communication and Information TechnologyGizaEgypt; Department of Electrical Systems EngineeringFaculty of EngineeringOctober University for Modern Sciences and Arts (MSA)GizaEgypt2020-01-092020-01-09202010848045https://doi.org/10.1016/j.jnca.2019.102467PubMed ID :https://t.ly/w1mB0ScopusThe huge demand for multimedia services has exponentially grown in mobile networks and is expected to congest cellular traffic in the near future. Since network resources are limited, content caching may be considered a superior solution to offload data traffic during peak times. Content caching in mobile devices together with Device-to-Device (D2D) communications can improve the performance of cellular wireless networks. Predicting user demand and his mobility pattern allows the network to proceed proactive caching in order to relieve the network congestion and hence decreases the network load as well as its service cost. Moreover, performing an optimal caching policy is one of the important issues to maximize the offloading probability and as a result enhances the overall network performance. In this paper, we are introducing an incentive caching policy in which networks jointly considers the user preference and group mobility for the caching problem. Firstly, the cost optimal caching problem for the network is formulated. Then, the overall network cost is minimized due to the effect of user demand and group mobility using the Frequency Searching Adaptive Bat Algorithm (FSABA) by optimizing the cached portions of requested files. System performance analysis in terms of the overall network gain, average transmission delay and offloading probability are derived and evaluated according to the achieved optimal cached portions. Extended simulations are carried out to validate the beneficial of the presented optimal caching policy. Additionally, to verify the effectiveness of FSABA, the results are compared with those obtained using the Particle Swarm Optimization (PSO) algorithm. The results show that the proposed caching scheme outperforms both the baseline scenario and the random mobility-based schemes. It is worth mentioning that the FSABA can achieve a superior convergence capability compared to the PSO. � 2019 Elsevier LtdEnglishAverage transmission delayCaching policyDevice-to-Device cachingFrequency searching adaptive bat algorithmGroup mobilityOffloading probabilityParticle swarm optimizationUser preferenceCache memoryMobile telecommunication systemsMultimedia servicesProbabilityWireless networksAverage transmission delaysBat algorithmsCaching policyDevice-to-Device cachingGroup mobilityUser preferenceParticle swarm optimization (PSO)Articlehttps://doi.org/10.1016/j.jnca.2019.102467PubMed ID :