Browsing by Author "Ali A.S."

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    Group mobility-based optimization of cache content in wireless device-to-device networks
    (Institute of Electrical and Electronics Engineers Inc., 2019) Naguib K.M.; Ali A.S.; Mahmoud K.R.; Department of Electrical Systems Engineering; October University for Modern Sciences and Arts (MSA); Giza; Egypt; Department of Electronics Communications and Computers; Helwan University; Cairo; Egypt
    Content caching in Device-to-Device (D2D) wireless cellular network can be considered an attractive solution to decrease network load during peak time hence improve network performance. In such network, predicting users' movement pattern allows proactive caching to alleviate its congestion leading to load decrease. Optimizing caching process is one important issue to enhance network performance and thus increase offloading probability. In this work, a caching policy strategy is introduced where the network jointly recognizes group mobility and user preferences to solve the caching optimization problem. Particle Swarm Optimization (PSO) algorithm is used to minimize the overall network load by optimizing the amount of data cached in users devices. Simulations are carried out to evaluate performance of presented optimal caching policy. Numerical results in terms of network gain show that the proposed caching scheme optimized by PSO outperforms both baseline scenario and random mobility-based schemes. � 2018 IEEE.
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    Optimal caching policy for wireless content delivery in D2D networks
    (Academic Press, 2020) Ali A.S.; Mahmoud K.R.; Naguib K.M.; Department of Electronics; Communications and Computers; Faculty of Engineering; Helwan University; Cairo; Egypt; National Telecommunications Regulatory Authority; Ministry of Communication and Information Technology; Giza; Egypt; Department of Electrical Systems Engineering; Faculty of Engineering; October University for Modern Sciences and Arts (MSA); Giza; Egypt
    The 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 Ltd