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IEEE Global Conference on Communications (GLOBECOM) / Workshop on Wireless Networking and Control for UAV

作者： Amer, Ramy Butt, M. Majid ElSawy, Hesham Bennis, Mehdi Kibilda, Jacek Marchetti, Nicola Univ Dublin Trinity Coll CONNECT Dublin Ireland KFUPM Dhahran Saudi Arabia Univ Oulu Ctr Wireless Commun Oulu Finland

ISBN: (纸本)9781538647271

We formulate and solve the energy minimization problem for a clustered device-to-device (d2d) network with cache-enabled mobile devices. devices are distributed according to a Poisson cluster process (PCP) and are assumed to have a surplus memory which is exploited to proactively cache files from a library. devices can retrieve the requested files from their caches, from neighboring devices in their proximity (cluster), or from the base station as a last resort. We minimize the energy consumption of the proposed network under a random probabilistic caching scheme, where files are independently cached according to a specific probability distribution. A closed form expression for the d2d coverage probability is obtained. The energy consumption problem is then formulated as a function of the caching distribution, and the optimal probabilistic caching distribution is obtained. Results reveal that the proposed caching distribution reduces energy consumption up to 33% as compared to caching popular files scheme.

关键词： d2d caching energy consumption clustered process

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caching on the Move: A User Interest-driven caching Strategy for d2d Content Sharing

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2019年第3期68卷 2958-2971页

作者： Zhang, Wei Wu, dan Yang, Wendong Cai, Yueming Army Engn Univ PLA Nanjing 210007 Jiangsu Peoples R China Space Engn Univ PLA Beijing 101416 Peoples R China

device-to-device (d2d) content sharing helps to accommodate the exponentially surge in mobile data traffic. However, how to cache in mobile users is crucial to ensure the above advantages. There are three issues that have not been fully considered in the previous works. First, the ignorance of mobility cannot depict the random connectivity of mobile users in d2d content sharing. Second, the lack of the diverse and complete information on user interest leads to unsatisfied demands of users. Third, caching a complete content will be wasteful due to the limited cache capacity, which is also not likely to be obtained in one connection. Regarding the three issues, we construct not only a user mobility model, which helps to provide the contact opportunity for the users sharing contents, but also a user interest prediction model, which combines the social proximity and the dynamic content popularity. Moreover, we exploit the maximum distance separable code to encode the contents into smaller partitions. Accordingly, we formulate a mobility-aware and user interest-driven caching problem as a 0-1 multiple knapsack problem. due to its NP-hard property, we prove that this problem falls into the category of monotone sub-modular function over one matroid and multiple knapsack constraints. Then, we develop a corresponding algorithm based on a greedy approach, which approximates the optimum within a constant factor in polynomial time. Numerical results demonstrate the performance and the effectiveness of our proposed algorithm.

关键词： d2d caching mobility awareness interest prediction submodular maximization matroid knapsack constraint

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Residual Energy-Aware caching in Energy Harvesting-Based Mobile d2d Network

IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING

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IEEE TRANSACTIONS ON GREEN COMMUNICATIONS ANd NETWORKING 2020年第3期4卷 845-857页

作者： Chen, Zhengchuan Chen, Zhixiong Jia, Yunjian Wang, Li-Chun Chongqing Univ Key Lab Dependable Serv Comp Cyber Phys Soc Minist Educ Chongqing 400044 Peoples R China Chongqing Univ Sch Microelect & Commun Engn Chongqing 400044 Peoples R China Natl Chiao Tung Univ Dept Elect & Comp Engn Hsinchu 30010 Taiwan

caching popular contents on mobile devices is a promising technique to alleviate the backhaul data rate requirements. Since both file placement and data exchange among mobile devices consume energy, the energy status of the device can have a significant impact on the caching utility of the whole system. This work considers the caching optimization in a cellular network, where mobile devices are charged with energy harvested from the ambient environment. As the devices can collect the file segments from the local storage via device-to-device (d2d) links and cellular links, we aim at minimizing the percentage of file segment that should be collected from the base station (BS) by optimizing the file placement scheme on the devices. We prove that the optimal file placement scheme cannot be found in polynomial time by showing the intractability of the problem. Since the problem is NP-hard, we propose a residual energy-aware file placement algorithm based on the popularity distribution of contents and causality of energy arrival. In particular, we show that the proposed algorithm can fastly find a suboptimal file placement solution using dynamic programming. Extensive simulation results show that the proposed algorithm can effectively reduce the percentage of file segments collected from the BS compared with other two conventional caching methods.

关键词： Energy harvesting d2d caching residual energy offloading loss dynamic programming

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4-dMWM Approach for caching Based Optimal d2d Pairing and Channel Allocation: Centralized and distributed Algorithm design

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IEEE ACCESS 2016年 4卷 9213-9224页

作者： Miao, Lu Bai, Bo Chen, Wei Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

caching popular contents at mobile devices can potentially improve the quality of service for mobile users and relieve traffic burden of base station in cellular networks. In this paper, we jointly consider the resource allocation, the cached contents, and the distance between two devices for the optimal device pairing problem in centralized and distributed cases, where the BS is the central controller in the centralized case. The joint optimization problem of device-to-device (d2d) caching with channel allocation is formulated as a weighted four-uniform hypergraph model. The optimal solution for the problem is 4-d maximum weighted matching (4-dMWM), which is NP-hard unfortunately. To approach the 4-dMWM with low-complexity, we adopt the greedy algorithm and the squareIMP algorithm in the centralized case. Moreover, distributed algorithms are also designed for the caching problem in both synchronous and asynchronous cases. The simulation results will illustrate that the squareIMP algorithm can be used to get a better transmission rate with the complexity of O(n(5)), while the greedy algorithm can be used in the case with stringent latency requirement for centralized 4-dMWM problem. The sum rate of distributed asynchronous algorithm is close to the centralized greedy algorithm with the complexity of O(n(2)) for each device. However, the simulation result of the synchronous algorithm is slightly lower than the centralized algorithm, where each device performs O(n(2)) computational operations in each iteration. Therefore, the algorithms proposed in this paper can be used in different cases for solving optimal d2d pairing and channel allocation problem.

关键词： d2d caching weighted 4-uniform hypergraph 4-dimensional maximum weighted matching (4-dMWM) centralized algorithm distributed algorithm

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System-Level Spatiotemporal Offloading With Inter-Cell Mobility Model for device-to-device (d2d) Communication-Based Mobile caching in Cellular Network

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IEEE ACCESS 2020年 8卷 51570-51581页

作者： Lee, Junman Lee, Sang Hyun Rim, Minjoong Kang, Chung G. Korea Univ Sch Elect Engn Seoul 02841 South Korea Dongguk Univ Dept Informat & Commun Engn Seoul 04620 South Korea

We present a new spatiotemporal offloading (STO) framework that can deal with the time-varying traffic demand in an overloaded location using proactive caching during off-peak times. Focusing on a conventional cellular network, the system-wide mobility can be captured by the inter-cell transitions along individual users & x2019;mobility pattern. It is opposed to the existing geographical caching for content placement during off-peak times, which treats a system built around multiple base stations as a single service area, thus limiting its performance to low hit probability. We formulate a system-level STO problem to determine a content placement strategy that minimizes the access link load by delivering the requested data through device-to-device (d2d) links, rather than through a cellular link, particularly targeting potentially overloaded cells. Because its complexity is seriously attributed to the individual users & x2019;cell-by-cell mobility and content preferences, an aggregated flow model has been proposed to reduce the search space by invoking the law of segment conservation. Simulation results clearly demonstrate the effect of the spatiotemporal offloading that can be realized through inter-cell mobility-aware proactive caching. An extremely important implication of the current framework is that a varying traffic demand can be spatiotemporally distributed in a cellular system, overcoming the traditional limitation that arises from conservative or inefficient resource allocation due to a reliance on over-dimensioning.

关键词： Content delivery wireless caching mobility-aware caching d2d caching spatiotemporal offloading

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Socially-Aware caching in Wireless Networks With Random d2d Communications

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IEEE ACCESS 2019年 7卷 58394-58406页

作者： Khai Nguyen doan Thang Van Nguyen Shin, Hyundong Quek, Tony Q. S. Singapore Univ Technol & Design Singapore 487372 Singapore Univ Coll Dublin Dept Elect & Elect Engn Dublin D04 V1W8 4 Ireland Kyung Hee Univ Dept Elect Engn Yongin 17104 South Korea

Pushing contents to users with device-to-device (d2d) data sharing is considered as a promising solution to overcome backhaul congestion. However, this model is associated with critical issues which are user selfishness in terms of sharing personal resources and security concern when connecting with strange devices. Therefore, in this paper, we propose the notion of random d2d connection where the probabilities that the devices are connected for receiving or sharing data are manipulated by users themselves. Moreover, these probability values can also be treated as variables to be optimized. Based on that, we address the backhaul congestion issue and formulate it as a non-convex optimization problem. Two solving schemes are proposed based on primal decomposition and the alternating direction method of multipliers algorithm, respectively. In addition, these methods are designed in both centralized and distributed manners. Besides that, the congestion probability expression is derived in the special case giving an upper bound for the performance of our presented solution. The numerical results are provided to illustrate the effectiveness of the proposed method.

关键词： caching random connection d2d caching power allocation backhaul congestion selfishness security

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Mobility-Aware and Interest-Predicted caching Strategy Based on IoT data Freshness in d2d Networks

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IEEE INTERNET OF THINGS JOURNAL 2021年第7期8卷 6024-6038页

作者： Zhao, Xu Zhu, Qi Nanjing Univ Posts & Telecommun Dept Commun & Informat Engn Nanjing 210009 Peoples R China

The Internet of Things (IoT) will generate a large amount of data and the desired data are similar for users in particular regions. In these situations, data can be shared by d2d communication, which can significantly ease the traffic on BSs and effectively reduce the load. In this article, we propose an optimization algorithm for solving the joint problem of file caching and updating aimed at the d2d content-sharing scenario in the IoT. First, we construct a user-mobility model based on a Markov chain and a user-interest prediction model based on social proximity, user preference, and freshness. Then, we formulate the mobility-aware, freshness-based, and user-interest predicted optimization problem as a 0-1 multiple Knapsack problem, which is decomposed into two subproblems: 1) a cache problem and 2) an update problem. We prove that the cache problem's optimization objective is of the monotone submodular function over one matroid and multiple Knapsack constraints categories, while the update problem's optimization objective is a monotone decreasing function. The simulation results confirm that the optimization algorithm proposed in our article predicts the interests of users more accurately, improves the caching hit probability of files effectively, and maximizes utility for IoT network users.

关键词： device-to-device communication Optimization Internet of Things Predictive models Base stations Prediction algorithms delays d2d caching data freshness interest prediction Internet of Things (IoT) mobility partition matroid submodular function

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Multi-Agent Reinforcement Learning for Efficient Content caching in Mobile d2d Networks

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2019年第3期18卷 1610-1622页

作者： Jiang, Wei Feng, Gang Qin, Shuang Yum, Tak Shing Peter Cao, Guohong Univ Elect Sci & Technol China Natl Key Lab Commun Chengdu 611731 Sichuan Peoples R China Univ Elect Sci & Technol China Ctr Intelligent Networking & Commun Chengdu 611731 Sichuan Peoples R China Zhejiang Lab Hangzhou 310000 Zhejiang Peoples R China Penn State Univ Dept Comp Sci & Engn State Coll PA 16801 USA

To address the increase of multimedia traffic dominated by streaming videos, user equipment (UE) can collaboratively cache and share contents to alleviate the burden of base stations. Prior work on device-to-device (d2d) caching policies assumes perfect knowledge of the content popularity distribution. Since the content popularity distribution is usually unavailable in advance, a machine learning-based caching strategy that exploits the knowledge of content demand history would be highly promising. Thus, we design d2d caching strategies using multi-agent reinforcement learning in this paper. Specifically, we model the d2d caching problem as a multi-agent multi-armed bandit problem and use Q-learning to learn how to coordinate the caching decisions. The UEs can be independent learners (ILs) if they learn the Q-values of their own actions, and joint action learners (JALs) if they learn the Q-values of their own actions in conjunction with those of the other UEs. As the action space is very vast leading to high computational complexity, a modified combinatorial upper confidence bound algorithm is proposed to reduce the action space for both IL and JAL. The simulation results show that the proposed JAL-based caching scheme outperforms the IL-based caching scheme and other popular caching schemes in terms of average downloading latency and cache hit rate.

关键词： d2d caching multi-agent reinforcement learning

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Energy Efficient downlink Resource Allocations for d2d-Assisted Cellular Networks With Mobile Edge caching

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IEEE ACCESS 2019年 7卷 2053-2067页

作者： Liu, Yuanfei Wang, Ying Sun, Ruijin Meng, Sachula Su, Runcong Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

In this paper, a downlink device-to-device (d2d)-assisted cellular networks with mobile edge caching, where most popular video files are independently cached in d2d users and cellular base station (BS), are studied. In the considered system model, each user may obtain the requested video from the cache of BS or/and d2d users surrounding them. According to the different collaborative schemes of BS caching and d2d caching, it can be divided into two different resource allocation schemes. In the hybrid caching transmission scheme, users could adopt the BS caching mode or alternatively the d2d caching mode. In the joint caching transmission scheme, each user may obtain the requested files from the BS server and the adjacent d2d users, simultaneously. By taking the required data rate and the interference constraint into account, we formulate two joint resource allocation problems integrating link selection, channel allocation, and power control to maximize the system energy efficiency (EE). Leveraging on the dinkelbach method, the EE optimization problems are transformed into mixed-integer nonlinear programming problems and can be decomposed into three subproblems: link selection, channel allocation, and power control. To solve these complicated problems, we propose two optimization algorithms that consist of a modified branch and bound method as well as Lagrange dual decomposition approach. The simulation results demonstrate the superiority of these two proposed algorithms in improving system throughput and EE compared with other algorithms.

关键词： MEC d2d caching link selection subchannel allocation power allocation

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Residual Energy-Aware caching in Mobile d2d Cellular Network

Residual Energy-Aware Caching in Mobile D2D Cellular Network

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IEEE International Conference on Communications (IEEE ICC)

作者： Chen, Zhixiong Chen, Zhengchuan Jia, Yunjian Liang, Liang Chongqing Univ Sch Microelect & Commun Engn Chongqing 400044 Peoples R China

ISBN: (纸本)9781538680889

caching popular contents at the mobile devices is a promising technique to alleviate the backhaul data rate demand. Since both file placement and data exchange among mobile devices consume energy, the energy status of devices has a significant effect on the caching utility of the whole system. This work considers the caching optimization in a cellular network where mobile devices are served by one base station (BS). As the devices can collect the file segments from the local storage, via device-to-device (d2d) links, and via a cellular link, we aim at minimizing the percentage of file segment that should be collected from the BS by optimizing the file placement scheme at devices to improve caching performance. due to the difficulty of solving the optimal caching problem, we propose a residual energy-aware file placement algorithm based on the popularity distribution of contents and causality of energy arrival. Simulation results show that in comparison to other two conventional caching methods, the proposed algorithm can effectively reduce the percentage of file segments that collected from the BS.

关键词： d2d caching residual energy offloading loss dynamic programming

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