Proactive content caching by exploiting transfer learning for mobile edge computing

To address the vast multimedia traffic volume and requirements of user quality of experience in the next‐generation mobile communication system (5G), it is imperative to develop efficient content caching strategy at mobile network edges, which is deemed as a key technique for 5G. Recent advances in edge/cloud computing and machine learning facilitate efficient content caching for 5G, where mobile edge computing can be exploited to reduce service latency by equipping computation and storage capacity at the edge network. In this paper, we propose a proactive caching mechanism named learning‐based cooperative caching (LECC) strategy based on mobile edge computing architecture to reduce transmission cost while improving user quality of experience for future mobile networks. In LECC, we exploit a transfer learning‐based approach for estimating content popularity and then formulate the proactive caching optimization model. As the optimization problem is NP‐hard, we resort to a greedy algorithm for solving the cache content placement problem. Performance evaluation reveals that LECC can apparently improve content cache hit rate and decrease content delivery latency and transmission cost in comparison with known existing caching strategies.     

Joint computation offloading and task caching for multi-user and multi-task MEC systems: reinforcement learning-based algorithms

Computation offloading at mobile edge computing (MEC) servers can mitigate the resource limitation and reduce the communication latency for mobile devices. Thereby, in this study, we proposed an offloading model for a multi-user MEC system with multi-task. In addition, a new caching concept is introduced for the computation tasks, where the application program and related code for the completed tasks are cached at the edge server. Furthermore, an efficient model of task offloading and caching integration is formulated as a nonlinear problem whose goal is to reduce the total overhead of time and energy. However, solving these types of problems is computationally prohibitive, especially for large-scale of mobile users. Thus, an equivalent form of reinforcement learning is created where the state spaces are defined based on all possible solutions and the actions are defined on the basis of movement between the different states. Afterwards, two effective Q-learning and Deep-Q-Network-based algorithms are proposed to derive the near-optimal solution for this problem. Finally, experimental evaluations verify that our proposed model can substantially minimize the mobile devices’ overhead by deploying computation offloading and task caching strategy reasonably.

     

基于网络代价的流媒体缓存策略研究

该文构造了一种新的流媒体缓存效用函数,该函数综合考虑流媒体节目的流行度特性及传输网络的代价参数;设计了一种针对多视频服务器、基于网络代价的流媒体缓存分配与替换算法(Network Cost Based cache allocation and replacement algorithm, NCB)。仿真实验结果显示,NCB算法有效提高了缓存命中率,降低了传送流媒体所消耗的总体网络代价;该算法在网络结构复杂、节目数量庞大的Internet流媒体应用环境中表现出较优越的性能。     

基于联盟链的运营商最佳缓存策略

基于区块链的边缘缓存技术可以实现更大范围的内容共享并提高缓存内容的使用效率。针对不同运营商各自建设边缘设备,缓存内容相互隔离,难以共享信息的问题,该文提出一种基于联盟链的边缘缓存系统框架并设计了内容共享和交易流程,实现了不同运营商之间的内容共享。此外,为了降低高维缓存节点的共识开销,设计了基于内容缓存的部分实用拜占庭容错(pPBFT)共识机制,仅选取缓存相关内容的联盟链节点作为验证智能合约的执行节点。最后,将运营商内容共享所带来的收益进行量化并构建为最大化收益的优化问题。通过所提出的内容缓存算法,得到了最优缓存决策的闭式表达式和与内容流行度相关的最优缓存策略。仿真结果表明,在该框架中所提出的共识机制和缓存策略能够有效增加运营商的缓存收益。     

雾无线接入网中基于内容流行度和信息新鲜度的缓存更新策略

将边缘缓存技术引入雾无线接入网,可以有效减少内容传输的冗余。然而,现有缓存策略很少考虑已缓存内容的动态特性。该文提出一种基于内容流行度和信息新鲜度的缓存更新算法,该算法充分考虑用户的移动性以及内容流行度的时空动态性,并引入信息年龄(AoI)实现内容的动态更新。首先,所提出算法根据用户的历史位置信息,使用双向长短期记忆网络(Bi-LSTM)预测下一时间段用户位置;其次,根据预测得到的用户位置,结合用户的偏好模型得到各位置区的内容流行度,进而在雾接入点进行内容缓存。然后,针对已缓存内容的信息年龄要求,结合内容流行度分布,通过动态设置缓存更新窗口以实现高时效、低时延的内容缓存。仿真结果表明,所提算法可以有效地提高内容缓存命中率,在保障信息的时效性的同时最大限度地减小缓存内容的平均服务时延。     

双基地雷达栅栏覆盖的二维布站优化方法

为解决双基地雷达栅栏覆盖的优化问题,该文提出一种基于相邻部署线的2维布站优化方法。该方法首先将感兴趣区域用矩形区域近似替代,再将矩形区域划分为多个相同的子栅栏覆盖区域;其次为了充分发挥发射器的效能,该方法不仅利用同条部署线上的发射器与接收器组成双基地雷达,同时也采用相邻部署线之间的发射器与接收器组成双基地雷达。为此提出一种新的基本布站模式,并以该模式为基础建立2维布站的优化模型。该模型以布站成本最小为准则,覆盖区域为约束条件。为了求解该优化模型,该文提出一种基于贪婪算法的求解方法,该方法可以确定2维布站中发射器与接收器的数量及其位置。最后,仿真试验和分析表明该文方法可以有效降低布站成本,减少发射器的使用数量,证明了该文布站优化方法的有效性。     

Mobility aware edge service migration strategy

To address the problem of load imbalance among edge servers and quality of service degradation caused by dynamic changes of user locations in mobile edge computing networks,a mobility aware edge service migration algorithm was proposed.Firstly,the optimization problem was formulated as a mix integer nonlinear programming problem,with the goal of minimizing the perceived delay of user service request.Then,the delay optimization problem was decoupled into the edge service migration and edge node selection sub-problems based on the Lyapunov optimization approach.Thereafter,the fast edge decision algorithm was proposed to optimize the resource allocation and edge service migration under a given radio access strategy.Finally,the asynchronous optimal response algorithm was proposed to iterate out the optimal radio access strategy.Simulation results validate the proposed algorithm can reduce the perceived delay under the service migration cost constraint while comparing with other existing algorithms.     

基于P2P的可运营媒体内容分发网络的设计与实现

为在3TNet 上开展视频业务提供高喷量媒体内容的分发支持,实现高性价比的可运营内容分发服务,采用CDN与P2P结合的架构,实现了基于P2P的可运营媒体内容分发网络.系统采用了灵活的内容分发算法管理平台,方便根据需要采用各种合适的副本分发、内容缓存算法.系统具有节点、媒体内容和系统部署成本高度可控,运营质量高,运营成本低等特点.     

Modeling and implementation of 5G edge caching over satellite

The fifth‐generation (5G) wireless networks have to deal with the high data rate and stringent latency requirements due to the massive invasion of connected devices and data‐hungry applications. Edge caching is a promising technique to overcome these challenges by prefetching the content closer to the end users at the edge node's local storage. In this paper, we analyze the performance of edge caching 5G networks with the aid of satellite communication systems. First, we investigate the satellite‐aided edge caching systems in two promising use cases: (a) in dense urban areas and (b) in sparsely populated regions, eg, rural areas. Second, we study the effectiveness of satellite systems via the proposed satellite‐aided caching algorithm, which can be used in three configurations: (a) mono‐beam satellite, (b) multi‐beam satellite, and (c) hybrid mode. Third, the proposed caching algorithm is evaluated by using both empirical Zipf‐distribution data and the more realistic Movielens dataset. Last but not least, the proposed caching scheme is implemented and tested by our developed demonstrators which allow real‐time analysis of the cache hit ratio and cost analysis.     

Cache‐at‐relay: energy‐efficient content placement for next‐generation wireless relays

Uploading and downloading content have recently become one of the major reasons for the growth of Internet traffic volume. With the increasing popularity of social networking tools and their video upload/download applications, as well as the connectivity enhancements in wireless networks, it has become a second nature for mobile users to access on‐demand content on‐the‐go. Urban hot spots, usually implemented via wireless relays, answer the bandwidth need of those users. On the other hand, the same popular contents are usually acquired by a large number of users at different times, and fetching those from the initial content source each and every time makes inefficient use of network resources. In‐network caching provides a solution to this problem by bringing contents closer to the users. Although in‐network caching has been previously studied from latency and transport energy minimization perspectives, energy‐efficient schemes to prolong user equipment lifetime have not been considered. To address this problem, we propose the cache‐at‐relay (CAR) scheme, which utilizes wireless relays for in‐network caching of popular contents with content access and caching energy minimization objectives. CAR consists of three integer linear programming models, namely, select relay, place content, and place relay, which respectively solve content access energy minimization, joint minimization of content access and caching energy, and joint minimization of content access energy and relay deployment cost problems. We have shown that place relay significantly minimizes the content access energy consumption of user equipments, while place content provides a compromise between the content access and the caching energy budgets of the network. Copyright © 2015 John Wiley & Sons, Ltd.     

Transient content caching and updating with modified harmony search for Internet of Things

Internet of Things (IoT) has emerged as one of the new use cases in the 5th Generation wireless networks. However, the transient nature of the data generated in IoT networks brings great challenges for content caching. In this paper, we study a joint content caching and updating strategy in IoT networks, taking both the energy consumption of the sensors and the freshness loss of the contents into account. In particular, we decide whether or not to cache the transient data and, if so, how often the servers should update their contents. We formulate this content caching and updating problem as a mixed 0–1 integer non-convex optimization programming, and devise a Harmony Search based content Caching and Updating (HSCU) algorithm, which is self-learning and derivative-free and hence stipulates no requirement on the relationship between the objective and variables. Finally, extensive simulation results verify the effectiveness of our proposed algorithm in terms of the achieved satisfaction ratio for content delivery, normalized energy consumption, and overall network utility, by comparing it with some baseline algorithms.     

命名数据网络中基于内容请求相关性的协作缓存算法

针对命名数据网络(Named Data Networking, NDN)存储空间的有效利用和应答内容的高效缓存问题,该文采用差异化缓存的方式,提出一种依据内容请求序列相关性的协作缓存算法。在内容请求中,预先发送对于后续相关数据单元的并行预测请求,增大内容请求的就近响应概率;缓存决策时,提出联合空间存储位置与缓存驻留时间的2维差异化缓存策略。根据内容活跃度的变化趋势,空间维度上逐跳推进内容存储位置,时间维度上动态调整内容缓存时间,以渐进式的方式将真正流行的请求内容推送至网络边缘存储。该算法减小了内容请求时延和缓存冗余,提高了缓存命中率,仿真结果验证了其有效性。     

Distributed servers architecture for networked video services

In an on-demand video system, the video repository generally has limited streaming capacities and may be far from the users. In order to achieve higher user capacity and lower network transmission cost, distributed servers architecture can be used, in which multiple local servers are placed close to user pools and, according to their local demands, dynamically cache the contents streamed from the repository. We study a number of caching schemes as applied in the local servers depending on whether the repository is able to multicast movie contents to the local servers or not, and whether the local servers can exchange their cached contents among themselves or not. Our caching schemes keep a circular buffer of data for the movie requested, and hence movies are partially cached. By adjusting the size of the buffer, such caching is able to achieve better tradeoff between network channels and local storage as compared to the traditional caching in which a movie is treated as an entity. For each caching scheme, we study the tradeoff between the local storage and the network channels, and address how the total cost of the system can be minimized by appropriately sizing the buffer. As compared to a number of traditional operations (request batching and multicasting, true-VOD, etc.), we show that distributed servers architecture is able to achieve much lower system cost to offer on-demand video services     

Optimizing content routers deployment in large‐scale information centric core‐edge separation Internet

In this paper, we investigate the optimization of content router deployment in large‐scale information centric core‐edge separation Internet. We formulate the target cost function, which captures the trade‐off between the cost for traffic transmission and cost due to additional deployment of content routers. To solve the problem, we first derive the analytical results of traffic ratio and its closed‐form approximation. We then construct a convex optimization problem, from which the optimal deployment probability can be solved. By extensive numerical results, the accuracy of the closed‐form approximation of traffic ratio is demonstrated. And, it is found that the optimal deployment probability is decided by the average number of hops for obtaining the content, the cost for traffic transmission, and the cost of extending router to content router. Copyright © 2013 John Wiley & Sons, Ltd.     

Cooperative caching algorithm of UAV and user in UAV-assisted cellular network

Aiming at the problem of mass data content transmission and limited wireless backhaul resource of UAV in UAV-assisted cellular network,a cooperative caching algorithm for cache-enabled UAV and user was proposed.By deploying caches on UAV and user device,the popular content requested by user was cached and delivered,which alleviated the backhaul resource and energy consumption of UAV,reduced the traffic load and user delay.A joint optimization problem of UAV and user caching was established with the goal of minimizing user content acquisition delay,and decomposed into UAV caching sub-problem and user caching sub-problem,which were solved based on alternating direction method of multiplier and global greedy algorithm respectively.The iterative way was used to obtain convergent optimization result,and the cooperative caching of UAV and user was realized.Simulation results show that the proposed algorithm can effectively reduce user content acquisition delay and improve system performance.     

移动边缘计算中服务功能链的自适应优化部署策略

为解决移动边缘计算中面向用户的服务功能链（Service Function Chain,SFC）部署成本开销过大、时延过长问题,提出了针对SFC的支出成本与时延联合自适应优化的部署策略。首先,在虚拟网络功能（Virtualized Network Function,VNF）节点选取阶段,考虑路径损耗这一无线信道衰落问题,根据有线用户与无线用户的位置情况,选择当前最佳节点以降低SFC的响应时延。其次,在服务节点配置阶段,根据用户请求处理的数据内容的新鲜度记录,自适应动态增加和删减相应的缓存,利用资源感知算法在保证数据传递可靠性的同时,减少服务节点的配置个数,降低配置开销。最后,在SFC部署阶段,利用基于KSP（K-shortest Paths）的功耗感知算法确定最佳节点映射排序与通信链路,在减少通信链路重映射的同时还能保证部署的SFC的低成本与低时延。实验仿真结果表明,相比于已有方案,该方法能够有效降低部署成本与时延,并能对不同用户的SFC部署做到自适应优化,提高了SFC的部署成功率。     

具负载平衡之IPTV影音串流系统

影音媒体具高带宽及实时特性,因此影音串流系统的服务质量的提升端赖影音服务器的有效管理。在此提出一套Video replication及Access request distribution的算法,藉由将热门影音分散到各影音服务器以及影音存取的分散,以达到各影音服务器系统负载平衡的效果。在此比较了3个不同的算法的负载平衡的状况,经实例验证,提出的算法确能达到影音服务器负载平衡的效果,承载更多的系统服务要求。该系统构建在Smart-i TV的IPTV系统台,并讨论了实作的相关技术。     

Efficient complementary caching for ISP-aware networks

Internet service providers(ISPs) have taken some measures to reduce intolerable inter-ISP peer-to-peer(P2P) traffic costs,therefore user experiences of various P2P applications have been affected.The recently emerging offline downloading service seeks to improve user experience by using dedicate servers to cache requested files and provide high-speed uploading.However,with rapid increase in user population,the server-side bandwidth resource of offline downloading system is expected to be insufficient in the near future.We propose a novel complementary caching scheme with the goal of mitigating inter-ISP traffic,alleviating the load on servers of Internet applications and enhancing user experience.Both architecture and caching algorithm are presented in this paper.On the one hand,with full knowledge of P2P file sharing system and offline downloading service,the infrastructure of complementary caching is designed to conveniently be deployed and work together with existing platforms.The co-operational mechanisms among different major components are also included.On the other hand,with in-depth understanding of traffic characteristics that are relevant to caching,we develop complementary caching algorithm with respect to the density of requests,the redundancy of file and file size.Since such relevant information can be real-time captured in our design,the proposed policy can be implemented to guide the storage and replacement of caching unities.Based on real-world traces over 3 months,we demonstrate that the complementary caching scheme is capable to achieve the ’three-win’ objective.That is,for P2P downloading,over 50% of traffic is redirected to cache;for offline downloading,the average server-dependence of tasks drops from 0.71 to 0.32;for user experience,the average P2P transfer rate is increased by more than 50 KB/s.     

抗侧信道攻击的服务功能链部署方法

侧信道攻击是当前云计算环境下多租户间信息泄露的主要途径,针对现有服务功能链(SFC)部署方法未充分考虑多租户环境下虚拟网络功能(VNF)面临的侧信道攻击问题,该文提出一种抗侧信道攻击的服务功能链部署方法。引入基于时间均值的租户分类策略以及结合历史信息的部署策略,在满足服务功能链资源约束条件下,以最小化租户所能覆盖的服务器数量为目标建立相应的优化模型,并设计了基于贪婪选择的部署算法。实验结果表明,与其他部署方法相比,该方法显著提高了恶意租户实现共存的难度与代价,降低了租户面临的侧信道攻击风险。