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.     

Terrestrial Relay‐Aided Cooperative High Throughput Satellite Systems

Full frequency reuse based dual satellite system (DSS) is investigated in this work. In the case of DSS, user terminals receive inter spot beam and intra spot beam interfering signals due to the simultaneous transmission of data from both satellites. Cooperative precoding algorithm is proposed to mitigate these effects. The achievable data rates with zero‐forcing (ZF) and regularized ZF precoding algorithms are characterized. If the user terminals served by both satellites are colocated, then the proposed cooperative precoding algorithm fails because of correlated channels. To this end, relay‐aided DSS (RA‐DSS) is proposed. The achievable data rates of both full‐duplex and half‐duplex RA‐DSSs are characterized. Through simulations, it is shown that the proposed full‐duplex RA‐DSS achieves better data rate than the DSS, single satellite system, and orthogonal transmission even if the users are closely placed.     

Dynamic process location management in 5G

5G, as the next generation of wireless networks, promises very high throughput and low latency to mobile users that calls for a substantial innovation in computing management platforms to attend QoS metrics. Thanks to emerging technologies such as software‐defined networking (SDN)/network function virtualization (NFV), many features are available in 5G design to detect and control two types of latency caused by computation and communication. In this paper, taking features of caching mechanisms and SDN into the account, a platform is proposed to minimize latency in 5G via caching big flows intelligently and avoiding bottlenecks that may cause by virtualized computing components. First, the pioneering idea of compromising between the cloud radio access network (CRAN) and mobile edge computing (MEC)/information‐centric network (ICN) via dynamic processing location management platform is investigated. Accordingly, a mathematical optimization problem to minimize the average latency is formulated. Due to the problem complexity, a heuristic algorithm is proposed to treat the latency via dynamic orchestration of processing functionalities. Through numerical results, the performance of the proposed algorithm is analyzed, and the simulations corroborate our analytical results and illustrate the superior performance of the proposed algorithm with acceptable optimality gap.     

Distance control strategy for deploying content replica servers in an edge cloud

To reduce fetching cost from a remote source,it is natural to cache information near the users who may access the information later.However,with development of 5 G ultra-dense cellular networks andmobile edge computing(MEC),a reasonable selection among edge servers for content delivery becomes a problem when the mobile edge obtaining sufficient replica servers.In order to minimize the total cost accounting for both caching and fetching process,we study the optimal resource allocation for the content replica servers’ deployment.We decompose the total cost as the superposition of cost in several coverages.Particularly,we consider the criterion for determining the coverage of a replica server and formulate the coverage as a tradeoff between caching cost and fetching cost.According to the criterion,a coverage isolation(CI) algorithm is proposed to solve the deployment problem.The numerical results show that the proposed CI algorithm can reduce the cost and obtain a higher tolerance for different centrality indices.     

Tile caching for scalable VR video streaming over 5G mobile networks

Currently, VR video delivery over 5G systems is still a very complicated endeavor. One of the major challenges for VR video streaming is the expectations for low latency that current mobile networks can hardly meet. Network caching can reduce the content delivery latency efficiently. However, current caching schemes cannot obtain ideal results for VR video since it requests the viewport interactively. In this paper, we propose a tiled scalable VR video caching scheme over 5G networks. VR chunks are first encoded into multi-granularity quality layers, and are then partitioned into tiles to facilitate viewport data access. By accommodating the 5G network infrastructure, the tiles are cooperatively cached in a three-level hierarchal system to reduce delivery latency. Furthermore, a quality-adaptive request routing algorithm is designed to cater for the 5G bandwidth dynamics. Experimental results show that the proposed scheme can reduce the transmission latency over conventional constant bitrate video caching schemes.     

Satellite constellation of MEO and IGSO network routing with dynamic grouping

Because inter‐satellite links (ISLs) among the distributed satellite nodes can be used to support autonomous control in satellite system operation to reduce dependency on the ground stations, it becomes a popular communication paradigm for the future satellite systems. However, this introduces great technical challenges, particularly for routing protocol to support such space communication system. Facing the challenges, we present out study of routing technology in this paper tailored for satellite network of MEO (Table 1) and IGSO with ISLs in addition to satellite–ground links. The study aims to explore the routing strategies and algorithms of satellite network based on the evolution law of network topology to provide reference design for data exchange in autonomous satellite system. A comprehensive investigation, ranging from the analysis of relevant factors affecting data exchange in satellite networks to the primary application and resource constraints in designing satellite routing strategy, has been conducted. Our main contribution is to propose an on‐demand computing and caching centralized routing strategy and algorithm on the satellite network. The routing strategy and algorithm is designed for satellite network topology dynamic grouping. The route calculation for user data transmission is divided into three phases: direction estimation, direction enhancement, and congestion avoidance. The strategy and algorithm provide significant advantages of high efficiency, low complexity, and flexible configuration, by which the satellite networks can provide the features of flexible configure, efficient transferring, easy management, structural survivability, and great potential in scalability. Copyright © 2013 John Wiley & Sons, Ltd.     

LTE‐based satellite communications in LEO mega‐constellations

The integration of satellite and terrestrial networks is a promising solution for extending broadband coverage to areas not connected to a terrestrial infrastructure, as also demonstrated by recent commercial and standardisation endeavours. However, the large delays and Doppler shifts over the satellite channel pose severe technical challenges to traditional terrestrial systems, as long‐term evolution (LTE) or 5G. In this paper, 2 architectures are proposed for a low Earth orbit mega‐constellation realising a satellite‐enabled LTE system, in which the on‐ground LTE entity is either an eNB (Sat‐eNB) or a relay node (Sat‐RN). The impact of satellite channel impairments as large delays and Doppler shifts on LTE PHY/MAC procedures is discussed and assessed. The proposed analysis shows that, while carrier spacings, random access and RN attach procedures do not pose specific issues and hybrid automatic repeat request requires substantial modifications. Moreover, advanced handover procedures will be also required due to the satellites' movement.     

An efficient in‐network caching decision algorithm for Internet of things

Recently, content‐centric networking (CCN) has become one of the important technologies for enabling the future networks. Along with its recognized potentialities as a content retrieval and dissemination solution, CCN has been also recently considered as a promising architecture for the Internet of things (IoT), because of 2 main features such as named‐based routing and in‐network caching. However, IoT is characterized by challenging features: small storage capacity of resource‐constrained devices due to cost and limitation of energy and especially transient data that impose stringent requirements on the information freshness. As a consequence, the intrinsic caching mechanisms existing in CCN approach do not well suit IoT domains; hence, providing a specific caching policy at intermediate nodes is a very challenging task. This paper proposes an effective multiattribute in‐network caching decision algorithm that performs a caching strategy in CCN‐IoT network by considering a set of crucial attributes including the content store size, hop count, particularly key temporal properties like data freshness, and the node energy level. Simulation results proved that our proposed approach outperforms 2 cache management schemes (probabilistic least recently used and AlwaysCache–first in first out in terms of improving total hit rate, reducing data retrieval delay, and enhancing content reusability in IoT environment).     

Dynamic theoretic proactive caching placement game for energy saving in H‐CRAN

Edge caching is an effective feature of the next 5G network to guarantee the availability of the service content and a reduced time response for the user. However, the placement of the cache content remains an issue to fully take advantage of edge caching. In this paper, we address the proactive caching problem in Heterogeneous Cloud Radio Access Network (H‐CRAN) from a game theoretic point of view. The problem is formulated as a bargaining game where the remote radio heads (RRHs) dynamically negotiate and decide which content to cache in which RRH under energy saving and cache capacity constraints. The Pareto optimal equilibrium is proved for the cooperative game by the iterative Nash bargaining algorithm. We compare between cooperative and noncooperative proactive caching games and demonstrate how the selfishness of different players can affect the overall system performance. We also showed that our cooperative proactive caching game improves the energy consumption of 40% as compared with noncooperative game and of 68% to no‐game strategy. Moreover, the number of satisfied requests at the RRHs with the proposed cooperative proactive caching scheme is significantly increased.     

Efficient packet scheduling for heterogeneous multimedia provisioning over broadband satellite networks: An adaptive multidimensional QoS‐based design

With their inherent broadcast capabilities and reliable extensive geographical coverage, the broadband satellite networks are emerging as a promising approach for the delivery of multimedia services in 3G and beyond systems. Given the limited capacity of the satellite component, to meet the diverse quality of service (QoS) demands of multimedia applications, it is highly desired that the available resources can be adaptively utilized in an optimized way. In this paper, we draw our attention on the development and evaluation of an efficient packet scheduling scheme in a representative broadband satellite system, namely satellite digital multimedia broadcasting (SDMB), which is positioned as one of the most attractive solutions in the convergence of a closer integration with the terrestrial mobile networks for a cost‐effective delivery of point‐to‐multipoint services. By taking into account essential aspects of a successful QoS provisioning while preserving the system power/resource constraints, the proposed adaptive multidimensional QoS‐based (AMQ) packet scheduling scheme in this paper aims to effectively satisfy diverse QoS requirements and adaptively optimize the resource utilization for the satellite multimedia broadcasting. The proposed scheme is formulated via an adaptive service prioritization algorithm and an adaptive resource allocation algorithm. By taking into account essential performance criteria, the former is capable of prioritizing contending flows based on the QoS preferences and performance dynamics, while the latter allocates the resources, in an adaptive manner, according to the current QoS satisfaction degree of each session. Simulation results show that the AMQ scheme achieves significantly better performance than those of existing schemes on multiple performance metrics, e.g. delay, throughput, channel utilization and fairness. Copyright © 2008 John Wiley & Sons, Ltd.     

A tradeoff resource allocation based on MF‐TDMA scheme in the multibeam data relay satellite systems

A tremendous increase in the number of distributed satellite constellations with the unscheduled burst data traffic will impose addition and diverse requirements on the DRS (data relay satellite) systems, which increases the complexity for beam management and affects a real‐time data return and acquisition. In this paper, we suggested that a large capacity can be achieved by a multibeam DRS system based on multifrequency time division multiple access scheme providing multiaccess for the distributed satellite constellations. Because the space‐based information network is characterized by the limited on‐board resources, a highly dynamic topology and time‐varying intersatellite links, we designed a 2‐stage dynamic optimization approach to separate the multiobjective optimization for frequency/time blocks and power, aiming at the rapidly converging to the optimal solution and at the same time meeting the fairness resource allocation. In particular, a capacity‐fairness tradeoff algorithm is proposed based on hybrid the enhanced genetic algorithm and the particle swarm optimization. Simulation results show that the tradeoff between maximizing total capacity and providing proportional fairness allocation is well balanced. The proposed algorithm can rapidly converge to adapt to the highly dynamic topology in data relay satellite systems.     

大规模无线通信网络移动边缘计算和缓存研究

面向未来6G移动通信的大规模网络移动边缘计算与缓存技术,首先,介绍了大规模无线网络下移动边缘计算和缓存的架构与原理,并阐释了移动边缘计算和缓存技术在大规模无线网络中的必要性和普适性。接着,从计算卸载、边缘缓存、多维资源分配、用户关联和隐私保护这5个关键问题出发,综述和分析了移动边缘计算和缓存赋能大规模无线网络时会引入的新型关键问题以及对应的解决方案研究,并进一步指出了未来的发展趋势和研究方向。最后,针对隐私保护问题,提出了一种基于联邦学习的隐私保护方案,并通过仿真结果表明所提方案能够同时保护用户数据隐私且改善系统服务质量。     

Location‐based distributed caching for device‐to‐device communications underlaying cellular networks

Device‐to‐device (D2D) communications have been viewed as a promising data offloading solution in cellular networks because of the explosive growth of multimedia applications. Because of the nature of distributed device location, distributed caching becomes an important function of D2D communications. By taking advantage of the caching capacity of the device, in this work, we explore the device storage and file frequent reuse to realize distributed content dissemination, that is, storing contents in mobile devices (named helpers). Specifically, we first investigate the average and lower bound of helper amount by dividing the network into small areas where the nodes are within each other's communication radius. Then, optimal helper amount is derived based on average helper amount and network topology. Subsequently, a location‐based distributed helper selection scheme for distributed caching is proposed based on the given optimal helper amount. In particular, nodes are selected as helpers according to their locations and degrees, and contents are placed in the manner for maximizing total user utility. Extensive simulation results demonstrate the factors that affect the optimal helper amount and the total user utility. Copyright © 2015 John Wiley & Sons, Ltd.     

Adaptive Backbone Based Cooperative Caching in Mobile Ad hoc Networks

Existing cooperative caching algorithms for mobile ad hoc networks face serious challenges due to message overhead and scalability issues. To solve these issues, we propose an adaptive virtual backbone based cooperative caching that uses a connective dominating set (CDS) to find the desired location of cached data. Message overhead in cooperative caching is mainly due to cache lookup process used for cooperative caching. The idea in this scheme is to reduce the number of nodes involved in cache look up process, by constructing a virtual backbone adaptive to the dynamic topology in mobile ad hoc networks. The proposed algorithm is decentralized and the nodes in the CDS perform data dissemination and discovery. Simulation results show that the message overhead created by the proposed cooperative caching technique is very less compared to other approaches. Moreover, due to the CDS based cache discovery we applied in this work, the proposed cooperative caching has the potential to increase the cache hit ratio and reduce average delay.     

Community oriented in‐network caching and edge caching for over‐the‐top services in adaptive network conditions to improve performance

Over‐the‐top (OTT) services such as Netflix, Amazon Prime, and YouTube generate the most dominant form of traffic on the Internet today. There is increasingly high demand for resource intensive 3D contents, interactive media, 360 media, and user‐generated contents. As the amount of contents keep increasing in multiple folds, it is important to cache contents intelligently. Caching algorithm needs to exploit in‐network caching, community‐based pre‐caching, and a combined approach. Hence, we survey CDN‐based edge caching infrastructures including OpenConnect (Netflix) and Google Edge, followed by CCN based in‐network caching. We implement and compare four different approaches for caching contents including (1) in‐network caching, (2) edge caching, (3) community‐based in‐network caching, and (4) community‐based edge caching. We run our algorithms on adaptive network conditions with different topologies, cache size, content popularity, and request arrivals in and compared the delay for all these four approaches. We verify our model by calculating important performance parameters including hop count, redundancy, and hop count variances. Hopcount is an important performance parameter as it influences the processing, queuing, and transmission delays. We focus on determining if an in‐network caching approach is any better than edge caching. We reach several conclusions. First, in most of the scenarios, community‐based in‐network caching performs the best. Second, if the cache size is lesser than 30% of the total content size then community‐based edge caching is better for less popular contents. Finally, our statistical analysis also reveals that a community‐based edge caching mechanism is least affected by varying cache sizes and dynamic user behavior, which makes it a better choice for providing Service Level Agreement.     

Caching algorithms for broadcasting and multicasting in disruption tolerant networks

In delay and disruption tolerant networks, the contacts among nodes are intermittent. Because of the importance of data access, providing efficient data access is the ultimate aim of analyzing and exploiting disruption tolerant networks. Caching is widely proved to be able to improve data access performance. In this paper, we consider caching schemes for broadcasting and multicasting to improve the performance of data access. First, we propose a caching algorithm for broadcasting, which selects the community central nodes as relays from both network structure perspective and social network perspective. Then, we accommodate the caching algorithm for multicasting by considering the data query pattern. Extensive trace‐driven simulations are conducted to investigate the essential difference between the caching algorithms for broadcasting and multicasting and evaluate the performance of these algorithms. Copyright © 2016 John Wiley & Sons, Ltd.     

Performance evaluation of adaptive routing algorithms in packet‐switched intersatellite link networks

This paper addresses the performance evaluation of adaptive routing algorithms in non‐geostationary packet‐switched satellite communication systems. The dynamic topology of satellite networks and variable traffic load in satellite coverage areas, due to the motion of satellites in their orbit planes, pose stringent requirements to routing algorithms. We have limited the scope of our interest to routing in the intersatellite link (ISL) segment. In order to analyse the applicability of different routing algorithms used in terrestrial networks, and to evaluate the performance of new algorithms designed for satellite networks, we have built a simulation model of a satellite communication system with intersatellite links. In the paper, we present simulation results considering a network‐uniform source/destination distribution model and a uniform source–destination traffic flow, thus showing the inherent routing characteristics of a selected Celestri‐like LEO satellite constellation. The updates of the routing tables are centrally calculated according to the Dijkstra shortest path algorithm. Copyright © 2002 John Wiley & Sons, Ltd.     

QoS provisioning in GEO satellite with onboard processing using predictor algorithms

Recently, IP satellite networks have attracted considerable interest as a technology to deliver high-bandwidth IP-based multimedia services to nationwide areas. In particular, IP satellite networks seem to be one of the most promising technologies for connecting users in rural areas, where a wired high-speed network (e.g., xDSL) is not foreseen to be used. However, one of the main problems arising here is to guarantee specific quality of service constraints in order to have good performance for each traffic class. Among various QoS approaches used in the Internet, recently the DiffServ technique has become the most promising solution, mainly for its scalability with respect to the IntServ approach. Moreover, in satellite communication systems, DiffServ computational capabilities are placed at the edge points, reducing the implementation complexity of the satellite onboard equipment. This article deals with the problem of QoS provisioning for packet traffic by considering some resource allocation schemes, including bandwidth allocation techniques and priority-driven onboard switching algorithms. As to the first aim, the proposed technique takes advantage of proper statistical traffic modeling to predict future bandwidth requests. This approach takes into consideration DiffServ-based traffic management to guarantee QoS priority among different users. Moreover, the satellite onboard switching problem has been addressed by considering a suitable implementation of the DiffServ policy based on a cellular neural network.     

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。