Incentive edge caching in software‐defined internet of vehicles: A Stackelberg game approach

In this paper, we investigate an incentive edge caching mechanism for an internet of vehicles (IoV) system based on the paradigm of software‐defined networking (SDN). We start by proposing a distributed SDN‐based IoV architecture. Then, based on this architecture, we focus on the economic side of caching by considering competitive cache‐enablers market composed of one content provider (CP) and multiple mobile network operators (MNOs). Each MNO manages a set of cache‐enabled small base stations (SBS). The CP incites the MNOs to store its popular contents in cache‐enabled SBSs with highest access probability to enhance the satisfaction of its users. By leasing their cache‐enabled SBSs, the MNOs aim to make more monetary profit. We formulate the interaction between the CP and the MNOs, using a Stackelberg game, where the CP acts first as the leader by announcing the popular content quantity that it which to cache and fixing the caching popularity threshold, a minimum access probability under it a content cannot be cached. Then, MNOs act subsequently as followers responding by the content quantity they accept to cache and the corresponding caching price. A noncooperative subgame is formulated to model the competition between the followers on the CP's limited content quantity. We analyze the leader and the follower's optimization problems, and we prove the Stackelberg equilibrium (SE). Simulation results show that our game‐based incentive caching model achieves optimal utilities and outperforms other incentive caching mechanisms with monopoly cache‐enablers whilst enhancing 30% of the user's satisfaction and reducing the caching cost.     

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.     

Cooperative caching for content dissemination in vehicular networks

The explosive growth of mobile data traffic has made cellular operators to seek low‐cost alternatives for cellular traffic off‐loading. In this paper, we consider a content delivery network where a vehicular communication network composed of roadside units (RSUs) is integrated into a cellular network to serve as an off‐loading platform. Each RSU subjecting to its storage capacity caches a subset of the contents of the central content server. Allocating the suitable subset of contents in each RSU cache such that maximizes the hit ratio of vehicles requests is a problem of paramount value that is targeted in this study. First, we propose a centralized solution in which, we model the cache content placement problem as a submodular maximization problem and show that it is NP‐hard. Second, we propose a distributed cooperative caching scheme, in which RSUs in an area periodically share information about their contents locally and thus update their cache. To this end, we model the distributed caching problem as a strategic resource allocation game that achieves at least 50% of the optimal solution. Finally, we evaluate our scheme using simulation for urban mobility simulator under realistic conditions. On average, the results show an improvement of 8% in the hit ratio of the proposed method compared with other well‐known cache content placement approaches.     

Cooperative caching game based on social trust for D2D communication networks

Content sharing via device‐to‐device (D2D) communications has become a promising method to increase system throughput and reduce traffic load. Due to the characteristic of spectrum sharing in D2D network, confidentiality is becoming a key issue in content transmission. Secure communication in D2D networks is generally guaranteed by a physical‐layer security mechanism. However, this method sacrifices the system transmission rate while ensuring security. Since mobile devices are carried by humans, we can leverage their trust relations to enhance the security of communications. As much, considering the psychology structure and social attributes of mobile users, we build a multidimensional trust evaluation mechanism to evaluate the trust relationship between users, and we pick out the trusted users based on the decision‐theoretic rough sets. By sharing content only between trust users, we can enhance the security of content transmissions without relying on physical‐layer security measures. Meanwhile, content caching is now widely used to improve accessing efficiency and reduce traffic load on cellular networks. However, caching content for other users incurs additional cost, which results in selfish and noncooperative behavior in users. Considering such selfishness, we introduce a cooperative caching game based on multidimensional trust relations to motivate users to cache contents for other devices. In this game, the trust relations and physical distance between two users are considered to formulate the cost function. Furthermore, we introduce an incentive caching algorithm based on social trust to minimize the total cost in the D2D network.     

Proactive caching with content‐based pricing for cooperative femtocells in two‐tier heterogeneous networks

With increase in the number of smart wireless devices, the demand for higher data rates also grows which puts immense pressure to the network. A vast majority of this demand comes from video files, and it is observed that only a few popular video files are requested more frequently during any specified time interval. Recent studies have shown that caching provides a better performance as it minimizes the network load by avoiding the fetching of same files multiple times from the server. In this paper, we propose to combine two ideas; proactive caching of files and content‐based pricing in macro‐femto heterogeneous networks. The femtocell access point (FAP) is allowed to manipulate its users' demand through content‐based pricing and serve the users' requests by proactively downloading suitable content into its cache memory which reduces the load of the femtocell. In addition, an incentive mechanism is also proposed which encourages the FAP to help macrocell users under its coverage zone by allowing access to its cached content and thereby reduces the macrocell load. The proposed content‐based pricing and proactive caching scheme for femtocells is modeled as a Stackelberg game among the macrocell base station and the FAP to jointly maximize both of their utilities. Performance analysis of the scheme is presented for a single femtocell scenario and compared with the conventional flat pricing‐based scheme via numerical examples. The results demonstrate significant reduction in network load using our proposed scheme.     

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.     

Satisfactory content delivery scheme for QoS provisioning in delay tolerant networks

We deal in this article with the content forwarding problem in delay tolerant networks (DTNs). We first formulate the content delivery interaction as a noncooperative satisfaction game. On one hand, the source node seeks to ensure a delivery probability above some given threshold. On the other hand, the relay nodes seek to maximize their own payoffs. The source node offers a reward (virtual coins) to the relay, which caches and forwards the file to the final destination. Each relay has to solve the dilemma of accepting/rejecting to cache the source's file. Cooperation incurs energy cost due to caching, carrying, and forwarding the source's file. Yet when a relay accepts to cooperate, it may receive some reward if it succeeds to be the first relay to forward the content to the destination. Otherwise, the relay may receive some penalty in the form of a constant regret; the latter parameter is introduced to make incentive for cooperation. Next, we introduce the concept of satisfaction equilibrium (SE) as a solution concept to the induced game. Now, the source node is solely interested in reaching a file delivery probability greater than some given threshold, while the relays behave rationally to maximize their respective payoffs. Full characterizations of the SEs for both pure and mixed strategies are derived. Furthermore, we propose two learning algorithms allowing the players (source/relays) to reach the SE strategies. Finally, extensive numerical investigations and some learning simulations are carried out to illustrate the behavior of the interacting nodes and to give some insightful thoughts on how to fine‐tune the network setting.     

D2D协作边缘缓存系统中基于传输时延的缓存策略

为了满足5G系统低时延高可靠的需求,针对单缓存终端直传(D2D)协作边缘缓存系统,提出了一种基于传输时延的缓存策略。运用随机几何理论,将请求用户和空闲用户的动态分布建模为相互独立的齐次泊松点过程,综合考虑内容流行度、用户位置信息、设备传输功率以及干扰,推导出用户的平均传输时延与缓存概率分布的关系式。以平均传输时延为目标函数建立优化问题,提出了一个低复杂度的迭代算法,得到平均传输时延次优的缓存策略。仿真结果表明,该缓存策略在传输时延方面优于常见的几种缓存策略。     

基于带缓存的云接入网络最优能效设计

在云接入网络(Cloud-RAN)中,现有工作大多假定射频拉远头(RRH)不具备缓存功能。然而下一代通信网络具有以内容为中心的特性,因此在Cloud-RAN中考虑带缓存的RRHs也变得有必要。该文考虑在Cloud-RAN中有效设计缓存方案,并通过资源分配有效减轻前程链路负担。假设系统采用正交频分多址接入(OFDMA)技术,通过联合优化子载波(SC)分配,RRH选择与传输功率,最小化系统下行总功耗,并通过拉格朗日对偶分解转化非凸问题,获得最优分配方案。仿真结果表明,比起其它缓存方案,该文提出的优化算法可以有效地提升系统能效,满足未来通信需求。     

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.     

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.     

Multi-tier cooperative caching in fog radio access network

Aiming at the problem of reducing the load of the backward link in the edge buffer and fog wireless access network technology,a multi-tier cooperative caching scheme in F-RAN was proposed to further reduce the backhaul traffic load.In particular,by considering the network topology,content popularity prediction and link capacity,the optimization problem was decomposed into knapsack subproblems in multi-tiers,and effective greedy algorithms were proposed to solve the corresponding subproblems.Simulation results show that the proposed multi-tier cooperative caching scheme can effectively reduce the backhaul traffic and achieve relatively high cache hit rate.     

Edge-first-based cooperative caching strategy in information centric networking

In order to optimize the replica placement in information centric networking,an edge-first-based cooperative caching strategy (ECCS) was proposed.According to the strategy,cache decision was made during the interest forwarding stage.The decision result and statistic information would been forwarded to upstream routers step by step.Utilizing the information,upstream nodes could update their cache information table immediately to achieve cooperative caching.The experimental results indicate ECCS can achieve salient performance gain in terms of server load reduction ratio,average hop reduction ratio,average cache hit ratio,compared with current strategies.     

网络缓存协作的实现方法

介绍了网络缓存发展的趋势:网络缓存协作。说明了网络缓存协作所要解决的问题,列举了网络 缓存协作的几种模型及相应的有代表性的协议,介绍了解决代理裁剪的几种方案。     

P2P缓存系统中总开销最小的协作缓存策略

为降低P2P缓存系统中的全局开销,提出一种基于总开销最小的协作缓存策略。该策略综合考虑P2P缓存系统中的传输开销和存储开销,使用跨ISP域间链路开销、流行度、文件大小、存储开销来衡量文件的缓存增益。需要替换时,首先替换掉缓存增益最小的内容。实验结果表明,所提策略能够有效降低系统的总开销。     

Blockchain-based collaborative edge caching scheme fortrustworthy content sharing

Moving data from cloud to the edge network can effectively reduce traffic burden on the core network, and edge collaboration can further improve the edge caching capacity and the quality of service ( QoS). However, it is difficult for various edge caching devices to cooperate due to the lack of trust and the existence of malicious nodes. In this paper,blockchain which has the distributed and immutable characteristics is utilized to build a trustworthy collaborative edge caching scheme to make full use of the storage resources of various edge devices. The collaboration process is described in this paper, and a proof of credit (PoC) protocol is proposed, in which credit and tokens are used to encourage nodes to cache and transmit more content in honest behavior. Untrusted nodes will pay for their malicious actions such as tampering or deleting cached data. Since each node chooses strategy independently to maximize its benefits in an environment of mutual influence, a non-cooperative game model is designed to study the caching behavior among edge nodes. The existence of Nash equilibrium (NE) is proved in this game, so the edge server (ES) can choose the optimal caching strategy for all collaborative devices, including itself, to obtain the maximum rewards. Simulation results show that the system can save mining overhead as well as organize a trusted collaborative edge caching effectively.     

面向软件定义无线接入网的高效协作内容缓存算法

为了缓解海量的移动业务数据与容量受限的无线接入网回传链路之间的矛盾,本文提出一种面向软件定义无线接入网（SD-RAN）的协作内容缓存网络架构.在宏蜂窝基站（MBS）的控制管理下,小蜂窝基站（SBS）可以在存储单元有序存储一些高流行度的内容.针对SBS存储单元空间受限问题,进一步提出SD-RAN网络架构下的协作内容缓存算法.该算法中,每个SBS缓存空间被分割成两部分：（1）用于存储全网流行度最高的公共内容以保证各小蜂窝小区本地命中率.（2）用于存储流行度较高的差异化的内容以促进MBS内SBS之间的协作.在此基础上,解析推导具有最优平均内容获取开销的分割参数闭合表达式.仿真结果表明该算法在不同系统参数条件下能显著降低SD-RAN的平均内容获取开销.     

雾网络中基于统计分布的内容缓存与交付方案

作为5G中的一种重要模型，雾无线接入网络(Fog Radio Access Network, F-RAN)通过设备到设备通信和无线中继等技术获得了显著的性能增益，而边缘设备中合适的缓存则可以让内容缓存用户(Caching Users, CUs)向内容请求用户(Requesting Users, RUs)直接发送缓存内容，有效减小前传链路的负担和下载延迟。考虑一个F-RAN模型下用户发出请求并获得交付的场景，将每个CU的内容请求队列建模为独立的M/D/1模型，分析导出CUs缓存命中率和平均下载延迟关于内容缓存与交付方案的表达式，证明CUs缓存命中率与内容统计分布之间的联系有助于实现前者的近似最优解。针对在一段时间内的期望视角下建立的优化问题，提出了基于统计分布的算法并注意了执行时的交付控制。仿真结果表明，相较于现有缓存策略，优化内容整体统计分布的方案能够最大化CUs缓存命中率，同时减小平均下载延迟。     

Energy‐delay‐aware caching strategy in green CCN using markov approximation

One of the basic challenges in content‐centric networking (CCN) is how to optimize the overall energy consumption of content transmission and caching. Furthermore, designing an appropriate caching policy that considers both energy consumption and quality of service (QoS) is a major goal in green CCN. In this paper, the problem of minimizing the total CCN energy consumption while being aware of the end‐to‐end delay is formulated as an integer linear programming model. Since it is an Non‐deterministic Polynomial‐time (NP)‐hard problem, the Markov approximation method for an energy‐delay aware caching strategy (MAEDC) is proposed through a log‐sum‐exp function to find a near‐optimal solution in a distributed manner. The numerical results show that the MAEDC achieves near‐optimal energy consumption with better delay profile compared with the optimal solution. Moreover, due to the possibility of distributed and parallel processing, the proposed method is proper for the online situation where the delay is a crucial issue.     

Cache consistency in Wireless Multimedia Sensor Networks

The production of cheap CMOS cameras, which are able to capture rich multimedia content, combined with the creation of low-power circuits, gave birth to what is called Wireless Multimedia Sensor Networks (WMSNs). WMSNs introduce several new research challenges, mainly related to mechanisms to deliver application-level Quality-of-Service (e.g., latency minimization). Such issues have almost completely been ignored in traditional WSNs, where the research focused on energy consumption minimization. Towards achieving this goal, the technique of cooperative caching multimedia content in sensor nodes can efficiently address the resource constraints, the variable channel capacity and the in-network processing challenges associated with WMSNs. The technological advances in gigabyte-storage flash memories make sensor caching to be the ideal solution for latency minimization. Though, with caching comes the issue of maintaining the freshness of cached contents. This article proposes a new cache consistency and replacement policy, called NICC, to address the cache consistency issues in a WMSN. The proposed policies recognize and exploit the mediator nodes that relay on the most “central” points in the sensor network so that they can forward messages with small latency. With the utilization of mediator nodes that lie between the source node and cache nodes, both push-based and pull-based strategies can be applied in order to minimize the query latency and the communication overhead. Simulation results attest that NICC outperforms the state-of-the-art cache consistency policy for MANETs.