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In peer-to-peer(P2P) networks, content delivery is very critical, but there are not many relevant research results in content delivery technology. In this paper, in order to simulate content delivery in P2P mode, the number of online players is abstracted into the number of servers that can provide services, the peers write content to buffer is abstracted into the arrival of customers, and the players read content from buffer is abstracted into the service process of the servers. Based on the consideration of the effect of the number of P2P online players on energy consumption, an M/M/c queueing model with random variation in the number of servers is developed, and negative customers and preemptive priority policies are introduced. The matrix–geometric solution method and Gauss-Seidel iterative method are used to derive the performance measures of the system at steady state for two types of contents. And some numerical examples are given using Matlab for analyzing the trend of performance measures in P2P networks with parameters. The benefit function is established to obtain the parameter values that make the social benefit optimal by Nash equilibrium and social optimal strategy, and provide the theoretical basis for the scheduling of P2P peers. [ABSTRACT FROM AUTHOR]

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Today, the rapid development, large volume, and global access of multimedia applications have demanded the shifting of network functionality from the central server to the near user. In recent times, Edge Computing (EC) and Information Centric Networking (ICN) have been presented as arising advances for content dissemination near the end user. The EC aims to provide content locally by reducing the burden of the core networks, while ICN allows content routing and forwarding based on content names directly. The inherent in-network caching feature of ICN facilitates caching by intermediate network nodes. The combined use of EC and ICN can efficiently handle content dissemination and ultimately improves user experience. In this regards, an ICN based edge caching scheme has been proposed for handling multimedia big data traffic in IoT based smart cities, while incorporating four caching attributes in its proposed design. Firstly, a layered network architecture has been presented that offers Device-to-Device (D2D) communication and ICN support at the application layer of Base station (BS) for utilizing caching of the requested content at edge of the network. Secondly, a decision on caching of contents at network nodes in layered network architecture has been presented based on various centrality measures, which supports efficient caching. Thirdly, this work offers caching of content near the delivery path in ICN network tiers, while leveraging near path caching for fast content dissemination. Lastly, reproactive caching where proactive caching is followed by reactive caching for controlling the network traffic during peak hours has been integrated in to the design model. The performance of the proposed scheme has been evaluated by conducting simulations in Icarus- an ICN caching simulator against various caching benchmark schemes. The results received from the experiments have shown significant performance improvement of our proposed scheme for different performance metrics including cache hit ratio, content retrieval delay, content path stretch, and internal link load. [ABSTRACT FROM AUTHOR]

The vehicular named data networking (VNDN) is gaining more attention as a future vehicular networking (VN) model. The VNDN's fundamental principles of data naming, data-centric forwarding, and in-network caching make it inherently capable of mitigating the challenges in traditional VN. However, broadcast communication for content discovery and delivery causes VNDN to face challenges such as overhead due to packets redundancy, collision, and retransmission. In this paper, we introduce an Interest-Data-flow tracking-based forwarding scheme (IDTracS) for VNDN. IDTracS aims to improve VNDN performance by prioritizing the potential best forwarders and addressing Interest and Data packet broadcast issues. IDTracS is a receiver- and time-contention-based forwarding scheme that controls both Interest and Data packets forwarding. IDTracS uses the node's degree of centrality to the Interest/Data flow and the node's geo-distance closeness from the last Interest/Data forwarder for the requested content name-prefix. Accordingly, it computes an Interest/Data forwarding delay timer for prioritizing Interest/Data among nodes. The simulation findings reveal that the proposed IDTracS achieves an enhanced Interest satisfaction ratio, delivery delay and network transmission overhead compared to related geo-position- and distance-based protocols. [ABSTRACT FROM AUTHOR]

Pre-caching at edge nodes may improve resource efficiency for future content-centric cellular networks by bringing contents closer to users. However, which mode (muticast or unicast) should be selected for the efficient delivery of those cached contents is still not well addressed, especially at the situation that some key parameters such as content popularity and transmission environments are unknown. To solve this problem, the criterion of delivery mode selection is studied based on the learning policy of multi-armed bandit. According to the criterion, a mode selection algorithm is proposed. In this algorithm, edge nodes can choose the better delivery modes in the current slot only dependent on existing observations in the previous slot. Performance evaluation results validate our analyses and proposals on the mode selection. [ABSTRACT FROM AUTHOR]

Information-Centric Networking (ICN) has been recently recognized as a promising future Internet paradigm by providing content-oriented functionality and in-network caching characteristic rather than relying on overlay or end-to-end communication mode. However, the deployment of ICN on the real network is very difficult or even almost impossible at the current stage. In other words, the end-to-end IP network always has the overwhelming development strengths. In spite of this, the end-to-end IP network has no the adequate in-network caching resources to offload the traffic. At the right time, as the essential and significant characteristic of ICN, in-network caching has great potential to be applied into IP network in order to dramatically reduce load pressure of Origin Server (OS). Therefore, we in this paper enable IP network to have the capacity of in-network caching, and on this base, we investigate the comprehensive routing and content delivery. Firstly, the network topology is divided into a number of Autonomous Systems (ASs), and each AS has an Information Management Center (IMC) which has rich functionalities by maintaining Content Index Table (CIT), Physical Topology Index Table (PTIT) and Response Request Table (RRT). Then, CIT is used to conduct both intra-AS routing and explicitly collaborative caching, and PTIT is used to conduct both inter-AS routing and adaptive content delivery including on-path and off-path. In particular, RRT is only sent to OS so that the end-to-end communication connection is switched off. Finally, the experimental results reveal that the proposed scheme can reduce load pressure of OS around 45.7% over Deltacom and 54.8% over GTS. In addition, compared to the previous work, the proposed scheme has better performance. [ABSTRACT FROM AUTHOR]

In recent years, vehicular ad-hoc network (VANET) is getting a growing interest due to its significant function in terms of vehicle information services and vehicular entertainment applications. In particular, VANET enables parking vehicles (PVs) and roadside units (RSUs) to share their contents with mobile vehicles (MVs), which improves the efficiency of content delivery. However, content delivery in VANET still confronts with several challenges. Due to the selfishness of the PVs, an incentive mechanism is needed to motivate them to contribute their cached contents. Moreover, MVs may be threatened by the trustless or even malicious PVs. In this paper, we propose a reputation-based cooperative content delivery mechanism to improve the efficiency and security of content delivery. We formulate the relationships among MVs, RSUs, and PVs as the two-layer auction game. With the auction game, MVs find the optimal PV and RSU for delivering contents and offering the optimized rewards. In addition, we present a dynamic reputation evaluation model. Based on the feature of content delivery, this model incentivizes these honest PVs and isolates malicious PVs, which improves the security of content delivery. Finally, simulation results show that the proposed mechanism can not only improve the effectiveness of content delivery in VANET, but also avoid the attacks of malicious PVs. [ABSTRACT FROM AUTHOR]

Content Centric Networking (CCN) has been introduced in recent years to effectively deliver the named content objects rather than relying on the traditional host-to-host communication model, in which a significant and non-negligible characteristic of CCN is in-network caching. In this paper, we stand on the shoulders of in-network caching to propose the light forwarding based approach in order to optimize CCN content delivery, i.e., the process of data routing irrespective of interest routing. At first, we specially devise an additional packet type which has no data entity at the same time the caching/delivery of data is the granularity of packet. Then, we present a generic content delivery scheme based on packet-level caching and new designed packets; in addition, we make a case study in Metropolitan Area Network (MAN) due to some realistic constraints. Finally, we implement the proposed light forwarding based content delivery scheme and compare it with three existing schemes, and the experimental results reveal that it has more efficient performance optimization, such as network load, delivery delay and energy saving. [ABSTRACT FROM AUTHOR]

Content delivery based on device-to-device (D2D) communications has been widely considered an effective response to the prevalence of content sharing and local services. In order to ensure its advantages, content requesters (CRs) should decide from which content providers (CPs) they obtain the desired content. Moreover, no CP will provide contents for free; thus, an incentive should be given to motivate the CPs. In this work, we solve the content delivery utilizing a monetary incentive. In particular, each CP just transmits a part of the content to CR to reduce the energy consumption. Simultaneously, we introduce the social tie to improve the incentive efficiency, with the popularity of mobile social networks. Specifically, considering the two-layer architecture consisting of the CR and the CPs, a Stackelberg game model is introduced to model the content delivery. The CR works as the leader, and decides the monetary incentive. The CPs work as the followers, and decide the proportion of the provided content. Then, the expression of the Stackelberg equilibrium is given, and a content delivery and pricing algorithm based on the Stackelberg game is designed to converge to the Stackelberg equilibrium through finite-time iterations. Simulation results provide evidences for its efficiency. [ABSTRACT FROM AUTHOR]

Nowadays, most of the traffic in vehicular networks is relevant to content, so the content-to-requester method could be an ideal solution for vehicular content delivery. However, due to the features of vehicular networks such as high mobility, the content-to-requester paradigm might cause the frequent content delivery failures and increase the content delivery cost. Inspired by the idea that the address-based mechanism can support mobility and reduce content delivery costs, we are motivated to take advantage of the address-based mechanism to achieve the content-to-requester paradigm. Based on this motivation, we propose a vehicular content delivery scheme with mobility support (VCDM). In VCDM, the receiver and provider handovers are achieved so that a receiver can correctly receive the requested content from a provider via one successful content delivery process. Moreover, a location-based address is proposed so that a requester can acquire the content from the nearest provider in a unicast way. Finally, VCDM is analyzed and evaluated, and the data show that VCDM effectively improves the content delivery success rate and reduces the content delivery cost and latency. [ABSTRACT FROM AUTHOR]

The expansion of the online video content continues in every area of the modern connected world and the need for measuring and predicting the Quality of Experience (QoE) for online video systems has never been this important. This paper has designed and developed a machine learning based methodology to derive QoE for online video systems. For this purpose, a platform has been developed where video content is unicasted to users so that objective video metrics are collected into a database. At the end of each video session, users are queried with a subjective survey about their experience. Both quantitative statistics and qualitative user survey information are used as training data to a variety of machine learning techniques including Artificial Neural Network (ANN), K-nearest Neighbours Algorithm (KNN) and Support Vector Machine (SVM) with a collection of cross-validation strategies. This methodology can efficiently answer the problem of predicting user experience for any online video service provider, while overcoming the problematic interpretation of subjective consumer experience in terms of quantitative system capacity metrics. [ABSTRACT FROM AUTHOR]

Content-centric networking (CCN) is gradually becoming the alternative approach to the traditional Internet architecture through enlightening information (content) distribution on the Internet with content names. The growing rate of Internet traffic has adapted a content-centric architecture to better serve the user requirement of accessing a content. For enhancing content delivery, ubiquitous in-network caching is utilized to store a content in each and every router by the side of the content delivery path. From the study, it is evaluated that a better performance can be achieved when caching is done by a subset of CRs instead of all CRs in a content delivery path. Motivated by this, we proposed an adaptive neuro-fuzzy inference system-based caching (ANFIS-BC) scheme for CCN to improve the cache performance. The proposed ANFIS-BC scheme utilizes the feature of centrality-measures for selection of a router for caching in a network. Our results demonstrated that the ANFIS-BC scheme consistently achieves better caching gain across the multiple network topologies. [ABSTRACT FROM AUTHOR]

Content-centric networking (CCN) is gradually becoming an alternative approach to the conventional Internet architecture through the distribution of enlightening information (named as content) on the Internet. It is evaluated that the better performance can be achieved by caching is done on a subset of content routers instead of all the routers in the content delivery path. The subset of a content router must be selected in a manner such that maximum cache performance can be achieved. Motivated by this, we propose a Centrality-measures based algorithm (CMBA) for selection of an appropriate content router for caching of the contents. The Centrality-measures are based on the question: ”Who are the most important or central content router in the network for the caching of contents?”. We found that our novel CMBA could improve content cache performance along the content delivery path by using only a subset of available content routers. Our results recommend that our proposed work consistently achieves better caching gain across the multiple network topologies. [ABSTRACT FROM AUTHOR]

We evaluate the throughput performance of a mobile network cell where device to device (D2D) communication, using part of the resource blocks of the considered cell, is used to offload the base station (BS) of part of its content delivery traffic. We suppose download requests occur according to a Poisson process from uniformly distributed user locations and are preferentially satisfied by one or more helpers whose number and positions are described by a Poisson process in the plane. We characterize optimal content placement for both regular caching, where sets of entire objects are cached by the helper devices, and coded caching, where each helper caches random coded chunks of certain objects such that a download may successively require several helpers and the BS. A multi-class processor sharing model is developed to determine the optimal resource partition between D2D and BS subsystems and evaluate the resulting throughput performance. Numerical results demonstrate significant capacity gains, notably for coded caching, that may well justify the added complexity of D2D communication. [ABSTRACT FROM AUTHOR]

The usage of the Internet has grown substantially in recent times. This has resulted in high volumes of data traffic. There is a concomitant rise in bandwidth demands that could result in excessive download delays (or latency). Thus, a single-server system is no more a prudent choice for data storage. Replication of content and placing them on multiple servers is a method that is used to reduce latency. However, this solution comes at a huge cost. Moreover, replicating objects randomly does not necessarily improve system performance. It is possible to arrive at a solution to the problem of placing content so as to achieve better cost performance. Other performance measures include latency, load balancing and data availability. We refer to the problem of locating content as data location problem in information networks, or DLPIN. The choice of server locations, query routing strategy and user assignment are some of the important problems that require attention along with the location of the data/content. Resource constraints and the nature of traffic (static/dynamic) are two important parameters in the problem environment, and therefore are key distinguishing features in the models. The main contribution of this paper is a novel classification and study of DLPIN on the basis of problem features. The research in this area started with files, the smallest units of allocation. Gradually, files and programs, database segments and entire databases (or mirrors) have been studied. We design examples from these use cases to elaborate a variety of problems in a comprehensive review. Facility location models from physical logistics are extensively used to model these problems. Our paper presents a literature survey of such mathematical models for data location problems. We present a gap analysis that provides pointers to possible future research in this area. This paper also serves to document the success in the use of mathematical programming approaches for data location in information networks. [ABSTRACT FROM AUTHOR]

A burst of requests may starve the upload capacity of server and degrade the Quality of Service (QoS) when a popular or time-critical content is released in content delivery system. With an enormous volume of popular content available in the network, as well as the growing size of online users, the previous improvement of download protocol is far from enough to handle the flash crowd in large-scale system. In this paper, a novel flash crowd mitigation algorithm called Peer Assisted Pre-allocation (PAPA) is proposed from a new perspective, in which 'proactive' strategies are provided to handle sudden workload of the system. Through numerical simulation and practical experiment in download platform of Tencent, it is proved that benefited from the collaboration of servers and helpers, PAPA is able to save the peak server bandwidth by over 30 % and thus greatly reduce the operating costs of system. [ABSTRACT FROM AUTHOR]

The increasing amount of over-the-top (OTT) live streams and the lack of global network layer multicast support poses challenges for a scalable and efficient streaming over the Internet. Content Delivery Networks (CDNs) help by delivering the streams to the edge of almost every Internet Service Provider (ISP) network of the world but usually also end there. From there on, the streams are to be delivered to the clients using IP unicast, although an IP multicast functionality would be desirable to reduce the load on CDN nodes, transit links, and the ISP infrastructure. IP multicast is usually not available due to missing control and management features of the protocol. Alternatively, Peer-to-Peer (P2P) mechanisms can be applied to extend the overlay multicast functionality of the CDN towards the clients. Unfortunately, P2P only improves the situation for the CDN but makes it more challenging for the ISP as even more unicast flows are generated between clients inside and outside the ISP network. To tackle this problem, a Software-Defined Networking-based cross-layer approach, called Software-Defined Multicast (SDM), is proposed in this paper, enabling ISPs to offer network layer multicast support for OTT and overlay-based live streaming as a service. SDM is specifically tailored towards the needs of P2P-based video stream delivery originating from outside the ISP network and can easily be integrated with existing streaming systems. Prototypical evaluations show significantly improved network layer transmission efficiencies when compared to other overlay streaming mechanisms, down to a level as low as for IP multicast, at linearly bounded costs. [ABSTRACT FROM AUTHOR]

Content delivery is one of the most important technologies used in Mobile Social Networks (MSNs). Smart devices could enable mobile users to create and use a rich set of services through available resources in the surrounding environment opportunistically. This paper presents the framework of distributed buffer storage aided hybrid Mobile Social Networks (MSN). Based on this, we propose a new scheme with distributed storage for efficient end-to-end content delivery in intermittently connected MSNs. Our proposed hybrid architecture is able to offer fast and reliable delivery services by distributing buffer storage located close to mobile users of the opportunistic MSN. Simulation experiments are conducted to evaluate the performance of the proposed method, which indicate that it is helpful to improve network performance in terms of content delivery ratio, throughput and end-to-end delays. [ABSTRACT FROM AUTHOR]

To model a layered video streaming system in super-peer overlay networks that faces with heterogeneity and volatility of peers, we formulate a layer scheduling problem from understanding some constraints such as layer dependency, transmission rule, and bandwidth heterogeneity. To solve this problem, we propose a new layer scheduling algorithm using a real-coded messy genetic algorithm, providing a feasible solution with low complexity in decision. We also propose a peer-utility-based promotion algorithm that selects the most qualified neighbor to guarantee the sustained quality of streaming despite high intensity of churn. Simulation results show that the proposed layer scheduling scheme can achieve the most near-optimal solutions compared to the four conventional scheduling heuristics in the average streaming ratio. It also highly outperforms those with different peer selection strategies in terms of the average bandwidth (6.9 % higher at least) and the variation of utilization (11.3 % lower at least). [ABSTRACT FROM AUTHOR]

Delivering content efficiently through biased neighbor selection has attracted a lot of researchers' attention in recent years. Meanwhile, how to help peers understand each other is a crucial precondition of biased neighbor selection in distributed P2P context. Recent researches have showed that reciprocation based schemes provide a feasible way of categorizing peers. These schemes can perform in direct or indirect ways. For example, tit-for-tat is a typical example of direct ways, while reputation-based schemes are the representative examples of indirect ways. Although tit-for-tat has been proved to be successful from practical deployment and academic studies, it still suffers from free-riding, malicious peers and other problems. On the other hand, reputation-based schemes pay little attention to malicious peers. However, in this paper we propose an approach to promote the whole system performance as well as cope with malicious peers. Firstly, by building a simple mathematical model for the content delivery process in BT-like system, we find that the delivery order is critical to system performance, after that we present the best selection policy from system and single peer's perspective respectively. Secondly, according to analysis results, we bring forward indirect reciprocate Reputation (iRep), detail the design issues and sketch security and overhead introduced by iRep. Finally, several simulation experiments are conducted to evaluate the performance of iRep through comparison with tit-for-tat and Eigentrust. The comparison results validate that iRep can efficiently promote system performance with limited overheads. [ABSTRACT FROM AUTHOR]

In this paper, we propose an architecture for multimedia content delivery considering Quality of Service (QoS), based on both the policy-based network and the best-effort network. The architecture consists of four fundamental elements: multimedia content model, application level QoS policy, QoS adaptation mechanism, and delivery mechanism. Applications based on current architecture loses their meaning by drastically degrading quality when network congestion occurs. Despite of this all-or-nothing architecture, applications based on our adaptive architecture can reduce its quality and then negotiate with the network entity, keeping its quality measure as much as possible even when network congestion occurs. We may consider a quality measure for Web pages, total page transmission time, and transmission order of inline objects as a segregation. We then define a language to specify application level QoS policies for Web pages and implement a delivery mechanism and a QoS adaptation mechanism to fulfill these policies. [ABSTRACT FROM AUTHOR]