Traditional Content Delivery Network Research Articles

Beaconnect

Content delivery networks (CDNs) are critical for minimizing access latency in the Web as they efficiently distribute online resources across the globe. But since CDNs can only be enabled on the scope of entire websites (and not for individual users or user groups), the effects of page speed acceleration are often quantified with potentially skewed before-after comparisons rather than statistically sound A/B tests. We introduce the system Beaconnect for collecting and analyzing Web performance data without being subject to these limitations. Our contributions are threefold. First, Beaconnect is natively compatible with A/B testing Web performance as it is built for a custom browser-based acceleration approach and thus does not rely on traditional CDN technology. Second, we present our continuous aggregation pipeline that achieves sub-minute end-to-end latency. Third, we describe and evaluate a scheme for continuous real-time reporting that is especially efficient for large customers and processes data from over 100 million monthly users at Baqend.

Fog-Based CDN Framework for Minimizing Latency of Web Services Using Fog-Based HTTP Browser

Cloud computing has been a dominant computing paradigm for many years. It provides applications with computing, storage, and networking capabilities. Furthermore, it enhances the scalability and quality of service (QoS) of applications and offers the better utilization of resources. Recently, these advantages of cloud computing have deteriorated in quality. Cloud services have been affected in terms of latency and QoS due to the high streams of data produced by many Internet of Things (IoT) devices, smart machines, and other computing devices joining the network, which in turn affects network capabilities. Content delivery networks (CDNs) previously provided a partial solution for content retrieval, availability, and resource download time. CDNs rely on the geographic distribution of cloud servers to provide better content reachability. CDNs are perceived as a network layer near cloud data centers. Recently, CDNs began to perceive the same degradations of QoS due to the same factors. Fog computing fills the gap between cloud services and consumers by bringing cloud capabilities close to end devices. Fog computing is perceived as another network layer near end devices. The adoption of the CDN model in fog computing is a promising approach to providing better QoS and latency for cloud services. Therefore, a fog-based CDN framework capable of reducing the load time of web services was proposed in this paper. To evaluate our proposed framework and provide a complete set of tools for its use, a fog-based browser was developed. We showed that our proposed fog-based CDN framework improved the load time of web pages compared to the results attained through the use of the traditional CDN. Different experiments were conducted with a simple network topology against six websites with different content sizes along with a different number of fog nodes at different network distances. The results of these experiments show that with a fog-based CDN framework offloading autonomy, latency can be reduced by 85% and enhance the user experience of websites.

An Improved Content Delivery Technology Based on Genetic Algorithm in Cloud Storage

Compared with the traditional content delivery network (CDN), content delivery based on cloud storage has the advantage of reducing storage costs while providing superior data security over common storage solutions. There has been a lot of research on content delivery technology, but existing research on content delivery technology is rarely used in cloud storage based CDN. In this paper, we analyze the charging and content delivery mechanism of cloud storage, then propose a reasonable network topology and cost model. Based on the analysis of existing heuristic algorithms such as user greedy and server greedy, an improved content delivery technology based on genetic algorithm in cloud storage is proposed, which effectively reduces the content delivery cost.

MABRESE: A New Server Selection Method for Smart SDN-Based CDN Architecture

A content delivery network (CDN) is able to handle high traffic and offer reliable services by geographically bringing the content data to the edge network, where replica servers are installed closer to the end users. The traditional CDN architecture lacks a global view of the whole network and, thus, cannot dynamically and optimally perform the server selection task. In this letter, we propose to integrate a software-defined network (SDN) into the CDN architecture. Our intuitive motivation is to decouple the control plane from the forwarding plane in order to offer flexibility and programmability by using the centralized controller. This letter also develops a novel server selection algorithm that is based on the so-called multi-armed bandit problem. Such an algorithm is proved to optimize the server selection function and provide a good experimental result in terms of both average response time and reward score.

Tapping the Knowledge of Dynamic Traffic Demands for Optimal CDN Design

The content delivery network (CDN) intensively uses cache to push the content close to end users. Over both traditional Internet architecture and emerging cloud-based framework, cache allocation has been the core problem that any CDN operator needs to address. As the first step for cache deployment, CDN operators need to discover or estimate the distribution of user requests in different geographic areas. This step results in a statistical spatial model for the user requests, which is used as the key input to solve the optimal cache deployment problem. More often than not, the temporal information in user requests is omitted to simplify the CDN design. In this paper, we disclose that the spatial request model alone may not lead to truly optimal cache deployment and revisit the problem by taking the dynamic traffic demands into consideration. Specifically, we model the time-varying traffic demands and formulate the distributed cache deployment optimization problem with an integer linear program (ILP). To solve the problem efficiently, we transform the ILP problem into a scalable form and propose a greedy diagram to tackle it. Via experiments over the North American ISPs points of presence (PoPs) network, our new solution outperforms traditional CDN design method and saves the overall delivery cost by 16% to 20%. We also study the impact of various traffic demand patterns to the CDN design cost, via experiments with both real-world traffic demand patterns and extensive synthetic trace data.

Performance Analysis of Thunder Crystal: A Crowdsourcing-Based Video Distribution Platform

Delivering high-definition (HD) videos to a large number of Internet users is a challenging research problem due to its heavy bandwidth consumption and inelastic quality-of-service (QoS) requirement. Different from the traditional content delivery networks and overlay peer-to-peer networks, crowdsourcing-based platforms, e.g., Thunder Crystal, deliver HD videos by renting agents’ bandwidth and storage resources. Cash will be rewarded to agents based on agents’ upload traffic. Online video providers, i.e., Tencent Video and YouKu, pay Thunder Crystal for its video distribution service. Therefore, a critical problem for Thunder Crystal is to evaluate the performance it can achieve, which determines Thunder Crystal’s competitiveness and its bargaining power with online video providers. Although previously studied proportional video replication and random request scheduling strategy are implemented by Thunder Crystal, the system performance cannot be evaluated by simply using existing models, because of its novel business model. To address this problem, this paper proposes a theoretical framework that can analyze the performance for synchronized streaming, video-on-demand (VoD) streaming, and video downloading, which are all supported by Thunder Crystal. A differentiated bandwidth allocation is designed to boost Thunder Crystal’s streaming performance by assigning downloading users more fluctuating bandwidth, which only slightly degrades downloading performance. Finally, simulation is conducted to validate the accuracy of our theoretical results.

A new surrogate placement algorithm for cloud-based content delivery networks

Cloud-based content delivery networks (CCDNs) have been developed as the next generation of content delivery networks (CDNs). In CCDNs, the cloud contributes to the cost-effective, pay-as-you-go model, and virtualization and the traditional CDNs contribute to content replications. Delivering infrastructure as a service in a networked cloud computing environment requires mapping virtual resources to physical resources, as well as traditional surrogate placement. In this paper, we develop a novel algorithm for virtual surrogate placement that combines multiple knapsack and competitive facility location problems. Moreover, we provide new formulations and theories for this problem. Finally, we compare our algorithm with the previous heuristics. Simulation results show that the proposed algorithm achieves significantly better results in terms of a decreased number of surrogate servers, decreased total path length between end users and surrogate servers, decreased average workload variance and CCDN deployment cost.

FLAPS: bandwidth and delay-efficient distributed data searching in Fog-supported P2P content delivery networks

Due to the growing interest for multimedia contents by mobile users, designing bandwidth and delay-efficient distributed algorithms for data searching over wireless (possibly, mobile) “ad hoc” Peer-to-Peer (P2P) content Delivery Networks (CDNs) is a topic of current interest. This is mainly due to the limited computing-plus-communication resources featuring state-of-the-art wireless P2P CDNs. In principle, an effective means to cope with this limitation is to empower traditional P2P CDNs by distributed Fog nodes. Motivated by this consideration, the goal of this paper is twofold. First, we propose and describe the main building blocks of a hybrid (e.g., mixed infrastructure and “ad hoc”) Fog-supported P2P architecture for wireless content delivery, namely, the Fog-Caching P2P architecture. It exploits the topological (possibly, time varying) information locally available at the serving Fog nodes, in order to speed up the data searching operations performed by the served peers. Second, we propose a bandwidth and delay-efficient, distributed and adaptive probabilistic search algorithm, that relies on the learning automata paradigm, e.g., the Fog-supported Learning Automata Adaptive Probabilistic Search (FLAPS) algorithm. The main feature of the FLAPS algorithm is the exploitation of the local topology information provided by the serving Fog nodes and the current status of the collaborating peers, in order to run a suitably distributed reinforcement algorithm for the adaptive discovery of peer-to-peer and peer-to-fog minimum-hop routes. The performance of the proposed FLAPS algorithm is numerically evaluated in terms of Success Rate, Hit-per-Query, Message-per-Query, Response Delay and Message Duplication Factor over a number of randomly generated benchmark CDN topologies. Furthermore, in order to corroborate the actual effectiveness of the FLAPS algorithm, extensive performance comparisons are carried out with some state-of-the-art searching algorithms, namely the Adaptive Probabilistic Search, Improved Adaptive Probabilistic Search and the Random Walk algorithms.

A Survey on Replica Server Placement Algorithms for Content Delivery Networks

Content delivery networks (CDNs) have gained immense popularity over the years. Replica server placement is a key design issue in CDNs. It entails placing replica servers at meticulous locations, such that cost is minimized and quality of service of end-users is satisfied. Many replica server placement models have been proposed in the literature of traditional CDN. As the CDN architecture is evolving through the adoption of emerging paradigms, such as, cloud computing and network functions virtualization, new algorithms are being proposed. In this paper, we present a comprehensive survey of replica server placement algorithms in traditional and emerging paradigm-based CDNs. We categorize the algorithms and provide a summary of their characteristics. Besides, we identify requirements for an efficient replica server placement algorithm and perform a comparison in the light of the requirements. Finally, we discuss potential avenues for further research in replica server placement in CDNs.

Reducing Latency Through Page-aware Management of Web Objects by Content Delivery Networks

As popular web sites turn to content delivery networks (CDNs) for full-site delivery, there is an opportunity to improve the end-user experience by optimizing the delivery of entire web pages, rather than just individual objects. In particular, this paper explores page-structure-aware strategies for placing objects in CDN cache hierarchies. The key idea is that the objects in a web page that have the largest impact on page latency should be served out of the closest or fastest caches in the hierarchy. We present schemes for identifying these objects and develop mechanisms to ensure that they are served with higher priority by the CDN, while balancing traditional CDN concerns such as optimizing the delivery of popular objects and minimizing bandwidth costs. To establish a baseline for evaluating improvements in page latencies, we collect and analyze publicly visible HTTP headers that reveal the distribution of objects among the various levels of a major CDN's cache hierarchy. Through extensive experiments on 83 real-world web pages, we show that latency reductions of over 100 ms can be obtained for 30% of the popular pages, with even larger reductions for the less popular pages. Using anonymized server logs provided by the CDN, we show the feasibility of reducing capacity and staleness misses of critical objects by 60% with minimal increase in overall miss rates, and bandwidth overheads of under 0.02%.

Envy-Free Resource Allocation and Request Routing in Hybrid CDN–P2P Networks

Hybrid CDN---P2P networks (HCDNs) combine Peer to Peer (P2P) networks and Content Delivery Networks (CDN) to benefit from their complementary advantages. In order to enable a traditional CDN to offer hybrid content delivery service, we introduce a resource scheduling mechanism to perform the request routing process and determine the desired level of contribution for users. The proposed mechanism relies on a truthful, profit maximizing, envy-free auction to optimize contributions of the end-users in P2P content delivery. Based on the proposed solution, economics of content delivery in the HCDN are studied and it is shown that through our resource scheduling mechanism, it is possible to serve a big fraction of end-users with higher quality content, increase the net profit of the HCDN provider, and decrease expenditures of the content provider simultaneously.

Enhancing Availability in Content Delivery Networks for Mobile Platforms

Ensuring high data availability is a vital prerogative for Content Delivery Networks (CDN), and as we look to deploy CDN mechanisms onto mobile platforms, this imperative becomes ever more challenging. In traditional CDNs, replication ensures high availability of data, with server-loads and content-popularity often used as parameters to tightly control the process. However, the highly transient properties of such wireless and mobile devices constitute a major hurdle for any replication algorithm, rendering most simplified methods inadequate. Our contribution begins with a unique message-pulsing mechanism operating within a wireless cluster, that detects devices and ascertains their reliability. Results show the viability of our pulsing algorithm in determining a base replication level. Next, a Markovian queueing model is introduced, allowing us to induce replication based on the required speed of service. This affords finer control over the replication process, creating a more effective replication strategy suited for mobile-based CDNs. Extensive analysis of the model were performed, with parameters derived from real-world conditions. Results indicate that the model is able to compute logical values for the expected waiting times in service and thus, control the speed of replication within the CDN.

An economic mechanism for request routing and resource allocation in hybrid CDN–P2P networks

SummaryHybrid content delivery networks (HCDN) benefit from the complementary advantages of P2P (Peer to Peer) networks and CDNs (Content Delivery Network). In order to extend a traditional CDN and enable it to offer hybrid content delivery service, we have modified a traditional domain name system‐based request routing mechanism. The proposed scheme relies on an oligopolistic mechanism to balance the load on the edge servers and employs a truthful profit‐maximizing auction to maximize the contribution of users in the P2P content delivery. In particular, economics of content delivery in HCDNs is studied, and it is shown that through our request routing mechanism, it is possible to deliver higher quality of service to majority of end‐users, increase the net profit of the HCDN provider and decrease the content distribution cost at the same time. Copyright © 2015 John Wiley & Sons, Ltd.

SAViNE: social network analysis - inspired content delivery network deployment and experimentation

Abstract Over the last years, the content delivery network (CDN) market has been witnessing globally an increase in the development of cloud-based CDNs, as they constitute a viable and cost-effective alternative to traditional commercial CDNs. Towards that direction, Social-Aware Virtual Network Embedding (SAViNE) for wireless content delivery within the OpenLab project aims at establishing, assessing, and prototyping a novel framework for deploying a CDN over the wireless cloud. Specifically, the goal of SAViNE is to provide experimental validation of the efficiency of social network analysis (SNA) - inspired surrogate server placement strategies, devised for fostering content delivery. The proposed framework has been integrated with the OpenLab experimental facilities, providing a run-time environment for CDN deployment, operation, and performance evaluation over the wireless environment. The framework’s feasibility and scalability is experimentally validated. The study is complemented with repeatability evaluation of experimental measurements, related to the resulting CDN’s operational efficiency.

Locality-Aware Peer-to-Peer Multimedia Delivery Over Next-Generation Optical Networks

The increasing success of multimedia services poses a serious challenge to both network operators and service providers. Traditional copper-based access technologies are being replaced by fiber-to-the-X (FTTX) deployments in order to meet this increasing bandwidth demand of individual users. However, the growing traffic volume in the access segment may overload the existing aggregation part of the network, therefore creating a bandwidth bottleneck in the core. To address this problem the traffic should be kept as much as possible in the access network, taking advantage of the high-capacity fiber infrastructure. Since multimedia traffic is dominating the network, locality-aware approaches to video content distribution can represent a good solution. In this work, we propose and evaluate a network-managed, peer-to-peer based caching scheme for multimedia distribution. Our results show that such a system is able to reduce core traffic compared to the traditional content delivery network (CDN) based strategies, while at the same time decreasing the overall power consumption of the network and offering cost-saving opportunities for operators.

Popularity–Based Adaptive Content Delivery Scheme with In-Network Caching

To solve the increasing popularity of video streaming services over the Internet, recent research activities have addressed the locality of content delivery from a network edge by introducing a storage module into a router. To employ in-network caching and persistent request routing, this paper introduces a hybrid content delivery network (CDN) system combining novel content routers in an underlay together with a traditional CDN server in an overlay. This system first selects the most suitable delivery scheme (that is, multicast or broadcast) for the content in question and then allocates an appropriate number of channels based on a consideration of the content's popularity. The proposed scheme aims to minimize traffic volume and achieve optimal delivery cost, since the most popular content is delivered through broadcast channels and the least popular through multicast channels. The performance of the adaptive scheme is clearly evaluated and compared against both the multicast and broadcast schemes in terms of the optimal in-network caching size and number of unicast channels in a content router to observe the significant impact of our proposed scheme.

An economic replica placement mechanism for streaming content distribution in Hybrid CDN-P2P networks

Hybrid CDN-P2P networks blend Content Delivery Networks (CDN) and Peer-to-Peer (P2P) networks to overcome their shortcomings. Replica placement in these networks is still an open problem. Hierarchical structure of these networks makes it inefficient to use available replica placement strategies specialized to CDN or P2P network domains. In this work, we introduce a novel replication strategy which enables traditional CDNs to offer Hybrid CDN-P2P streaming content delivery services. The proposed solution relies on economic model of the Hybrid CDN and employs a dynamic mechanism to optimize the number and places of replicas for P2P service. In particular, processing and communication complexities of the proposed solution are studied and its performance is analyzed in a typical Hybrid CDN-P2P network in comparison to related strategies.

Push or pull? Toward optimal content delivery using cloud storage

Cloud computing and ‘Storage As A Service’ (SaaS) are experiencing a momentous popularity increase due to its flexible, and scalable access to resources. Especially, cloud storage is becoming an economical alternative to traditional content delivery networks (CDNs) such as Akamai and Limelight Networks for moderate-size content providers. Previous research on content distribution mainly focuses on reducing latency experienced by content customers. A few recent studies address the issue of bandwidth usage in CDNs, as the bandwidth consumption is an important issue due to its relevance to the cost of content providers. However, few researches consider both bandwidth consumption and delay performance for the content providers that use cloud storages with limited budgets, which is the focus of this paper. We develop an efficient light-weight approximation algorithm toward the joint optimization problem of content placement. We also conduct the analysis of its theoretical complexities. The performance bound of the proposed approximation algorithm exhibits a much better worst case than those in previous studies. We further extend the approximate algorithm into a distributed version that allows it to promptly react to dynamic changes in users’ interests. The extensive results from both simulations and Planetlab experiments exhibit that the performance is near optimal for most of the practical conditions.

A Cloud-Oriented Content Delivery Network Paradigm: Modeling and Assessment

Cloud-oriented content delivery networks (CCDNs) constitute a promising alternative to traditional content delivery networks. Exploiting the advantages and principles of the cloud, such as the pay as you go business model and geographical dispersion of resources, CCDN can provide a viable and cost-effective solution for realizing content delivery networks and services. In this paper, a hierarchical framework is proposed and evaluated toward an efficient and scalable solution of content distribution over a multiprovider networked cloud environment, where inter and intra cloud communication resources are simultaneously considered along with traditional cloud computing resources. To efficiently deal with the CCDN deployment problem in this emerging and challenging computing paradigm, the problem is decomposed to graph partitioning and replica placement problems while appropriate cost models are introduced/adapted. Novel approaches on the replica placement problem within the cloud are proposed while the limitations of the physical substrate are taken into consideration. The performance of the proposed hierarchical CCDN framework is assessed via modeling and simulation, while appropriate metrics are defined/adopted associated with and reflecting the interests of the different identified involved key players.