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The main technical underpinnings of Cloud Computing infrastructures and services include virtualization, service-orientation, elasticity, multi-tenancy, power efficiency, and economics of scale. The perceived advantages for Cloud-service clients include the ability to add more capacity at peak demand, reduce cost, experiment with new services, and to remove unneeded capacity. This special issue came to be due to the direct and indirect involvement of many researchers, academicians, developers, designers, and industry practitioners. As the volume of data produced at the Internet surges, the pub/sub paradigm becomes increasingly popular for content access and dissemination. The authors focus on content-centric pub/sub networks and describe a new placement and replica assignment algorithm. The authors propose a novel distributed caching scheme where caches are organized in domains so as to fetch content from other caches and share content between caches in the domain. 55 18 3987 3990 Cited By :1

Content distribution networks (CDNs) have gained considerable attention in the past few years. Hence there is need for developing frameworks for carrying out CDN simulations. In this article we present a modeling and simulation framework for CDNs, called CDNsim. CDNsim has been designated to provide a realistic simulation for CDNs, simulating the surrogate servers, the TCP/IP protocol, and the main CDN functions. The main advantages of this tool are its high performance, its extensibility, and its user interface, which is used to configure its parameters. CDNsim provides an automated environment for conducting experiments and extracting client, server, and network statistics. The purpose of CDNsim is to be used as a testbed for CDN evaluation and experimentation. This is quite useful to both the research community (to experiment with new CDN data management techniques), and for CDN developers (to evaluate profits on prior certain CDN installations). © 2010 ACM. 20 2 Cited By :33

Cloud computing is a disruptive technology with profound implications not only for Internet services but also for the IT sector as a whole. Its emergence promises to streamline the on-demand provisioning of software, hardware, and data as a service, achieving economies of scale in IT solutions' deployment and operation. This issue's articles tackle topics including architecture and management of cloud computing infrastructures, SaaS and IaaS applications, discovery of services and data in cloud computing infrastructures, and cross-platform interoperability. Still, several outstanding issues exist, particularly related to SLAs, security and privacy, and power efficiency. Other open issues include ownership, data transfer bottlenecks, performance unpredictability, reliability, and software licensing issues. Finally, hosted applications' business models must show a clear pathway to monetizing cloud computing. Several companies have already built Internet consumer services such as search, social networking, Web email, and online commerce that use cloud computing infrastructure. Above all, cloud computing's still unknown "killer application" will determine many of the challenges and the solutions we must develop to make this technology work in practice.

Content distribution networks (CDNs) improve scalability and reliability, by replicating content to the "edge" of the Internet. Apart from the pure networking issues of the CDNs relevant to the establishment of the infrastructure, some very crucial data management issues must be resolved to exploit the full potential of CDNs to reduce the "last mile" latencies. A very important issue is the selection of the content to be prefetched to the CDN servers. All the approaches developed so far, assume the existence of adequate content popularity statistics to drive the prefetch decisions. Such information though, is not always available, or it is extremely volatile, turning such methods problematic. To address this issue, we develop self-adaptive techniques to select the outsourced content in a CDN infrastructure, which requires no apriori knowledge of request statistics. We identify clusters of "correlated" Web pages in a site, called Web site communities, and make these communities the basic outsourcing unit. Through a detailed simulation environment, using both real and synthetic data, we show that the proposed techniques are very robust and effective in reducing the user-perceived latency, performing very close to an unfeasible, off-line policy, which has full knowledge of the content popularity. © 2007 Springer Science+Business Media, LLC. 11 1 39 70 Cited By :31

CDNs improve network performance and offer fast and reliable applications and services by distributing content to cache servers located close to users. The Web's growth has transformed communications and business services such that speed, accuracy, and availability of network-delivered content has become absolutely critical - both on their own terms and in terms of measuring Web performance. Proxy servers partially address the need for rapid content delivery by providing multiple clients with a shared cache location. In this context, if a requested object exists in a cache (and the cached version has not expired), clients get a cached copy, which typically reduces delivery time. CDNs act as trusted overlay networks that offer high-performance delivery of common Web objects, static data, and rich multimedia content by distributing content load among servers that are close to the clients. CDN benefits include reduced origin server load, reduced latency for end users, and increased throughput. CDNs can also improve Web scalability and disperse flash-crowd events. Here we offer an overview of the CDN architecture and popular CDN service providers.

Cloud computing is a recent trend in information technology and networking that has the potential to change radically the way computer services are constructed, managed, and delivered. The key driving forces behind the emergence of cloud computing include the overcapacity of today's large corporate data centers, the ubiquity of broadband and wireless networking, the falling cost of storage, and progressive improvements in networking technologies. Cloud computing opens new perspectives with profound implications in the area of communication networks, raising new issues in their architecture, design, and implementation.

The rapid proliferation of Online Social Network (OSN) sites has made a profound impact on the WWW, which tends to reshape its structure, design, and utility. Industry experts believe that OSNs create a potentially transformational change in consumer behavior and will bring a far-reaching impact on traditional industries of content, media, and communications. This chapter starts out by presenting the current status of OSNs through a taxonomy which delineates the spectrum of attributes that relate to these systems. It also presents an overall reference system architecture that aims at capturing the building blocks of prominent OSNs. Additionally, it provides a state-of-the-art survey of popular OSN systems, examining their architectural designs and business models. Finally, the chapter explores the future trends of OSN systems, presents significant research challenges and discusses their societal and business impact. © 2011 Springer-Verlag Berlin Heidelberg. 331 213 234 Cited By :29

Content distribution networks (CDNs) balance costs and quality in services related to content delivery. Devising an efficient content outsourcing policy is crucial since, based on such policies, CDN providers can provide client-tailored content, improve performance, and result in significant economical gains. Earlier content outsourcing approaches may often prove ineffective since they drive prefetching decisions by assuming knowledge of content popularity statistics, which are not always available and are extremely volatile. This work addresses this issue, by proposing a novel self-adaptive technique under a CDN framework on which outsourced content is identified with no a priori knowledge of (earlier) request statistics. This is employed by using a structure-based approach identifying coherent clusters of "correlated" Web server content objects, the so-called Web page communities. These communities are the core outsourcing unit, and in this paper, a detailed simulation experimentation has shown that the proposed technique is robust and effective in reducing user-perceived latency as compared with competing approaches, i.e., two communities-based approaches, Web caching, and non-CDN. © 2009 IEEE. 21 1 137 151 Cited By :18

Content Delivery Networks (CDNs) provide an efficient support for serving "resource-hungry" applications while minimizing the network impact of content delivery as well as shifting the traffic away from overloaded origin servers. However, their performance gain is limited since the storage space in CDN's servers is not used optimally. In order to manage their storage capacity in an efficient way, we integrate caching techniques in CDNs. The challenge is to decide which objects would be devoted to caching so as the CDN's server may be used both as a replicator and as a proxy server. In this article, we propose a nonlinear, nonparametric model which classifies the CDN's server cache into two parts. Through a detailed simulation environment, we show that the proposed technique can yield significant reduction in user-perceived latency as compared with other heuristic schemes. Copyright © 2008, IGI Global. 4 4 1 12

9 LNEE 127 153 Cited By :2

Web prefetching is an attractive solution to reduce the network resources consumed by Web services as well as the access latencies perceived by Web users. Unlike Web caching, which exploits the temporal locality, Web prefetching utilizes the spatial locality of Web objects. Specifically, Web prefetching fetches objects that are likely to be accessed in the near future and stores them in advance. In this context, a sophisticated combination of these two techniques may cause significant improvements on the performance of the Web infrastructure. Considering that there have been several caching policies proposed in the past, the challenge is to extend them by using data mining techniques. In this paper, we present a clustering-based prefetching scheme where a graph-based clustering algorithm identifies clusters of "correlated" Web pages based on the users' access patterns. This scheme can be integrated easily into a Web proxy server, improving its performance. Through a simulation environment, using a real data set, we show that the proposed integrated framework is robust and effective in improving the performance of the Web caching environment. © 2007 Elsevier Ltd. All rights reserved. 34 4 309 323 Cited By :52

Content Delivery Networks (CDNs) provide an efficient support for serving "resource-hungry" applications while minimizing the network impact of content delivery as well as shifting the traffic away from overloaded origin servers. However, their performance gain is limited since the storage space in CDN's servers is not used optimally. In order to manage their storage capacity in an efficient way, we integrate caching techniques in CDNs. The challenge is to decide which objects would be devoted to caching so as the CDN's server may be used both as a replicator and as a proxy server. In this paper we propose a nonlinear non-parametric model which classifies the CDN's server cache into two parts. Through a detailed simulation environment, we show that the proposed technique can yield significant reduction in user-perceived latency as compared with other heuristic schemes. ©2008 IEEE. 586 590 Conference code: 73247 Cited By :4

Understanding users' navigation on the Web is important towards improving the quality of information and the speed of accessing large-scale Web data sources. Clustering of users' navigation into sessions has been proposed in order to identify patterns and similarities which are then managed in the context of Web users oriented applications (searching, e-commerce, etc.). This paper deals with the problem of assessing the quality of user session clusters in order to make inferences regarding the users' navigation behavior. A common model-based clustering algorithm is used to result in clusters of Web users' sessions. These clusters are validated by using a statistical test, which measures the distances of the clusters' distributions to infer their dissimilarity and distinguishing level. Furthermore, a visualization method is proposed in order to interpret the relation between clusters. Using real data sets, we illustrate how the proposed analysis can be applied in popular application scenarios to reveal valuable associations among Web users' navigation sessions. © 2006 Elsevier Ltd. All rights reserved. 43 5 1348 1367 Cited By :19

Content Distribution Networks (CDNs) are increasingly being used to disseminate data in today's Internet. The growing interest in CDNs is motivated by a common problem across disciplines: how does one reduce the load on the origin server and the traffic on the Internet, and ultimately improve response time to users? In this direction, crucial data management issues should be addressed. A very important issue is the optimal placement of the outsourced content to CDN's servers. Taking into account that this problem is NP complete, an heuristic method should be developed. All the approaches developed so far assume the existence of adequate popularity statistics. Such information though, is not always available, or it is extremely volatile, turning such methods problematic. This paper develops a network-adaptive, non-parameterized technique to place the outsourced content to CDN's servers, which requires no a-priori knowledge of request statistics. We place the outsourced objects to these servers with respect to the network latency that each object produces. Through a detailed simulation environment, using both real and synthetic data, we show that the proposed technique can yield up to 25% reduction in user-perceived latency, compared with other heuristic schemes which have knowledge of the content popularity. © 2005 IEEE. 2005 140 147 Sponsors: CLEI-Latin American Center for Informatics Studies CYTED-Ibero American Program for Cooperation in Sci DCC-Center for Web Research, University of Chile Engineering School, National University of La Pampa, Argentina HP Research Labs Conference code: 69146 Cited By :27

Web caching and content replication techniques emerged to solve performance problems related to the Web. We propose a generic non-parametric heuristic method that integrates both techniques under a CDN. We provide experimentation showing that our method outperforms the so far separate implementations of Web caching and content replication. Moreover, we show that the performance improvement compared with an existing algorithm is significant. We test all these techniques in a simulation environment under a flash crowd event and a workload of a typical light-weighted CDN operation. © 2006 IEEE. 239 242 Conference code: 71486 Cited By :11

Web caching and replication tune capacity with performance and they have become essential components of the Web. In practice, caching and replication techniques have been applied in proxy servers and Content Distribution Networks (CDNs) respectively. In this paper, we investigate the benefits of integrating caching policies on a CDN' s infrastructure. Using a simulation testbed, our results indicate that there is much room for performance improvement in terms of perceived latency, hit ratio and byte hit ratio. Moreover, we show that the combination of caching with replication fortifies CDNs against flash crowd events. © Springer-Verlag Berlin Heidelberg 2006. 4152 LNCS 200 215 Sponsors: Altec G-net Ministry of National Education and Religious Affairs Conference code: 68347 Cited By :5

Users tend to use the Internet for "resource-hungry" applications (which involve content such as video, audio on-demand and distributed data) and at the same time, more and more applications (such as e-commerce, elearning etc.) are relying on the Web. In this framework, Content Distribution Networks (CDNs) are increasingly being used to disseminate data in today's Internet, providing a delicate balance between costs for Web content providers and quality of services for Web customers. The growing interest in CDNs is motivated by a common problem across disciplines: how does one reduce the load on the origin server and the traffic on the Internet, and ultimately improve response time to users? In this direction, crucial data management issues should be addressed. A very important issue is the optimal placement of the outsourced content to CDN's servers. Taking into account that this problem is NP complete, an heuristic method should be developed. All the approaches developed so far either take as criterion the network's latency or the workload. This paper develops a novel technique to place the outsourced content to CDN's servers, integrating both the latency and the load. Through a detailed simulation environment, using both real and synthetic data, we show that the proposed method can improve significantly the response time of requests while keeping the CDNs' servers' load at a very low level. © 2006 IEEE. Sponsors: Conference code: 123751 Cited By :12

Content delivery over the Web has become an important element of improving web performance. Content delivery Networks (CDN) has been proposed to maximize bandwidth, improve accessibility, and maintain correctness through content replication. CDN reduce the customer's need to invest in website infrastructure and decrease the operational costs of managing such infrastructure, bypass traffic jams on the web and reduce the load on origin servers. CDN topology is built such that the client-perceived performance is maximized and the infrastructure cost is minimized. CDN maintains a mapping between content and surrogate servers, and each request is directed to the closet surrogate server. Data mining techniques offer an effective benefit for CDN, since CDN manage large collection of data over highly distributed infrastructure. CDN is still in early stage of development and is essential to understand the existing practices involved in a CDN framework in order to predict evolutionary steps. 49 1 101 106 Cited By :252

Caching Web objects has become a common practice towards improving content delivery and users' servicing. A Web caching framework is characterized by its cache replacement policy, which identifies the objects (i.e. the elements on a Web page, which include text, graphics, and scripts) to be replaced in a cache upon a request arrival. In this paper, we present a cache replacement algorithm (so-called FRES-CAR), which identifies the objects that should be evicted by considering together three important criteria: object's frequency, recency and size. Experimentation under synthetic workloads has shown that FRES-CAR achieves higher hit rates when compared with the most popular and existing algorithms. © 2005 IEEE. 2005 74 79 Sponsors: IEEE Computer Society Database Society of Japan, DBSJ Information Processing Society of Japan, IPSJ Institute of Electronics, Info. and Com. Eng., IEICE Conference code: 68742 Cited By :2

One of the main issues in Web usage mining is the discovery of patterns in the navigational behavior of Web users. Standard approaches, such as clustering of users' sessions and discovering association rules or frequent navigational paths, do not generally allow to characterize or quantify the unobservable factors that lead to common navigational patterns. Therefore, it is necessary to develop techniques that can discover hidden and useful relationships among users as well as between users and Web objects. Correspondence Analysis (CO-AN) is particularly useful in this context, since it can uncover meaningful associations among users and pages. We present a model-based cluster analysis for Web users sessions including a novel visualization and interpretation approach which is based on CO-AN. © Springer-Verlag Berlin Heidelberg 2005. 3488 LNAI 219 227 Conference code: 67057 Cited By :14

Cluster analysis is one of the most important aspects in the data mining process for discovering groups and identifying interesting distributions or patterns over the considered data sets. In the context of Web data mining, model-based clustering algorithms are often used to cluster similar users' sessions in order to determine Website access behaviors. An important issue in cluster analysis is the evaluation of clustering results to find the partitioning that best fits the underlying data. In this paper, we present a novel validation technique for model-based clustering approaches. © 2004 IEEE. 5 4129 4134 Sponsors: IEEE Conference code: 64440 Cited By :6

The popularity of the World-Wide-Web has increased dramatically in the past few years. Web proxy servers have an important role in reducing server loads, network traffic, and client request latencies. This paper presents a detailed workload characterization study of a busy Web proxy server. The study aims in identifying the major characteristics which will improve modelling of Web proxy accessing. A set of log files is processed for workload characterization. Throughout the study, emphasis is given on identifying the criteria for a Web caching model. A statistical analysis, based on the previous criteria, is presented in order to characterize the major workload parameters. Results of this analysis are presented and the paper concludes with a discussion about workload characterization and content delivery issues. 21 779 784 Sponsors: International Assoc. of Sc. and Technol. for Developm. (IASTED) Conference code: 62395 Cited By :3