Web caching plays a key role in delivering web objects to the end-users which is one of the advantages of World Wide Web (WWW). However, the size of the cache is limited which is considered as one of the drawbacks of web caching. Furthermore, retrieving the same web object from the origin server many times consumes the network bandwidth. Moreover, cache pollution is a drawback of traditional web caching policies such as Least Recently Used (LRU) web caching policy where web objects that are stored in the cache are not visited frequently. In this work, new intelligent cooperative web caching approach based on J48 classifier is presented. A simulation is carried out to evaluate the performance of the proposed approach. The results show that the new approach improves the performance of the LRU web caching policy.

Web caching plays a key role in delivering web items to end users in World Wide Web (WWW). On the other hand, cache size is considered as a limitation of web caching. Furthermore, retrieving the same media object from the origin server many times consumes the network bandwidth. Furthermore, full caching for media objects is not a practical solution and consumes cache storage in keeping few media objects because of its limited capacity. Moreover, traditional web caching policies such as Least Recently Used (LRU), Least Frequently Used (LFU), and Greedy Dual Size (GDS) suffer from caching pollution (i.e. media objects that are stored in the cache are not frequently visited which negatively affects on the performance of web proxy caching). In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. The proposed approaches take the advantages of structured peer-to-peer systems where the contents of peers' caches are shared using Distributed Hash Table (DHT) in order to enhance the performance of the web caching policy. The performance of the proposed approaches is evaluated by running a trace-driven simulation on a dataset that is collected from IRCache network. The results demonstrate that the new proposed policies improve the performance of traditional web caching policies that are LRU, LFU, and GDS in terms of Hit

Nowadays, the idea of media contents streaming through the Internet has become a very important issue. On the other hand, full caching for media objects is not a practical solution and leads to consume the cache storage in keeping few media objects because of its limited capacity. Furthermore, repeated traffic which is being sent to clients wastes the network bandwidth. Thus, utilizing the bandwidth of the network is considered as an important objective for network administrators. Media objects have some characteristics that have to be considered when a caching algorithm is going to be performed. In this paper, recent approaches that have been proposed for media streams caching in peer-to-peer systems are reviewed.

Deployment of file sharing systems on wireless networks introduces several challenges specially when mobility comes into view. Thus, many researches have been performed in this field. The aim of this paper is to perform a systematic review on the existing solutions for file sharing in mobile devices based on Peer-to-Peer or shortly P2P approach. Five approaches are presented that are based on unstructured P2P systems; structured P2P system; mobile-to-mobile technique; tree-structured based; and incentive. These approaches of file sharing can work on one of the two wireless network configurations which are Mobile Ad Hoc Network (MANET) and infrastructure based network. Furthermore, we discussed the advantages and limitations of these approaches. Finally, this paper concludes with some insights for research directions in this area.

Web caching plays a key role in delivering web items to end users in World Wide Web (WWW). On the other hand, cache size is considered as a limitation of web caching. Furthermore, retrieving the same media object from the origin server many times consumes the network bandwidth. Furthermore, full caching for media objects is not a practical solution and consumes cache storage in keeping few media objects because of its limited capacity. Moreover, traditional web caching policies such as Least Recently Used (LRU), Least Frequently Used (LFU), and Greedy Dual Size (GDS) suffer from caching pollution (i.e. media objects that are stored in the cache are not frequently visited which negatively affects on the performance of web proxy caching). In this work, intelligent cooperative web caching approaches based on J48 decision tree and Naïve Bayes (NB) supervised machine learning algorithms are presented. The proposed approaches take the advantages of structured peer-to-peer systems where the contents of peers’ caches are shared using Distributed Hash Table (DHT) in order to enhance the performance of the web caching policy. The performance of the proposed approaches is evaluated by running a trace-driven simulation on a dataset that is collected from IRCache network. The results demonstrate that the new proposed policies improve the performance of traditional web caching policies that are LRU, LFU, and GDS in terms of Hit Ratio (HR) and Byte Hit Ratio (BHR). Moreover, the results are compared to the most relevant and state-of-the-art web proxy caching policies.