Cooperative web proxy caching for media objects based on peer-to-peer systems

Web proxy caches are used to improve the performance of the World Wide Web (WWW). Many advantages can be gathered from caching such as improving the hit rates, reducing network traffic, and alleviating loads on origin servers. On the other hand, retrieving the same object many times consumes the network bandwidth. Thus, in order to overcome this Imitation, in this work, a cooperative web caching approach for media objects based on peer-to-peer systems is proposed. Tow performance metrics are used that are Hit Ratio (HR) and Byte Hit Ratio (BHR). A simulation is carried out to study the affects of cooperative caching on the performance of web proxy caching policies. The results show that cooperative caching improves the performance of web proxy caching policies in delivering media objects

Μελέτη μηχανισμού διασφάλισης συνέπειας εξυπηρετητών κρυφής μνήμης Παγκόσμιου Ιστού, με εφαρμογή της θεωρίας Βέλτιστης Παύσης

Η κρυφή μνήμη (cache) και ο μηχανισμός διαχειρισής της (caching) είναι απο τα πλέον σημαντικά ζητήματα στην Πληροφορική επιστήμη. Το πρόβλημα που ανακύπτει απο την χρήση ενός τέτοιου μηχανισμού είναι γνωστό ως πρόβλημα συνέπειας κρυφής μνήμης (cache consistency problem). Η χρήση ενός caching μηχανισμού στον Παγκόσμιο Ιστό, ΠΙ (World Wide Web, WWW ή Web) ονομάζεται Web caching και το αντίστοιχο πρόβλημα Web caching consistency problem. Μέσω Web caching ικανοποιείται η επιτακτική ανάγκη για έναν ΠΙ γρήγορο και εύρωστο. Η πρόσφατη εξάπλωση του ΠΙ θέτει εκ νέου το πρόβλημα της επεκτασιμότητας, με άμεση συνέπεια τη μεγαλύτερη ανάγκη για αποδοτικότερο Web caching που θα διασφαλίζει αποσυμφόρηση δικτύου, μείωση φόρτου στους εξυπηρετητές, εξοικονόμηση εύρους ζώνης και μείωση καθυστέρησης απόκρισης, ενώ ταυτόχρονα θα προσφέρει υψηλή συνέπεια. Στη παρούσα διπλωματική εργασία μελετάται το Web caching consistency πρόβλημα απο τη πλευρά των εξυπηρετητών κρυφής μνήμης και απο μια νέα σκοπιά, αυτή της θεωρίας Βέλτιστης Παύσης. Συγκεκριμένα, μελετάται η δυνατότητα υλοποίησης ενός μηχανισμού διασφάλισης συνέπειας στους εξυπηρετητές κρυφής μνήμης ΠΙ, εφαρμόζοντας αρχές της θεωρίας Βέλτιστης Παύσης. Για το λόγο αυτό υλοποιείται ένας προσομοιωτής βάσει της θεωρίας αυτής, στον οποίο εισάγονται δεδομένα απο web traces και στη συνέχεια εκτελούνται κατάλληλες προσομοιώσεις οι οποίες βοηθούν στην εξαγωγή συμπερασμάτων.The cache memory along with its management mechanism are amongst the most significant issues in Computer science. The problem related with caching is known as cache consistency problem. The use of a caching mechanism in the World Wide Web (WWW or Web) is called Web caching and the relative problem Web caching consistency problem. The urgent need for a robust and fast Web is satisfied through Web caching. The recent wide spreading of Web has posed once again the scalability problem, with direct consequence the even bigger need for a more efficient Web caching which will reduce network congestion, load in servers, bandwidth consumption and latency, while at the same time will provide high consistency. In the current master thesis, the Web caching consistency problem is studied from the cache servers point of view and from a new perspective which is related with the Optimal Stopping theory. More specifically, it is being studied the potential of a consistency mechanism implementation for the Web caching servers, applying the principles of Optimal Stopping theory. Thus, a simulator based on that theory was implemented, and trace driven simulations were executed for the drawing of the necessary conclusions

Intelligent cooperative web caching policies for media objects based on J48 decision tree and naïve Bayes supervised machine learning algorithms in structured peer-to-peer systems

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

Intelligent cooperative web caching policies for media objects based on J48 decision tree and naïve Bayes supervised machine learning algorithms in structured peer-to-peer systems

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

Autonomous Replication in Wide-Area Internetworks

The number of users connected to the Internet has been growing at an exponential rate, resulting in similar increases in network traffic and Internet server load. Advances in microprocessors and network technologies have kept up with growth so far, but we are reaching the limits of hardware solutions. In order for the Internet's growth to continue, we must efficiently distribute server load and reduce the network traffic generated by its various services. Traditional wide-area caching schemes are client initiated. Decisions on where and when to cache information are made without the benefit of the server's global knowledge of the situation. We introduce a technique--push-caching--that is server initiated; it leaves caching decisions to the server. The server uses its knowledge of network topology, geography, and access patterns to minimize network traffic and server load. The World Wide Web is an example of a large-scale distributed information system that will benefit from this geographical distribution, and we present an architecture that allows a Web server to autonomously replicate Web files. We use a trace-driven simulation of the Internet to evaluate several competing caching strategies. Our results show that while simple client caching reduces server load and network bandwidth demands by up to 30%, adding server-initiated caching reduces server load by an additional 20% and network bandwidth demands by an additional 10%. Furthermore, push-caching is more efficient than client-caching, using an order of magnitude less cache space for comparable bandwidth and load savings. To determine the optimal cache consistency protocol we used a generic server simulator to evaluate several cache-consistency protocols, and found that weak consistency protocols are sufficient for the World Wide Web since they use the same bandwidth as an atomic protocol, impose less server load, and return stale data less than 1% of the time.Engineering and Applied Science

Intelligent cooperative web caching policies for media objects based on J48 decision tree and Naive bayes supervised machine learning algorithms in structured peer-to-peer systems

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. 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

Key factors in web latency savings in an experimental prefetching system

Although Internet service providers and communications companies are continuously offering higher and higher bandwidths, users still complain about the high latency they perceive when downloading pages from the web. Therefore, latency can be considered as the main web performance metric from the user's point of view. Many studies have demonstrated that web prefetching can be an interesting technique to reduce such latency at the expense of slightly increasing the network traffic. In this context, this paper presents an empirical study to investigate the maximum benefits that web users can expect from prefetching techniques in the current web. Unlike previous theoretical studies, this work considers a realistic prefetching architecture using real traces. In this way, the influence of real imple- mentation constraints are considered and analyzed. 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Performance Improvement Studies in Accessing Web Documents

As the World Wide Web has now become the standard interface for interactive information services over the Internet, the perceived latency in WWW interaction is becoming an important and crucial issue. Currently, Web users often experience response delay of several seconds or even longer to non-local Web sites especially when the pages they attempt to access are very popular. For WWW to be acceptable for general daily use, the response delay must be reduced. The potential solutions to the problem lie in the extensive use of caching (disk based) and prefetching in WWW. Both caching and prefetching explore the patterns and knowledge in the Web accesses. This thesis describes and tests the efficiency of a batch prefetching update (refreshing) in accessing HTTP and FTP documents on the global Internet. The update is scheduled to run at idle time when the traffic is less congested and the server activity is low. The batch refreshing effort would be fruitful when the refreshed documents are really requested before they tum stale again. The effectiveness of the batch refreshing is verified by running a statistical analysis of the access log files. In the first part of the study, a Proxy Server at the LAN of FTMSK, ITM was set-up, configured and monitored for the use of 400 users. Access log files are collected and analysed for a period of six months. The analysis result would be a benchmark for the caching proxy with batch refreshing in the second part of the work

Basis Token Consistency: A Practical Mechanism for Strong Web Cache Consistency

With web caching and cache-related services like CDNs and edge services playing an increasingly significant role in the modern internet, the problem of the weak consistency and coherence provisions in current web protocols is becoming increasingly significant and drawing the attention of the standards community [LCD01]. Toward this end, we present definitions of consistency and coherence for web-like environments, that is, distributed client-server information systems where the semantics of interactions with resource are more general than the read/write operations found in memory hierarchies and distributed file systems. We then present a brief review of proposed mechanisms which strengthen the consistency of caches in the web, focusing upon their conceptual contributions and their weaknesses in real-world practice. These insights motivate a new mechanism, which we call "Basis Token Consistency" or BTC; when implemented at the server, this mechanism allows any client (independent of the presence and conformity of any intermediaries) to maintain a self-consistent view of the server's state. This is accomplished by annotating responses with additional per-resource application information which allows client caches to recognize the obsolescence of currently cached entities and identify responses from other caches which are already stale in light of what has already been seen. The mechanism requires no deviation from the existing client-server communication model, and does not require servers to maintain any additional per-client state. We discuss how our mechanism could be integrated into a fragment-assembling Content Management System (CMS), and present a simulation-driven performance comparison between the BTC algorithm and the use of the Time-To-Live (TTL) heuristic.National Science Foundation (ANI-9986397, ANI-0095988