On the effects of content compression on Web cache performance

The last decade has seen tremendous growth in usage of the World Wide Web. Web caching is a technology aimed at reducing the transmission of redundant network traffic and improving access to the Web. The key idea in Web caching is to cache frequently- accessed content so that it may be used profitably later. This leads to cost savings, reduction in network traffic, improved access and better content availability. Web Caching and Its Applications gives the reader an understanding of the latest developments in Web caching research. Topics covered include architectural aspects, aspects requiring coordination among caches, aspects related to network traffic, techniques that complement caching, practical aspects, and aspects related to performance. While Web Caching and Its Applications is designed for a professional audience, students will appreciate the exercises for applying the knowledge to solving practical problems related to Web caching and Internet performance. The book includes an exhaustive list of references for further study.

Caching is a promising technique that can effectively reduce peak traffic by pushing popular content items proactively to the users during off- peak hours. Two key performance metrics for proactive caching are the energy efficiency and hit ratio. In this paper, we are interested in balancing the hit ratio and energy efficiency in social-aware proactive caching. More specifically, we present a social behavior driven pushing and caching policy that is capable of maximizing the hit ratio while satisfying the power constraint. For two notable schemes, namely uncoded caching and coded caching, we formulate two optimization problems that give the optimal tradeoff between the energy efficiency and caching hit ratio. Furthermore, the optimal solutions present the energy efficient joint pushing and buffer update polices. Our simulation results show that the social-aware pushing and update policies may bring a significant hit ratio gain when the buffer size is far less than the number of items.

The increasing popularity of photo sharing in social networking service (SNS) complicates the challenge of storing and transmitting large photo data for SNS providers. Distributed web caches are generally used by SNS providers to improve data transmission performance effectively. Two critical factors affect the efficiency of web caches: storage media and replacement algorithms. Solid-state drive (SSD) is often used in web caches due to its good performance. Random write performance and SSD endurance are directly affected by the characteristic of write amplification, this characteristic is also related to replacement algorithms. The least recently used (LRU) algorithm effectively computes cache hit ratio but induces severe write amplification. First in first out (FIFO) method minimizes write amplification, whereas a weak hit ratio increases bandwidth consumption. In this paper, we present a hybrid replacement strategy, namely, F-SkLRU. This strategy facilitates a good trade-off between performance and the cost of web cache. F-SkLRU takes advantage of sequential writing to reduce SSD wear. This strategy also consolidates multiple factors to improve hit ratio. Simulation results show that F-SkLRU can reduce bandwidth consumption by 14.11% to 23.4% in comparison with that of FIFO and LRU. The proposed strategy can also reduce the cost of SSD by up to 300% more than LRU can in extreme situations.

SUMMARY Peer-to-peer (P2P) web caching has been studied recently as it can exploit local caches of peers for web caching without additional infrastructure. However, dynamic join/leave behaviors or local caching strategies of the peers due to their autonomy in a P2P network may limit the performance of P2P web caching. To overcome these limitations, we propose an effective directory-based P2P web caching system under dynamic participation of peers. We introduce the object lifetime in a P2P network considering the lifetimes of both an object in the local cache of a peer and a peer who owns the object, and utilize this object lifetime information for neighbor selection and storage management in the P2P web caching framework. For the neighbor selection, the proposed system utilizes the object lifetimes in selecting accurately a neighbor who would still retain the requested object and still remain in the P2P network. To improve the storage management, the proposed system uses efficiently the entire cache storage of the P2P network in such a way that the object is stored selectively in the local cache of the peer who requested it, considering the object lifetime. The trace-driven simulation results show that the proposed system has higher accuracy and fewer redirection failures than the conventional directory-based P2P web caching system in the feasible P2P network.

As the explosion of Internet traffic is quickly leading to overloaded cellular network, device-to-device (D2D)-based content sharing is proposed as a method to offload mobile data traffic. The performance of D2D-based content sharing is dramatically affected by the success rate of content fetching from nearby devices and quality of content transmission, which is determined by the geographic distribution of mobile devices, the number of devices having contents in their caches, and the condition of D2D links. Hence, a key problem is how to cache various contents in the limited storage of mobile devices for improving the success rate of content fetching. In this paper, we aim to design a caching policy by considering the joint impact of locality of real-world mobile data traffic and device contact pattern to improve the success rate of content fetching. To do this, we first study the characteristics of network traffic and device contact pattern by analyzing traces from realistic networks. Then, we design a locality-based caching policy and derive the content caching probability and hit ratio through mathematical analysis. Through numerical evaluation and trace-driven simulations, we not only quantify how content popularity, content active lifetime, content size, content bit rate, device storage, transmission rate, and closeness centrality affect the content hit ratio, but also provide comparison on hit ratio and storage cost in different caching policy, which is a strong evidence that the joint impacts from characteristics of content and device are the necessary consideration when to design a caching policy.

The World-Wide-Web has experienced exponential growth in recent years. This growth has created a tremendous increase in network and server loads that have subsequently adversely affected user-response times. Among many viable and available approaches to reducing user-response time, Web caching appears to be one approach that has recently received considerable attention. In this dissertation we explore a new approach to the study of Web cache policies, namely model-driven simulation. We present a good model of Web-access user patterns based on sound theory and principles from the information sciences. This model is justified by the empirical web access data from several different web sites. The importance of removal policies in improving cache performance motivates us to propose a dynamic and robust removal policy which incorporates the characteristics of user access patterns. We show that our proposed removal policy performs rigorously well over a variety of parameters. In this research we take a model-driven simulation approach to evaluate the impact of different factors and policies on cache performance. The results indicate that cache size, user access patterns and removal policy are major factors affecting cache performance. Continuous removal method is a good and simple method. The increase of average document size, low comfort level (less than 50% cache size) and threshold policy would degrade web cache performance. Finally, we discuss the limitations of our current research and give some directions of future research.

In this paper, we design and implement a P2P cooperative proxy caching system based on a novel P2P cooperative proxy caching scheme. To effectively locate the cached web documents, a TTL-based routing protocol is proposed to manage the query and response messages in the P2P cooperative proxy cache system. Furthermore, we design a predict query-route algorithm to improve the TTL-based routing protocol by adding extra information in the query message packets. To select a suitable cache replacement algorithm for the P2P cooperative proxy cache system, three different cache replacement algorithms, LRU, LFU and SIZE, are evaluated using web trace based performance studies on the implemented P2P cooperative proxy cache system. The experimental results show that LRU is an overall better cache replacement algorithm for the P2P proxy cache system although SIZE based cache replacement approach produces slightly better cache hit ratio when cache size is very small. The performance studies also demonstrate that the proposed message routing protocols significantly improve the performance of the P2P cooperative proxy cache system, in terms of cache hit ratio, byte hit ratio, user request latency, and the number of query messages generated in the proxy cache system, compared to the flooding based message routing protocol.

Web caching has been used extensively to enhance content delivery to the clients by minimizing client-observed latency, reducing network bandwidth usage and improving scalability of the network. Caching performance can be improved by designing good replacement policies, prefetching techniques, clustering of web users and proper placement of proxy caches in the network. In this paper, we discuss the various approaches that were designed based on neural networks, genetic algorithms and fuzzy logic to optimize the performance of web caching. The approaches discussed here proved to be more effective in solving the problems as compared to the conventional techniques that were used earlier in this problem domain. Neural networks and evolutionary algorithms can be considered for further exploration in the various issues related to web caching and content delivery.

Modern applications demand support for a large number of clients and require large scale storage subsystems. This paper presents a theoretical model of prefetching and caching of storage objects under a parallel storage units architecture. The storage objects are defined as variable sized data blocks and a specific cache area is reserved for data prefetching and caching. An evolutionary algorithm is proposed for identifying the storage objects to be prefetched and cached. The storage object prefetching approach is experimented under certain artificial workloads of requests for a set of storage units and has shown significant performance improvement with respect to request service times, as well as cache and byte hit ratios.

The World Wide Web has become the primary means for information dissemination. Due to the limited resources of the network bandwidth, users always suffer from long time waiting. Web prefetching and Web caching are the primary approaches to reducing the user perceived access latency and improving the quality of service. In this paper, a SPN (Stochastic Petri Nets) model of Web prefetching and caching system is constructed, and based on which, the performance analysis of the integrated Web prefetching and caching model are made. The performance metrics latency, throughput are compared and analyzed theoretically. Simulations show that compared with caching mechanism, Web prefetching mechanism can further reduce the access latency, improve the throughput and the hit ratio efficiently. The performance evaluation based on the SPN model provides an implementation basis for Web prefetching and caching.

The rapid growth of the World Wide Web is increasing the demand for efficient distribution and fast access of information around the world. As hardware upgrades are not always able to keep up with increase in web traffic, considerable latency is often experienced in retrieving web objects from the Internet during peak periods. Therefore, better content distribution techniques in addition to hardware upgrades are needed to improve the performance of web accesses. Caching and replication are two primary content distribution approaches to enhance web performance. This thesis investigates four related issues in web caching and replication. In the first part of the thesis, we study cache cooperation strategies at different levels of the Internet hierarchy. At the upper level (e.g., that of a regional ISP), web caches are geographically distributed and often structured in a cascaded fashion where requests not hitting a lower level cache are forwarded to a higher level cache. We present a general analytical framework for coordinated management of cascaded caches. The optimal locations for caching objects are computed by a dynamic programming algorithm. Based on the framework, a novel caching scheme that integrates both object placement and replacement strategies is proposed. At the lower level of the Internet hierarchy (e.g., that of a client organization), web caches are geographically clustered. Hash routing is an effective coordination technique to improve the overall hit ratio and reduce the outbound traffic for clustered caches. We have developed an analytical model for hash routing and investigated the problem of determining the optimal object and DNS allocation strategies to minimize the average response time of client requests. The analytical results are applied to the design of two adaptive hash routing schemes for static and dynamic client configurations respectively. An important price to pay for web replication is that the content provider needs to keep the replicas consistent with the authoritative origin copy. In the second part of the thesis, we study the optimal cost of consistency management for two different scenarios. In the first scenario, the construction of a distribution tree is investigated with the objective of minimizing the cost of expiration-based consistency management for geographically distributed replicas. This is formulated as an optimization problem and is proven to be NP-hard. The optimal distribution tree is identified in some special cases and three heuristic algorithms are proposed for the general problem. In the second scenario, the replication of dynamic web contents is studied. Unlike static web contents which only involve file fetches when they are requested, dynamic contents are constructed by running application programs on base data. Therefore, the cost of consistency management includes both the network cost of update transfers and the computation cost of object reconstruction. We present a theoretical framework on minimal cost replication of dynamic web contents under a flat model of update delivery. A polynomial optimal solution is proposed that determines where each data object should be replicated and how to keep the replicas up-to-date.

As the Internet has become a more central aspect for information technology, so have concerns with supplying enough bandwidth and serving web requests to end users in an appropriate time frame. Web caching was introduced in the 1990s to help decrease network traffic, lessen user perceived lag, and reduce loads on origin servers by storing copies of web objects on servers closer to end users as opposed to forwarding all requests to the origin servers. Since web caches have limited space, web caches must effectively decide which objects are worth caching or replacing for other objects. This problem is known as cache replacement. We used neural networks to solve this problem and proposed the Neural Network Proxy Cache Replacement (NNPCR) method. The goal of this research is to implement NNPCR in a real environment like Squid proxy server. In order to do so, we propose an improved strategy of NNPCR referred to as NNPCR-2. We show how the improved model can be trained with up to twelve times more data and gain a 5–10% increase in Correct Classification Ratio (CCR) than NNPCR. We implemented NNPCR-2 in Squid proxy server and compared it with four other cache replacement strategies. In this paper, we use 84 times more data than NNPCR was tested against and present exhaustive test results for NNPCR-2 with different trace files and neural network structures. Our results demonstrate that NNPCR-2 made important, balanced decisions in relation to the hit rate and byte hit rate; the two performance metrics most commonly used to measure the performance of web proxy caches.

While web proxy caching is a widely deployed technique, the performance of a proxy cache is limited by the local storage. Some studies have addressed this limitation by using the residual resources of clients via a p2p method and have achieved a very high hit rate. However, these approaches treat web objects as homogeneous objects and there is no consideration of various web characteristics. Consequently, the byte hit rate of the system is limited, external bandwidth is wasted, and perceived user latency is increased. The present paper suggests an efficient p2p based web caching technique that manages objects with different policies so as to exploit the characteristics of web objects, such as size and temporal locality. Small objects are stored alone whereas large objects are stored by dividing them into numerous small blocks, which are distributed in clients. On a proxy cache, header blocks of large objects take the place of objects themselves and smaller objects are cached. This technique increases the hit rate. Unlike a web cache, which evicts large objects as soon as possible in the case where clients fulfill the role of backup storage, large objects are given higher priority than small objects in the proposed approach. This maximizes the effect of hits for large objects and thereby increases the byte hit rate. Furthermore, we construct simple latency models for various p2p based web caching systems and analyze the effects of the proposed policies on these systems. We then examine the performances of the efficient policies via a trace driven simulation. The results demonstrate that the proposed techniques effectively enhance web cache performance, including hit rate, byte hit rate, and response time.

Most existing work on cooperative caching has been-focused on serving misses collaboratively. Very few have studied the effect of cooperation on document placement schemes and its potential enhancements on cache hit ratio and latency reduction. In this paper we propose a new document placement scheme, called the Expiration Age based scheme (EA scheme), which takes into account the contentions at individual caches in order to limit the replication of documents within a cache group and increase document hit ratio. The main idea of this new scheme is to view the aggregate disk space of the cache group as a global resource of the group, and uses the concept of cache expiration age to measure the contention of individual caches. The decision of whether to cache a document at a proxy is made collectively, among the caches that already have a copy of this document. The experiments show that the EA scheme yields higher hit rates and better response times compared to the existing document placement schemes used in most of the caching proxies.

Cellular vehicle‐to‐everything‐ (C‐V2X‐) based communications can support various content‐oriented applications and have gained significant progress in recent years. However, the limited backhaul bandwidth and dynamic topology make it difficult to obtain the multimedia service with high‐reliability and low‐latency communication in C‐V2X networks, which may degrade the quality of experience (QoE). In this paper, we propose a novel cluster‐based cooperative cache deployment and coded delivery strategy for C‐V2X networks to improve the cache hit ratio and response time, reduce the request‐response delay, and improve the bandwidth efficiency. To begin with, we design an effective vehicle cluster method. Based on the constructed cluster, we propose a two‐level cooperative cache deployment approach to cache the frequently requested files on the edge nodes, LTE evolved NodeB (eNodeB) and cluster head (CH), to maximize the overall cache hit ratio. Furthermore, we propose an effective coded delivery strategy to minimize the network load and the ratio of redundant files. Simulation results demonstrate that our proposed method can effectively reduce the average response delay and network load and improve both the hit ratio and the ratio of redundant files.