Client-side Caching Research Articles

A COOPERATIVE MODEL FOR PREFERENCE-BASED INFORMATION SHARING IN NARROW BANDWIDTH NETWORKS

Users of wide area network applications are usually concerned about both response time and content validity. The common solution of client-side caching that reuses cached content based on arbitrary time-to-live may not be applicable in narrow bandwidth environment, where heavy load is imposed on sparse transmission abilities. In such cases, some users may wait for a long time for fresh content extracted from the origin server although they would settle for obsolescent content, while other users may receive the cached copy which is considered valid, although they would be ready to wait longer for fresher content. In this work, a new model for caching is introduced, where clients introduce preferences regarding their expectations for the time they are willing to wait, and the level of obsolescence they are willing to tolerate. The cache manager considers user preferences, and is capable of balancing the relative importance of each dimension. A cost model is used to determine which of the following three alternatives is most promising: delivery of a local cached copy, delivery of a copy from a cooperating cache, or delivery of a fresh copy from the origin server. The proposed model is proven to be useful by experiments that used both synthetic data and real Web traces simulation. The experiments reveal that using the proposed model, it becomes possible to meet client needs with reduced latency. We also show the benefit of cache cooperation in increasing hit ratios and reducing latency. A prototype of the proposed model was built and deployed on real-world environment demonstrating how users can set preferences towards Web pages, and how cache managers are affected.

Performance Analysis and Improvement of Storage Virtualization in an OS-Online System

An OS-online system called TransCom is based on a virtual storage system that supports heterogeneous services of the operating system and applications online. In TransCom, OS and software which run in the client are stored on the centralized servers, while computing tasks are carried out by the clients, so the server is the bottleneck of the system performance. This paper firstly analyzes the characteristics of its real usage workload and builds a queuing model to locate the system bottlenecks. According to the study, the disk is the primary bottleneck, so an optimal two-level cache arrangement policy is developed on both the server and the client, which aims to avoid most of the server disk accesses. LRU algorithm is used in the client-side cache. A cache management algorithm called Frequency-based Multi-Priority Queues (FMPQ) proposed in this paper is used in the server-side cache. Experiment results show that the appropriate cache arrangement can significantly improve the capability of the TransCom server.

Neuro-fuzzy system in partitioned client-side Web cache

This paper proposes a novel contribution in Web caching area, especially in Web cache replacement, so-called intelligent client-side Web caching scheme (ICWCS). This approach is developed by splitting the client-side cache into two caches: short-term cache that receives the Web objects from the Internet directly, and long-term cache that receives the Web objects from the short-term cache. The objects in short-term cache are removed by least recently used (LRU) algorithm as short-term cache is full. More significantly, when the long-term cache saturates, the neuro-fuzzy system is employed efficiently in managing contents of the long-term cache. The proposed solution is validated by implementing trace-driven simulation and the results are compared with least recently used (LRU) and least frequently used (LFU) algorithms; the most common policies of evaluating Web caching performance. The simulation results have revealed that the proposed approach improves the performance of Web caching in terms of hit ratio (HR), up to 14.8% and 17.9% over LRU and LFU. In terms of byte hit ratio (BHR), the Web caching performance is improved up to 2.57% and 26.25%, and for latency saving ratio (LSR), the performance is better with 8.3% and 18.9% over LRU and LFU, respectively.

Reducing User Perceived Latency with a Proactive Prefetching Middleware for Mobile SOA Access

Network latency is one of the most critical factors for the usability of mobile SOA applications. This paper introduces prefetching and caching enhancements for an existing SOA framework for mobile applications to reduce the user perceived latency. Latency reduction is achieved by proactively sending data to the mobile device that could most likely be requested at a later time. This additional data is piggybacked onto responses to actual requests and injected into a client side cache, so that it can be used without an additional connection. The prefetching is done automatically using a sequence prediction algorithm. The benefit of prefetching and caching enhancements were evaluated for different network settings and a reduction of user perceived latency of up to 31% was found in a typical scenario. In contrast to other prefetching solutions, our piggybacking approach also allows to significantly increase battery lifetime of the mobile device.

Study on the Expended-Enterprise Information Portal Based on the Role Control Theory

Adopting the role-based access control solution, this paper focuses on the study of access level, the most important part of the enterprise information portal. In this paper, the original RBAC model was modified, methods such as domain and permission levels are applied to simplify and improve the access control, reducing the computation; client-side cache is adopted to improve the performance of the access control system. Finally, this paper uses the development of the portal modules to increase information portal functions, so that the needs of different users can be met.

Improving Data Availability for Better Access Performance: A Study on Caching Scientific Data on Distributed Desktop Workstations

Client-side data caching serves as an excellent mechanism to store and analyze the rapidly growing scientific data, motivating distributed, client-side caches built from unreliable desktop storage contributions to store and access large scientific data. They offer several desirable properties, such as performance impedance matching, improved space utilization, and high parallel I/O bandwidth. In this context, we are faced with two key challenges: (1) the finite amount of contributed cache space is stretched by the ever increasing scientific dataset sizes and (2) the transient nature of volunteered storage nodes impacts data availability. In this article, we address these challenges by exploiting the existence of external, primary copies of datasets. We propose a novel combination of prefix caching, collective download, and remote partial data recovery (RPDR), to deal with optimal cache space consumption and storage node volatility. Our evaluation, performed on our FreeLoader prototype, indicates that prefix caching can significantly improve the cache hit rate and partial data recovery is better than (or comparable to) many persistent-data availability techniques.

Scheduling data reads and writes using feedback control on a weakly connected environment

A database is maintained at the server and broadcast to mobile clients. While data are broadcast, many resources are updating data at the server. Such concurrent transactions must be controlled to maintain consistency and currency of data received by the mobile clients. Through client side caching, feedback control mechanism and careful network management, it is possible to provide acceptable performance in mobile environment for read requests and write updates, even with low bandwidth connection. This paper describes sharing of weak network connections between read and write data traffic, controlling concurrency between update and broadcast transactions to maintain consistency and currency.

RDTC Optimized Compression of Image-Based Scene Representations (Part I): Modeling and Theoretical Analysis

Rendering of virtual views in interactive streaming of compressed image-based scene representations requires random access to arbitrary parts of the reference image data. The degree of interframe dependencies exploited during encoding has an impact on the transmission and decoding time and, at the same time, delimits the (storage) rate-distortion (RD) tradeoff that can be achieved. In this work, we extend the classical RD optimization approach using hybrid video coding concepts to a tradeoff between the storage rate (R), distortion (D), transmission data rate (T), and decoding complexity (C). We present a theoretical model for this RDTC space with a focus on the decoding complexity and, in addition, the impact of client side caching on the RDTC measures is considered and evaluated. Experimental results qualitatively match those predicted by our theoretical models and show that an adaptation of the encoding process to scenario specific parameters like computational power of the receiver and channel throughput can significantly reduce the user-perceived delay or required storage for RDTC optimized streams compared to RD optimized or independently encoded scene representations.

RDTC Optimized Compression of Image-Based Scene Representations (Part II): Practical Coding

Interactive streaming of compressed image-based scene representations requires random access to the reference image data. The degree of interframe dependencies exploited during encoding has an impact on the transmission and decoding time and, at the same time, delimits the (storage) rate-distortion (RD) tradeoff that can be achieved. The transmission data rate and the decoding complexity at the client have received attention in the literature, but their incorporation into the optimization procedure for compression and streaming is missing. If scenario-specific measures are considered, the traditional RD optimization can be extended to a tradeoff between the (storage) rate (R), distortion (D), transmission data rate (T), and decoding complexity (C). In the first part of this sequel of papers, we have theoretically analyzed the RDTC space for the compression of densely sampled image-based scene representations. In this second part, we consider practical RDTC optimization. We propose a modeling and encoding parameter selection procedure that allows us to adapt the compression to scenario-specific properties. The impact of client side caching is considered and evaluated using an experimental testbed. Our results show a significant reduction of the user perceived delay, memory consumption or required minimum channel and storage bitrate for RDTC optimized streams compared to classical RD optimized or independently encoded scene representations.

Effectiveness of caching in a distributed digital library system

Today independent publishers are offering digital libraries with fulltext archives. In an attempt to provide a single user-interface to a large set of archives, the studied Article-Database-Service offers a consolidated interface to a geographically distributed set of archives. While this approach offers a tremendous functional advantage to a user, the fulltext download delays caused by the network and queuing in servers make the user-perceived interactive performance poor. This paper studies how effective caching of articles at the client level can be achieved as well as at intermediate points as manifested by gateways that implement the interfaces to the many fulltext archives. A central research question in this approach is: What is the nature of locality in the user access stream to such a digital library? Based on access logs that drive the simulations, it is shown that client-side caching can result in a 20% hit rate. Even at the gateway level temporal locality is observable, but published replacement algorithms are unable to exploit this temporal locality. Additionally, spatial locality can be exploited by considering loading into cache all articles in an issue, volume, or journal, if a single article is accessed. But our experiments showed that improvement introduced a lot of overhead. Finally, it is shown that the reason for this cache behavior is the long time distance between re-accesses, which makes caching quite unfeasible.

COPACC: An Architecture of Cooperative Proxy-Client Caching System for On-Demand Media Streaming

Proxy caching is a key technique to reduce transmission cost for on-demand multimedia streaming. The effectiveness of current caching schemes, however, is limited by the insufficient storage space and weak cooperation among proxies and their clients, particularly considering the high bandwidth demands from media objects. In this paper, we propose COPACC, a cooperative proxy-and-client caching system that addresses the above deficiencies. This innovative approach combines the advantages of both proxy caching and peer-to-peer client communications. It leverages the client-side caching to amplify the aggregated cache space and rely on dedicated proxies to effectively coordinate the communications. We propose a comprehensive suite of distributed protocols to facilitate the interactions among different network entities in COPACC. It also realizes a smart and cost-effective cache indexing, searching, and verifying scheme. Furthermore, we develop an efficient cache allocation algorithm for distributing video segments among the proxies and clients. The algorithm not only minimizes the aggregated transmission cost of the whole system, but also accommodates heterogeneous computation and storage constraints of proxies and clients. We have extensively evaluated the performance of COPACC under various network and end-system configurations. The results demonstrate that it achieves remarkably lower transmission cost as compared to pure proxy-based caching with limited storage space. On the other hand, it is much more robust than a pure peer-to-peer communication system in the presence of node failures. Meanwhile, its computation and control overheads are both kept in low levels

Client-side caching for nearest neighbor queries

The Voronoi diagram (VD) is the most suitable mechanism to find the nearest neighbor (NN) for mobile clients. In NN query processing, it is important to reduce the query response time, since a late query response may contain out-of-date information. In this paper, we study the issue of location dependent information services (LDISs) using a VD. To begin our study, we first introduce a broadcast-based spatial query processing methods designed to support NN query processing. In further sections, we introduce a generic method for location-dependent sequential prefetching and caching. The performance of this scheme is studied in different simulated environments. The core contribution of this research, resides in our analytical proof and experimental results.

Channel folding - an algorithm to improve efficiency of multicast video-on-demand systems

Recently a number of researchers have proposed and investigated new video-on-demand architectures that make use of network multicast to achieve vastly improved efficiency. Techniques such as batching, patching, periodic broadcasting, chaining, and piggybacking have been explored both in isolation and in combinations. This study investigates a new tool in the arsenal-channel folding, where aggressive client-side caching is used to merge clients from one multicast channel into the other. In particular, this channel folding algorithm is applied to a previously proposed unified video-on-demand (UVoD)) architecture to demonstrate and to quantify its impact on the performance and the tradeoff in a multicast video distribution architecture. This paper presents this channel folding algorithm in the context of UVoD) and derives a performance model to obtain the system latency, the near-optimal channel partition policy, and the client buffer requirement. Numerical results show that channel folding can double the capacity of UVoD) with a remarkably small overhead in the client buffer requirement.

Client-side caching for TLS

We propose two new mechanisms for caching handshake information on TLS clients. The "fast-track" mechanism provides a client-side cache of a server's public parameters and negotiated parameters in the course of an initial, enabling handshake. These parameters need not be resent on subsequent handshakes. Fast-track reduces both network traffic and the number of round trips, and requires no additional server state. These savings are most useful in high-latency environments such as wireless networks. The second mechanism, "client-side session caching," allows the server to store an encrypted version of the session information on a client, allowing a server to maintain a much larger number of active sessions in a given memory footprint. Our design is fully backward-compatible with TLS: extended clients can interoperate with servers unaware of our extensions and vice versa. We have implemented our fast-track proposal to demonstrate the resulting efficiency improvements.

Network-aware partial caching for Internet streaming media

The delivery of multimedia over the Internet is affected by adverse network conditions such as high packet loss rate and long delay. This paper aims at mitigating such effects by leveraging client-side caching proxies. We present a novel cache architecture and associated cache management algorithms that turn edge caches into accelerators of streaming media delivery. This architecture allows partial caching of media objects and joint delivery from caches and origin servers. Most importantly, the caching algorithms are both network-aware and stream-aware; they take into account the popularity of streaming media objects, their bit rate requirements, and the available bandwidth between clients and servers. Using Internet bandwidth models derived from proxy cache logs and measured over real Internet paths, we have conducted extensive simulations to evaluate the performance of various cache management algorithms. Our experiments demonstrate that network-aware caching algorithms can significantly reduce startup delay and improve stream quality. Our experiments also show that partial caching is particularly effective when bandwidth variability is not very high.

Design, performance analysis, and implementation of a super-scalar video-on-demand system

Despite the availability of video-on-demand (VoD) services in a number of cities around the world, large-scale deployment of VoD services in a metropolitan area is still economically impractical. This study presents a novel super-scalar architecture for building very large-scale and efficient VoD systems. The proposed architecture combines the use of static multicast, dynamic multicast, and intelligent client-side caching to vastly reduce server and network resource requirement. Moreover, in sharp contrast to conventional VoD systems where the system cost increases at least linearly with the system scale, the proposed architecture becomes more efficient as the system scales up and can ultimately be scaled up to serve any number of users while still keeping the startup latency short. This paper presents this new architecture, proposes methods to support interactive playback controls without the need for additional server or client resources, and derives an approximate performance model to relate the startup latency with other system parameters. The performance model is validated using simulation and the architecture is evaluated under various system settings. Lastly, a system implementation is presented and benchmarking results obtained to further verify the architecture, the performance model, and the simulation results.

Middleware Support for Transparent Client-Side Caching

This paper reflects on existing caching concepts in proxies and stubs of component technologies and lines out their advantages and deficiencies. A new concept is introduced that averts proliferation of component stubs on client side while transparently providing efficient caching of attributes that doesn't require any changes to existing code at all. Common object-oriented design facilities and code generation tools are leveraged to support seamless integration of these caching concepts into the development cycle.

Evaluation of Strong Consistency Web Caching Techniques

The growth of the World Wide Web (WWW or Web) and its increasing use in all types of business have created bottlenecks that lead to high network and server overload and, eventually, high client latency. Web Caching has become an important topic of research, in the hope that these problems can be addressed by appropriate caching techniques. Conventional wisdom holds that strong cache consistency, with (almost) transactional consistency guarantees, may neither be necessary for Web applications, nor suitable due to its high overhead. However, as business transactions on the Web become more popular, strong consistency will be increasingly necessary. Consequently, it is important to have a comprehensive understanding of the performance behavior of these protocols. The existing studies, unfortunately, are ad hoc and the results cannot be compared across different studies. In this paper we evaluate the performance of different categories of cache consistency algorithms using a standard benchmark: TPC-W, which is the Web commerce benchmark. Our experiments show that we could still enforce strong cache consistency without much overhead, and Invalidation, as an event-driven strong cache consistency algorithm, is most suitable for online e-business. We also evaluate the optimum deployment of caches and find that proxy-side cache has a 30–35% performance advantage over client-side cache with regard to system throughput.

EJVM: an economic Java run‐time environment for embedded devices

As network-enabled embedded devices and Java grow in their popularity, embedded system researchers start seeking ways to make these devices Java-enabled. However, it is a challenge to apply Java technology to these devices due to their shortage of resources. In this paper, we propose EJVM (Economic Java Virtual Machine), an economic way to run Java programs on network-enabled and resource-limited embedded devices. Espousing the architecture proposed by distributed JVM, we store all Java codes on the server to reduce the storage needs of the client devices. In addition, we use two novel techniques to reduce the client-side memory footprints: server-side class representation conversion and on-demand bytecode loading. Finally, we maintain client-side caches and provide performance evaluation on different caching policies. We implement EJVM by modifying a freely available JVM implementation, Kaffe. From the experiment results, we show that EJVM can reduce Java heap requirements by about 20–50% and achieve 90% of the original performance. Copyright © 2001 John Wiley & Sons, Ltd.

A predicate-based caching scheme for client-server database architectures

We propose a new client-side data-caching scheme for relational databases with a central server and multiple clients. Data are loaded into each client cache based on queries executed on the central database at the server. These queries are used to form predicates that describe the cache contents. A subsequent query at the client may be satisfied in its local cache if we can determine that the query result is entirely contained in the cache. This issue is called cache completeness. A separate issue, cache currency, deals with the effect on client caches of updates committed at the central database. We examine the various performance tradeoffs and optimization issues involved in addressing the questions of cache currency and completeness using predicate descriptions and suggest solutions that promote good dynamic behavior. Lower query-response times, reduced message traffic, higher server throughput, and better scalability are some of the expected benefits of our approach over commonly used relational server-side and object ID-based or page-based client-side caching.