Search results

Internet users and Web-based applications continue to grow every day. The response time on a Web application really determines the convenience of its users. Caching Web content is one strategy that can be used to speed up response time. This strategy is divided into three main techniques, namely, Web caching, Web prefetching and application-level caching. The purpose of this paper is to put forward a literature review of caching strategy research that can be used in Web-based applications.

The methods used in this paper were as follows: determined the review method, conducted a review process, pros and cons analysis and explained conclusions. The review method is carried out by searching literature from leading journals and conferences. The first search process starts by determining keywords related to caching strategies. To limit the latest literature in accordance with current developments in website technology, search results are limited to the past 10 years, in English only and related to computer science only.

Note in advance that Web caching and Web prefetching are slightly overlapping techniques because they have the same goal of reducing latency on the user’s side. But actually, the two techniques are motivated by different basic mechanisms. Web caching uses the basic mechanism of cache replacement or the algorithm to change cache objects in memory when the cache capacity is full, whereas Web prefetching uses the basic mechanism of predicting cache objects that can be accessed in the future. This paper also contributes practical guidelines for choosing the appropriate caching strategy for Web-based applications.

This paper conducts a state-of-the art review of caching strategies that can be used in Web applications. Exclusively, this paper presents taxonomy, pros and cons of selected research and discusses data sets that are often used in caching strategy research. This paper also provides another contribution, namely, practical instructions for Web developers to decide the caching strategy.

This paper investigates query processing in MANETs. Cache techniques and multi‐join database operations are studied. For data caching, a group‐caching strategy is proposed. Using the cache and the index of the cached data, queries can be processed at a single node or within the group containing this single node. For multi‐join, a cost evaluation model and a query plan generation algorithm are presented. Query cost is evaluated based on the parameters including the size of the transmitted data, the transmission distance and the query cost at each single node. According to the evaluations, the nodes on which the query should be executed and the join order are determined. Theoretical analysis and experiment results show that the proposed group‐caching based query processing and the cost based join strategy are efficient in MANETs. It is suitable for the mobility, the disconnection and the multi‐hop features of MANETs. The communication cost between nodes is reduced and the efficiency of the query is improved greatly.

Caching is commonly used to improve the performance of mobile computers. Due to the limitations of wireless networks (e.g. low bandwidth, intermittent connectivity), ensuring the consistency of cached data becomes a difficult issue. Existing research have shown that broadcast‐based cache invalidation techniques can effectively maintain cache consistency for mobile applications. However, most existing performance analysis of cache invalidation algorithms were carried out through simulation. Therefore, an analytical study is important to provide a deeper understanding of broadcast‐based invalidation techniques. In this paper, we present detailed analytical models of the major existing cache invalidation schemes. The models provide a basis to highlight the strengths and weaknesses of the different schemes and facilitate further investigation into cache invalidation for mobile environments. Extensive simulation has also been performed, and verifies the accuracy of the models developed.

Proposes how a global Hypermedia system could evolve from the “Hyper‐G” system, currently being developed at Graz University. Overviews the development of Internet from post‐war visionary speculation to present. Explains some limitations of the current architecture (World Wide Web, Gopher, WAIS). Presents in detail the architecture of a massively distributed hypermedia system. Explains how the proposed system would be much faster, overcoming such problems as documents being oriented by location rather than by subject. Suggests possible applications.

Recently the advances in wireless communication technology and the popularity of portable computers have rendered mobile computing environments from which mobile users with battery‐operated palmtops can access the information via wireless channels, without space and time restriction. In mobile computing environments, mobile users cache the data items to use the bandwidth efficiently and improve the response time of mobile transactions. If the data items cached in mobile users are updated at the server, the server broadcasts an invalidation report for maintaining the cache consistency of mobile users. However, this method has an obstacle that does not guarantee the serializable execution of mobile transactions. The purpose of this paper is to propose the four types of reports for mobile transaction (FTR‐MT) method for ensuring the serializable execution of mobile transactions.

The paper describes the FTR‐MT method, which is composed of four types of algorithms, e.g. group report composition algorithm, immediate commit decision algorithm, cache consistency algorithm, and disconnection cache consistency algorithm. FTR‐MT method for improving the response time of mobile transactions makes a commit decision by using the four types of reports.

With the FTR‐MT method, mobile users can make a commit decision by using the four types of reports. The response time of mobile transactions can be reduced. Furthermore, the FTR‐MT method can improve the cache efficiency in the case that the disconnection of mobile users is longer than the broadcast interval of the window report.

This paper proposes a new method for guaranteeing the serializable execution of mobile transactions, called FTR‐MT, using four types of reports. Also, it can prevent the entire cache dropping, even though the disconnection of a mobile host is longer than the broadcast interval of a window report. Through the analytical model, this method is felt to be superior to other methods, in terms of the average response time and the commit rate of mobile transactions, and bandwidth usage.

Information-centric networking (ICN) is an innovative paradigm for the future internet architecture. This paper aims to provide a view on how academic video lectures can exploit the ICN paradigm. It discusses the design of academic video lectures over named data networking (NDN) (an ICN architecture) and speculates their future development. To the best of author’s knowledge, a similar study has not been presented.

The paper is a visionary essay that introduces the background, elaborates the basic concepts and presents the author’s views and insights into academic video lectures that exploit the latest development of NDN approach and its applications.

The ICN paradigm is closely related to the levels of automation and large-scale uptake of multimedia applications that provide video lectures. Academic video lectures over NDN have: improved efficiency, better scalability with respect to information/bandwidth demand and better robustness in challenging communication scenarios. A framework of academic video lectures over NDN must take into account various key issues such as naming (name resolution), optimized routing, resource control, congestion control, security and privacy. The size of the network in which academic video lectures are distributed, the content location dynamics and the popularity of the stored video lectures will determine which routing scheme must be selected. If semantic information is included into academic video lectures, the network dynamically may assist video (streaming) lecture service by permitting the network to locate the proper version of the requested video lecture that can be better delivered to e-learners and/or select the appropriate network paths.

The paper helps researchers already working on video lectures in finding a direction for designing and deploying platforms that will provide content-centric academic video lectures.

The paper pioneers the investigation of academic video lecture distribution in ICN and presents an in-depth view to its potentials and research trends.

In the last decade, XML has become the de facto standard for data exchange in the world wide web (WWW). The positive benefits of data exchangeability to support system and software heterogeneity on application level and easy WWW integration make XML an ideal data format for many other application and network scenarios like wireless sensor networks (WSNs). Moreover, the usage of XML encourages using standardized techniques like SOAP to adapt the service‐oriented paradigm to sensor network engineering. Nevertheless, integrating XML usage in WSN data management is limited by the low hardware resources that require efficient XML data management strategies suitable to bridge the general resource gap. The purpose of this paper is to present two separate strategies on integrating XML data management in WSNs.

The paper presents two separate strategies on integrating XML data management in WSNs that have been implemented and are running on today's sensor node platforms. The paper shows how XML data can be processed and how XPath queries can be evaluated dynamically. In an extended evaluation, the performance of both strategies concerning the memory and energy efficiency are compared and both solutions are shown to have application domains fully applicable on today's sensor node products.

This work shows that dynamic XML data management and query evaluation is possible on sensor nodes with strict limitations in terms of memory, processing power and energy supply.

The paper presents an optimized stream‐based XML compression technique and shows how XML queries can be evaluated on compressed XML bit streams using generic pushdown automata. To the best of the authors' knowledge, this is the first complete approach on integrating dynamic XML data management into WSNs.

The purpose of this study is to introduce several metrics that enable universal and fine-grained characterization of arbitrary Linked Data repositories. Publicly accessible SPARQL endpoints contain vast amounts of knowledge from a large variety of domains. However, oftentimes these endpoints are not configured to process specific workloads as efficiently as possible. Assisting users in leveraging SPARQL endpoints requires insight into functional and non-functional properties of these knowledge bases.

This study presents comprehensive approaches for deriving these metrics. More specifically, the study utilizes concrete SPARQL queries to determine corresponding values. Furthermore, it validates and discusses the introduced metrics through extensive evaluation on real-world SPARQL endpoints.

The evaluation determined that endpoints exhibit different characteristics. While it comes as no surprise that latency and throughput are influenced by the network infrastructure, the costs for join operations depend on a number of factors that are not obvious to a data consumer. Moreover, as the author discusses mean, median and upper quartile values, it was found both endpoints behaving consistently as well as repositories offering varying levels of performance.

On the one hand, the contribution of the authors work lies in assisting data consumers in evaluation of the quality of service of publicly available SPARQL endpoints. On the other hand, the performance metrics introduced in this study can also be considered as additional input features for distributed query processing frameworks. Moreover, the author provides a universal means for discerning characteristics of different SPARQL endpoints without the need of (synthetic or real-world) query workloads.

Multipath routing holds a great potential to provide sufficient bandwidth to a plethora of applications in wireless sensor networks. In this paper, we consider the problem of interference that can significantly affect the expected performances. We focus on the performance evaluation of the iterative paths discovery approach as opposed to the traditional concurrent multipath routing. Five different variants of multipath protocols are simulated and evaluated using different performance metrics. We mainly show that the iterative approach allows better performances when used jointly with an interference-aware metric or when an interference-zone marking strategy is employed. This latter appears to exhibit the best performances in terms of success ratio, achieved throughput, control messages overhead as well as energy consumption.

Big data challenges and opportunities on the Internet of Vehicles (IoV) have emerged as a transformative paradigm to change intelligent transportation systems. With the growth of data-driven applications and the advances in data analysis techniques, the potential for data-adaptive innovation in IoV applications becomes an outstanding development in future IoV. Therefore, this paper aims to focus on big data in IoV and to provide an analysis of the current state of research.

This review paper uses a systematic literature review methodology. It conducts a thorough search of academic databases to identify relevant scientific articles. By reviewing and analyzing the primary articles found in the big data in the IoV domain, 45 research articles from 2019 to 2023 were selected for detailed analysis.

This paper discovers the main applications, use cases and primary contexts considered for big data in IoV. Next, it documents challenges, opportunities, future research directions and open issues.

This paper is based on academic articles published from 2019 to 2023. Therefore, scientific outputs published before 2019 are omitted.

This paper provides a thorough analysis of big data in IoV and considers distinct research questions corresponding to big data challenges and opportunities in IoV. It also provides valuable insights for researchers and practitioners in evolving this field by examining the existing fields and future directions for big data in the IoV ecosystem.