Reliable Web Services Research Articles

Performance Analysis of an E-commerce Website Using Distributed Servers (Case Study: Ecommerce Bumdes Sarining Kukuh Winangun)

Digital transformation has significantly altered our interactions by leveraging the internet for fast global information exchange and collaboration. This shift impacts businesses, individuals, organizations, and governments by increasing the demand for fast, reliable web services. To meet these demands, many organizations are turning to distributed server infrastructures, which help handle large storage needs and avoid performance issues. This research focuses on creating a distributed web server system that uses Round-Robin load balancing to evenly distribute traffic and enhance performance. The Round-Robin algorithm’s simplicity and effectiveness in balancing loads, combined with the advantages of virtualization, such as cost efficiency, improved performance, and better resource management are central to this approach. Virtualization also offers improved scalability, accuracy, and security, further enhancing overall system efficiency and effectiveness in data centers. This research evaluates and contrasts the performance of websites utilizing distributed servers against those using single servers. The findings indicate that websites with distributed servers significantly outperform those with single servers. Specifically, distributed servers offer response times that are 5.8 times faster, achieve 2.2 times more successful responses, and transfer 2.1 times more data than single servers. Additionally, single servers experience a much higher rate of timeouts, with 14.2 times more occurrences compared to distributed servers.

An advancing method for web service reliability and scalability using ResNet convolution neural network optimized with Zebra Optimization Algorithm

AbstractWeb service reliability and scalability is an important mission that keeps web services running normally. Within web service, the web services invoked by users not only depend on the service itself, but also on web load condition. Due to the features of web dynamics, traditional reliability and scalability methods have become inappropriate; at the same time, the web condition parameter sparsity problem will cause inaccurate reliability prediction. To address these challenges, Web Service Reliability and Scalability Determination Using ResNet Convolutional Neural Network optimized with Zero Optimization Algorithm (WRS‐ResNetCNN‐ZOA) is proposed in this manuscript. Initially, the input data is collected from WSRec dataset. The ResNet convolutional neural network (ResNetCNN) with Business Process Execution Language (BPEL) specification is introduced to forecast the reliability and scalability of web service. The results are categorized as right and wrong based on ResNetCNN. The weight parameters of the ResNetCNN is optimized by Zebra Optimization Algorithm to improve accuracy of the prediction. The performance of the proposed method is examined under some performance metrics, like F‐measure, reliability, scalability, accuracy, sensitivity, specificity, and precision. The proposed technique attains 15.36%, 35.39%, 23.87%, 20.67% better reliability, 42.39%, 11.39%, 34.16%, 25.78% better accuracy when analyzed to the existing methods, like Web Reliability based on K‐clustering, (WRS‐KClustering), Web Reliability prediction based on AdaBoostM1 and J48 (WRS‐AdaM1‐J48), Web Reliability prediction based on Online service Reliability (WRS‐OPUN), and Web Reliability prediction based on Dynamic Bayesian Network (WRS‐DBNS), respectively.

Web service reliability and scalability determination using optimized depth wise separable convolutional neural network

AbstractWeb service composition (WSC), a distributed architecture, creates new services atop existing ones. Ensuring trust and assessing performance and dependability in online services coordination is essential. In this paper, “Web Service Reliability and Scalability Determination Using Depth Wise Separable Convolutional Neural Network” (WSRS‐DWSCNN) is proposed to assess the trustworthiness of online service compositions, particularly focusing on performance and dependability. This work addresses the need to predict the reliability and scalability of Business Process Execution Language (BPEL) composite web services. The proposed approach transforms the BPEL specification into a Depth Wise Separable Convolutional Neural Network (DWSCNN) and annotates it with probabilistic properties for prediction. The DWSCNN model classifies the outcomes as correct or incorrect, and to enhances the prediction of web service composition scalability and reliability, we optimize the DWSCNN's weight parameters using the Adolescent Identity Search Algorithm (AISA). The proposed technique is activated in Python and its efficacy is analyzed under some metrics, such as reliability, scalability, accuracy, sensitivity, specificity, precision, F‐measure. The proposed method provides 12.36%, 45.39%, and 25.97% better reliability, 41.39%, 11.39%, 34.16% better accuracy compared with existing methods like, Web service reliability prediction depending on machine learning (WSRS‐K‐means), reliability prediction method for multiple state cloud/edge‐basis network utilizing deep neural network (WSRS‐DNN‐BO), and improving reliability of mobile social cloud computing utilizing machine learning in content addressable network (WSRS‐CAN), respectively.

Blockchain Based Decentralized Web Hosting System

Abstract: In today’s digital era, the internet heavily depends on a centralized framework where powerful servers support content on well-known platforms such as Facebook and Twitter. Although this centralization is proficient in content delivery, it comes with significant drawbacks, including a single point of failure and vulnerability to censorship. The need for a decentralized web hosting structure is growing due to its promise of content accessibility regardless of a user’s geographical location, while still maintaining the speed and reliability of conventional web services. Currently, the internet’s structure is defined by centralization, introducing risks related to cyber-attacks and service disturbances. For example, even a brief disruption to a large platform like Facebook can leave millions without internet access. Additionally, large corporations and government bodies possess significant control over the internet, enabling them to alter and censor content. To confront these problems, it becomes essential to develop a decentralized web structure that is publicly owned. This study delves into the issues arising from the centralized internet and investigates potential solutions by utilizing blockchain technology to decentralize web structure, subsequently improving traditional web services and fortifying the internet’s robustness and accessibility

(Retracted) Internet of things assisted improved web service to optimize power-sharing for a gadget application

Smartphones have grown in prominence and utility due to their widespread use. Batteries have not reached their full potential due to a lack of innovation. The shortage of energy resources necessitates the necessity for efficient and effective management. To do so, smartphone users and manufacturers must be aware of the phone’s energy consumption characteristics. Each component’s energy consumption and operating circumstances must be understood. This article explains how the internet of things-based power-sharing (PS) technique contributes to a smartphone’s excessive use of power, along with suggestions for lowering consumption for each element. In the last several years, the internet, its intermittent wireless connection, and online services have become more prevalent, and the mobile environment has grown. When a web service is dependable, it lowers communication costs while also guaranteeing a fast response time. Web services may be made more reliable by adopting middleware architectures. This research article describes a middleware-based reliable service architecture that may be used to ensure reliable web service usage. The unique architecture makes verifying and tracking request execution easier due to connectivity restrictions and service unavailability. It considers most variables, such as the request and response sizes and time spent. As a result of this central processing unit (CPU) PS mechanism based on mobile devices, battery life and CPU performance should be improved.

A Two Phases Self-healing Framework for Service-oriented Systems

Service-Oriented Architectures (SOA) enable the automatic creation of business applications from independently developed and deployed Web services. As Web services are inherently a priori unknown, how to deliver reliable Web services compositions is a significant and challenging problem. Services involved in an SOA often do not operate under a single processing environment and need to communicate using different protocols over a network. Under such conditions, designing a fault management system that is both efficient and extensible is a challenging task. In this article, we propose SFSS, a self-healing framework for SOA fault management. SFSS is predicting, identifying, and solving faults in SOAs. In SFSS, we identified a set of high-level exception handling strategies based on the QoS performances of different component services and the preferences articled by the service consumers. Multiple recovery plans are generated and evaluated according to the performance of the selected component services, and then we execute the best recovery plan. We assess the overall user dependence (i.e., the service is independent of other services) using the generated plan and the available invocation information of the component services. Due to the experiment results, the given technique enhances the service selection quality by choosing the services that have the highest score and betters the overall system performance. The experiment results indicate the applicability of SFSS and show improved performance in comparison to similar approaches.

A Correct-by-Construction Model for Verifying Transactional Composite Services Configuration

Reusability is a central concept of Web services as it allows for the construction of composite Web services at a lower cost/effort. Web services offer diverse functional capabilities (e.g., ticket purchase, hotel booking) and inherent transactional properties. However, due to the lack of an explicit and formal description of these functional and transactional perspectives, the correctness of the transactional reliability and functional properties cannot be verified. The composite Web service reliability is computed using a set of transactional requirements defined by designers throughout the Accepted Termination States (ATS) concept. The main objective of this article is to introduce a formal model of the Web service configuration and its correctness requirements that permit to ensure the correct Web service execution from functional and transactional points of view. For that purpose, we developed a Correct Configuration Model for Transactional Composite Services (CCM4TCS) using the <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Event-B</small> method. This model is used to formally validate the consistency of composite Web service configuration’s properties and requirements. It allows also to check the correctness of ATS constraints that we use as reliability parameters. The correctness and the validation of our model are ensured by discharging proof obligations and by animating the specification using the ProB model-checker.

Web service reliability prediction based on machine learning

Web service reliability is an important mission that keeps web services running normally. Within web service, the web services invoked by users not only depend on the service itself, but also on web load condition (such as latency). Due to the features of web dynamics, traditional reliability methods have become inappropriate; at the same time, the web condition parameter sparsity problem will cause inaccurate reliability prediction. To address these new challenges, in this paper, we propose a new web service reliability prediction method based on machine learning considering user, web service and web condition. First we solve the web condition parameter sparsity problem, then we use the k-means clustering method to aggregate past invocation data, incorporate user, service, and web condition parameters to build a reliability feedback matrix, at last we predict web service reliability by considering specific web condition environments. The experiment shows that our machine learning method is able to solve the data sparsity problem and improve accurate web service reliability prediction, and we discuss how data sparsity and the number of feedback clusters to affect web service reliability prediction.

RAMWS: Reliable approach using middleware and WebSockets in mobile cloud computing

Abstract The widespread usage of mobile applications with the limited resources of mobile devices pushed towards the investment in Mobile Cloud Computing (MCC). In MCC, web services are available on the cloud server and are invoked by mobile applications whenever and wherever needed via a hybrid wired and wireless networks. One of the most important issues in the mobile experience is the web service request Time-out problem. This problem is tightly coupled with the increase in the service response size, database query time, and the required computations on the server, which occurs because of the increased application usage. This paper proposes a Reliable Approach using Middleware and WebSockets (RAMWS) that overcomes the Time-out problem and achieves reliable web service consumption. The enhanced architecture is a hybrid between the middleware approach and the WebSocket open connection communication protocol. The RAMWS reduces the network usage time up to 7 times better than the direct-cloud approach (Invoking the cloud service directly from the mobile device), by using the shortest time response from two expected responses, and accordingly, enhances the mobile experience.

Web service composition on IoT reliability test based on cross entropy

AbstractWeb service has developed the managed IoT application to let connected devices easily and securely interact with cloud applications and other devices. As an important factor for web service, the reliability of web services refers to the probability of web service running success. For modeling web service composition, we should abstract the process of web service composition. Due to the diversity and complexity of web service composition, it is unlikely to do exhaustive testing. In order to improve the quality of web service composition test cases and find out which path leads to the greatest probability of service combination failure, heuristic test case generation method is adopted to obtain the optimal test path. First, the web service composition test is abstracted into the MDP model. The QoS of the web service composition is taken as the software test optimization goal, and the cross‐entropy strategy is used to optimize the test case. The experimental results show that the test profile given by the cross‐strategy is better than the random test strategy. Detect and exclude the same number of software defects. Cross‐entropy strategy can significantly reduce the number of test cases, reduce test costs, and improve defect detection efficiency.

Prediction of web services reliability based on decision tree classification method

With the development of the service-oriented computing (SOC), web service has an important and popular solution for the design of the application system to various enterprises. Nowadays, the numerous web services are prov... | Find, read and cite all the research you need on Tech Science Press

Web Services Failures and Recovery Strategies: A Review

Objectives: Due to heterogeneity, cross-boundary integration, and deployment over the Internet, Web services are highly vulnerable to a wide variety of failures. This study provides an overview of different types of failures, and recovery strategies for Web services. Method/findings: To conduct this study, we have reviewed several novel research studies to provide a precise and all-in-one summary of different types of failures and possible recovery solutions for Web services. The study reveals that, a clear understanding of different failures-types and possible recovery solutions will help to develop services which are highly reliable and dependable. Applications: Highly reliable and dependable Web services are the key focus of all sensitive and mission-critical applications like navigating systems in aircrafts, nuclear reactor systems, robotics, and so on.Keywords: Web Services, Failures, Recovery Strategies, Fault-tolerance

Adaptive and Optimized Meta-Heuristic Framework for Establishing QoS and Transaction Properties-based Dynamic Web Service Composition

The dynamic web service composition based on QoS and transactional properties is considered to be the most important challenging research issues. Most of the works explored in the area of dynamic web service composition have mainly focused on some specific QoS parameters, which avoid potential factors from utilization. Further, the transaction properties also play a vital role in handling uncertainty which introduces most vital functionalities into the reactive environment. In this paper, an Adaptive and Optimized Meta-Heuristic Framework (AOMHF) is proposed for establishing dynamic web service composition based on QoS and transaction properties. This proposed AOMHF framework considered the user preferences and unpredictable service QoS for achieving reliable dynamic web service composition. This proposed AOMHF framework is developed as a dual staged web service composition scheme which incorporates the merits of monitoring mechanism which improves the possibility of improving and guaranteeing reliability and availability under reliable web service composition.

Making Linked Data more reliable with a failover server system: a case study with seismological data at INGV.

Since the introduction of the Linked Data concept more than a decade ago, today the way scientists use and share their research data is increasingly changing. The growing availability of big amounts of Open Research Data is challenging the old-fashioned habit of replicating large datasets locally prior to their processing, and the new Open Science paradigm tries to update the way researchers works by pushing them into solutions enabling a quicker, lightweight and more efficient circulation of research results. Granting access to its data resources is an activity taken very seriously at INGV, moreover as it is head of two important European Research Infrastructure Consortium (ERIC), namely the European Multidisciplinary Seafloor and water-column Observatory (EMSO), and the European Plate Observing System (EPOS). As more and more data are becoming accessible via web services, an increasing number of researchers are starting to include their use in their workflows, thus, heavily relying on their correct and continuous operational functioning, in other words, in their service continuity. Experimenting solutions for enhancing the reliability of web services is at the core of the present work. We propose here a solution that is able to guarantee the functioning of a service in case of an IT infrastructure fail, a mechanism that is able to automatically switch to a secondary server located in another network. The solution is made possible thanks to a collaboration with GARR, the ultra-broadband network dedicated to the Public Italian Research, and is able to deal with network problems, server hardware problems, as well as service level problems.

Novel Technique for Atomic Web Services Reliability for Service Oriented Architecture

To address the challenges in prediction of atomic web service reliability for the Service Oriented Architecture (SOA), in this paper we proposed the clustering based approach called the Dynamic Clustering (DCLUS). The DCLUS is based on recent work reported called CLUS. The novelty in DCLUS compared to CLUS technique is use of dynamic width clustering technique. In CLUS, k-means clustering method exploited for the users and services clustering. However, due to the limitations of k-means, the dynamic width clustering is proposed to optimize the performance of clustering and hence the prediction accuracy. The proposed DCLUS model for the reliability prediction of atomic web services that estimates the reliability for an ongoing service invocation based on the data assembled from previous invocations. With the aim to improve the accuracy of the current state-of-the-art prediction models, we incorporate user–, service– and environment–specific parameters of the invocation context

Your neighbors are misunderstood: On modeling accurate similarity driven by data range to collaborative web service QoS prediction

Quality of service (QoS) is a set of non-functional attributes of Web services for differentiating enriched Web services with same or similar functionality. Predicting the unknown QoS of Web services for service users is often required for any QoS based service computing because QoS plays a fundamental role in reliable Web service recommendation, composition and selection. Existing collaborative filtering based QoS prediction methods suffer from a serious acclimatization issue caused by the difference of QoS data range, which dramatically degrades the prediction accuracy and even impedes its adaptability. The fact that Web service QoS data exhibit large service effect with different data ranges, is verified on public real-world datasets. In this study, we aim to tackle the problem of QoS prediction while considering the influences of QoS data range in the context of collaborative filtering. In particular, a simple yet effective similarity model called JacMinMax, which is driven by QoS data range, is designed. Furthermore, two neighborhood selection strategies using JacMinMax are proposed, and the obtained neighbors are systemically integrated into neighborhood- and model-based methods for collaborative QoS predictions. Experimental results show that the proposed method efficiently alleviates the influence of the concerned QoS data ranges, and performs better than many state-of-the-art approaches with respect to accuracy.

Система каталогизации и мониторинга территориально распределенных вычислительных узлов в среде WPS сервисов для решения геологических задач

The study describes an approach for heterogeneous web services cataloguing of geographically distributed computing nodes in the computational and analytical geological environment. The approach of creation of web services monitoring system is proposed. In this study the approach for web services catalogue organization based on SOAP (Simple Object Access Protocol) protocol, with use of UDDI (Universal Description Discovery and Integration) registries is reviewed. The scheme for heterogeneous web services description with an ability of further creation of catalogue is proposed. The catalogue includes functions for searching and receiving of metainformation about every web service in it. The study also describes an approach for computational and analytical geological environment creation. A number of web services for heterogeneous data processing used in geological research is described. The approaches for organization of cataloguing and web services monitoring provide a higher level of reliability of computational and analytical geological environment. They provide an information about web service reliability within environment.

Grenade-Cauchy operator integrated artificial bee colony optimisation for QoS-based reliable web service composition

Majority of the dynamic web service composition techniques in the literature addresses the problem of web service composition through the perspectives of quality of service (QoS) or transactional characteristics. Grenade with Cauchy operator integrated artificial bee colony optimisation (GCO-ABC) algorithm is proposed as an attempt of developing a dynamic service composition involved computation methodology that depends on the integration of transactional and QoS-based properties of web services. GCO-ABC algorithm is applied on the work flow sequence of web service composition developed as a constrained directed acyclic graph for determining the near optimal solution with efficacy and it is also predominant in comparison to the traditional ant colony optimisation algorithm (ACOM) and its variant improved ant colony optimisation algorithm (IACOM). The determined results investigated through empirical and simulation means infer that the proposed scheme is not only efficient but also capable of approximating the searching solutions into a much more optimal candidate solution.

Distributed Testing System for Web Service Based on Crowdsourcing

To appropriately realize the performance of a web service, it is essential to give it a comprehensive testing. Although an elastic test could be guaranteed in traditional cloud testing systems, the geographical test that supports real user behavior simulation remains a problem. In this paper, we propose a testing system based on a crowdsourcing model to carry out the distributed test on a target web server automatically. The proposed crowdsourcing-based testing system (CTS) provides a reliable testing model to simulate real user web browsing behaviors with the help of web browsers scattered all around the world. In order to make the entire test process the same as the real situation, two test modes are proposed to simulate real user activity. By evaluating every single resource of web service automatically, a tester can not only find out internal problems but also understand the performance of the web service. In addition, the complete geographical test is available with the performance measurements coming from different regions in the world. Several experiments are performed to validate the functionality and usability of CTS. It demonstrates that CTS is a complete and reliable web service testing system, which provides unique functions and satisfies different requirements.

Some Aspects of Reliability Evaluation of Multi Service Multi-Functional SOAP Based Web Services

Reliability evaluation of multi service multi-functional SOAP based web services for high load of users is important from the perspective of operational quality of the service, users and developers. In this article, the authors have emphasized on developing a novel methodology for evaluating the reliability of web service for high load. A prototype research medical web service is considered to predict the reliability of the service by using this methodology. The authors called the service as PMedWS (Prototype Medical Web Service). They performed stress and load testing on the web service using Mercury Load Runner to study the reliability aspects against massive users. The experimental results and the statistical analysis demonstrate the applicability and effectiveness of our methodology.