A Scheduling Model for Soft Real-time Component System

With the proliferation of Web services as a business solution to enterprise application integration, ranking and selecting the best Web services among the providers become an important factor in the success of the business solution. Quality of service (QoS) determines the quality and usability of a service including its price, performance, reliability, integrity, accessibility, availability, interoperability, and security. Given a set of QoS attributes from a variety of sources, it is a challenge to sort through all of them and be able to get the best services that meet QoS requirement. In this paper, we describe a novel method by which Web services can be ranked and selected automatically based on a number of observed QoS parameters and feedback responses learned from prior knowledge. This new approach treats the observed Web services QoS attributes and target Web services relationship, represented by a matrix, as a statistical problem. Using singular value decomposition (SVD) technique, and an user assisted weighting system, implicit higher order correlations among Web services and their associated QoS attributes are extracted and used to estimate the selection of recommended Web services.

This paper derives the power spectral density (PSD) of the output generated by a discrete-time feedback control system in which feedback measurements are dropped with a known probability, /spl epsi/. This class of systems is a model for soft real-time control systems in which the feedback path is implemented on a nondeterministic computer network. The PSD computed in this paper is a function of the dropout probability. The dropout probability is taken as a measure of the network quality of service (QoS). Based on the derived PSD, the power semi-norm of the output is predicted. So a direct way of linking control system performance(as measured by the power semi-norm of the output) to the network's QoS (as measured by the dropout probability) is provided.

With the increasing number of Web services, the Semantic Web research community is moving toward enhancing procedures so that clients may effectively discover appropriate Web services that maximally satisfy not only functional but also non-functional requirements. Using purely syntactic approaches to discover Web services has limited efficiency. Therefore, semantic matchmaking registries can play an important role in providing better results. However, most of the semantic registries make decisions based on only functional requirements. Due to the proliferation of Web services that have similar functionality, there is a need to further filter Web services according to Quality of Service (QoS) specifications. This work introduces a rich QoS ontology inspired from the World Wide Web Consortium that defines relationships among QoS attributes. The QoS attributes defined here are mainly used to define network related characteristics. However, the work can be extended by defining QoS ontologies for other domains. Additionally, we extend the test collection OWLS-TC according to the QoS ontology. The extension is intended to integrate quantified values for QoS attributes into Web service descriptions. A matchmaking algorithm based on similarity measurements is presented. Moreover, deterministic and adaptive parameter control techniques are introduced to guide the requester, when needed, to adjust QoS specifications so better similarity can be achieved. Parameter control algorithms integrate Pellet, an OWL reasoner, to reason about dependencies among QoS concepts in the QoS ontology.

A web service is an interface of the software component that can be accessed by standard Internet protocols. The web service technology enables an application to application communication and interoperability. The increasing number of web service providers throughout the globe have produced numerous web services providing the same or similar functionality. This necessitates the use of tools and techniques to search the suitable services available over the Web. UDDI (universal description, discovery and integration) is the first initiative to find the suitable web services based on the requester's functional demands. However, the requester's requirements may also include non-functional aspects like quality of service (QoS). In this paper, the authors define a QoS model for QoS aware and business driven web service publishing and selection. The authors propose a QoS requirement format for the requesters, to specify their complex demands on QoS for the web service selection. The authors define a tree structure called quality constraint tree (QCT) to represent the requester's variety of requirements on QoS properties having varied preferences. The paper proposes a QoS broker based architecture for web service selection, which facilitates the requesters to specify their QoS requirements to select qualitatively optimal web service. A web service selection algorithm is presented, which ranks the functionally similar web services based on the degree of satisfaction of the requester's QoS requirements and preferences. The paper defines web service provider qualities to distinguish qualitatively competitive web services. The paper also presents the modelling and selection mechanism for the requester's alternative constraints defined on the QoS. The authors implement the QoS broker based system to prove the correctness of the proposed web service selection mechanism.

Normally web services are classified by the quality of services; however, the term quality is not absolute and defined relatively. The quality of web services is measured or derived using various parameters like reliability, scalability, flexibility, and availability. The limitation of the methods employing these parameters is that sometimes they are producing similar web services in recommendation lists. To address this research problem, the novel improved clustering-based web service recommendation method is proposed in this paper. This approach is mainly dealing with producing diversity in the results of web service recommendations. In this method, functional interest, quality of service (QoS) preference, and diversity features are combined to produce a unique recommendation list of web services to end-users. To produce the unique recommendation results, we propose a varied web service classification order that is clustering-based on web services’ functional relevance such as non-useful pertinence, recorded client intrigue importance, and potential client intrigue significance. Additionally, to further improve the performance of this approach, we designed web service graph construction, an algorithm of various widths clustering. This approach serves to enhance the exceptional quality, that is, the accuracy of web service recommendation outcomes. The performance of this method was implemented and evaluated against existing systems for precision, and f-score performance metrics, using the research datasets.

Utility computing enables the use of computational resources and services by consumers with service obligations and expectations defined in Service Level Agreements (SLAs). Parallel applications and workflows can be executed across multiple sites to benefit from access to a wide range of resources and to respond to dynamic runtime requirements. A utility computing provider has the difficult role of ensuring that all current SLAs are provisioned, while concurrently forming new SLAs and providing multiple services to numerous consumers. Scheduling to satisfy SLAs can result in a low return from a provider's resources due to trading off Quality of Service (QoS) guarantees against utilisation. One technique is to employ advance reservations so that an SLA aware scheduler can properly manage and schedule its resources. To improve system utilisation we exploit the principle that some consumers will be more flexible than others in relation to the starting or completion time, and that we can juggle the execution schedule right up until each execution starts. In this paper we present a QoS scheduler that uses SLAs to efficiently schedule advance reservations for computation services based on their flexibility. In our SLA model users can reduce or increase the flexibility of their QoS requirements over time according to their needs and resource provider policies. We introduce our scheduling algorithms, and show experimentally that it is possible to use flexible advance reservations to meet specified QoS while improving resource utilisation.

How to guarantee user's QoS (Quality of Service) demands becomes increasingly important in service-oriented grid environment. Current research on grid resource advance reservation, a well-known and effective mechanism to guarantee QoS, forces on proposing theoretic architecture to support advance reservation. Detailed research on advance reservation is scarce. For that, SNAP (Service Negotiation and Acquisition Protocol) is extended to support QoS description in fine granularity and new calculation method of QoS deviation distance is proposed. Then, advance reservation state switching is analyzed and QoS deviation distance based negotiation algorithm is addressed. Preliminary results show that proposed negotiation algorithm that considers QoS deviation distance can produce remarkable improvement in user satisfaction and resource utilization.

With the rapid growth of functionally identical web services, Quality of Service (QoS) plays vital role for deciding the most suitable services for consumers. Although, QoS for web services has gained extensive attention in the literature, most of the existing efforts are unable to consider the multiperspective QoS of web services. Unlike conventional software paradigms, web services are provided, developed and used by different users such as provider, consumer and broker. As a result, QoS requirements vary from user to user. Existing researches are unable to provide standard solution, which can deal with what service providers, consumers and broker should expose in service description as QoS parameters. Therefore, in this book chapter, a multiperspective PCB-QoS classification of non-functional parameters along with new QoS parameters, i.e. access rate and Overall Aggregated Effective Quality of Service (OAEQoS) is presented. Due to the extensible nature of PCB-QoS classification, it can be extended to accommodate more number of QoS parameters. This QoS classification is based on the idea of partitioning the generic QoS parameters according to multi-user’s perspective. An Average Real Value Sum Method (ARSM) based on default priority constraints is also proposed for ranking of web services that uses the presented QoS classification. With the help of proposed approach, the user can specify the service requirements without taking the hurdle of specifying the weights for each QoS parameter during web service operations. It also prevents the services from malicious service provider to publish the incorrect and inaccurate QoS information. Experimental evaluation shows the effectiveness of proposed approach over the existing approach.

Background/Objectives: The primary objective of the study is to evaluate the performance of Composite Web Service based on the parameters relating to Quality of Service by using statistical methodologies. Methods/Statistical Analysis: By using Web Service Crawler Engine we have collected data on eleven parameters of interest from a more number of Web Services. Among the eleven parameters we have selected six parameters of importance using the sampling of thirty Web Services. We have constructed the weight matrix for the parameters. By using Web Services Relevancy Function ranking has been done for three different scenarios. Using Spearman's Rank Correlation Coefficient we have compared the scenarios. Findings: The graphical representation of the three scenarios shows varying pattern. The Spearman's Rank Correlation coefficient of the Web Services Relevancy Function varied widely among the sampled Web Services. F-Test revealed that there are no significant differences in respect of weights of Quality of Web Services for three different scenarios. We concluded that weight assigned for Quality of Service parameters in Scenario I is preferred than the scenarios II and III through the evaluations. Application/Improvements: The technique developed in this research paper can be applied for the comparison of Web Services during discovery to enhance the performance of the Composite Web Service.

The development, registration, discovery, and invocation of quality Web services are vital for the successful implementation of applications using Web services. Considerable research focuses on quality for Web services. Unfortunately, current research on Quality of Service (QoS) for Web services is concentrated on service users and the implementation stage. This research highlights the importance of incorporating QoS at the design and development stages; the authors propose the introduction of QoS at the same time as functional requirements. However, Web Service Description Language (WSDL) describes the functional elements of a Web service, and QoS is significant for this description. Therefore, the authors propose an extension to the WSDL through a generic QoS metamodel, incorporating QoS specifications into the functionalities. This paper begins by defining the required QoS specifications for the development of quality Web services and explores the potential of the Unified Modeling Language as a technique and notation to specify QoS. To properly integrate QoS in the design, the authors propose extensions to the existing UML QoS profile. The paper concludes with the evaluation of the proposed framework and summarises its advantages.

This paper studies QoS (quality of service) management functions that are needed in 3/sup rd/ generation packet data networks. The current architecture of the UMTS (Universal Mobile Telecommunication System) is described. The UMTS QoS architecture and QoS model are presented with important QoS parameters. The QoS management functionality is analysed against the presented QoS architecture and QoS model. The paper presents the functionality that needs to be implemented, to UMTS packet data networks, to be able to provide QoS for end-users. The paper concludes with the description of functions and their locations to be able to provide QoS efficiently in UMTS.

How to assure Quality of Service (QoS) of the third-party services is very important for the SOA. Effective monitoring technique towards QoS, which is an important measurement for third-party service quality, is necessary to ensure quality of Web service. Current monitoring approaches do not consider the influences of environment factors such as the position of server, user usage, and the load at runtime. Ignoring these influences, which do exist among the monitoring process, may cause existing monitoring approaches producing unpredictable monitoring results. In order to overcome this limitation, this paper proposes a novel Web Service QoS (WS-Qos) monitoring approach sensitive to environmental factors called weighted Bayesian Runtime Monitor (wBSRM) based on weighted naïve Bayesian classifiers and Term Frequency-Inverse Document Frequency (TF-IDF) algorithm. wBSRM constructs weighted naïve Bayesian classifier by learning a part of samples to classify the monitoring results. The results meeting QoS standard are classified as [Formula: see text] and the one that does not meet is classified as [Formula: see text]. Classifier can also output ratio between posterior probability of [Formula: see text] and [Formula: see text], and consequently the analysis can lead to three monitoring results including [Formula: see text], [Formula: see text] or inconclusive. A set of dedicated experiments are conducted to validate wBSRM. The experiments are based on a public dataset and a simulated dataset under the given standard. The experimental results demonstrate that wBSRM is better than previous approaches.

Web service composition (WSC) is the task of combining a chain of connected single services together to create a more complex and value-added composite service. Quality of service (QoS) has been mostly applied to represent nonfunctional properties of web services and differentiate those with the same functionality. Many research has been done on QoS-aware service composition, as it significantly affects the quality of a composite service. However, existing methods are restricted to predefined workflows, which can incur a couple of limitations, including the lack of guarantee for the optimality on overall QoS and for the completeness of finding a composite service solution. In this paper, instead of predefining a workflow model for service composition, we propose a novel planning-based approach that can automatically convert a QoS-aware composition task to a planning problem with temporal and numerical features. Furthermore, we use state-of-the-art planners, including an existing one and a self-developed one, to handle complex temporal planning problems with logical reasoning and numerical optimization. Our approach can find a composite service graph with the optimal overall QoS value while satisfying multiple global QoS constraints. We implement a prototype system and conduct extensive experiments on large web service repositories. The experimental results show that our proposed approach largely outperforms existing ones in terms of solution quality and is efficient enough for practical deployment.

SUMMARYWireless mesh networks (WMNs) as community‐ and city‐wide type networks are required to extend their capability to offer real‐time multimedia services. While technologies exist to support quality of service (QoS) at node level, we propose here a network‐wide multi‐step solution to manage and offer QoS across a WMN. From a provider perspective, the provisioning and fulfillment of QoS‐based services fall under the realms of service management, network and traffic engineering functions. We describe the relevant functions required to design, implement and operate a WMN for providing a qualitative QoS to end‐users. Our proposed solution considers network planning aspects, including node placement, node clustering and frequency assignments, route discovery between ingress–egress points and appropriate QoS provisioning across the network. Route‐level QoS provisioning is defined as the process of allocating resources to the nodes along the identified routes to meet a priori known aggregated traffic demands in order to satisfy the QoS requirements for different types of application. Simulation and experimental tests are conducted to validate the correct behavior of processes/algorithms and to access the solution in achieving QoS for aggregate user traffic. Copyright © 2012 John Wiley & Sons, Ltd.

A probabilistic approach to modeling and estimating the QoS of web-services-based workflows