Fruit fly optimization algorithm for network-aware web service composition in the cloud

Service Oriented Computing (SOC) provides a framework for the realization of loosely coupled service oriented applications. Web services are central to the concept of SOC. Currently, research into how web services can be composed to yield QoS optimal composite service has gathered significant attention. However, the number and spread of web services across the cloud data centers has increased, thereby increasing the impact of the network on composite service performance experienced by the user. Recently, QoS-based web service composition techniques focus on optimizing web service QoS attributes such as cost, response time, execution time, etc. In doing so, existing approaches do not separate QoS of the network from web service QoS during service composition. In this paper, we propose a network-aware service composition approach which separates QoS of the network from QoS of web services in the Cloud. Consequently, our approach searches for composite services that are not only QoS-optimal but also have optimal QoS of the network. Our approach consists of a network model which estimates the QoS of the network in the form of network latency between services on the cloud. It also consists of a service composition technique based on fruit fly optimization algorithm which leverages the network model to search for low latency compositions without compromising service QoS levels. The approach is discussed and the results of evaluation are presented. The results indicate that the proposed approach is competitive in finding QoS optimal and low latency solutions when compared to recent techniques

Discovering the best web service: A neural network-based solution

Differentiating between Web services that share similar functionalities is becoming a major challenge into the discovery of Web services. In this paper we propose a framework for enabling the efficient discovery of Web services using Artificial Neural Networks (ANN) best known for their generalization capabilities. The core of this framework is applying a novel neural network model to Web services to determine suitable Web services based on the notion of the Quality of Web Service (QWS). The main concept of QWS is to assess a Web service\u27s behaviour and ability to deliver the requested functionality. Through the aggregation of QWS for Web services, the neural network is capable of identifying those services that belong to a variety of class objects. The overall performance of the proposed method shows a 95% success rate for discovering Web services of interest. To test the robustness and effectiveness of the neural network algorithm, some of the QWS features were excluded from the training set and results showed a significant impact in the overall performance of the system. Hence, discovering Web services through a wide selection of quality attributes can considerably be influenced with the selection of QWS features used to provide an overall assessment of Web services. ©2009 IEEE

A trust and reputation model based on bayesian network for web services

Trust and reputation for web services emerges as an important research issue in web service selection. Current web service trust models either do not integrate different important sources of trust (subjective and objective for example), or do not focus on satisfying different user’s requirements about different quality of service (QoS) attributes such as performance, availability etc. In this paper, we propose a Bayesian network trust and reputation model for web services that can overcome such limitations by considering several factors when assessing web services’ trust: direct opinion from the truster, user rating (subjective view) and QoS monitoring information (objective view). Our comprehensive approach also addresses the problems of users’ preferences and multiple QoSbased trust by specifying different conditions for the Bayesian network and targets at building a reasonable credibility model for the raters of web services

Security for Grid Services

Grid computing is concerned with the sharing and coordinated use of diverse resources in distributed "virtual organizations." The dynamic and multi-institutional nature of these environments introduces challenging security issues that demand new technical approaches. In particular, one must deal with diverse local mechanisms, support dynamic creation of services, and enable dynamic creation of trust domains. We describe how these issues are addressed in two generations of the Globus Toolkit. First, we review the Globus Toolkit version 2 (GT2) approach; then, we describe new approaches developed to support the Globus Toolkit version 3 (GT3) implementation of the Open Grid Services Architecture, an initiative that is recasting Grid concepts within a service oriented framework based on Web services. GT3's security implementation uses Web services security mechanisms for credential exchange and other purposes, and introduces a tight least-privilege model that avoids the need for any privileged network service.Comment: 10 pages; 4 figure

A Framework for QoS-aware Execution of Workflows over the Cloud

The Cloud Computing paradigm is providing system architects with a new powerful tool for building scalable applications. Clouds allow allocation of resources on a "pay-as-you-go" model, so that additional resources can be requested during peak loads and released after that. However, this flexibility asks for appropriate dynamic reconfiguration strategies. In this paper we describe SAVER (qoS-Aware workflows oVER the Cloud), a QoS-aware algorithm for executing workflows involving Web Services hosted in a Cloud environment. SAVER allows execution of arbitrary workflows subject to response time constraints. SAVER uses a passive monitor to identify workload fluctuations based on the observed system response time. The information collected by the monitor is used by a planner component to identify the minimum number of instances of each Web Service which should be allocated in order to satisfy the response time constraint. SAVER uses a simple Queueing Network (QN) model to identify the optimal resource allocation. Specifically, the QN model is used to identify bottlenecks, and predict the system performance as Cloud resources are allocated or released. The parameters used to evaluate the model are those collected by the monitor, which means that SAVER does not require any particular knowledge of the Web Services and workflows being executed. Our approach has been validated through numerical simulations, whose results are reported in this paper

eWOM & Referrals in Social Network Services

If a few decades ago the development of the Internet was instrumental in the interconnection between markets, nowadays the services provided by Web 2.0, such as social network sites (SNS) are the cutting edge. A proof of this trend is the exponential growth of social network users. The main objective of this work is to explore the mechanisms that promote the transmission and reception (WOM and referrals) of online opinions, in the context of the SNS, by buyers of travel services. The research includes some research lines: technology acceptance model (TAM), Social Identification Theory and Word-of-Mouth communication in virtual environment (eWOM). Based on these theories an explicative model has been proposed applying SEM analysis to a sample of SNS users’ of tourist service buyers. The results support the majority of the hypotheses and some relevant practical and theoretical implications have been pointed out for tourist managers

A KPN based Model for Describing and Verifying the Interaction of Web Services

Correct interaction between Web services is essential for successful Web service composition. This paper proposes a Web Service Interaction Model (IWSN) that aims to ensure correct interaction between Web services, improve the scalability of Web service composition, solve behavioral compatibility issues in the process of Web service interaction, and promote the application of service composition technology in related fields. The Kahn Process Network (KPN) supports parallel computing based on data streams and channels, and the proposed Web Service Interaction Model in this article is based on the KPN. The formal semantics of the IWSN model are based on process algebra Pi calculus, and the model's properties are discussed. Finally, an application case is used to demonstrate how the IWSN model can be applied to Web service composition and interaction

Cross-Layer Routing Based on Semantic Web Services Discovery with Energy Evaluation and Optimization in MANET

The web services discovery process in mobile adhoc networks is considered as a very difficult challenge due to the continuous change in the topology of the network and also the lack of a fixed central directory for publishing web services. Several approaches have been proposed which are based on either keywords or identifiers representing the service to be searched or by using a specific scenario of discovery. All of those proposed solutions try to respect the constraints of ad hoc networks such as energy, bandwidth, throughput ... etc. In this paper we present our new proposed model for measuring the cost of the overall energy consumption in ad hoc networks depending on the web services discovery protocols. We also present a new optimized web services discovery protocol in MANET based on cross_layer routing techniques with the dissemination in the routing process at the same time the semantic web services information and a Discovery_Diameter parameter that we have proposed to limit the area of discovery in the network. Finally, we present simulation results of our defined approach showing a significant optimization of the energy consumption level and the average throughput

Small-world networks, distributed hash tables and the e-resource discovery problem

Resource discovery is one of the most important underpinning problems behind producing a scalable, robust and efficient global infrastructure for e-Science. A number of approaches to the resource discovery and management problem have been made in various computational grid environments and prototypes over the last decade. Computational resources and services in modern grid and cloud environments can be modelled as an overlay network superposed on the physical network structure of the Internet and World Wide Web. We discuss some of the main approaches to resource discovery in the context of the general properties of such an overlay network. We present some performance data and predicted properties based on algorithmic approaches such as distributed hash table resource discovery and management. We describe a prototype system and use its model to explore some of the known key graph aspects of the global resource overlay network - including small-world and scale-free properties

A Dataflow Language for Decentralised Orchestration of Web Service Workflows

Orchestrating centralised service-oriented workflows presents significant scalability challenges that include: the consumption of network bandwidth, degradation of performance, and single points of failure. This paper presents a high-level dataflow specification language that attempts to address these scalability challenges. This language provides simple abstractions for orchestrating large-scale web service workflows, and separates between the workflow logic and its execution. It is based on a data-driven model that permits parallelism to improve the workflow performance. We provide a decentralised architecture that allows the computation logic to be moved "closer" to services involved in the workflow. This is achieved through partitioning the workflow specification into smaller fragments that may be sent to remote orchestration services for execution. The orchestration services rely on proxies that exploit connectivity to services in the workflow. These proxies perform service invocations and compositions on behalf of the orchestration services, and carry out data collection, retrieval, and mediation tasks. The evaluation of our architecture implementation concludes that our decentralised approach reduces the execution time of workflows, and scales accordingly with the increasing size of data sets.Comment: To appear in Proceedings of the IEEE 2013 7th International Workshop on Scientific Workflows, in conjunction with IEEE SERVICES 201