A Location Based Value Prediction for Quality of Web Service

The number of web services with functionality increases, the service users usually depends on web recommendation systems. Now a days the service users pay more importance on non functional properties which are also known as Quality of Service (QoS) while finding and selecting appropriate web services. Collaborative filtering approach predicts the QoS values of the web services effectively. Existing recommendation systems rarely consider the personalized influence of the users and services in determining the similarity between users and services. The proposed system is a ranking oriented hybrid approach which integrates user-based and item-based QoS predictions. Many of the non-functional properties depends on the user and the service location. The system thus employs the location information of users and services in selecting similar neighbors for the target user and service and thereby making personalized service recommendation for service users

A QoS-Aware BPEL Framework for Service Selection and Composition Using QoS Properties

Abstract—The promise of service oriented computing, and the availability of web services in particular, promote delivery of services and creation of new services composed of existing services – service components are assembled to achieve integrated computational goals. Business organizations strive to utilize the services and to provide new service solutions and they will need appropriate tools to achieve these goals. As web and internet based services grow into clouds, inter-dependency of services and their complexity increases tremendously. The cloud ontology depicts service layers from a high-level, such as Application and Software, to a low-level, such as Infrastructure and Platform. Each component resides at one layer can be useful to others as a service. It hints the amount of complexity resulting from not only horizontal but also vertical integrations in building and deploying a composite service. Our framework tackles the complexity of the selection and composition issues with additional qualitative information to the service descriptions using Business Process Execution Language (BPEL). Engineers can use BPEL to explore design options, and have the QoS properties analyzed for the design. QoS properties of each service are annotated with our extension to Web Service Description Language (WSDL). In this paper, we describe our framework and illustrate its application to one QoS property, performance. We translate BPEL orchestration and choreography into appropriate queuing networks, and analyze the resulting model to obtain the performance properties of the composed service. Our framework is also designed to support utilizations of other QoS extensions of WSDL, adaptable business logic languages, and composition models for other QoS properties

Towards intelligent distributed computing : cell-oriented computing

Distributed computing systems are of huge importance in a number of recently established and future functions in computer science. For example, they are vital to banking applications, communication of electronic systems, air traffic control, manufacturing automation, biomedical operation works, space monitoring systems and robotics information systems. As the nature of computing comes to be increasingly directed towards intelligence and autonomy, intelligent computations will be the key for all future applications. Intelligent distributed computing will become the base for the growth of an innovative generation of intelligent distributed systems. Nowadays, research centres require the development of architectures of intelligent and collaborated systems; these systems must be capable of solving problems by themselves to save processing time and reduce costs. Building an intelligent style of distributed computing that controls the whole distributed system requires communications that must be based on a completely consistent system. The model of the ideal system to be adopted in building an intelligent distributed computing structure is the human body system, specifically the body’s cells. As an artificial and virtual simulation of the high degree of intelligence that controls the body’s cells, this chapter proposes a Cell-Oriented Computing model as a solution to accomplish the desired Intelligent Distributed Computing system

Using Constraint Reasoning on Feature Models to Populate Ecosystem-driven Cloud Services e- Marketplace

Service providers leverage cloud ecosystems and cloud e-marketplaces to increase the business value of their services and reach a wider range of service users. A cloud ecosystem enable participating services to combine with other services, along their QoS properties; while the e-marketplace provides an environment where atomic services interconnect in unprecedented ways to be traded on the marketplace platform. Noting the unprofitability, impracticality and error-prone nature of performing ad hoc service combination of atomic services, the concern addressed in this technical report is how to guide the combination of atomic services participating in an ecosystem in a seamless manner. In this technical report, we proposed the use of feature models to model the inter-relationships and constraints among the atomic services, which is transformed into a constraint satisfaction problem and off-the-shelve constraint solvers are used to determining valid combinations. The collection of valid combinations become the blueprint that guides service composition and populates the e-marketplace service directory; users can then make service selection decisions based on the list. The applicability of the approach proposed in this report is demonstrated via an example of Customer relationship management as a service ecosystem

COMITMENT: A Fog Computing Trust Management Approach

none8siAs an extension of cloud computing, fog computing is considered to be relatively more secure than cloud computing due to data being transiently maintained and analyzed on local fog nodes closer to data sources. However, there exist several security and privacy concerns when fog nodes collaborate and share data to execute certain tasks. For example, offloading data to a malicious fog node can result into an unauthorized collection or manipulation of users’ private data. Cryptographic-based techniques can prevent external attacks, but are not useful when fog nodes are already authenticated and part of a networks using legitimate identities. We therefore resort to trust to identify and isolate malicious fog nodes and mitigate security, respectively. In this paper, we present a fog COMputIng Trust manageMENT (COMITMENT) approach that uses quality of service and quality of protection history measures from previous direct and indirect fog node interactions for assessing and managing the trust level of the nodes within the fog computing environment. Using COMITMENT approach, we were able to reduce/identify the malicious attacks/interactions among fog nodes by approximately 66%, while reducing the service response time by approximately 15 s.openAl-khafajiy M.; Baker T.; Asim M.; Guo Z.; Ranjan R.; Longo A.; Puthal D.; Taylor M.Al-khafajiy, M.; Baker, T.; Asim, M.; Guo, Z.; Ranjan, R.; Longo, A.; Puthal, D.; Taylor, M

e3 service: A Critical Reflection and Future Research

Commercial services are of utmost importance for the economy. Due to the widespread use of information and communication technologies, many of these services may be delivered online by means of service value networks. To automate this delivery, however, issues such as composition, integration, and operationalization need to be addressed. In this paper, the authors share their long-term vision on composition of service value networks and describe relationships with fields such as cloud computing and enterprise computing. As a demonstration of the state of the art, capabilities and limitations of e 3 service are described and research challenges are defined