Towards a Component Model supporting Proactive Configuration of Service-Oriented Systems

Components within service-oriented systems require a mechanism to get in touch with offered services. A traditional approach from the field of Web services is a discovery agency provided by the infrastructure, where service providers register and service requestors submit their queries. In the field of dynamic adaptive systems we deal with systems which change their behavior according to the needs of their users during runtime based on context information. Therefore, the wiring of service providers and service requestors - known as the system configuration - may change often. As a consequence of the dynamics it is reasonable not to let the service requestor take care about the service discovery. Instead we propose a component model enabling the proactive configuration of service-oriented systems which will be described in this paper.

Discovery of service providers that are useful to service requesters is a common problem in large, dynamic service-oriented systems, such as Grids. Simple service indices do not address this problem adequately when the service requesters need to describe complex conditions to be met by the service providers. Furthermore, the problem of sharing services among multiple service providers in order to enable the system to serve as many independent requesters as possible while still meeting their conditions is not addressed by such systems. This paper presents an architecture of a service discovery system for Grids, that allows dynamic registration of services and their provided capabilities. Discovery is based on matching of requested and provided capabilities. The matching process enables trading the degree of satisfaction of requested capabilities for availability of the system to multiple requesters. The discovery service seamlessly integrates with existing Grid infrastructure and specifications.

Service discovery and selection approaches are often done using a centralized registry-based technique, which only captures common Quality of Service criteria. With more and more services offered via social networks, these approaches are not able to evaluate trust in service providers and often fail to comply with new requester's expectations. This is because theses approaches are not able (i) to take into consideration the social dimension and (ii) to capitalize on information resulting from previous experiences. To address these challenges, we propose the use of multi-agent systems as they have demonstrated the capability to use previous interactions, knowledge representation and distributed reasoning, as well as social metaphors like trust. More precisely, in this paper, we enhance service discovery and selection processes by integrating the societal view in trust modeling. Based on relationships between agents, their previous experiences and extracted information from social network, we define a trust model built upon social, expert and recommender-based components. The social-based component judges whether the provider is worthwhile pursuing before using his services (viz. trust in sociability). The expert-based component estimates whether the service behaves well and as expected (viz. trust in expertise). The recommender-based component assesses for an agent whether one's can rely on its recommendations (viz. trust in recommendation). However, when searching for a service in a social network, agents (service requester and service providers) may have no direct interactions or previous experiences. This requires a method to infer trust between them. Based on a probabilistic model, we estimate trust between non adjacent agents while taking into account roles (recommender or provider) of intermediate agents. Moreover, we propose a distributed algorithm for trustworthy service discovery and selection using referral systems in social networks. Experiments demonstrate that our approach is effective and outperforms existing ones, and can deliver more trustworthy results.

Intelligent Transportation Systems (ITS) are gaining momentum among researchers. ITS encompasses several technologies, including wireless communications, sensor networks, data and voice communication, real-time driving assistant systems, etc. These states of the art technologies are expected to pave the way for a plethora of vehicular network applications. In fact, recently we have witnessed a growing interest in Vehicular Networks from both the research community and industry. Several potential applications of Vehicular Networks are envisioned such as road safety and security, traffic monitoring and driving comfort, just to mention a few. It is critical that the existence of convenience or driving comfort services do not negatively affect the performance of safety services. In essence, the dissemination of safety services or the discovery of convenience applications requires the communication among service providers and service requesters through constrained bandwidth resources. Therefore, service discovery techniques for vehicular networks must efficiently use the available common resources. In this thesis, we focus on the design of bandwidth-efficient and scalable service discovery protocols for Vehicular Networks. Three types of service discovery architectures are introduced: infrastructure-less, infrastructure-based, and hybrid architectures. Our proposed algorithms are network layer based where service discovery messages are integrated into the routing messages for a lightweight discovery. Moreover, our protocols use the channel diversity for efficient service discovery. We describe our algorithms and discuss their implementation. Finally, we present the main results of the extensive set of simulation experiments that have been used in order to evaluate their performance.

With the integration of Mobile Edge Computing (MEC) and Network Function Virtualization (NFV), service providers are able to provide low-latency services to mobile users for profit. In this paper, we study the problem of service instance placement and request assignment in an MEC network for a given monitoring period, where service requests arrive into the system without the knowledge of future arrivals. Each incoming request requires a specific service with a maximum tolerable service delay requirement. The problem is to maximize the profit of the service provider by admitting service requests for the monitoring period, which can be achieved by preinstalling service instances into cloudlets to shorten service delays, and accommodating new services by removing some idle service instances from cloudlets due to limited computing resources. We then devise an efficient deep-reinforcement-learning-based algorithm for this dynamic online service instance placement problem. We finally evaluate the performance of the proposed algorithm by conducting experiments through simulations. Simulation results demonstrate that the proposed algorithm is promising.

As cloud computing becomes more and more popular, understanding the economics of cloud computing becomes critically important. To maximize the profit, a service provider should understand both service charges and business costs, and how they are determined by the characteristics of the applications and the configuration of a multiserver system. The problem of optimal multiserver configuration for profit maximization in a cloud computing environment is studied. Our pricing model takes such factors into considerations as the amount of a service, the workload of an application environment, the configuration of a multiserver system, the service-level agreement, the satisfaction of a consumer, the quality of a service, the penalty of a low-quality service, the cost of renting, the cost of energy consumption, and a service provider's margin and profit. Our approach is to treat a multiserver system as an M/M/m queuing model, such that our optimization problem can be formulated and solved analytically. Two server speed and power consumption models are considered, namely, the idle-speed model and the constant-speed model. The probability density function of the waiting time of a newly arrived service request is derived. The expected service charge to a service request is calculated. The expected net business gain in one unit of time is obtained. Numerical calculations of the optimal server size and the optimal server speed are demonstrated.

A formal approach for matching and ranking trustworthy context-dependent services

We propose a formal specification framework for functional aspects of services. We define services as operations which are specified by means of pre- and postconditions, for the specification of which we use extensions of description logic. The (extensions of) description logic and the specification framework itself are defined as institutions. This gives the framework a uniformity of definition and a solid algebraic and logical foundation. The framework can be used for the specification of service requests and service providers. Given a signature morphism from request to provider, we define when a service request is matched by a service provider, which can be used in service discovery. We provide a model-theoretic definition of matching and show that matching can be characterized by a semantic entailment relation which is formulated over a particular standard description logic. Thus proofs of matching can be reduced to standard reasoning in description logic for which one can use description logic reasoners.

This paper presents a game theoretic model and an iterative bidding framework for the service request prioritizing and scheduling problem in Software as a Service (SaaS) environments. We focus on a type of settings in which the service provider's existing capacity is over demanded and customers' service requests are constrained with completion times. To gain more profit, the provider needs to prioritize customers' requests based on their profitability and schedule as many profitable requests as possible. The prioritizing and scheduling problem is considered in a strategic setting in which customers' values on the service requests are their private information that is not known to the provider, which calls for economic based models. The key issue here is how to maximize economic social welfare across all customers given the presence of customers' self-interests. We propose an iterative bidding framework as a multilateral negotiation platform for the service provider and its customers to allocate compute capacity among service requests. The proposed bidding framework is evaluated by a computational study. The data from the experiments show that the proposed approach produces near optimal solutions with moderate information revelation. It also scales well to large size problem instances.

In service-oriented business applications, B2B integration happens when a service requester invokes services of one or more service providers. Typically, there are several candidate services with similar capabilities that can be chosen by a requester in order to serve his business needs. The selection of the service to be invoked may depend on different functional and non-functional properties. The nonfunctional properties usually address security, reliability, performance, and so forth. The functional properties address the business process interplay at the level of the technical Web service interface and the message choreography associated with it. At the technical integration level, the description of functional and non-functional service properties has been exhaustively addressed in the scientific literature in the past. The business level however, namely, the requester’s business need, the business meaning of an offered service, and the capability of a service provider to successfully perform the requested business transaction, has been rather ignored. This chapter describes a solution for service discovery and selection at the business level, that is, at the level of offered business capability of a service provider and the ability to serve a concrete requested business transaction. The proposed solution is based on semantic interpretation of offered service capabilities, contractual restrictions, business rules of the requestor specifying selection preferences, and the parameters of the run-time service request. The applicability of the proposed solution is demonstrated on a shipper-carrier integration scenario.

Service discovery in mobile ad hoc networks: an overall perspective on architectural choices and network layer support issues

Nowadays Web users have clearly expressed their wishes to receive personalized services directly. Personalization is the way to tailor services directly to the immediate requirements of the user. However, the current Web Services System does not provide any features supporting this such as consideration of personalization of services and intelligent matchmaking. In this research a flexible, personalized Rule-based Web Services System to address these problems and to enable efficient search, discovery and construction across general Web documents and Semantic Web documents in a Web Services System is proposed. This system utilizes matchmaking among service requesters', service providers' and users' preferences using a Rule-based Search Method, and subsequently ranks search results. A prototype of efficient Web Services search and construction for the suggested system is developed based on the current work.

To manage the delivery of services competitively on a large, global scale, an IT (information technology) service provider must efficiently use service delivery resources-in particular, skilled service delivery teams. Service requests form a large and important component of the management of a client's IT infrastructure. Currently, the fulfillment of IT service requests is often managed on a per-account basis. Service-delivery teams fulfill service requests according to account-specific processes by using an account-specific service-request-management environment, making it difficult to leverage the skills of the various delivery teams for multiple accounts. The service delivery management platform (SDMP) uses reusable service components that can be performed by multiple delivery teams and can be assembled into service compositions to which multiple clients can subscribe. The SDMP catalog is the information repository that manages service components, composition, providers, and subscriptions and is used by the service-request runtime environment to implement specific customer service requests. In this paper, we describe a catalog-based architecture for service delivery management and demonstrate how its use can provide a global service-delivery organization with a platform for achieving significant productivity gains.

While Web service models become increasingly popular and many service providers start to offer all kinds of Web services, the quality of service (QoS) for Web services has become an important factor for service requesters to consider during the selection process of appropriate Web services. In this paper, we present an evaluation and selection framework (CosmosQoS) for QoS-required Web services. A novel architecture and reputation appraisal model to monitor, store and evaluate the physical usage and post-condition of requested Web services in a requester-located network is proposed to better support service requesters such that they can select suitable Web services based on their QoS requirements, trustworthiness of Web services, and effect of network connection and configuration between service requesters and providers.

The expansion of web service provider's number over the web has motivated the research community to invest in web service discovery area. However, in order to efficiently identify appropriate services, web services requesters should express their requests in rich, standard and machine-readable manner. In this context, we propose the use of a Service Request Template based on SAWSDL and WS-Policy standards. We use SAWSDL language which constitutes an extension of WSDL to express both functional and semantic needs, while we use WS-Policy framework to specify both non-functional requirements and user's preferences. We think that the proposed template would make it possible to overcome problems due to the heterogeneity between web services requests and published web services when executing discovery process. To perform efficient service discovery, we develop a structure-based matching algorithm that offers three mechanisms: semantic, data types and policy matching.