Broker-based service-oriented content adaptation framework

Electronic documents are becoming increasingly rich in content and varied in format and structure. At the same time, user preferences vary towards the contents and their devices are getting increasingly varied in capabilities. This mismatch between rich contents and user preferences along with the end device capability presents a challenge in providing ubiquitous access to these contents. Content adaptation is primarily used to bridge the mismatch by providing users with contents that is tailored to the given contexts e.g., device capability, preferences, or network bandwidth. Existing content adaptation systems employing these approaches such as client-side, server-side or proxy-side adaptation, operate in isolation, often encounter limited adaptation functionality, get overload if too many concurrent users and open to single point of failure, thus limiting the scope and scale of their services. To move beyond these shortcomings, this thesis establishes the basis for developing content adaptation solutions that are efficient and scalable. It presents a framework to enable content adaptation to be consumed as Web services provided by third-party service providers, which is termed as “service-oriented content adaptation”. Towards this perspective, this thesis addresses five key issues – how to enable content adaptation as services (serviceoriented framework); how to locate services in the network (service discovery protocol); how to select best possible services (path determination); how to provide quality assurance (service level agreement (SLA) framework); and how to negotiate quality of service (QoS negotiation). Specifically, we have: (i) identified the key research challenges for service-oriented content adaptation, along with a systematic understanding of the content adaptation research spectrum, captured in a taxonomy of content adaptation systems; (ii) developed an architectural framework that provides the basis for enabling content adaptation as Web services, providing the facilities to serve clients’ content adaptation requests through the client-side brokering; (iii) developed a service discovery protocol, by taking into account the searching space, searching time, match type of the services and physical location of the service providers; (iv) developed a mechanism to choose the best possible combination of services to serve a given content adaptation request, considering QoS levels offered; (v) developed an architectural framework that provides the basis for managing quality through the conceptualization of service level agreement; and (vi) introduced a strategy for QoS negotiation between multiple brokers and service providers, by taking into account the incoming requests and server utilization and, thus requiring the basis of determining serving priority and negotiating new QoS levels. The performance of the proposed solutions are compared with other competitive solutions and shown to be substantially better

Location-aware scalable service composition.

The problem of service composition is the process of assigning resources to services from a pool of available ones in the shortest possible time so that the overall quality of service is maximized. This article provides solutions for the composition problem that takes into account its scalability, services’ locations, and users’ restrictions, which are key for the management of applications using state-of-the-art technologies. The provided solutions use different techniques, including genetic algorithms and heuristics. We provide an extensive experimental evaluation, which shows the pros and cons of each of them, and allows us to characterize the preferred option for each specific problem. Since no solution dominates the others, we propose a decision tree, based on our results, to select the best composition algorithm in each situation.Spanish Government projects TED2021-130666B-I00 and PID2021-125527NB-I00. Funding for open access charge: Universidad de Málaga / CBUA

Wedding planner in a box

Marriage describes the connection of two souls who promise to become one heart. Everyone dreams their marriage to be nearly perfect and that will happen only if they are able to make their wedding plan with best packages. In this busy world, many couples delay their wedding mainly because of high budget required to meet their dream wedding ceremony. Wedding ceremony requires careful and meticulous planning from many aspects such as choosing the food, make up, decoration, and gifts

Semantics-aware planning methodology for automatic web service composition

Service-Oriented Computing (SOC) has been a major research topic in the past years. It is based on the idea of composing distributed applications even in heterogeneous environments by discovering and invoking network-available Web Services to accomplish some complex tasks when no existing service can satisfy the user request. Service-Oriented Architecture (SOA) is a key design principle to facilitate building of these autonomous, platform-independent Web Services. However, in distributed environments, the use of services without considering their underlying semantics, either functional semantics or quality guarantees can negatively affect a composition process by raising intermittent failures or leading to slow performance. More recently, Artificial Intelligence (AI) Planning technologies have been exploited to facilitate the automated composition. But most of the AI planning based algorithms do not scale well when the number of Web Services increases, and there is no guarantee that a solution for a composition problem will be found even if it exists. AI Planning Graph tries to address various limitations in traditional AI planning by providing a unique search space in a directed layered graph. However, the existing AI Planning Graph algorithm only focuses on finding complete solutions without taking account of other services which are not achieving the goals. It will result in the failure of creating such a graph in the case that many services are available, despite most of them being irrelevant to the goals. This dissertation puts forward a concept of building a more intelligent planning mechanism which should be a combination of semantics-aware service selection and a goal-directed planning algorithm. Based on this concept, a new planning system so-called Semantics Enhanced web service Mining (SEwsMining) has been developed. Semantic-aware service selection is achieved by calculating on-demand multi-attributes semantics similarity based on semantic annotations (QWSMO-Lite). The planning algorithm is a substantial revision of the AI GraphPlan algorithm. To reduce the size of planning graph, a bi-directional planning strategy has been developed

Methods for Efficient and Accurate Discovery of Services

With an increasing number of services developed and offered in an enterprise setting or the Web, users can hardly verify their requirements manually in order to find appropriate services. In this thesis, we develop a method to discover semantically described services. We exploit comprehensive service and request descriptions such that a wide variety of use cases can be supported. In our discovery method, we compute the matchmaking decision by employing an efficient model checking technique