Distributed Distance Sensitive iMesh Based Service Discovery in Dense WSAN

Many disaster recovery and military operations require the frequent movement of specialized personnel and equipment from one operations zone to another. Technology can play a significant role in facilitating resource organization and movements to where the need arises. In this study, we adopt the concept of service discovery in mobile ad hoc networks (MANET) and adapt it to the nature of such operations. For this purpose, we introduce a novel MANET service discovery and reservation technique that is tailored to support such environments and operations. In these situations, the network is often established hastily and the communication devices are of low computational and bandwidth capabilities. The nature of service is rather unique in the sense that a service provider is required to physically move to the location of need. A service provider is often able to service only one requestor over a period of time. The proposed technique functions as a service-oriented routing protocol that locates the resource on the basis of service levels and requirements. We evaluate the technique using a simulator that we developed specifically for this purpose. The evaluation results show the high success rate of the technique in locating and reserving services with changing operational conditions such as network density and rate of requests.

Self-scaling cooperative discovery of service compositions in unstructured P2P networks

With the maturation of wireless networks technologies, Telematics service is becoming a new rising and popular network service and application. In this paper, a centralized vehicular Peer-to-Peer Telematics (C-VP2P) service discovery platform is proposed to provide efficient and feasible service discovery. This paper focuses on the issues of developing a Telematics service platform over the vehicular network environment. When a user needs a service on the road, two issues need to be considered: (1) how to have the candidate list of service providers? (2) how to select suitable service providers from the candidate list? In order to tackle these two issues, we propose a C-VP2P-based system service discovery mechanism using the vehicular P2P messaging protocol. In this paper, the vehicular P2P messaging protocol is designed to communicate among Telematics central server, clients and service providers. In addition, a service discovery mechanism in the C-VP2P system is proposed to achieve high precision discovery for service providers. We also exhibit the performance merits of the proposed C-VP2P Telematics service discovery platform in this paper.

Sensor network is a novel technology about acquiring and processing information. This paper introduces the basic interaction patterns between requesters and providers of services during a typical Service Discovery task. It discusses existing service discovery protocols and provides a preliminary analysis of the mechanisms for service and resource discovery in the Wireless Sensor Network domain.

The integration of social networking concepts into the Internet of Things (IoT) paradigm has given rise to Social IoT (SIoT) ecosystems, aiming to address challenges related to network navigation, service discovery, and service composition. A fundamental issue in SIoT is the careful selection of trustworthy devices that provide services. A service provider can offer multiple and diverse services, and different service providers may offer the same services with varying parameters, making it difficult for service requesters to navigate and identify the best service provider that meets their requirements. Moreover, heterogeneous devices and dynamic social relationships in SIoT networks pose challenges in recommending reliable service providers. This research focuses on identifying and recommending consistent and trustworthy service providers in SIoT. The proposed trust model evaluates interactions, friendships, community similarity, cooperativeness, hidden features of service providers and their services, and predicts uncertainties associated with service providers while assessing their trustworthiness. A set of research experiments is conducted on an available dataset to demonstrate the effectiveness and efficiency of the proposed method. The trust model leverages device interactions, cooperativeness, trustworthy relationships, usage patterns, and uncertainty features of service providers. The Root Mean Square Error (RMSE) and Mean Square Error (MSE) metrics are used to evaluate the accuracy of service provider recommendations in the SIoT environment. The proposed model achieves lower RMSE and MSE values, indicating improved recommendation performance. Additionally, the Normalized Discounted Cumulative Gain (NDCG) metric is employed to assess the quality and efficiency of the recommended service providers. The proposed trust model achieves an NDCG score of approximately 90%, demonstrating its ability to recommend highly trusted service providers effectively.

In this paper, an agent-based cross-layer secure service discovery scheme has been presented. Service discovery in MANET is a critical task and it presents numerous security challenges. These threats can compromise the availability, privacy and integrity of service discovery process and infrastructure. This paper highlights various security challenges prevalent to service discovery in MANET. Then, in order to address these security challenges, the paper proposes a cross-layer, agent based secure service discovery scheme for MANET based on deep neural network. The software agents will monitor the intrusive activities in the network based on an Intrusion Detection System (IDS). The service discovery operation is performed based on periodic dissemination of service, routing and security information. The QoS provisioning is achieved by encapsulating QoS information in the periodic advertisements done by service providers. The proposed approach has been implemented in JIST/ SWANS simulator. The results show that proposed approach provides improved security, scalability, latency, packet delivery ratio and service discovery success ratio, for various simulation scenarios.

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.

Introduction: The increasing number of prenatal tests for fetal abnormalities calls for a prenatal care policy which will reflect not only medical values, but also the needs and attitudes of the services’ consumers. Objectives: To compare attitudes of prenatal service consumers and providers regarding extent of prenatal testing and to evaluate these attitudes in relation to sociodemographic and professional characteristics. Methods: Women were interviewed by phone 5–8 weeks postpartum (n = 596) using a structured questionnaire. Health professionals (n = 351) completed a parallel questionnaire. Results: Health professionals were significantly more supportive of comprehensive prenatal testing than women (61.1 vs. 34.1%, respectively). In a multivariable analysis, age over 35, Ashkenazi origin and being better informed regarding tests, predicted a preference for comprehensive testing among women. Among health professionals, predictors of that attitude were secularism and a paramedical profession. Conclusions: Providers and consumers of prenatal services differ in their perceptions and opinions. Policy makers should have mechanisms in place to properly represent this diversity.

The theme of service-oriented computing is largely centered on reusing already existing services. Service providers model common features among potential applications, realize them as reusable services, and publish in service registries. Service consumers discover appropriate services and subscribe them. In developing application with reusable services, there exists a key technical problem, called mismatch problem which is a gap between the required feature and the feature of a candidate service. The adaptability of available services is a key factor in determining the reusability of the published services by resolving mismatches. Hence, we claim that the design of adapters should be an essential activity for developing service-oriented applications. In this paper, we identify recurring mismatch types in discovering services. And, we present four adapter patterns handling the mismatch problems. By using the adapter patterns, service providers could develop highly reusable services, and service consumers will be able to reuse more services available.

We live in a highly networked world where users and their devices interact with other devices with the help of services. With the current trend of social networking and the engendering of user generated multimedia content through personal mobile devices, services are not just confined to enterprise servers. In fact, services travel along with users and/or devices that may act as both mobile service providers as well as service consumers. This trend paves the way for the next generation of Internet (Future Internet) where a very large number of such mobile devices will provide and consume ubiquitous services. The Future Internet (FI) is an opportunity to address service discovery combined with mobility enabling: (i) service providers to join networks and announce their services and (ii) service consumers to discover and invoke services irrespectively of their location. This paper focuses on service discovery for large scale network in the context of Future Internet, taking into account protocol interoperability and scalability.

As Cloud computing and Mobile Computing become more and more prevalent, most of service consumers expect discovery suitable SaaS service in mobile environment. At the same time, in order to economize SaaS service advertisement cost, service provider need recommend SaaS service accurately based on consumer’s behavior. Therefore, how to determine a suitable policy of service discovery in mobile environment has become a challenging issue. It is considered that service in mobile environment need involve such contexts: Domain, QoS and Spatial. In this paper, we propose a context-aware framework that benefit for SaaS service discovery and recommend based on service consumer’s behavior habit and their context environment. In order to reach this target, we also present a model to describe SaaS service based on context Ontology.

The dynamic property of pervasive computing hinders users to have complete knowledge of the relationship among services, service providers, and credentials. The involvement of only the necessary users and service providers for service discovery in pervasive computing environments is challenging. Without prudence, users' and service providers' requests or service information, their identities, and their presence information may be sacrificed. The problem may be as difficult as a chicken-and-egg problem, in which both users and service providers want the other parties to expose sensitive information first. In this paper, we propose a progressive approach to solve the problem. Users and service providers expose partial information in turn and avoid unnecessary exposure if there is any mismatch. Although 1 or 2 bits of information are exchanged in each message, the theoretical analysis and experiments show that our approach protects sensitive information with little overhead.

Objective: The aim of this paper is to introduce a method that can measure and analyze the judgment gaps between service providers and customers. Background: It is important to understand the good service that service providers and customers are thinking. If there is judgment gap between service providers and customers, it would cause an unsatisfactory service. The judgment gap should be thoroughly investigated for a good service design. Method: Lens model is a human decision making model that was proposed by Brunswick(1952). This study indicates whether the Lens model can be applied to analyze judgment gaps between service providers and customers. As a case study, a library lending service was selected. 5 librarians and 15 customers participated in the experiment that investigates their judgments on a good service. The obtained data were analyzed by a modified lens model. Results: Cue weighting policies of consumers and service providers were similar, except that consumers gave higher weight on tangibility than service providers. Service providers and consumers had a good knowledge on the service quality, but they could not well apply the knowledge to judge it. Conclusion: The lens model may be used to analyze judgment gaps between service providers and consumers in the other service areas. The decision cues that were used in this study can be changed, depending on the characteristics of the target service. Application: The method that is proposed in this study may help to investigate and analyze both consumers’ and service providers’ judgments on a variety of services.

Discovery services, such as Serials Solutions Summon, OCLC Local WorldCat, ExLibris Primo, and EBSCO Discovery Service, are built around increasingly comprehensive indexes to books, articles, and other materials. Discovery services and the global bodies of metadata which support them make up an online discovery environment. This chapter outlines the current makeup of this metadata environment. It explores the possibilities and the challenges this environment presents for libraries. It addresses discovery services’ central role in reducing the fragmentation of library resources. The chapter looks at the areas where discovery services can provide access to expanded and more comprehensive collections of materials. It discusses discovery services’ role as central hubs, seamlessly linking library access and delivery services together. The chapter addresses opportunities for more centralized and cooperative management of library metadata, and the need for less reliance on duplication of MARC format metadata.