Context-aware Service Discovery Research Articles

Context-Aware Service Discovery: Graph Techniques for IoT Network Learning and Socially Connected Objects

Adopting Internet-of-things (IoT) in large-scale environments such as smart cities raises compatibility and trustworthiness challenges, hindering conventional service discovery and network navigability processes. The IoT network is known for its highly dynamic topology and frequently changing characteristics (e.g., the devices’ status, such as battery capacity and computational power); traditional methods fail to learn and understand the evolving behavior of the network to enable real-time and context-aware service discovery in such diverse and large-scale topologies of IoT networks. The Social IoT (SIoT) concept, which defines the relationships among the connected objects, can be exploited to extract established relationships between devices and enable trustworthy and context-aware services. In fact, SIoT expresses the possible connections that devices can establish in the network and reflect compatibility, trustworthiness, and so on. In this paper, we investigate the service discovery process in SIoT networks by proposing a low-complexity context-aware Graph Neural Network (GNN) approach to enable rapid and dynamic service discovery. Unlike the conventional graph-based techniques, the proposed approach simultaneously embeds the devices’ features and their SIoT relations. Our simulations on a real-world IoT dataset show that the proposed GNN-based approach can provide more concise clusters compared to traditional techniques, namely the Louvain and Leiden algorithms. This allows a better IoT network learning and understanding and also, speeds up the service lookup search space. Finally, we discuss implementing the GNN-assisted context-service discovery processes in novel smart city IoT-enabled applications.

ADSDA: Adaptive Distributed Service Discovery Algorithm for Internet of Things Based Mobile Wireless Sensor Networks

Emerging technologies and applications in the Internet of Things (IoT) domain require highly dynamic sensor network infrastructure. Discovering service available on such dynamic networks is a fundamental but challenging problem that needs to be addressed. In this paper, we present a new adaptive distributed service discovery algorithm (ADSDA) that allows service discovery (SD) and selection of services for IoT-based highly dynamic sensor network environments. The proposed lightweight context-aware service discovery architecture provides an effective infrastructure to facilitate environment-aware and user-centric SD. The performance of the proposed ADSDA is analyzed through extensive simulation. The evaluation and comparison of results with the existing baseline approaches prove the effectiveness of our proposed ADSDA in terms of query success rate, number of transmission messages, and transmission cost per query.

An Extensive Survey for Context Aware Framework Based Scheduling in Cloud Computing

Cloud Computing is a vast paradigm to operate on remote devices using which one can access any data, platform or any kind of infrastructure.In this paper we have done a survey on the context aware framework that is used in the smart cities. In this paper CAMELO framework is studied along with the advantages and ease of use in it. A context-aware service discovery framework based on mobile cloud computing environment is reviewed in this paper.

Context Aware QOS based Web Service Discovery

This work concentrates on context of the execution environment in service selection process due to dynamically varying QoS attributes in service execution environment. In this paper, a context aware QoS Web Service(WS) description and discovery is proposed to overcome the issues related to QoS requirements in WS. In the proposed scheme, OWL-Q with OWL CONtext ONtology (CONON) ontology is modeled to provide the WS description with context aware QoS descriptions. To discover the most appropriate WS based on context and QoS descriptions, a context aware QoS semantic matchmaking algorithm is newly proposed based on Constraint Satisfaction Optimization Approach (CSOP). An efficient User Priority based Ranking (UPR) mechanism is performed based on user preferences to rank the matched WSs. Consequently, precision and recall of proposed context aware QoS WS discovery is compared with the existing QoS WS discovery and conclude that proposed approach achieves high precision and recall than existing QoS based approach.

A Location Context Aware Service Discovery Model and Algorithm to Support Mobile Service Personalization

Along with the rapid development of mobile Internet, more and more services have emerged on the mobile platform. In this study, it proposes the model of location context aware service discovery oriented to mobile Internet. Firstly, it introduces the Location-Based Service (LBS), users' behavior preference expression and the process of content filtering. Secondly, it puts forward the model of Location Context-based Service Discovery (LCMSD) by acquiring the data of users' behavior and gaining their requirements. Thus it keeps track of users' behavior preference and updates their preference according to the location context. Thirdly, the algorithm of location-based service discovery is brought forward, which focuses on the model of location context and describing users' preference and location-based service in detail. So it solves the problem that users can't discover the required services in the current location context timely. Finally we design a simulation experiment of mobile service which computes the similarity of mobile service and users' behavior preference through mining users' preference. The result shows that it can support mobile service personalization.

A location-based context-aware service discovery approach for cycling experience

This study explored the use of context–aware information to facilitate web service discovery in a ubiquitous computing setting. Consumer electronics and internet access enable ubiquitous computing and have played an essential part in our daily lives, including cycling experience. Future applications for cyclists will be required to interact with multiple specialised services. In this study, a service–oriented architecture (SOA)–based service discovery framework that is implemented using the extensible messaging and presence protocol (XMPP) technology is proposed, and the framework design is presented. An example of a restaurant recommendation system for cyclists is highlighted as a proof of concept prototype to demonstrate and investigate the feasibility and effectiveness of the proposed framework.

Towards Context Aware QOS-Based Web Service Description and Discovery

This work concentrates on context of the execution environment in service selection process due to dynamically varying QoS attributes in service execution environment. In this paper, a context aware QoS Web Service (WS) description and discovery is proposed to overcome the issues related to QoS requirements in WS. In the proposed scheme, OWL-Q with OWL CONtext ONtology (CONON) ontology is modelled to provide the WS description with context aware QoS descriptions. To discover the most appropriate WS based on context and QoS descriptions, a context aware QoS semantic matchmaking algorithm is newly proposed based on Constraint Satisfaction Optimization Approach (CSOP). An efficient User Priority based Ranking (UPR) mechanism is performed based on user preferences to rank the matched WSs. Consequently, precision and recall of proposed context aware QoS WS discovery is compared with the existing QoS WS discovery and conclude that proposed approach achieves high precision and recall than existing QoS based approach.

New Framework and Mechanisms of Context-Aware Service Composition in the Future Internet

The ongoing proliferation of new services, applications, and contents is leading the Internet to an architectural crisis owing to its inability to provide efficient solutions to new requirements. Clean-slate architectures for the future Internet offer a new approach to tackle current and future challenges. This proposal introduces a novel clean-slate architecture in which the TCP/IP protocol stack is decoupled in basic functionalities, that is, atomic services (ASs). A negotiation protocol, which enables context-aware service discovery for providing adapted communications, is also specified. Then, we present how ASs can be discovered and composed according to requesters' requirements. In addition, a media service provisioning use case shows the benefits of our framework. Finally, a proof-of-concept implementation of the framework is described and analyzed. This paper describes the first clean-slate architecture aligned with the work done within the ISO/IEC Future Network working group.

Web Service Assurance: The Notion and the Issues

Web service technology provides basic infrastructure for deploying collaborative business processes. Web Service security standards and protocols aim to provide secure communication and conversation between service providers and consumers. Still, for a client calling a Web service it is difficult to ascertain that a particular service instance satisfies—at execution time—specific non-functional properties. In this paper we introduce the notion of certified Web service assurance, characterizing how service consumers can specify the set of security properties that a service should satisfy. Also, we illustrate a mechanism to re-check non-functional properties when the execution context changes. To this end, we introduce the concept of context-aware certificate, and describe a dynamic, context-aware service discovery environment.

Hybrid approach for context-aware service discovery in healthcare domain

Context-awareness computing is a research field which often refers to healthcare as an interesting and rich area of application. Context aware computing attains environments monitoring by means of sensors to provide relevant information or services according to the identified context. In particular, wireless ad hoc sensor networks for medical purposes are playing an increasing role within healthcare. Body Sensor Networks (BSN) are being designed for prophylactic and follow-up monitoring of patients in e.g. their homes, during hospitalization, and in emergencies. This work presents an integrated environment aimed at providing personalized healthcare services which appropriately meet the userʼs context. Deploying the semantics embedded in web services and context models is a mandatory step in the automation of service discovery, invocation and composition. Nevertheless, in a context aware domain purely logic-based reasoning on respectively context and services may not be enough. The main idea of this work is related to enrich with qualitative representation of context underling data by means of Fuzzy Logic in order to automatically recognize the context and to consequently find the right set of healthcare services among the available ones. Semantic formalisms (e.g., OWL, OWL-S, etc.) enable the context and services modeling in terms of domain ontology concepts. On the other hand, soft computing techniques support activity of unsupervised context analysis and healthcare semantic service discovery. Goal is to define context-aware system whose quality of retrieved services relies on the acquisition of user context by means of a robust theoretical approach. Moreover, this work defines hybrid architecture which attains a synergy between the agent-based paradigm and the fuzzy modeling. Specifically, the system exploits some task oriented agents in order to achieve context recognition, services matchmaking and brokerage activities.

SmartCon: a context-aware service discovery and selection mechanism using Artificial Neural Networks

In this paper, we present SmartCon, a context-aware system for the discovery and selection of mobile services using Artificial Neural Networks (ANNs). The solution we have developed is a mobile agent-enabled system that adaptively and iteratively learns to select the best available mobile service derived from the extraction of a series of features utilising contextual information such as the Composite Capabilities/Preference Profiles (CC/PP), service-specific and non-uniform user-specific features which are supplied to a Back-Propagation Neural Network. Based on the features provided, the neural network classifies the most relevant mobile service. In the present work, the system is also capable through iterative learning to generalise and gather information using cognitive feedback based on the user's decisions and interactivity with a Mobile Device. SmartCon is evaluated using a series of preliminary empirical data and results show an 87% success rate in the discovery and selection of the best or most relevant mobile service.

Impromptu Service Discovery and Delivery in Mobile Environments

Wireless hotspots and broadband coverage are permeating the globe, giving rise to interesting spontaneous networking scenarios. The discovery and delivery of the most relevant and suitable services in a spontaneous network is a problem of great importance. In this paper we present an architecture that can support context-aware service discovery and delivery for resource-constrained mobile devices. At the heart of the architecture is the μJini proxy which mediates the discovery and delivery processes. Its discovery subsystem exploits relevant context information for the highest quality instance discovery. Its delivery subsystem provides thin-client based adaptation for fat service delivery not supported by thin client devices. To demonstrate its effectiveness, we developed a proofof-concept prototype for Java mobile service environments.

CASD: Management of a context-aware service directory

Traditional web service discovery is strongly related to the use of service directories. Especially in the case of mobile web services, where both service requestors and providers are mobile, the dynamics impose the need for directory-based discovery. Context plays an eminent role with mobility, as a filtering mechanism that enhances service discovery through the selection of the most appropriate service. However, current service directory specifications do not focus on mobility of services or context-awareness. In this paper, we propose CASD, a context-aware service directory, envisioned as a context-based index for services on top of any traditional service directory, and design algorithms for construction, search, update and merge of such directories. Furthermore, we describe the architecture of our system for context-aware service discovery, we present a prototype implementation and discuss the experimental results as well as the overall evaluation. The contribution of this work is the proposal for a novel, enhanced representation model for a context-aware service directory.

A System Architecture for Context-Aware Service Discovery

Recent technological advances have enabled both the consumption and provision of mobile services (m-services) by small, portable, handheld devices. However, mobile devices still have restricted capabilities with respect to processing, storage space, energy consumption, stable connectivity, bandwidth availability. In order to address these shortcomings, a potential solution is context-awareness (by context we refer to the implicit information related both to the requesting user and service provider that can affect the usefulness of the returned results). Context plays the role of a filtering mechanism, allowing only transmission of relevant data and services back to the device, thus saving bandwidth and reducing processing costs. In this paper, we present an architecture for context-aware service discovery. We describe in detail the system implementation and we present the system evaluation as a tradeoff between a) the increase of the quality of service discovery when context-awareness is taken into account and b) the extra cost/burden imposed by context management.