Adaptive and Context-Aware Service Discovery for the Internet of Things

Butt, Talal Ashraf; Phillips, Iain; Guan, Lin; Oikonomou, George

doi:10.1007/978-3-642-40316-3_4

Cited by 46 publications

(31 citation statements)

References 13 publications

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“…Guinard et al [18] have proposed a web service discovery, query, selection, and ranking approach using context information related to the IoT domain. Similarly, TRENDY [19] is a registry-based service discovery protocol based on CoAP (Constrained Application Protocol) [20] based web services with context awareness. This protocol has been proposed to be used in the Web of Things (WoT) domain with the objective of dealing with a massive number of web services (e.g.…”

Section: Background and Related Workmentioning

confidence: 99%

Sensor Search Techniques for Sensing as a Service Architecture for the Internet of Things

Perera¹,

Zaslavsky²,

Liu

et al. 2014

IEEE Sensors J.

175

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Abstract-The Internet of Things (IoT) is part of the Internet of the future and will comprise billions of intelligent communicating "things" or Internet Connected Objects (ICO) which will have sensing, actuating, and data processing capabilities. Each ICO will have one or more embedded sensors that will capture potentially enormous amounts of data. The sensors and related data streams can be clustered physically or virtually, which raises the challenge of searching and selecting the right sensors for a query in an efficient and effective way. This paper proposes a context-aware sensor search, selection and ranking model, called CASSARAM, to address the challenge of efficiently selecting a subset of relevant sensors out of a large set of sensors with similar functionality and capabilities. CASSARAM takes into account user preferences and considers a broad range of sensor characteristics, such as reliability, accuracy, location, battery life, and many more. The paper highlights the importance of sensor search, selection and ranking for the IoT, identifies important characteristics of both sensors and data capture processes, and discusses how semantic and quantitative reasoning can be combined together. This work also addresses challenges such as efficient distributed sensor search and relational-expression based filtering. CASSARAM testing and performance evaluation results are presented and discussed.Index Terms-Internet of Things, context awareness, sensors, search and selection, indexing and ranking, semantic querying, quantitative reasoning, multi-dimensional data fusion.

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Section: Background and Related Workmentioning

confidence: 99%

Sensor Search Techniques for Sensing as a Service Architecture for the Internet of Things

Perera¹,

Zaslavsky²,

Liu

et al. 2014

IEEE Sensors J.

175

View full text Add to dashboard Cite

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“…Talal Ashraf Butt [39] proposes a RESTful web services based service discovery solution called TRENDY to overcome the problems introduced in the context of interoperability in constrained domains. The proposed method uses demand based adaptive timer and caching mechanism to reduce the communication overhead and service invocation delay.…”

Section: Literature From Past Research Workmentioning

confidence: 99%

“…This smart object is equipped with microcontrollers, a radio interface, sensors and or actuators and offers the functionality as services. The abstraction of resources as services has opened IoT to the excess of potential applications [10]. The adopted web service paradigm is useful for promoting interoperability among the heterogeneous devices by offering a standard interface to interact with others.…”

Section: Introductionmentioning

confidence: 99%

Aspect Oriented Middleware for Internet of Things: A State-of-the Art Survey of Service Discovery Approaches

Balakrishnan¹,

Sangaiah²

2015

IJIES

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Abstract:Internet of Things refers to a paradigm consisting of a variety of uniquely identifiable day to day things communicating with one another to form a large scale dynamic network. The integration of these heterogeneous things in the constrained network is a challenging issue, for which service oriented and architecture based solutions are considered to be useful. The key element of any service oriented paradigm is service discovery which allows the client to get access to the right service at the right time to complete the requested tasks. This paper presented a comprehensive survey of major solutions for service and resource discovery detailing techniques and features used in existing systems. The survey presented the findings in tabular representation and outlined the proposed aspect oriented middleware framework for IoT highlighting context awareness and solving certain pitfalls in the existing service discovery approaches. The survey results might be helpful in deriving the limitations of the existing protocols in literature and identify future research opportunities in service discovery.

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“…Butt et al have proposed a service discovery architecture for the IoT and its accompanying RESTful protocol. Their work targets severely constrained IoT deployments in terms of device processing power and network bandwidth [28], [29].…”

Section: Introductionmentioning

confidence: 99%

A Distributed Consensus Algorithm for Decision Making in Service-Oriented Internet of Things

Oikonomou

Tryfonas

et al. 2014

IEEE Trans. Ind. Inf.

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This is the accepted version of the paper.This version of the publication may differ from the final published version. Abstract-In a service-oriented Internet of things (IoT) deployment, it is difficult to make consensus decisions for services at different IoT edge nodes where available information might be insufficient or overloaded. Existing statistical methods attempt to resolve the inconsistency, which requires adequate information to make decisions. Distributed consensus decision making (CDM) methods can provide an efficient and reliable means of synthesizing information by using a wider range of information than existing statistical methods. In this paper, we first discuss service composition for the IoT by minimizing the multi-parameter dependent matching value. Subsequently, a cluster-based distributed algorithm is proposed, whereby consensuses are first calculated locally and subsequently combined in an iterative fashion to reach global consensus. The distributed consensus method improves the robustness and trustiness of the decision process. Permanent repository link

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Adaptive and Context-Aware Service Discovery for the Internet of Things

Cited by 46 publications

References 13 publications

Sensor Search Techniques for Sensing as a Service Architecture for the Internet of Things

Sensor Search Techniques for Sensing as a Service Architecture for the Internet of Things

Aspect Oriented Middleware for Internet of Things: A State-of-the Art Survey of Service Discovery Approaches

A Distributed Consensus Algorithm for Decision Making in Service-Oriented Internet of Things

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