Decentralized service discovery and selection in Internet of Things applications based on artificial potential fields

Rapti, Elli; Karageorgos, Anthony; Houstis, Catherine E.; Houstis, Elias N.

doi:10.1007/s11761-016-0198-1

Cited by 26 publications

(6 citation statements)

References 36 publications

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“…However, it is not clear how these approaches would scale in large networks of different sizes. Moreover, the proposed model does not consider alternative ways when part of the requested resources is missing [30].…”

Section: Service Discoverymentioning

confidence: 99%

A QoS-aware service discovery and selection mechanism for IoT environments

Demir

2021

Sādhanā

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Internet of Things (IoT) enables the interconnection of computing devices embedded in everyday objects to create smart environments. In such an environment, an user-defined task can be performed composing multiple services provided by the physical objects. Discovering and selecting an appropriate service meeting Quality of Services (QoS) requirements among the large amount of dynamic IoT service provider nodes are significant issues. Existing approaches employ either query message broadcasting or regular service probing methods to discover the IoT services with near-real-time QoS values, which are both costly approaches. In particular, the centralized approach could suffer from single-point failure and scalability issues. To address these issues, we propose QoS and energy-aware service discovery and selection algorithms. The proposed discovery algorithm makes use of a peer-to-peer (P2P)-based resource discovery mechanism running on an overlay network constructed using users' devices. This structure paves the way for the exploration of near-real-time QoS values of the services, avoiding high message overhead as well as overcoming the availability and scalability shortcomings of the existing centralized and decentralized approaches. Furthermore, selecting the most convenient services concerning diverse QoS attributes among the services found becomes an optimization problem. We propose an optimization algorithm that reflects the likely QoS through assigning a dominance value to services. The performance of the proposed algorithms in terms of message overhead, latency, scalability, reliability and QoS accuracy is evaluated through extensive simulations on a highly realistic test-bed. Performance comparisons with the existing works clearly prove the effectiveness of the proposed idea.

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Section: Service Discoverymentioning

confidence: 99%

A QoS-aware service discovery and selection mechanism for IoT environments

Demir

2021

Sādhanā

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“…Therefore, the use of the gateway may not always be available to assume the service discovery [18]. Rapti et al [19] propose a decentralized service discover based on artificial potential fields (APFs), which are formed upon each user service request and becomes active at points where services can be provided. However, this proposition focuses on local service discovery.…”

Section: Background and Related Workmentioning

confidence: 99%

Decentralized service discovery and localization in Internet of Things applications based on ant colony algorithm

Azizou¹,

Boudries²,

Amad³

2020

IJCDS

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“…a. At present, the application of the Internet of Things mainly focuses on management and control in the fields of aerospace, public transportation, intelligent agriculture and logistics express delivery [28]. For example, the Internet of Things technology is used to monitor the real-time information of aviation components and effectively control internal performance and quality.…”

Section: A Principle and Application Of The Internet Of Things Technmentioning

confidence: 99%

Research on Intelligent Monitoring and Analysis of Physical Fitness Based on the Internet of Things

et al. 2019

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In the process of physical fitness training, it is an important subject of scientific physical fitness training to adjust and control the physical load intensity in real-time, accurately and effectively according to the physiological load inside the human body so as to make it consistent with the predetermined goal of the training plan. Aiming at the current demand of smartphone popularization and athlete training monitoring, this paper designs an intelligent monitoring system of physical fitness based on the Internet of Things technology. By selecting such factors as vertical jump, fast leg raising, sitting forward, height, chest circumference, percentage of body constitution, YOYO intermittent endurance running and so on, using RFID technology to mark different athletes, and after using the particle swarm optimization method of BP network to establish the evaluation model of the athletes' physical condition. Through simulation, the physical condition of athletes is accurately predicted, which provides a new scientific and technological means to improve the efficiency of physical training and make physical training scientific. INDEX TERMS Physical fitness, intelligent monitoring, The Internet of Things, BP neural network, particle swarm.

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Decentralized service discovery and selection in Internet of Things applications based on artificial potential fields

Cited by 26 publications

References 36 publications

A QoS-aware service discovery and selection mechanism for IoT environments

A QoS-aware service discovery and selection mechanism for IoT environments

Decentralized service discovery and localization in Internet of Things applications based on ant colony algorithm

Research on Intelligent Monitoring and Analysis of Physical Fitness Based on the Internet of Things

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