A Novel Architecture for Cognitive Internet of Things

Zhang, Mingchuan; Quan, Yong; Zheng, Ruijuang; Bai, Xin; Wei, Wangyang; Wu, Qingtao

doi:10.14257/ijsia.2015.9.9.21

Cited by 10 publications

(6 citation statements)

References 25 publications

(16 reference statements)

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“…A CIoT is an IoT with cognitive capability which is integrated to promote performance and achieve intelligence. Given that there is a business process flow corresponding to a given application, CIoT comprehends current business types and network conditions, analyzes the perceived information based on the prior knowledge, makes intelligent decisions, and performs adaptive and control actions, aiming to maximize network performance and meet the application requirements [ 71 ].…”

Section: Other Names Given To the Iotmentioning

confidence: 99%

Tracking the Evolution of the Internet of Things Concept Across Different Application Domains

Ibarra-Esquer

González-Navarro

Flores-Ríos

et al. 2017

Sensors

128

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Both the idea and technology for connecting sensors and actuators to a network to remotely monitor and control physical systems have been known for many years and developed accordingly. However, a little more than a decade ago the concept of the Internet of Things (IoT) was coined and used to integrate such approaches into a common framework. Technology has been constantly evolving and so has the concept of the Internet of Things, incorporating new terminology appropriate to technological advances and different application domains. This paper presents the changes that the IoT has undertaken since its conception and research on how technological advances have shaped it and fostered the arising of derived names suitable to specific domains. A two-step literature review through major publishers and indexing databases was conducted; first by searching for proposals on the Internet of Things concept and analyzing them to find similarities, differences, and technological features that allow us to create a timeline showing its development; in the second step the most mentioned names given to the IoT for specific domains, as well as closely related concepts were identified and briefly analyzed. The study confirms the claim that a consensus on the IoT definition has not yet been reached, as enabling technology keeps evolving and new application domains are being proposed. However, recent changes have been relatively moderated, and its variations on application domains are clearly differentiated, with data and data technologies playing an important role in the IoT landscape.

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Section: Other Names Given To the Iotmentioning

confidence: 99%

Tracking the Evolution of the Internet of Things Concept Across Different Application Domains

Ibarra-Esquer

González-Navarro

Flores-Ríos

et al. 2017

Sensors

128

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“…Therefore, it can be seen from Figure 4 that the first node death time and network death time of R-bUCRP are significantly later than those of the LEACH protocol, EEUC protocol, and MADSEC protocol. compute and following (8) and 9 give up the competition and become a normal node (17) end if For every normal node (18) if is in one cluster coverage (19) apply to join into the cluster (19) pay reputation value to the cluster head (20) else (21) select cluster following (10) (22) pay reputation value to the cluster head (23) end if Algorithm 1: Cluster establishment. consumption rate by using R-bUCRP is significantly smaller than the other three kinds of protocols, and the network has a longer survival time, with the better network quality.…”

Section: Results Analysismentioning

confidence: 99%

“…The thought of cognition promoted the development of network intelligence greatly. Cognitive radio network [2,3], cognitive network [4][5][6], and Cognitive Internet of Things [7,8] have greatly interested the researchers, and large numbers of achievements have been attained, which greatly promoted the evolution of network intelligence.…”

Section: Introductionmentioning

confidence: 99%

R-bUCRP: A Novel Reputation-Based Uneven Clustering Routing Protocol for Cognitive Wireless Sensor Networks

et al. 2016

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Energy of nodes is an important factor that affects the performance of Wireless Sensor Networks (WSNs), especially in the case of existing selfish nodes, which attracted many researchers’ attention recently. In this paper, we present a reputation-based uneven clustering routing protocol (R-bUCRP) considering both energy saving and reputation assessment. In the cluster establishment phase, we adopt an uneven clustering mechanism which controls the competitive scope of cluster head candidates to save the energy of WSNs. In the cluster heads election phase, the residual energy and reputation value are used as the indexes to select the optimal cluster head, where the reputation mechanism is introduced to support reputation assessment. Simulation results show that the proposed R-bUCRP can save node energy consumption, balance network energy distribution, and prolong network lifetime.

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“…The Cognitive internet of things is known as a network or an environment in which everyone and everything is connected, also nowadays is considered that the Internet of Things is growing rapidly, with more devices connected every day [14]. Based on the LIDA research [15] and SOAR research [16] mentioned it is also considered in the existence of different types of structures based on prominent agents and architectures in cognitive systems.…”

Section: Cognitive Iot Architecturementioning

confidence: 99%

CIoT-Net: a scalable cognitive IoT based smart city network architecture

Park

Salim

et al. 2019

Hum. Cent. Comput. Inf. Sci.

102

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In the recent era, artificial intelligence (AI) is being used to support numerous solutions for human beings, such as healthcare, autonomous transportation, and so on. Cognitive computing is represented as a next-generation application AI-based solutions which provide human–machine interaction with personalized interactions and services that imitate human behavior. On the other hand, a large volume of data is generated from smart city applications such as healthcare, smart transportation, retail industry, and firefighting. There is always a concern on how to efficiently manage the large volume of generated data. Recently many existing researches discussed the analysis of the large quantity of data using cognitive computing; however, these researches are failed to handle the certain problems, namely scalability, and flexibility of data gathered in a smart city environment. Data captured from millions of sensors can be cross implemented across various cognitive computing applications to ensure real-time responses. In this paper, we study the cognitive internet of things (CIoT) and propose a CIoT-based smart city network (CIoT-Net) architecture which describes how data gathered from smart city applications can be analyzed using cognitive computing and handle the scalability and flexibility problems. We discuss various technologies such as AI and big data analysis to implement the proposed architecture. Finally, we describe the possible research challenges and opportunities while implementing the proposed architecture.

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A Novel Architecture for Cognitive Internet of Things

Cited by 10 publications

References 25 publications

Tracking the Evolution of the Internet of Things Concept Across Different Application Domains

Tracking the Evolution of the Internet of Things Concept Across Different Application Domains

R-bUCRP: A Novel Reputation-Based Uneven Clustering Routing Protocol for Cognitive Wireless Sensor Networks

CIoT-Net: a scalable cognitive IoT based smart city network architecture

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