Effect of Size of Giant Component for actor node selection in WSANs: A comparison study

Elmazi, Donald; Cuka, Miralda; Ikeda, Makoto; Barolli, Leonard

doi:10.1002/cpe.5106

Cited by 3 publications

(3 citation statements)

References 38 publications

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“…In the paper “Effect of Size of Giant Component for actor node selection in WSANs: A comparison study” by D. Elmazi, M. Cuka, M. Ikeda, and L. Barolli two Fuzzy Based Systems FBS1 & FBS2 for actor selection in WSANs were presented. The proposed systems decided whether the person will be selected for the required job/or not, based on information supplied by sensors and condition.…”

Section: The Main Topics Of Coginnov 2018 Special Issuementioning

confidence: 99%

Cognitive and innovative computation paradigms for big data and cloud computing applications

Ogiela

2019

Concurrency and Computation

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Section: The Main Topics Of Coginnov 2018 Special Issuementioning

confidence: 99%

Cognitive and innovative computation paradigms for big data and cloud computing applications

Ogiela

2019

Concurrency and Computation

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“…In recent years, centrality analysis, a kind of network analysis tool, has been applied in the area of Internet of Things (IoT) and can be used to analyze the topology of the IoT network. For example, closeness centrality can be chosen as the measurement for IoT device selection by identifying the central nodes in the dynamic IoT network [1]. However, if attackers use centrality analysis to find the important nodes in the IoT network, they can launch more accurate attacks such as DDoS attacks or deceive the important nodes to spread fraudulent information in the network [2].…”

Section: Introductionmentioning

confidence: 99%

Heuristic Approaches for Enhancing the Privacy of the Leader in IoT Networks

Shuai

et al. 2019

Sensors

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The privacy and security of the Internet of Things (IoT) are emerging as popular issues in the IoT. At present, there exist several pieces of research on network analysis on the IoT network, and malicious network analysis may threaten the privacy and security of the leader in the IoT networks. With this in mind, we focus on how to avoid malicious network analysis by modifying the topology of the IoT network and we choose closeness centrality as the network analysis tool. This paper makes three key contributions toward this problem: (1) An optimization problem of removing k edges to minimize (maximize) the closeness value (rank) of the leader; (2) A greedy (greedy and simulated annealing) algorithm to solve the closeness value (rank) case of the proposed optimization problem in polynomial time; and (3)UpdateCloseness (FastTopRank)—algorithm for computing closeness value (rank) efficiently. Experimental results prove the efficiency of our pruning algorithms and show that our heuristic algorithms can obtain accurate solutions compared with the optimal solution (the approximation ratio in the worst case is 0.85) and outperform the solutions obtained by other baseline algorithms (e.g., choose k edges with the highest degree sum).

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“…Different to our other published works [16][17][18], in this work we have added Number of Sensors per Actor (NSA) and Transmission Range (TR) to make the comparison between two fuzzy-based systems and also to evaluate the simulation results of one of the systems with the experimental results.…”

Section: Introductionmentioning

confidence: 99%

Application of Fuzzy Logic for Selection of Actor Nodes in WSANs —Implementation of Two Fuzzy-Based Systems and a Testbed

Elmazi

Cuka

Ikeda

et al. 2019

Sensors

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The development of sensor networks and the importance of smart devices in the physical world has brought attention to Wireless Sensor and Actor Networks (WSANs). They consist of a large number of static sensors and also a few other smart devices, such as different types of robots. Sensor nodes have responsibility for sensing and sending information towards an actor node any time there is an event that needs immediate intervention such as natural disasters or malicious attacks in the network. The actor node is responsible for processing and taking prompt action accordingly. But in order to select an appropriate actor to do one task, we need to consider different parameters, which make the problem NP-hard. For this reason, we consider Fuzzy Logic and propose two Fuzzy Based Simulation Systems (FBSS). FBSS1 has three input parameters such as Number of Sensors per Actor (NSA), Remaining Energy (RE) and Distance to Event (DE). On the other hand, FBSS2 has one new parameter—Transmission Range (TR)—and for this reason it is more complex. We will explain in detail the differences between these two systems. We also implement a testbed and compare simulation results with experimental results.

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Effect of Size of Giant Component for actor node selection in WSANs: A comparison study

Cited by 3 publications

References 38 publications

Cognitive and innovative computation paradigms for big data and cloud computing applications

Cognitive and innovative computation paradigms for big data and cloud computing applications

Heuristic Approaches for Enhancing the Privacy of the Leader in IoT Networks

Application of Fuzzy Logic for Selection of Actor Nodes in WSANs —Implementation of Two Fuzzy-Based Systems and a Testbed

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