Application Specific Node Deployment in WSN

Pillai, Meera R; Jain, Rekha

doi:10.1109/gcwcn.2018.8668617

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…It is assumed that N homogeneous IoT devices are randomly distributed in a two-dimensional area to form a MANET-IoT network, which is modeled as a graph sequence denoted by G as in [39]. Thus, the initial network at time point t 1 is modeled as the graph…”

Section: Network Model and Problem Formulationmentioning

confidence: 99%

Identification of Critical Nodes for Enhanced Network Defense in MANET-IoT Networks

Niu

et al. 2020

IEEE Access

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In heterogeneous environments, the Internet of Things (IoT) combined with mobile ad hoc network (MANET), i.e., MANET-IoT network, becomes more attractive to end users and economically successful. However, the introduction of MANET potentially makes the system more prone to attacks due to its lack of centralized management, weak connectivity, and resource constraints. To enhance the network robustness to intentional attacks, the critical nodes of the MANET-IoT network should be firstly identified and then protected. Most of the existing methods for identifying critical nodes usually focus on static networks or a single topology snapshot in dynamic networks without considering the correlation between topology snapshots, which cannot effectively deal with the dynamic changes in the topology of MANET-IoT networks. In this paper, a dynamic critical node identification (DCNI) method is proposed. First, we propose a comprehensive metric to measure the node importance in the topology snapshot. Then, we introduce a sliding time window to filter out the topology snapshots which have a close correlation with the current snapshot, and fuse the importance values of the same node in different topology snapshots. Finally, the critical nodes are selected based on the ranking result of fused importance. Thereafter, the port hopping mechanism could be applied to the critical nodes for enhancing network defense capability. The simulation results show that the proposed method is more effective in identifying critical nodes than existing static methods in MANET-IoT networks, and the port hopping mechanism can improve network defense significantly to denial of service (DoS) attacks.

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Section: Network Model and Problem Formulationmentioning

confidence: 99%

Identification of Critical Nodes for Enhanced Network Defense in MANET-IoT Networks

Niu

et al. 2020

IEEE Access

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“…Unfortunately, it suggests that only a network with such a topology will be able to prevent this potentially devastating attack. In (11), it was suggested that a TrueLink scheme be used to prevent wormhole attacks. TrueLink employs a time-based solution to the wormhole problem as well as other problems.…”

Section: Introductionmentioning

confidence: 99%

The Performance Analysis and Security Aspects of Manet

Singamaneni¹,

Alotaibi²,

K³

et al. 2022

ECS Trans.

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Mobile Ad hoc NETwork (MANET) is a type of network that is built by connecting a number of mobile devices together in a temporary manner through impermanent connections. Through broadcasting, the information should be distributed to all nodes in the network. A MANET is a network of self-configurable mobile nodes that are connected wirelessly. The security aspect of MANET is a major challenge, and there is a great deal of research being done in this area. The availability of energy is a critical criterion for a decentralised network. The protocol for AODV and DSR routing, as well as the security of the black hole node, are all investigated in this study. Protocols that are used during the route discovery process are particularly vulnerable to attack by the black hole. The goal of this survey, as a result, is to thoroughly investigate black hole attacks while also evaluating the performance of AODV and DSR during black hole attack scenarios. With Network Simulator 3, the work is completed by simulating both protocols under normal operation as well as under a black hole attack. The work is completed with Network Simulator 3 by simulating both protocols under a black hole attack (NS-3). AODV is more vulnerable to a black hole attack than the DSR, according to the results of simulations, and this vulnerability is greater under normal operating conditions. It has been discovered that MANET attacks are carried out with the assistance of a "black hole," according to simulation results.

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ESND-FA: An Energy-Efficient Scheduled Based Node Deployment Approach Using Firefly Algorithm for Target Coverage in Wireless Sensor Networks

Jaiswal,

Anand

2024

Int J Wireless Inf Networks

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Application Specific Node Deployment in WSN

Cited by 4 publications

References 12 publications

Identification of Critical Nodes for Enhanced Network Defense in MANET-IoT Networks

Identification of Critical Nodes for Enhanced Network Defense in MANET-IoT Networks

The Performance Analysis and Security Aspects of Manet

ESND-FA: An Energy-Efficient Scheduled Based Node Deployment Approach Using Firefly Algorithm for Target Coverage in Wireless Sensor Networks

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