Type II fuzzy-based clustering with improved ant colony optimization-based routing (t2fcatr) protocol for secured data transmission in manet

Nagendranth, M V S S; Khanna, M. Rajesh; Krishnaraj, N.; Sikkandar, Mohamed Yacin; Aboamer, Mohamed Abdelkader; Surendran, R

doi:10.1007/s11227-021-04262-w

Cited by 16 publications

(10 citation statements)

References 21 publications

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“…Aiming at the blindness and relatively slow convergence speed in path planning search, Zhai et al [37] proposed an improved ACO algorithm based on artificial potential field and quantum evolution theory. Nagendranth et al [38] proposed a new algorithm based on type II fuzzy-based clustering with improved ACO algorithm based routing protocol for secure data transmission in manet. Optimizing ACO algorithm to solve the standard TSP, Zeng et al [39] proposed a more general replenishment arc TSP.…”

Section: Improved Aco Algorithmmentioning

confidence: 99%

An optimized resource scheduling algorithm based on GA and ACO algorithm

Yin

Peng

et al. 2023

Preprint

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With the development of Internet of things (IoT) technology, fog computing has gradually come into people’s vision because of the characteristics of real-time and low delay. Providing computing and storage services at the edge of the network, fog computing can meet the needs of users in delay-sensitive applications as a highly virtualized platform. Resource scheduling plays an important role in fog computing, because it can meet the requirements of customers and improve the quality of service. However, if largescale service requests can not solve the resource scheduling problem effectively, it will reduce resource utilization and user satisfaction. Focus on the above problem, we establish a resource scheduling model named normalization processing, which can achieve the goal of the lowest total cost by finding the optimal pheromone. The optimal resource scheduling results can be obtained by changing the pheromone concentration of ants during the simulated foraging process. At the same time, we propose a new resource scheduling algorithm named new genetic ant colony optimization (NGACO) algorithm, which can update pheromone generation by roulette algorithm. The experimental results show that the resource scheduling performance of NGACO algorithm is 14.7%, 25%, 12.8% lower than that of ACO algorithm in makespan, economic cost, total cost respectively, and load balancing is 34.7% higher than ACO algorithm.

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Section: Improved Aco Algorithmmentioning

confidence: 99%

An optimized resource scheduling algorithm based on GA and ACO algorithm

Yin

Peng

et al. 2023

Preprint

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“…The topology of a mobile ad hoc network is constantly changing as nodes move [12]. The radio range of the other nodes in the ad hoc network is continually changing, requiring constant updating of the routing information [13]. MANET's have a wide range of applications, from large-scale moveable and dynamic networks to small networks constrained by their power supply.…”

Section: Literature Surveymentioning

confidence: 99%

“…To determine whether a packet should be sent or received locally, each node within that range must receive it. Even if the majority of these packets are discarded, they use energy under this basic energy model [13]. The capacity of the power management system to respond to variations in traffic load is reflected in the length of the soft-state timer.…”

Section: Literature Surveymentioning

confidence: 99%

Cooperative Channel and Optimized Route Selection in Adhoc Network

Manohari¹,

Kavitha²,

Periyakaruppan³

et al. 2023

Intelligent Automation &Amp; Soft Computing

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Over the last decade, mobile Adhoc networks have expanded dramatically in popularity, and their impact on the communication sector on a variety of levels is enormous. Its uses have expanded in lockstep with its growth. Due to its instability in usage and the fact that numerous nodes communicate data concurrently, adequate channel and forwarder selection is essential. In this proposed design for a Cognitive Radio Cognitive Network (CRCN), we gain the confidence of each forwarding node by contacting one-hop and second level nodes, obtaining reports from them, and selecting the forwarder appropriately with the use of an optimization technique. At that point, we concentrate our efforts on their channel, selection, and lastly, the transmission of data packets via the designated forwarder. The simulation work is validated in this section using the MATLAB program. Additionally, steps show how the node acts as a confident forwarder and shares the channel in a compatible method to communicate, allowing for more packet bits to be transmitted by conveniently picking the channel between them. We calculate the confidence of the node at the start of the network by combining the reliability report for the first hop and the reliability report for the secondary hop. We then refer to the same node as the confident node in order to operate as a forwarder. As a result, we witness an increase in the leftover energy in the output. The percentage of data packets delivered has also increased.

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“…Then, using the found optimum path, the encrypted DPs are sent from the sender to taget, and lastly, relayed to the base station. [27][28][29][30][31] Because of the constant node migration and the limited resources available, security management is a severe challenge [32][33][34][35][36][37]. Rekeying is only done for the so-called clusters of subnetworks to avoid having to repeatedly renew the group key for the entire wide network.…”

Section: Related Workmentioning

confidence: 99%

“…From this scenario, we can observe the efficacy of the proposed work in the presence of attackers. For comparison, two existing works such as PSO-Secure routing [30], and Fuzzy clustering [31] are considered. Both works have developed in the MANET environment.…”

Section: Comparative Analysismentioning

confidence: 99%

Blockchain-assisted Secure Routing Protocol for Cluster-based Mobile-ad Hoc Networks

Ilakkiya

Rajaram

2023

INT J COMPUT COMMUN, Int. J. Comput. Commun. Control

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MANETs aredecentralized network that involves mobile nodes. As the overall network is mobile and has no centralization, network management, routing, and security become very challenging. Though many works have been presented, still there is a lack in organizing the network due to unauthorized access, centralized security schemes, and the dynamic nature of the nodes. This paper proposed a novel Blockchain-assisted Secure Routing (Block-Sec) protocol for MANETs. All mobile nodes are authenticated by Distributed One-Time Passcode (DOT) based authorization scheme. All authorized nodes are segregated into multiple clusters based on Weight based Dynamic Clustering (WDC) algorithm in which multiple metrics are considered in clustering and re-clustering processes. After cluster formation, each cluster is elected with optimal Cluster Head (CH) by Strawberry Optimization (SBO) algorithm with a new objective function. After cluster formation, the optimal route is selected by Fast Neural Net-assisted Fuzzy (FNNF) algorithm by combining multiple variables. Data transmission is secured by Efficient Elliptic Curve (E2C2) algorithm. With the combined algorithms, the proposed approach obtainedimproved efficiency in packet delivery ratio (PDR), throughput, time analysis, and security level.

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Type II fuzzy-based clustering with improved ant colony optimization-based routing (t2fcatr) protocol for secured data transmission in manet

Cited by 16 publications

References 21 publications

An optimized resource scheduling algorithm based on GA and ACO algorithm

An optimized resource scheduling algorithm based on GA and ACO algorithm

Cooperative Channel and Optimized Route Selection in Adhoc Network

Blockchain-assisted Secure Routing Protocol for Cluster-based Mobile-ad Hoc Networks

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