EESSMT: An Energy Efficient Hybrid Scheme for Securing Mobile Ad hoc Networks Using IoT

Singh, Priyanka; Khari, Manju; Vimal, S.

doi:10.1007/s11277-021-08764-x

Cited by 21 publications

(23 citation statements)

References 37 publications

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“…The different existing techniques mainly taken for comparison are FSEE‐ADOV, 13 OEERA, 16 QoS‐AIHCRP, 19 OLSR, 31 and FAES‐AONDVP 14 . A brief description of these techniques is provided below:…”

Section: Resultsmentioning

confidence: 99%

Integrating interval type‐2 fuzzy logic and modified dingo optimization for node ranking and energy efficient MANET

Mamatha

Ramakrishna

2023

Trans Emerging Tel Tech

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In mobile ad hoc networks (MANET), the mobility of the node changes dynamically, thus affecting the stability of the connection and increasing energy consumption. The heterogeneity of the MANET nodes in terms of mobility, battery capacity, and processing capabilities often complicates the routing process and results in increased energy consumption and traffic overhead. To overcome the challenges associated with diverse MANET nodes, this article presents a hybrid interval type‐2 fuzzy logic controller and modified dingo optimization (IT2FLC‐MDO) algorithm‐based optimized link‐state routing protocol. In our proposed IT2FLC‐MDO algorithm, multiple Quality of Service (QoS) parameters (node distance, lifetime, residual energy, speed, queue length, etc) are integrated into a single multicriteria node metric to improve the multipath route analysis and topology formation. In this way, the need to broadcast multiple parameters for each session is reduced thus minimizing the control overhead. The proposed routing protocol mainly aims to achieve a tradeoff between the QoS metrics and energy consumption during data transmission, addresses the QoS and energy issues associated with multipath routing, and uses a multicriteria node metric. The proposed IT2FLC‐MDO protocol takes both the energy consumption and QoS parameters into account, thus achieving a balance between the energy consumption and QoS. The cluster head primarily chooses the path with the highest link quality to ensure reliable data transmission. The proposed IT2FLC‐MDO protocol's efficiency is demonstrated using several performance measures such as packet delivery ratio, average end‐to‐end delay, and normalized control overhead. The simulation results indicate that the proposed algorithm can handle MANET uncertainty while minimizing control overhead. The results show that the proposed algorithm offers a packet delivery rate nearly equal to 96% and improves the MANET's lifetime by up to 59%.

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Section: Resultsmentioning

confidence: 99%

Integrating interval type‐2 fuzzy logic and modified dingo optimization for node ranking and energy efficient MANET

Mamatha

Ramakrishna

2023

Trans Emerging Tel Tech

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“…The proposed scheme offers a higher throughput along with lower end-to-end delay and energy consumption. Furthermore, the rate of success of the proposed scheme is to guarantee and ensure that packet delivery to the destination is very high through multiple paths and in a more secured manner [18]. Vimal et al [19] proposed a hybrid model for mitigating jamming and energy monitoring using the MOACO model along with the double Q-learning model.…”

Section: Iot Monitoring Center Energy Consumption Modelingmentioning

confidence: 99%

“…The max-min ant algorithm used in this article updates the pheromone pair only when the virtual machine-server sequence pair has the minimum value of the objective function value. In Equation (18), FðS best Þ represents the objective function, which is the minimum number of servers that are in a working state after deployment. To avoid stagnation in the search, the value range of the pheromone trace quantity τ ij on each solution element is limited to the ½τ min , τ max interval.…”

Section: Updates On Pheromonesmentioning

confidence: 99%

Energy Consumption Optimization of an IoT Monitoring Center Based on a Max-Min Ant Colony Algorithm

Tong

2023

Wireless Communications and Mobile Computing

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As a result of the green IoT, application layer users are increasingly seeking more services, and it is particularly important to reduce the energy consumption of an IoT monitoring center while ensuring service reliability. In this paper, the max-min ant colony algorithm is proposed to effectively solve the problems of user service reliability and energy consumption optimization of an IoT monitoring center. First, the service reliability of the application layer users is modeled based on a Markov chain, and the quantitative reliability performance indicators are given. Second, an optimization model between the user service reliability and the energy consumption of an IoT monitoring center is established. Finally, the optimization problem is solved based on the improved max-min ant system. Simulation experimental results show that compared with the improved FFD algorithm, the average power consumption of the max-min ant colony algorithm can be reduced by up to 7.14%.

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“…The accessibility of network resources, integrity, confidentiality are dependent upon 92 Computer Science & Information Technology security processes 9 . The MANETs design enables them vulnerable to security attacks 10,11 . Even though several factors contribute to the vulnerability of MANETs, vulnerabilities come through insecure boundaries including compromised nodes 12,13 .…”

Section: Introductionmentioning

confidence: 99%

“…9 The MANETs design enables them vulnerable to security attacks. 10,11 Even though several factors contribute to the vulnerability of MANETs, vulnerabilities come through insecure boundaries including compromised nodes. 12,13 The feasible mode for lessening attacks is prevention measures, not security measures to eliminate attacks, which will necessitate more resources.…”

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confidence: 99%

Proficient link state routing in mobile ad hoc network‐based deep Q‐learning network optimized with chaotic bat swarm optimization algorithm

Rahul¹,

Kaarthick²

2022

Int J Communication

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Mobile ad-hoc network (MANET) is a category of ad-hoc network that can be reconfigurable its network. MANETS are self-organized networks, that can use the wireless links to connect various networks via mobile nodes: but it consumes more energy and it also has routing problems. This is the major drawback of being connected with the MANET technology. Therefore, this study proposes a new protocol as deep Q-learning network optimized with chaotic bat swarm optimization algorithm (CBS)-based optimized link state routing (OLSR) (CBS-OLSR) for MANET. This protocol reduces MANET energy usage and adopts OLSR multi-point relay (MPR) technology. MANET's OLSR and the CBS algorithm utilize a similar method to locate the best optimum path from source to destination node. By embedding the new improved deep Qlearning and OLSR algorithms, both are used for optimizing the MPR sets selection, it can efficiently diminish the energy consumption in the network topology, but automatically increase the lifespan of the network. It also enhances the package delivery ratio and decreases end-to-end delay. The experimental outcomes prove that the proposed protocol is reliable and proficient that is appropriate for numerous MANET applications. K E Y W O R D Schaotic bat swarm optimization, deep Q-learning algorithm, end-to-end delay, mobile adhoc network, MPR (multi-point relay), optimized link state routing, packet delivery rate | INTRODUCTIONMANET is an autonomous system that consists of individually connected set of self-configuring nodes that is implemented using a number of techniques, viz Bluetooth or WLAN. 1 The feature of MANET is autonomous, due to every node treating its host and router simultaneously. 2 To communicate among the distant nodes, they depend on direct communication with multi-hops. These advantages allow them to accommodate multiple nodes and decentralize management with its structure at any time. 3 Unlike other wireless systems, MANET has lack of central authority to monitor traffic transmission. 4 MANET systems have an infrastructure with a lesser configuration of corresponding nodes that are connected by wireless connections. The nodes are moving spontaneously or rather in a random section. 5 From node to network level, security in MANETs is important. 6 Owing to the dynamic nature of MANETs, there needs to be an acceptable level of trust. 7,8 Due to the dynamic nature and characteristics of MANETs, security on the MANET is more challenge

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EESSMT: An Energy Efficient Hybrid Scheme for Securing Mobile Ad hoc Networks Using IoT

Cited by 21 publications

References 37 publications

Integrating interval type‐2 fuzzy logic and modified dingo optimization for node ranking and energy efficient MANET

Integrating interval type‐2 fuzzy logic and modified dingo optimization for node ranking and energy efficient MANET

Energy Consumption Optimization of an IoT Monitoring Center Based on a Max-Min Ant Colony Algorithm

Proficient link state routing in mobile ad hoc network‐based deep Q‐learning network optimized with chaotic bat swarm optimization algorithm

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