Secure and energy efficient MANET routing incorporating trust values using hybrid ACO

Prabaharan, S. Beski; Ponnusamy, R.

doi:10.1109/iccci.2016.7479933

Cited by 12 publications

(6 citation statements)

References 24 publications

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“…Where T represents the threshold value, Q is the pheromone strength,n is the total number of ants. the path length of the mth ant, _ represents the coefficient of the Pheromone volatilization [10]. volatilization, _ 2 (0; 1) .…”

Section: Pheromone Update Strategymentioning

confidence: 99%

“…However, this distance affects the network energy consumption. Within the communication range choosing the node closer to the sink node the smaller total energy consumption of the network will be reached [10]. Thus the heuristic information should not only consider the distance to the next node but also the distance to the sink.…”

Section: Pheromone Update Strategymentioning

confidence: 99%

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The Spectrum Sensing and Path Optimization Techniques in Cognitive Radio Networks

Gadiparthi¹,

Bathina²,

Emani³

et al. 2019

IJITEE

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Cognitive Radio (CR) is a versatile, insightful radio and system innovation that can naturally recognize accessible directs in a remote range and change transmission parameters empowering more interchanges to run simultaneously and furthermore improve radio working conduct. The primary thought of the intellectual system is to give the range band to the unlicensed clients without making any damage to the earth. By utilizing the recurrence range band, we came to utilization of these intellectual systems. Right off the bat, we have to frame the system through any methodologies .we are utilizing optimization Mechanisms for path identification in cognitive Radio.

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Section: Pheromone Update Strategymentioning

confidence: 99%

Section: Pheromone Update Strategymentioning

confidence: 99%

The Spectrum Sensing and Path Optimization Techniques in Cognitive Radio Networks

Gadiparthi¹,

Bathina²,

Emani³

et al. 2019

IJITEE

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show abstract

“…However, ACECR does not guarantee that the total transmission power is minimized over a chosen route. The literature [ 24 ] used the simulated annealing algorithm (SA) to find the global optimal path, combining SA with ACO. The algorithm first selects the next hop node with SA, and then updates the pheromone with the rule of ACO.…”

Section: Introductionmentioning

confidence: 99%

“…In summary, the literature [ 17 , 24 , 25 ] just improved the convergence speed of the algorithm, while the literatures [ 20 , 22 , 23 ] only improved the energy aspect of the node. Aiming at these problems, in this paper, from the perspective of topology-based routing protocols, considering the mobility and energy-constrained features of nodes, the ant colony optimization algorithm is used to design routing protocols.…”

Section: Introductionmentioning

confidence: 99%

Energy-Balanced Routing Algorithm Based on Ant Colony Optimization for Mobile Ad Hoc Networks

Yang

Xia

et al. 2018

Sensors

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The mobile ad hoc network (MANET) is a multi-hop, non-central network composed of mobile terminals with self-organizing features. Aiming at the problem of extra energy consumption caused by node motion in MANETs, this paper proposes an improved energy and mobility ant colony optimization (IEMACO) routing algorithm. Firstly, the algorithm accelerates the convergence speed of the routing algorithm and reduces the number of route discovery packets by introducing an offset coefficient of the transition probability. Then, based on the energy consumption rate, the remaining lifetime of nodes (RLTn) is considered. The position and velocity information predicts the remaining lifetime of the link (RLTl). The algorithm combines RLTn and RLTl to design the pheromone generation method, which selects the better quality path according to the transition probability to ensure continuous data transmission. As a result, the energy consumption in the network is balanced. The simulation results show that compared to the Ad Hoc on-demand multipath distance vector (AOMDV) algorithm with multipath routing and the Ant Hoc Max-Min-Path (AntHocMMP) algorithm in consideration of node energy consumption and mobility, the IEMACO algorithm can reduce the frequency of route discovery and has lower end-to-end delay as well as packet loss rate especially when nodes move, and can extend the network lifetime.

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“…Hybrid ACO Recently, S. B. Prabaharan and R. Ponnusamy [74] have proposed a hybrid ACO routing protocol that emphasizes the security and energy efficiency. This protocol is abbreviated as Hybrid ACO from here on.…”

Section: Eaarmentioning

confidence: 99%

A Security Aware Fuzzy Enhanced ACO Routing Protocol in MANETs

Zhang¹

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As Mobile Ad hoc NETworks (MANETs) grow more popular and are deployed as solutions in various applications such as road safety in Vehicular Ad hoc NETworks (VANETs), wildlife tracking in Wireless Sensor Networks (WSNs) and Device-to-Device (D2D) communications in 5G, the need for efficient routing that is robust against malfunctioning or malicious network nodes is increasing. A fuzzy logic enhanced Ant Colony Optimization (ACO)-based routing algorithm, which addresses these issues, is proposed in this thesis. The Security Aware Fuzzy Enhanced Ant Colony Optimization (SAFEACO) routing protocol makes use of a distributed fuzzy logic module to identify misbehaving nodes and exclude them from the routing process. The SAFEACO routing protocol is implemented in the NS-3 simulator and various experiments have been performed in both MANET and VANET scenarios. The performance of SAFEACO is compared with other modern and widely known approaches. Simulation results show that SAFEACO has superior performance in all relevant metrics, such as packet delivery ratio (PDR) and end-to-end delay. Due to its ability to identify misbehaving nodes, SAFEACO also provides a higher level of robustness against black hole, Sybil and flooding attacks.

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Secure and energy efficient MANET routing incorporating trust values using hybrid ACO

Cited by 12 publications

References 24 publications

The Spectrum Sensing and Path Optimization Techniques in Cognitive Radio Networks

The Spectrum Sensing and Path Optimization Techniques in Cognitive Radio Networks

Energy-Balanced Routing Algorithm Based on Ant Colony Optimization for Mobile Ad Hoc Networks

A Security Aware Fuzzy Enhanced ACO Routing Protocol in MANETs

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