A survey on ACO based multipath routing algorithms for ad hoc networks

Sharma, Ishu; Ramkumar, K.

doi:10.1108/ijpcc-d-17-00015

Cited by 13 publications

(3 citation statements)

References 21 publications

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“…The heuristic function for finding the probability of selection of nodes is proposed (25) . The formula to evaluate the total pheromone concentration of the path covering next vehicle is explained (26) .The real-world ants smell and deposit pheromone wherever they travel, while artificial ants update artificial pheromone during round trip time only (27) . An ACO-based algorithm was proposed by combining reactive and proactive scheme.…”

Section: Ant Colony Optimizationmentioning

confidence: 99%

Implementation of ACO in Vanet with Detection of Faulty Node

Faisal¹,

Zaidi²

2021

IJST

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Objective: To propose an Ant Colony Optimization (ACO) based routing approach for estimating the reliability parameter of backward and forward ants. Methods: The ACO-based proposed methodology is used to predict path or route discovery in VANET. This study has discovered the best optimal path for data transmission. The forward ant movement has a minimum hop count of four for vehicle number 6. The vehicle 6 is a source vehicle, and it starts data transmission. The pheromone concentration of the entire vehicle defers and, after updating, the performance was analyzed. The best path is selected based on hop count, then a path with maximum pheromone concentration is selected. The pheromone evaporation factor is updated after a certain time interval. Findings: We have checked the reliability of the path, considering pheromone evaporation as a factor, the pheromone table is updated at a regular time interval, and the reliability parameter is also proposed for performing a task without failure in an efficient manner. We have arranged a routing table in descending order of hop count and then select the best of three paths with a minimum hop count. We search for hop count less than or equal to 5 and total pheromone greater than or equal to 17.55. We find that Ant 3 having a hop count of 5 and total pheromone concentration of 19.37. In this work, we have taken the evaporation factor as 0.5. If the transmission of a message is successful, then the reliability assigned to the edge will be 100, and for unsuccessful transmission, reliability is taken down by 20. If the reliability of the path will become 40, then the vehicle has to search for a new path. In this way, we eliminate malicious nodes for efficient transmission of message. Novelty: The performance of VANET is improved using ACO based proposed routing approach. The optimal path is selected with a minimum hop count and reliability parameter to identify the successful and unsuccessful path.

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Section: Ant Colony Optimizationmentioning

confidence: 99%

Implementation of ACO in Vanet with Detection of Faulty Node

Faisal¹,

Zaidi²

2021

IJST

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“…Our proposed protocol DPIDA relays on ant-colony-optimization (ACO) metaheuristic. This last is widely used in the context of WSNs (Saleem et al, 2011;Zungeru et al, 2012;Liu, 2017;Sharma and Ramkumar, 2017;Guleria and Anil, 2018) and is based on the cooperative and self-organized work of simple agents, that allow, through their local behavior, to emerge solutions to optimization problems without the intervention of any central entity. DPIDA borrows some ideas from an already proposed protocol, called CSTMAN (Shen et al, 2008) that aims to resolve this same problem of the constrained Steiner tree, and introduces others that improve this last regarding different elements.…”

Section: Wireless Sensor Network 97mentioning

confidence: 99%

Ant-based delay-bounded and power-efficient data aggregation in wireless sensor networks

Benaouda

Lahlouhi

2019

IJPCC

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Purpose The purpose of this paper is to present a novel delay-bounded and power-efficient routing for in-network data aggregation, called DPIDA, which aims to ensure a compromise between the energy consumed during the collection of data sensed by a set of source sensor nodes and their timely delivery to the sink node. Design/methodology/approach Based on the ant-colony-optimization metaheuristic, the proposal establishes a routing structure that maximizes the number of overlapping routes and minimizes the total transmission power while ensuring delay-bounded paths and a symmetric transmission power assignment to reliably deliver the sensed data. Findings The proposal was extensively compared to two other known protocols regarding different keys factors. Simulation results, including topology snapshots, show the ability of DPIDA to ensure the energy–latency tradeoff. They also show the superiority of DPIDA compared to the two considered protocols. Originality/value This paper presents a novel ant-based protocol that uses in-network data aggregation and transmission power-adjustment techniques to conserve the energy of nodes while ensuring delay-bounded paths and a reliable deliverance of data which is ensured by providing a symmetric transmission power assignment.

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“…ACO as a swarm intelligence algorithm has been used for the MANET routing task by many researchers [15,16]. The ACO algorithms' capabilities fit well with the MANET routing requirements, which are mainly: (1) the presence of autonomous agents trying to reach some physical target; and (2) the absence of any central administration entity in the network that controls the agents' search process.…”

Section: Introductionmentioning

confidence: 99%

Tuning the Evaporation Parameter in ACO MANET Routing Using a Satisfaction-Form Game-Theoretic Approach

2022

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A Mobile Ad Hoc Network (MANET) is a communication network that links communicating devices (nodes) and does not contain permanent infrastructure. There are no dedicated routing devices in MANETs, where the routing task is assigned to a routing algorithm installed on all communicating nodes. In this work, communicating nodes utilize one of the most widely used algorithms: Ant Colony Optimization (ACO) routing algorithms. The ACO algorithms aim to balance between exploring new routes for the communication packets vs. utilizing the best-known routes discovered during the communication session. Achieving the optimality in this tradeoff is traditionally set manually by assigning many values to some parameters and measuring the network performance after the simulation session. This manual optimality tuning approach depends on human intuition and does not cope with MANET's dynamic topology. In this research, we introduce a novel method to find an optimal balance for the exploration-exploitation tradeoff during the communication session. We formulate weighing the benefits of exploring new routes vs. exploiting known ones upon the MANET performance as a game between the two semantic players. This equilibrium is reflected as an optimal value for the pheromone evaporation parameter of the ACO algorithm during the communication session. Experimental results show a higher performance of this online tuning algorithm than the traditional offline tuning algorithms.

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A survey on ACO based multipath routing algorithms for ad hoc networks

Cited by 13 publications

References 21 publications

Implementation of ACO in Vanet with Detection of Faulty Node

Implementation of ACO in Vanet with Detection of Faulty Node

Ant-based delay-bounded and power-efficient data aggregation in wireless sensor networks

Tuning the Evaporation Parameter in ACO MANET Routing Using a Satisfaction-Form Game-Theoretic Approach

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