An enhanced distance and residual energy‐based congestion aware ant colony optimization routing for vehicular ad hoc networks

Ramamoorthy, Raghu; Thangavelu, Menakadevi

doi:10.1002/dac.5179

Cited by 16 publications

(9 citation statements)

References 84 publications

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“…Ramamoorthy and Thangavelu [19] presented Enhanced Distance and Residual energy based Congestion Aware Ant Colony Optimization (EDR-CAACO) for discovering the optimum shortest path. The EDR-CAACO considered the vehicle's residual, distance and congestion levels for evaluating the pheromone levels.…”

Section: Related Workmentioning

confidence: 99%

“…The existing methods such as LARgeoOPT [17], DREAMgeoOPT [17], ZRPgeoOPT [17], EDR-CAACO [19] and IHS [20] are used to compare the efficiency of MDCEAEO-TAR. Here, the comparison is provided with two different cases.…”

Section: Comparative Analysismentioning

confidence: 99%

“…Table 2 and 3 shows the comparative analysis of the MDCEAEO-TAR for Case 1 and Case 2 respectively, where NA represents the values which are not available in those researches. From the tables, it is concluded that the MDCEAEO-TAR achieves better performance than the LARgeoOPT [17], DREAMgeoOPT [17], ZRPgeoOPT [17], EDR-CAACO [19] and IHS [20].…”

Section: Comparative Analysismentioning

confidence: 99%

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Traffic Aware Routing using Multi-Objective Delay Centric Enhanced Artificial Ecosystem-Based Optimization for VANET

2023

IJIES

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A vehicular Ad hoc Network (VANET) is generally a heterogeneous wireless network generated between vehicles. The vehicles of the VANET have wireless transceivers and computerized control for allowing the vehicles to operate as network nodes, hence the vehicles can communicate in a VANET environment. However, the communication of VANET is affected because of the higher network congestion and energy usage caused by the dynamic topology of VANET. Therefore, an effective Traffic-Aware Routing (TAR) approach is required to be developed to enhance communication. In this paper, the Multi-Objective Delay Centric Enhanced Artificial Ecosystem-based Optimization (MDCEAEO) is proposed to develop a TAR in VANET. The End to End Delay (EED) is considered as primary cost in the MDCEAEO to develop the TAR where a vehicle's average predicted speed is utilized for identifying the traffic in VANET. The developed MDCEAEO-TAR method is used to improve data transmission by avoiding collisions. The performances of MDCEAEO-TAR are evaluated using EED, energy consumption, Packet Delivery Ratio (PDR), and the routing overhead. The existing research such as LARgeoOPT, DREAMgeoOPT, ZRPgeoOPT, Improved Harmony Search (IHS) and Enhanced Distance, Residual energy based Congestion Aware Ant Colony Optimization (EDR-CAACO), Artificial Ecosystem-based Optimization (AEO), FixedStep Average and Subtraction Based Optimizer (FS-ASBO) and Three Influential Members Based Optimizer (TIMBO) are used to evaluate the MDCEAEO-TAR. The PDR of the MDCEAEO-TAR is 0.9836 at 1000s, which is high when compared to the IHS.

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Section: Related Workmentioning

confidence: 99%

Section: Comparative Analysismentioning

confidence: 99%

Section: Comparative Analysismentioning

confidence: 99%

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Traffic Aware Routing using Multi-Objective Delay Centric Enhanced Artificial Ecosystem-Based Optimization for VANET

2023

IJIES

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“…These switch hubs are organized in circles or rings. However, these plates are not actually shaped like a circle; they are by and large shut circles, which envelop the point of convergence of the area 34 …”

Section: Residual‐energy‐based Data Availability Approachmentioning

confidence: 99%

An improved optimal energy aware data availability approach for secure clustering and routing in wireless sensor networks

Roberts¹,

Thangavel²

2022

Trans Emerging Tel Tech

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Maintaining high residual energy is one of the major challenges of wireless sensor networks (WSNs), where nodes are moving at a random speed. In addition, data availability is also a major concern that must be maintained constantly during the packet transmission phase. In this research work, a Residual‐Energy‐Based Data Availability Approach (REDAA) for WSNs is developed to increase the network lifetime by focusing on the selection of stable routing paths and cluster heads. During the first phase of the work, the network model, and assumptions for route creations are adopted to effectively initialize the data transmission phase. During the second phase, a cluster was formed, and two categories of cluster heads were created based on quadrature low energy adaptive clustering hierarchy (Q‐LEACH) and multi‐hop low energy adaptive clustering (MH‐LEACH) algorithms to formalize the route and to make data available whenever requested. During the third phase, energy conservation routes are initialized, and data gathering is improved through slot‐based code division multiple access schemes. Simulation results demonstrate that the proposed REDAA approach can achieve an improvement in terms of throughput and energy consumption by 37% and 70% respectively when compared to MH‐LEACH approach, whereas in comparison to Q‐LEACH approach, these improvements are found to be 30% and 73% respectively.

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“…This technique guarantees reliable data transmission and is commonly used in routing problems. While previous studies have discussed ACO optimization for routing in TCP networks [17][18][19], this paper focuses on optimizing the flow of packets in a congested router by tuning the PI controller using the MOACO technique. Finally, the authors present a MATLAB simulation to demonstrate the performance of the proposed method (MOACO) for the PI-AQM control system.…”

Section: Introductionmentioning

confidence: 99%

Perspective Chapter: Enhancing Network Efficiency Using Ant Colony Optimization and Pareto Optimality for Tuning PI Controller in Congested Routers

Chebli

2023

Disturbance Rejection Control

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The objective of this manuscript is to stabilize the queue of the router congestion window by designing an active queue management (AQM). The problem is dealt with under the theory of the command by using the regulator PI for that purpose. The tuning of this controller is based on a new approach of stabilization that relies on an extension of Hermite-Biehler theorem applied to quasi-polynomials. This stabilization method turns out relevant to seek the optimized results achieved within this stability region. For that, the optimization is performed using an improved multi-objective ant colony optimization (ACO) algorithm. The performance of the proposed control scheme is evaluated via a series of numerical simulations in MATLAB and Simulink.

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An enhanced distance and residual energy‐based congestion aware ant colony optimization routing for vehicular ad hoc networks

Cited by 16 publications

References 84 publications

Traffic Aware Routing using Multi-Objective Delay Centric Enhanced Artificial Ecosystem-Based Optimization for VANET

Traffic Aware Routing using Multi-Objective Delay Centric Enhanced Artificial Ecosystem-Based Optimization for VANET

An improved optimal energy aware data availability approach for secure clustering and routing in wireless sensor networks

Perspective Chapter: Enhancing Network Efficiency Using Ant Colony Optimization and Pareto Optimality for Tuning PI Controller in Congested Routers

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