scholarly journals Design and performance evaluation of Improved DFACO protocol based on dynamic clustering in VANETs

2021 ◽  
Vol 3 (4) ◽  
Author(s):  
Sahar Ebadinezhad
Keyword(s):  
Performance Evaluation ◽  
Ant Colony Optimization ◽  
Routing Protocols ◽  
Clustering Algorithm ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Clustering Algorithms ◽  
Cluster Head ◽  
Ant Colony ◽  
Minimum Number

AbstractThis study focuses on Vehicular Ad-hoc Networks (VANETs) stability in an environment that is dynamic which often leads to major challenges in VANETs, such as dynamic topology changes, shortest routing paths and also scalability. One of the best solutions for such challenges is clustering. In this study, we present five novel routing protocols based on Dynamic Flying Ant Colony Optimization (DFACO) algorithm to achieve minimum number of clusters, high accuracy, minimum time and solution cost by selecting the best cluster-head which is obtained from a new mechanism of dynamic metaheuristic-based clustering. In this regard, major improvements are applied on classical DFACO by adjusting the procedure for updating the pheromone and tuning the evaporation rate that has a major role in DFACO. In this research two individual phases of experiments are conducted for performance evaluation of proposed routing protocols. The presented solution is verified and compared to classic Ant Colony Optimization (ACO), DFACO and ACO Based Clustering Algorithm for VANET (CACONET) algorithms in phase one; and compared to clustering algorithms such as Center Position and Mobility CPM), Highest-Degree algorithm (HD), Angle-based Clustering Algorithm (ACA) in phase two through NS-2 and SUMO simulation tools. Simulation results have confirmed the expected behaviour and show that our proposed protocols achieve better node connectivity and cluster stability than the former.

scholarly journals A Simple Ant Colony Optimization Algorithm to Select Cluster Heads in Ad Hoc Networks

2018 ◽  
Author(s):  
Mahboobeh Parsapoor ◽  
Urban Bilstrup
Keyword(s):  
Ad Hoc Networks ◽  
Ant Colony Optimization ◽  
Clustering Algorithm ◽  
Ad Hoc ◽  
Clustering Algorithms ◽  
Cluster Head ◽  
Ant Colony ◽  
Ant Colony Optimization Algorithm ◽  
Cluster Heads ◽  
Hoc Networks

Forming a clustered network structure has been proposed as a solution to increase network performance, scalability, stability and manageability in an ad hoc network. A good clustering algorithm aims to select cluster heads among available nodes so that a number of specific constraints are satisfied; thus the cluster head selection problem is a multiobjective optimization problem. This paper proposes an algorithm on the basis of ant colony optimization (ACO) to be used to solve this problem. The proposed algorithm is a simple, one hop cluster formation algorithm, to form a clustered structure with the minimum number of clusters. The centralized ACO-based clustering algorithm is evaluated and compared with other clustering algorithms in ad hoc networks in terms of cluster density.

scholarly journals Intelligent clustering using moth flame optimizer for vehicular ad hoc networks

2019 ◽  
Vol 15 (1) ◽  
pp. 155014771882446 ◽  
Author(s):  
Atif Ishtiaq ◽  
Sheeraz Ahmed ◽  
Muhammad Fahad Khan ◽  
Farhan Aadil ◽  
Muazzam Maqsood ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Ad Hoc Networks ◽  
Ant Colony Optimization ◽  
Clustering Algorithm ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Particle Swarm ◽  
Ant Colony ◽  
Swarm Optimization ◽  
Hoc Networks

Vehicular ad hoc networks consist of access points for communication, transmission, and collecting information of nodes and environment for managing traffic loads. Clustering can be performed in the vehicular ad hoc networks for achieving the desired goals. Due to the random range of vehicular ad hoc networks, stability is the major issue on which major research is still in progress. In this article, a moth flame optimization–driven clustering algorithm is presented for vehicular ad hoc networks, replicating the social behavior of moth flames in creating efficient clusters. The proposed framework is extracted from the living routine of moth flames. The proposed framework allows efficient communication by creating the augmented number of clusters due to which it is termed as intelligent algorithm. Besides this, the use of unsupervised clustering technique emphasizes to call it as an intelligent clustering algorithm. The recommended intelligent clustering using moth flame optimization framework is executed for resolving and optimizing the clustering problem in vehicular ad hoc networks, the primary focus of the proposed scheme is to improve the stability in vehicular ad hoc networks. This proposed method can also be used for the transmission of data in vehicular networks. Intelligent clustering using moth flame optimization is then proved by relative study with two variants of particle swarm optimization: multiple-objective particle swarm optimization and comprehensive learning particle swarm optimization and a variant of ant colony optimization: ant colony optimization–based clustering algorithm for vehicular ad hoc network. The simulation demonstrates that the intelligent clustering using moth flame optimization is provisioning optimal outcomes in contrast to widely known metaheuristics. Furthermore, it provides a robust routing mechanism based on the clustering. It is suitable for large highways for the productivity of quality communication, reliable delivery for each vehicle and can be widely applicant.

(SET) Smart Energy Management and Throughput Maximization

2017 ◽  
pp. 1-28 ◽  
Author(s):  
Hassan El Alami ◽  
Abdellah Najid
Keyword(s):  
Energy Management ◽  
Routing Protocols ◽  
Clustering Algorithm ◽  
Cluster Formation ◽  
Clustering Algorithms ◽  
Cluster Head ◽  
Base Station ◽  
Throughput Maximization ◽  
Cluster Heads ◽  
Smart Energy Management

Energy efficiency and throughput are critical factors in the design routing protocols of WSNs. Many routing protocols based on clustering algorithm have been proposed. Current clustering algorithms often use cluster head selection and cluster formation to reduce energy consumption and maximize throughput in WSNs. In this chapter, the authors present a new routing protocol based on smart energy management and throughput maximization for clustered WSNs. The main objective of this protocol is to solve the constraint of closest sensors to the base station which consume relatively more energy in sensed information traffics, and also decrease workload on CHs. This approach divides network field into free area which contains the closest sensors to the base station that communicate directly with, and clustered area which contains the sensors that transmit data to the base station through cluster head. So due to the sensors that communicate directly to the base station, the load on cluster heads is decreased. Thus, the cluster heads consume less energy causing the increase of network lifetime.

scholarly journals Efficient and Reliable Cluster-Based Data Transmission for Vehicular Ad Hoc Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Xiang Ji ◽  
Huiqun Yu ◽  
Guisheng Fan ◽  
Huaiying Sun ◽  
Liqiong Chen
Keyword(s):  
Routing Protocol ◽  
Data Transmission ◽  
Intelligent Transportation Systems ◽  
Clustering Algorithm ◽  
Vehicular Ad Hoc Networks ◽  
Ad Hoc ◽  
Cluster Formation ◽  
Cluster Head ◽  
Sampling Strategy ◽  
Transportation Systems

Vehicular ad hoc network (VANET) is an emerging technology for the future intelligent transportation systems (ITSs). The current researches are intensely focusing on the problems of routing protocol reliability and scalability across the urban VANETs. Vehicle clustering is testified to be a promising approach to improve routing reliability and scalability by grouping vehicles together to serve as the foundation for ITS applications. However, some prominent characteristics, like high mobility and uneven spatial distribution of vehicles, may affect the clustering performance. Therefore, how to establish and maintain stable clusters has become a challenging problem in VANETs. This paper proposes a link reliability-based clustering algorithm (LRCA) to provide efficient and reliable data transmission in VANETs. Before clustering, a novel link lifetime-based (LLT-based) neighbor sampling strategy is put forward to filter out the redundant unstable neighbors. The proposed clustering scheme mainly composes of three parts: cluster head selection, cluster formation, and cluster maintenance. Furthermore, we propose a routing protocol of LRCA to serve the infotainment applications in VANET. To make routing decisions appropriate, we nominate special nodes at intersections to evaluate the network condition by assigning weights to the road segments. Routes with the lowest weights are then selected as the optimal data forwarding paths. We evaluate clustering stability and routing performance of the proposed approach by comparing with some existing schemes. The extensive simulation results show that our approach outperforms in both cluster stability and data transmission.

scholarly journals Swarm Intelligence based efficient routing algorithm for platooning in VANET through Ant Colony Optimization

2019 ◽  
Vol 8 (9) ◽  
pp. 1238-1244
Keyword(s):  
Ant Colony Optimization ◽  
Swarm Intelligence ◽  
Routing Protocols ◽  
Ad Hoc ◽  
Routing Algorithm ◽  
Optimization Technique ◽  
Ant Colony ◽  
Delivery Ratio ◽  
Average Delay ◽  
Size Number

Today’s era is of smart technology, Computing intelligence and simulations. Many areas are now fully depended on simulation results for implementing real time workflow. Worldwide researchers and many automobile consortium are working to make intelligent Vehicular Ad hoc Network but till yet it is just a theory-based permutation. If we take VANET routing procedures then it is mainly focussing on AODV, DSDV and DSR routing protocols. Similarly, one more area of Swarm Intelligence is also attained attention of industry and researchers. Due the behavior of dynamic movement of vehicle and ants, Ant Colony Optimization is best suited for VANET performance simulations. Much of the work has already done and in progress for routing protocols in VANET but not focused on platooning techniques of vehicle nodes in VANET. In our research idea, we came up with a hypothesis that proposes efficient routing algorithm that made platooning in VANET optimized by minimizing the average delay waiting and stoppage time. In our methodology, we have used OMNET++, SUMO, Veins and Traci for testing of our hypothesis. Parameters that we took into consideration are end-to-end delay as an average, packet data delivery ratio, throughput, data packet size, number of vehicle nodes etc. Swarm Intelligence has proved a way forward in VANET scenarios and simulation for more accurate results. In this paper, we implemented Ant Colony Optimization technique in VANET simulation and proved through results that if it integrates with VANET routing scenarios then result will be at its best.

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