Colony Optimization Based Routing Protocol Research Articles

Congestion Detection and Alleviation Mechanism Using a Multi-Level Cluster Based Cuckoo Hosted Rider Search Multi-Hop Hierarchical Routing Protocol in Wireless Sensor Networks

Wireless sensor networks congestion occurs easily due to its centralized traffic pattern. Normally, mono-sync wireless sensor network experiences multiple traffic flow congestion in the dense environment of the network, which leads to excess energy consumption and severe packet loss. To overcome these issues, a congestion detection and alleviation mechanism using cluster based heuristic optimized hierarchical routing protocol is proposed in this paper. Here, congestion detection and alleviation utilize the features of sensor nodes. The congestion is categorized into two types: (i) node level congestion and (ii) link level congestion. The node level congestion is detected by assessing the buffer utilization and the interval amid the consecutive data packets. The link level congestion is considered with computing link usage utilizing back-off step of round robin carrier sense multi-access with collision avoidance. Congestion detection and alleviation reactively affected node/link through cuckoo hosted rider search multi-hop routing algorithm. It has two phases: the cluster head selection and multi-path routing. Cluster head selection is performed through Taylor multiple random forest kernel fuzzy C-means clustering algorithm and multi-path routing is performed through cuckoo hosted rider search multi-hop routing algorithm. The simulation of the proposed method is done in network simulator tool. Here, the performance metrics, like packet delivery ratio, delay, energy consumption, packet drop, overhead, network lifetime and throughput are calculated. The experimental outcomes of the proposed technique shows 11.6%, 18.4% and 28.1% lower delay, 78.2%, 65.4% and 52.6% higher packet delivery ratio, and 29.2%, 37.4% and 40.8% lower packet drop compared with the existing methods, like congestion detection and alleviation using multi-attribute decision-making in optimization-based hybrid congestion alleviation routing protocol in wireless sensor networks, congestion detection and alleviation using hybrid K-means with greedy best first search algorithms in packet rate reduction utilizing adaptive weight firefly algorithm ant colony optimization based routing protocol in wireless sensor networks and congestion detection and alleviation using multi-input time on task optimization algorithm for altered gravitational search algorithm routing protocol in wireless sensor networks.

An Optimal Route Discovery using Biogeography based Optimization for Vehicular Ad Hoc Networks

Vehicular ad hoc network (VANET) is a subdivision of the mobile ad hoc networks which uses the moving vehicles as mobile nodes to form the mobile network. In conventional vehicular communications, the restricted radio frequency bandwidth affects the network performances. Therefore, Visible Light Communication (VLC) is integrated with the growing vehicular ad hoc network to obtain high data rate and less energy consumption during the communication. In this paper, vehicular communication is integrated with visible light communication to avoid the issues caused by the restricted radio frequency bandwidth. Moreover, the Routing using Biogeography Based Optimization (RBBO) is proposed to develop an optimal route between the source vehicles to the destination. This research performs two different communications such as vehicle to vehicle and vehicle to the infrastructure. The performance of the RBBOVLC-VANET method is analyzed by means of throughput, packet delivery ratio, delay and routing overhead as well as these performances are compared with the existing method namely ant colony optimization based routing protocol. The throughput of the routing using the biogeography based optimization method is 589.763 kbps for 500 nodes which is high when compared to the existing method.

An Optimal Route Discovery using Biogeography based Optimization for Vehicular Ad Hoc Networks

Vehicular ad hoc network (VANET) is a subdivision of the mobile ad hoc networks which uses the moving vehicles as mobile nodes to form the mobile network. In conventional vehicular communications, the restricted radio frequency bandwidth affects the network performances. Therefore, Visible Light Communication (VLC) is integrated with the growing vehicular ad hoc network to obtain high data rate and less energy consumption during the communication. In this paper, vehicular communication is integrated with visible light communication to avoid the issues caused by the restricted radio frequency bandwidth. Moreover, the Routing using Biogeography Based Optimization (RBBO) is proposed to develop an optimal route between the source vehicles to the destination. This research performs two different communications such as vehicle to vehicle and vehicle to the infrastructure. The performance of the RBBOVLC-VANET method is analyzed by means of throughput, packet delivery ratio, delay and routing overhead as well as these performances are compared with the existing method namely ant colony optimization based routing protocol. The throughput of the routing using the biogeography based optimization method is 589.763 kbps for 500 nodes which is high when compared to the existing method.

A Survey of Various Ant Colony Optimization based Routing Protocols for Mobile Ad hoc Networks

A Survey of Various Ant Colony Optimization based Routing Protocols for Mobile Ad hoc Networks

A Novel Approach to Comparative Analysis of Legacy and Nature Inspired Ant Colony Optimization based Routing Protocol in MANET

Performance, scalability, Quality of Service (QoS), users’ response, etc. of any network depends upon the efficient network design and communication technologies being exploited. Mobile Ad hoc Networks (MANETs) have become widespread due to their zero-configuration requirements, scalability, maintenance and adaptable nature to cater varying requirements. The core process of any network is routing which is performed by routing protocols. Routing protocols play a crucial role to enhance and improve the performance indicators of any network. Traditional MANET routing protocols have been failed to address growing demands of wireless mobile ad hoc network. In this paper we study and compare a nature inspired Ant Colony Optimization (ACO) algorithm with legacy of MANET protocols. Simulation results show that ACO algorithm has high potential to be used in large scale MANET or other wireless networks. We compared ACO with proactive and reactive routing protocols because despite of their weaknesses these types of protocols are still being used in different and same wireless arrangements.

Enhanced New Clustering Ant Colony Optimization based Routing Protocol AODV-R

Enhanced New Clustering Ant Colony Optimization based Routing Protocol AODV-R

A Survey of Ant Colony Optimization Based Routing Protocols for Mobile Ad Hoc Networks

Developing highly efficient routing protocols for Mobile Ad hoc NETworks (MANETs) is a challenging task. In order to fulfill multiple routing requirements, such as low packet delay, high packet delivery rate, and effective adaptation to network topology changes with low control overhead, and so on, new ways to approximate solutions to the known NP-hard optimization problem of routing in MANETs have to be investigated. Swarm intelligence (SI)-inspired algorithms have attracted a lot of attention, because they can offer possible optimized solutions ensuring high robustness, flexibility, and low cost. Moreover, they can solve large-scale sophisticated problems without a centralized control entity. A successful example in the SI field is the ant colony optimization (ACO) meta-heuristic. It presents a common framework for approximating solutions to NP-hard optimization problems. ACO has been successfully applied to balance the various routing related requirements in dynamic MANETs. This paper presents a comprehensive survey and comparison of various ACO-based routing protocols in MANETs. The main contributions of this survey include: 1) introducing the ACO principles as applied in routing protocols for MANETs; 2) classifying ACO-based routing approaches reviewed in this paper into five main categories; 3) surveying and comparing the selected routing protocols from the perspective of design and simulation parameters; and 4) discussing open issues and future possible design directions of ACO-based routing protocols.

Ant Colony Optimization (ACO) based Routing Protocols for Wireless Sensor Networks (WSN): A Survey

Wireless Sensor Networks have several issues and challenges with regard to Energy Efficiency, Limited Computational capability, Routing Overhead, Packet Delivery and many more. Designing Energy Efficient Routing Protocol has always been a limiting factor cum issue for Wireless Sensor Networks. Varied routing protocols being proposed till date for overcoming these issues based on Swarm Intelligence. Swarm Intelligence is concerned with study of combined behavior of systems designed by varied components for coordinating among themselves via decentralized controls and self-organization. Algorithms based on Swarm Intelligence, nature based intelligence are highly robust, adaptive and scalable. This paper presents comprehensive survey of Ant Colony Optimization based routing protocols for Wireless Sensor Networks to give better platform for researchers to work on various shortcomings of protocols developed till date to develop efficient routing protocol for WSN in near future.

Analyzing ant colony optimization based routing protocol against the hole problem for enhancing user’s connectivity experience

This paper investigates the ant colony optimization (ACO) based routing protocol against holes (or voids) to address user’s connectivity via Pervasive Wireless Sensor Networks (PWSNs). A hole is an area that has no active sensors, which makes a connection between one side of the network and the other side impossible. To avoid such holes, prior works detected them only when packets reached nodes near the hole, called dead-ends. In this case, the packets need to be rerouted, which results in additional communication cost. The ant colony optimization (ACO) approach is known to be suitable for dynamic environments, which makes it a good choice to deal with the hole problem. We study the capability of an ACO-based routing protocol, called the biologically inspired secure autonomous routing protocol (BIOSARP), for resolving this issue. Because of its routing criteria, BIOSARP does not try to detect the holes after their appearance, but rather avoids them. Network simulator 2 (ns-2) is utilized to perform an analysis by adopting a flag-based feedback mechanism in BIOSARP and is further compared with on-demand routing with the void avoidance (ODVA) protocol in terms of the delivery ratio and energy consumption. Findings clearly demonstrate that BIOSARP can efficiently maintain the network prior to any possible hole problems, by switching data forwarding to the most optimal neighboring node. Thus, it can self-adapt to faults appearing in PWSN and efficiently maintains the network communication.