Intelligent Routing Techniques for Mobile Ad hoc Networks using Swarm Intelligence

Raghavendran, Ch. V.; Satish, G. Naga; Varma, P. Suresh

doi:10.5815/ijisa.2013.01.08

Cited by 22 publications

(14 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Suppose, a TSP problem has ten cities and a solution is 1-2-3-6-4-5-7-8-9-10. A SO (4,6) gives the new solution S'. Here '+' means to apply SO(s) on the solution.…”

Section: B Scrounging To Follow the Producermentioning

confidence: 99%

“…For proper understanding, we also solved the benchmark problems with genetic algorithm (GA) [1,2], ant colony optimization (ACO) [3,[6][7][8]. GA is the popular and pioneer method for optimization task and ACO is the prominent swarm intelligence based method for TSP.…”

Section: A Benchmark Problems and Experimental Setupmentioning

confidence: 99%

“…Among them, genetic algorithm, inspired by biological systems' fitness improvement through evolution, is the pioneer one and widely used to solve many scientific and engineering problems [1,2]. Recently, swarm intelligence (SI), inspired from the collective behavior of animals, has drawn attraction to solve computational problems [3][4][5][6]. Among various SI algorithms, ant colony optimization (ACO) [7,8] and particle swarm optimization (PSO) [9,10] are famous methods.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Producer-Scrounger Method to Solve Traveling Salesman Problem

Akhand¹,

Shill²,

Hossain³

et al. 2015

IJISA

View full text Add to dashboard Cite

Abstract-Algorithms inspired from natural phenomena are seem to be efficient to solve various optimization problems. This paper investigates a new technique inspiring from the animal group living behavior to solve traveling salesman problem (TSP), the most popular combinatorial optimization problem. The proposed producer-scrounger method (PSM) models roles and interactions of three types of animal group members: producer, scrounger and dispersed. PSM considers a producer having the best tour, few dispersed members having worse tours and scroungers. In each iteration, the producer scans for better tour, scroungers explore new tours while moving toward producer's tour; and dispersed members randomly checks new tours. For producer's scanning, PSM randomly selects a city from the producer's tour and rearranges its connection with several near cities for better tours. Swap operator and swap sequence based operation is employed in PSM to update a scrounger towards the producer. The proposed PSM has been tested on a large number of benchmark TSPs and outcomes compared to genetic algorithm and ant colony optimization. Experimental results revealed that proposed PSM is a good technique to solve TSP providing the best tours in most of the TSPs.

show abstract

“…Suppose, a TSP problem has ten cities and a solution is 1-2-3-6-4-5-7-8-9-10. A SO (4,6) gives the new solution S'. Here '+' means to apply SO(s) on the solution.…”

Section: B Scrounging To Follow the Producermentioning

confidence: 99%

Section: A Benchmark Problems and Experimental Setupmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Producer-Scrounger Method to Solve Traveling Salesman Problem

Akhand¹,

Shill²,

Hossain³

et al. 2015

IJISA

View full text Add to dashboard Cite

show abstract

“…Swarm intelligence algorithms were applied widely for dynamic traffic routing of computer network and road network [1][2][3][4][5]. One of the most promising approaches of swarm intelligence is the Ant routing methodology, this approach inspired from the behavior of real ants when foraging, this methodology capable of finding near optimal solutions at low computational cost.…”

Section: Introductionmentioning

confidence: 99%

Improving the performance of TAntNet-2 by using multi forward scouts

Ghazy

Hefny

2015

2015 Tenth International Conference on Computer Engineering &Amp; Systems (ICCES)

View full text Add to dashboard Cite

Dynamic Traffic Routing System is an important intelligent transport system that is used to direct vehicles to good routes and consequently reduce congestion on the road network. The performance of dynamic routing system depends on a dynamic routing algorithm. AntNet algorithm is a routing algorithm inspired from the foraging behavior of ants. TAntNet is a family of dynamic routing algorithms that uses a threshold travel time to enhance the performance of AntNet algorithm when applied to traffic road networks. This paper presents new improvements on TAntNet algorithms. The new improving TAntNet algorithm uses Multi forward agents instead of one compared with AntNet and TAntNet-2. The new technique saves the discovered routes of each of the forward agents and the corresponding backward ant uses the best of them. Experiments showed better performance for the proposed new mechanism of launching multi forward agents for each single agent compared with the old mechanisms of launching only one forward agent for each backward agent.

show abstract

“…CH. V. Raghavendran et.al [11] proposed in this paper that in order to provide routing within the network the Swarm intelligence algorithms can also be used. The natural behaviors of various animals such as fish, ants, bees and other insects are studied and on the basis of them the algorithms are generated.…”

Section: Introductionmentioning

confidence: 99%

Efficient Path Establishment Algorithm in MANETs using Bio-Inspired Techniques

Kaur

Verma

2017

IJARCSSE

View full text Add to dashboard Cite

Abstract-The network in which the nodes can enter or leave the network as per their need is known as mobile ad-hoc network. This is a self-configuring type of network and so the routing in this type of network is very difficult. Numerous routing protocols are involved here which are classified on the basis of their properties into reactive, proactive and hybrid protocols. There are several important parameters such as delay, packet loss and throughput. These parameters are utilized for checking the performance of three routing protocols namely AODV, DSR and DSDV within this research. In comparison to the other protocols, the AODV routing protocol provides better results. In order to provide efficient path establishment from source to destination, enhancement has been proposed here within the AODV protocol which includes the utilization of cuckoo search and bee colony named bio-inspired techniques in it. The nodes that are found to be common in the selected paths are chosen to be the best nodes for the path. The NS2 tool is used for performing the simulations. As per the results achieved it can be seen that the AODV protocol provides better results in terms of the above mentioned parameters.Keywords-MANET, Reactive, Proactive, Hybrid, ADOV, DSDV, DSR I. INTRODUCTIONThe wireless networks are being prominently utilized nowadays within the day-to-day communication systems. Numerous applications within the fields such as industrial field, military areas and applications involving personal usage include the wireless networks within them. These networks are easy to install, are scalable and flexible and thus are growing popularity with time. The self-configuring type of network that has dynamic topology is known as the mobile ad-hoc network [1]. In order to provide the facilities that can handle the radio communication channels, multi-user interference and other effects, the nodes present within MANETs find their own ways. It is not easy to find an efficient routing protocol for MANETs. Due to their independent nature which provides the nodes to enter or leave the network as per their own requirements, these networks are deployed within numerous applications. There is a dynamic change of the topology of network due to the continuous mobility of nodes. There is a specific area which is covered for providing network communication. The scalability of infrastructure-less networks is better as they are decentralized in nature [2]. The performance of the ad hoc networks is better within various emergency applications as they have operations that can be executed faster and also the configuration is less. An optimal path is to be generated which must involve least number of intermediate nodes from source to destination by the chosen protocol. It is also to be ensured that there is very less overhead and limited consumption of bandwidth within the route [3]. This helps in transmitting the message as per the time duration given across the network. The updated state of the topology of network is obtained with the help of these ty...

show abstract

Intelligent Routing Techniques for Mobile Ad hoc Networks using Swarm Intelligence

Cited by 22 publications

References 21 publications

Producer-Scrounger Method to Solve Traveling Salesman Problem

Producer-Scrounger Method to Solve Traveling Salesman Problem

Improving the performance of TAntNet-2 by using multi forward scouts

Efficient Path Establishment Algorithm in MANETs using Bio-Inspired Techniques

Contact Info

Product

Resources

About