A parallel ant colony optimization algorithm for all-pair routing in MANETs

Islam, Mohammad Towhidul; Thulasiraman, Parimala; Thulasiram, Ruppa K.

doi:10.1109/ipdps.2003.1213470

Cited by 35 publications

(22 citation statements)

References 12 publications

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“…[20] proposed a Source Update algorithm which suggests new ways to update pheromones. Figure 8a illustrates the way pheromone update in general ACO algorithm.…”

Section: Source Updatementioning

confidence: 99%

“…path field is used to know shortest path. visited field comes from [20] and prevents revisit and the graph cycle. …”

Section: Design Of Aco Packetmentioning

confidence: 99%

“…The original study of ACO algorithm was to solve TSP or vehicle routing problems and network routing problems. Especially, ACO is expected to be a good solution for dynamic topology and ad-hoc networks such as mobile ad-hoc network (MANET) [18][19][20][21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

“…[18,19,27] showed that novel routing algorithms that applied the ACO algorithm can be more effective than AODV or DSR. According to our research [16,[18][19][20][28][29][30][31][32], most of the papers were studied using a simulator, and there is no ACO routing implementation for the real network. But this paper focuses on the real network routing problem, so our first objective is the implementation of ACO routing agent running in the complex enough but not dynamic topology real network.…”

Section: Introductionmentioning

confidence: 99%

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Function-Oriented Networking and On-Demand Routing System in Network Using Ant Colony Optimization Algorithm

Sim

Lee

2017

Symmetry

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Abstract:In this paper, we proposed and developed Function-Oriented Networking (FON), a platform for network users. It has a different philosophy as opposed to technologies for network managers of Software-Defined Networking technology, OpenFlow. It is a technology that can immediately reflect the demands of the network users in the network, unlike the existing OpenFlow and Network Functions Virtualization (NFV), which do not reflect directly the needs of the network users. It allows the network user to determine the policy of the direct network, so it can be applied more precisely than the policy applied by the network manager. This is expected to increase the satisfaction of the service users when the network users try to provide new services. We developed FON function that performs on-demand routing for Low-Delay Required service. We analyzed the characteristics of the Ant Colony Optimization (ACO) algorithm and found that the algorithm is suitable for low-delay required services. It was also the first in the world to implement the routing software using ACO Algorithm in the real Ethernet network. In order to improve the routing performance, several algorithms of the ACO Algorithm have been developed to enable faster path search-routing and path recovery. The relationship between the network performance index and the ACO routing parameters is derived, and the results are compared and analyzed. Through this, it was possible to develop the ACO algorithm.

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“…[20] proposed a Source Update algorithm which suggests new ways to update pheromones. Figure 8a illustrates the way pheromone update in general ACO algorithm.…”

Section: Source Updatementioning

confidence: 99%

“…path field is used to know shortest path. visited field comes from [20] and prevents revisit and the graph cycle. …”

Section: Design Of Aco Packetmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Function-Oriented Networking and On-Demand Routing System in Network Using Ant Colony Optimization Algorithm

Sim

Lee

2017

Symmetry

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“…Central node is divided into secondary nodes. These secondary nodes handle the load sent by overloaded primary nodes [12] [24].…”

Section: Figure 1: Load Balancer Implementationmentioning

confidence: 99%

A Framework to Optimize Load Balancing to Improve the Performance of Distributed Systems

Payal¹,

Garg²

2015

IJCA

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Load balancing in distributed systems is the technique to handle maximum requests in minimum time. Load balancing aims to optimize resource use, maximum throughput, minimize response time, increase reliability and scalability. Trying to achieve this is however not an easy task. Various techniques and approaches have been used to achieve this goal. The proposed work is inspired by the Ant Colony Optimization (ACO) technique. The algorithm is designed on a Semi-Distributed system where clusters are formed and each cluster consists of number nodes. Ant is created on these clusters and acts accordingly the needs of the environment. The objective of paper is to develop an efficient load balancing technique that can improve the performance of system.

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Parallel Metaheuristics Applications

Crainic

Hail

2005

Parallel Metaheuristics

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PARALLEL META-HEURISTICS APPLICATIONS problems, set covering and partitioning, satisfiability and max-sat problems, quadratic assignment, location and network design, traveling salesman and vehicle routing problems. We do not pretend to be exhaustive. We have also restricted to a minimum the presentation of general parallel computation issues as well as that of the parallel meta-heuristic strategies. The reader may consult a number of surveys, taxonomies, and syntheses of parallel meta-heuristics, of which quite a few address the "classical" meta-heuristics, Simulated Annealing, Genetic Algorithms, and Tabu Search, while some others address the field in more comprehensive terms:

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A parallel ant colony optimization algorithm for all-pair routing in MANETs

Cited by 35 publications

References 12 publications

Function-Oriented Networking and On-Demand Routing System in Network Using Ant Colony Optimization Algorithm

Function-Oriented Networking and On-Demand Routing System in Network Using Ant Colony Optimization Algorithm

A Framework to Optimize Load Balancing to Improve the Performance of Distributed Systems

Parallel Metaheuristics Applications

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