ACO Based Routing Algorithms for Ad-hoc Network (WSN, MANETs): A Survey

Shirkande, S. D.; Vatti, Rambabu

doi:10.1109/csnt.2013.56

Cited by 19 publications

(18 citation statements)

References 7 publications

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“…These routing contrivances have taken into consideration the intrinsic topographies of WSNs along with the application and architecture rations. The task of finding and maintaining routes in WSNs is nontrivial since energy restrictions (Guo and Jia, 2012;Shirkande and Vatti, 2013) and sudden changes in node status (e.g., failure) cause frequent and unpredictable topological changes. To minimize latency and energy consumption, routing techniques proposed in this literature employ some well-known routing tactics e.g., data aggregation and clustering (Rao et al, 2003;Baghyalakshmi et al, 2010).…”

Section: Sink Oriented Approach In Wsnmentioning

confidence: 99%

“…This makes the sink node to propagate awareness for whole event and to utilize the resources, querying the availability, node transmission, mobility ratio, packet base aspect. This leads to free mobility of roaming sink base with the routing grid or routing information table (Shirkande and Vatti, 2013;Yong-Chang and Gang, 2008). …”

Section: Source Oriented Approach In Wsnmentioning

confidence: 99%

“…To overcome these issues in our approach each nodes hold on the information which are necessary about the node on the local field (Shirkande and Vatti, 2013;Yong-Chang and Gang, 2008;Visu and Kannan, 2013;Okdem and Karaboga, 2009;Arif and Rani, 2012). Information such as node id, source transceiver's id, base station, host parameters.…”

Section: Local Fieldmentioning

confidence: 99%

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Ffa-Context Aware Energy Efficient Routing Using Fast Reactive and Adaptive Algorithm

Rani¹

2014

American Journal of Applied Sciences

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A vital issue of routing is how to efficiently strengthen energy consumption of the whole network and to avoid the energy-hole which leads to node failure or node death; this scenario makes the network to work improperly and leads to network death, Here we proves our hypothesis with linearity between routing and linear principles. Our proposed work effectively utilizes the adaption of Optimized particle swarm algorithm (Fast Reactive and fast adaptive algorithm) in order to solve the routing problem in wireless sensor networks to avoid the energy hole. Our approach effectively defines the node leader based on energy level and path optimization for node traversing using particle swarm which effectively utilizes the solution for problem in linearity into routing problem. Our algorithm FFA redefines the particle swarm rules which are reliable in routing strategies and adapts to the working principle. The optimization in our algorithm is to balance energy level and to withstand for its context. This study proves the accuracy using our algorithm respectively by theoretical survey and analysis with simulated results.

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Section: Sink Oriented Approach In Wsnmentioning

confidence: 99%

Section: Source Oriented Approach In Wsnmentioning

confidence: 99%

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Ffa-Context Aware Energy Efficient Routing Using Fast Reactive and Adaptive Algorithm

Rani¹

2014

American Journal of Applied Sciences

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“…The path choosing process is realized stochastically according to the paths' pheromone values as in the expression (1). In this way, the path-choosing probability is at the D ratio.…”

Section: Data Sendingmentioning

confidence: 99%

“…Routing is one of the most important problems in Adhoc networks (MANETs) [1]. The fact that the nodes are mobile causes latency in the data flow and therefore, packet losses occur in routing.…”

Section: Introductionmentioning

confidence: 99%

ACO-based load balancing scheme for MANETs

Çelik

2015

Teh. vjesn.

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Original scientific paper Routing is one of the most important problems in Mobile Ad-hoc Networks (MANETs). Various techniques have been developed to cope with this problem. Ant-based routing is optimization technique used commonly. Ant-based routing is derived from ant colony optimization, which was inspired by ants. This article recommends a load balancing scheme based on the ant colony. The scheme recommended makes use of the on-demand path finding techniques. Using ant colony optimization develops these techniques. The scheme recommended reduced latency and packet loss without being affected by the increase in the scheme node number and the packet density. The comparisons are made via AODV and AntHocNet which are known as MANET routing algorithms. Keywords: ACO; AntODV; load balancing; MANET ACO temeljena shema balansiranja opterećenja za MANETsIzvorni znanstveni članak Usmjeravanje (routing) je jedan od najvažnijih problema u mobilnim ad-hoc mrežama (MANETs). Razvijene su različite tehnike za rješavanje tog problema. Usmjeravanje zasnovano na mravima (ant-based routing) je metoda optimizacije koja se općenito koristi. Nastala je iz optimizacije kolonije mrava, inspirirane mravima. Ovaj članak preporučuje shemu balansiranja opterećenja zasnovanu na koloniji mrava. Preporučena shema koristi tehniku pronalaženja putanje na zahtjev. Primjena optimizacije kolonije mrava razvija te tehnike. Preporučena shema smanjila je kašnjenje i gubitak paketa, a da na nju nije utjecalo povećanje broja čvorova i gustoće paketa u shemi. Napravljene su usporedbe putem AODV i AntHocNet poznatih kao MANET algoritmi usmjeravanja.

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Geographic GReedy Routing with ACO Recovery Strategy GRACO

Rekik

Mitton

Chtourou³

2015

Ad-Hoc, Mobile, and Wireless Networks

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Geographic routing is an attractive routing strategy in wireless sensor networks. It works well in dense networks, but it may suffer from the void problem. For this purpose, a recovery step is required to guarantee packet delivery. Face routing has widely been used as a recovery strategy since proved to guarantee delivery. However, it relies on a planar graph not always achievable in realistic wireless networks and may generate long paths. In this paper, we propose GRACO, a new geographic routing algorithm that combines a greedy forwarding and a recovery strategy based on swarm intelligence. During recovery, ant packets search for alternative paths and drop pheromone trails to guide next packets within the network. GRACO avoids holes and produces near optimal paths. Simulation results demonstrate that GRACO leads to a significant improvement of routing performance and scalability when compared to the literature algorithms.

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ACO Based Routing Algorithms for Ad-hoc Network (WSN, MANETs): A Survey

Cited by 19 publications

References 7 publications

Ffa-Context Aware Energy Efficient Routing Using Fast Reactive and Adaptive Algorithm

Ffa-Context Aware Energy Efficient Routing Using Fast Reactive and Adaptive Algorithm

ACO-based load balancing scheme for MANETs

Geographic GReedy Routing with ACO Recovery Strategy GRACO

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