A Node-Grade Based AODV Routing Protocol for Wireless Sensor Network

Tong, Fei; Tang, Wan; Peng, Limei; Xie, Renchao; Yang, Won-Hyuk; Kim, Young-Chon

doi:10.1109/nswctc.2010.178

Cited by 19 publications

(10 citation statements)

References 7 publications

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“…Each node in PRI-MAC only maintains a grade [8] and a schedule with two state attributes, which improves the adaptability to the network topology changes (e.g., some nodes dying over time, some new nodes being added later, and some nodes moving to different locations). The grade and schedule in a node are established during the initialization process and are adjusted when necessary based on the gossip messages overheard from its neighbors-no precise synchronization required.…”

Section: A Contributions Of Our Workmentioning

confidence: 99%

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A Pipelined-forwarding, Routing-integrated and effectively-Identifying MAC for large-scale WSN

Tong

Shu

et al. 2013

2013 IEEE Global Communications Conference (GLOBECOM)

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This paper presents the design of a dutycycling MAC, called PRI-MAC (Pipelined-forwarding, Routingintegrated, and effectively-Identifying MAC), for large-scale wireless sensor networks. PRI-MAC divides the whole network into grades around the sink node. The higher grade a node is in, logically the further away it is from the sink which is in the lowest grade. Staggered sleep-wakeup schedules are established between any two adjacent grades such that data can be forwarded in a pipelined fashion, largely reducing the packet delivery latency to meet the real-time transmission requirement. Meanwhile, the routing function is seamlessly integrated into PRI-MAC, which reduces the protocol overhead and increases the network scalability. Furthermore, each node utilizes a randomlygenerated integer as its identifier only when it is involved in a data transmission, instead of allocating a unique address for each sensor node. The performance of PRI-MAC is evaluated in comparison with PW-MAC by OPNET, in terms of the packet delivery latency, energy efficiency, and throughput.Globecom 2013 -Ad Hoc and Sensor Networking Symposium 978-1-4799-1353-4/13/$31.00 ©2013 IEEE

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Section: A Contributions Of Our Workmentioning

confidence: 99%

“…Therefore, a node's grade can be viewed as the hop distance from the node to the sink. The node grade is used to guide data transmission, as data packet can be forwarded from the higher grade nodes to the lower-grade nodes, and finally to the sink [8]. This grade division process is initiated from the sink.…”

Section: A Pri-mac Overviewmentioning

confidence: 99%

A Pipelined-forwarding, Routing-integrated and effectively-Identifying MAC for large-scale WSN

Tong

Shu

et al. 2013

2013 IEEE Global Communications Conference (GLOBECOM)

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“…Then the efficiency depends on the kind of knowledge base that is possessed by the node. Many researchers have defined grade as hop distance (Tong et al, 2010) and have obtained better results by considering the value of the grade. As there is a lot of external influence on the node in the autonomic network, the network topology is dynamic in nature.…”

Section: Necessity Of Gradingmentioning

confidence: 99%

An intelligent routing approach using genetic algorithms for quality graded network

Nair

Sooda²

2012

IJISTA

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Intelligent routing in networks has opened up many challenges in modelling and methods, over the past decade. Many techniques do exist for routing on such an environment where path determination was carried out by advertisement, position and near-optimum node selection schemes. In this paper, an efficient routing scheme has been proposed using genetic algorithm for a grade-based two-level node selection method. This method assumes that nodes have the knowledge of its environment and is capable of taking decision for route discovery. The data learnt from the topology which is under consideration for routing, is saved in its local memory. In this two-level node selection scheme, the route discovery operation takes place in multiple levels. At the first level, the grade based selection is applied for considering the most optimal nodes which would be fit for sending data. At the second level, the optimal path is discovered using Genetic Algorithm. The simulation result shows that faster convergence of path took place in the case of the proposed method with good fitness value, as compared to non-graded network.

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“…The proposal [13] makes an improvement to AODV for WSN, called Grade-AODV (G-AODV) which includes a nodegrade metric. This metric evaluates the distance between the nodes to the base-station.…”

Section: Related Workmentioning

confidence: 99%

“…The cost of each path can be computed with the aid of one or more cross-layer metrics, such as quality of links, energy-efficiency, network size, distance of nodes and other features [2]. Several routing protocols have been outlined in the literature, such as AODV (Ad-hoc On demand Distance Vector) [9], G-AODV [13], EBRM [10], and LABILE [3]. However, they are lacking in energy-efficiency, fairness and the provision of route selection with quality level support.…”

Section: Introductionmentioning

confidence: 99%

Design of a routing protocol using remaining energy and link quality indicator (REL)

Machado

Rosário

Nakamura³

et al. 2011

Proceedings of the 6th Latin America Networking Conference

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This paper sets out an extension of an AODV routing protocol, called Routing by Energy and Link quality indicator (REL). The proposed protocol adopts a new cross-layer approach as a mechanism to select the best routes. The paths are selected on the basis of remaining energy, a proposed link quality estimator (WeakLink), and hop count. Thus, REL provides reliability, energy-efficiency, and a fair distribution of network resources.

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A Node-Grade Based AODV Routing Protocol for Wireless Sensor Network

Cited by 19 publications

References 7 publications

A Pipelined-forwarding, Routing-integrated and effectively-Identifying MAC for large-scale WSN

A Pipelined-forwarding, Routing-integrated and effectively-Identifying MAC for large-scale WSN

An intelligent routing approach using genetic algorithms for quality graded network

Design of a routing protocol using remaining energy and link quality indicator (REL)

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