A Structured Overlay Network for Aggregating Sensor Data

Takeda, Atsushi; Oide, Takuma; Takahashi, Akiko

doi:10.1109/bwcca.2012.119

Cited by 5 publications

(7 citation statements)

References 14 publications

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“…Many structured p2p networks with data aggregation mechanisms have been proposed [2] [7]. In these data aggregation mechanisms, each node collects values of other nodes.…”

Section: Related Workmentioning

confidence: 99%

“…Therefore, a Synchronous Data Aggregation mechanism presents problems of scalability. However, in an Asynchronous Data Aggregation mechanism, each node calculates partial aggregation results independently [6] [7]. When a node requires comprehensive aggregation results, the node only collects the partial aggregation results.…”

Section: Related Workmentioning

confidence: 99%

“…However, in these data aggregation mechanisms, the amount of communication data required for calculating comprehensive aggregation results is O(N ), where N denotes the number of nodes on the structured p2p network. Some studies, however, have proposed scalable aggregation mechanisms on structured p2p networks [6] [7]. In these mechanisms, the amount of communication data required for data aggregation is O(log N ), Therefore, we are studying these aggregation mechanisms and we have proposed a scalable data aggregation algorithm on a structured p2p network Chord# [7].…”

Section: Introductionmentioning

confidence: 99%

“…Some studies, however, have proposed scalable aggregation mechanisms on structured p2p networks [6] [7]. In these mechanisms, the amount of communication data required for data aggregation is O(log N ), Therefore, we are studying these aggregation mechanisms and we have proposed a scalable data aggregation algorithm on a structured p2p network Chord# [7]. On the other hand, through the research, we found that these aggregation mechanisms do not achieve accurate data aggregation on an unstable environment.…”

Section: Introductionmentioning

confidence: 99%

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Accurate Data Aggregation on Unstable Structured P2P Network

Takeda

Oide

Takahashi

et al. 2015

2015 IEEE 29th International Conference on Advanced Information Networking and Applications

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Smartphones and sensor devices have come into widespread use, and we can observe huge amounts of data from the devices via the Internet. In order to develop a network application which uses these devices effectively, we need an accurate and scalable data aggregation mechanism. In this paper, we propose a accurate data aggregation mechanism which is based on a scalable structured p2p network. The proposed mechanism is constructed by two concepts: Asynchronous Data Aggregation and Time-slot-based Data Aggregation. In the proposed mechanism, the amount of communication data required for data aggregation is O(log N), where N is the number of nodes. Additionally, the proposed mechanism achieves accurate data aggregation even if the structured p2p network is unstable. In this paper, we explain an algorithm and a communication protocol for the proposed data aggregation mechanism. Furthermore, using experimentally obtained results, we indicate advantages of our proposal over existing data aggregation mechanisms.

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“…Many structured p2p networks with data aggregation mechanisms have been proposed [2] [7]. In these data aggregation mechanisms, each node collects values of other nodes.…”

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Accurate Data Aggregation on Unstable Structured P2P Network

Takeda

Oide

Takahashi

et al. 2015

2015 IEEE 29th International Conference on Advanced Information Networking and Applications

Self Cite

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“…Takeda et al [10] have proposed a scalable structured p2p network which supports data aggregation. In the proposed p2p network, each node forwards partial statistical results to other nodes, and each node aggregates partial statistical results in order to calculate a complete statistical result.…”

Section: Literature Reviewmentioning

confidence: 99%

Cluster Based Compressed Data Aggregation and Routing in WSN

Jothi¹,

Chandrasekaran²

2016

IJIES

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Due to non uniform distribution of nodes, there is an imbalance of energy consumption among the nodes in cluster-based wireless sensor networks. Based on this problem, we propose an efficient data aggregation tree for communication and routing based on the previous clustering architecture. Here based on the parameters such as Residual Energy, Node Density and Load cluster heads are elected using fuzzy logic technique. The inter-cluster routing algorithm balances the energy consumption among cluster heads by adjusting inter-cluster energy consumption. Then data compression is applied for reducing the energy consumption using data correlation model.

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