An efficient data-centric storage method using time parameter for sensor networks

Park, Yonghun; Seo, Dongmin; Yun, Je Moon; Ryu, Christopher; Kim, Jun; Yoo, Jaesoo

doi:10.1016/j.ins.2010.08.036

Cited by 11 publications

(4 citation statements)

References 21 publications

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“…To resolve this problem, several methods have been proposed such as zone partitioning and zone partial replication 10 based on Multi-dimensional Range Query which locally detect and dissolves query hotspots. Also, in time-parameterized DCS, 11 the time at which the sensed data is generated determines the node which is used to store the data. Since data zones are altered periodically, both storage and query process are scattered across the network.…”

Section: Related Workmentioning

confidence: 99%

An adaptive hybrid schema for data-centric storage in wireless sensor networks

Hejazi

2016

International Journal of Distributed Sensor Networks

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Storage, query cost, and energy efficiency are among the most important data dissemination issues in wireless sensor networks. Data-centric storage approach can be viewed as energy efficient and low cost solution to these issues, which itself suffers from hotspot storage problem. Some provided solutions tried to handle this mentioned problem and also brought load balancing and scalability to the network. In this article, we present a method called adaptive resilient datacentric storage which reduces the storage cost and also improves the load balancing and fault tolerance in the network by making data-centric storage adaptive based on the frequency of sensed events. Then, we propose a mathematical model to determine the threshold for the frequency of occurrence of sensed events. Finally, we developed a discreteevent-based simulator for two-dimensional graphical view of the network and collected the results. Simulations and analytical results show the superiority of the proposed method over the compared approaches with the miscellaneous frequency of events.

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Section: Related Workmentioning

confidence: 99%

An adaptive hybrid schema for data-centric storage in wireless sensor networks

Hejazi

2016

International Journal of Distributed Sensor Networks

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“…To overcome this problem, two DIM based algorithms called Zone Partitioning (ZP) and Zone Partial Replication (ZPR) are proposed in [12] that can locally detect and decompose query hotspots. Also in [13], a method called Time-Parameterized Data-Centric Storage (TPDCS) is proposed that can address both storage hotspots and query hotspots problems. Here, both sensor generated data and its time of generation are used in deciding which sensor should store data.…”

Section: Related Workmentioning

confidence: 99%

An adaptive method for structured replication data-centric storage in wireless sensor networks

Hejazi

Amin

2011

ICIMU 2011 : Proceedings of the 5th International Conference on Information Technology &Amp; Multimedia

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Data-centric storage solutions are energy-efficient algorithms in wireless sensor networks and will greatly reduce total network load. However, storage nodes will become bottlenecks when the amount of events and queries targeted for a particular node is more than its capacity. This paper proposes a novel approach that brings load-balancing and scalability to the network as well as its ability to adapt itself to network conditions. This adaptability is made possible through a load-control mechanism provided by two thresholds which are responsible for changing hierarchy depth and the number of storage replicas as the frequency of events fluctuates in the network. Thus, the proposed method will not only reduce storage cost when the event frequency is high but also prevents hotspot problem in the root storage node. Moreover, it will reduce query traffic by merging replica nodes as the event frequency goes back to its normal state. Also, a simulator based on discrete-event system simulation methodology is developed to evaluate the proposed method on the basis of storage traffic, query traffic and the number of dead sensors. The result of evaluation shows that the proposed method has performance improvement over other compared methods.

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“…The proposed data dissemination and storage model uses a distributed algorithm to construct data dissemination paths to one or more data storage points. Our work differs from other recent developments within this space [2] , [3], [4], [5] and [6] in that we do not employ greedy mechanisms for data dissemination, depend on topological constraints or require knowledge of information location. Further, the aggregated data is stored at multiple levels of resolutions to enable fast query resolution without the need for accessing detailed level of information always.…”

Section: Introductionmentioning

confidence: 96%

Information discovery in multidimensional wireless sensor networks

Tissera

Doss

et al. 2013

The International Conference on Information Networking 2013 (ICOIN)

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Wireless sensor networks (WSN) are attractive for information discovery in large-scale data rich environments and can add value to mission-critical applications such as battle-field surveillance, environmental monitoring and emergency response. However, in order to fully exploit these networks for such applications, energy-efficient and scalable solutions for information discovery are essential.Multidimensional WSNs are deployed in complex environments to sense and collect data relating to multiple attributes (multidimensional data). Such networks present unique challenges to data dissemination, data storage and in-network query processing (information discovery). In this paper, we propose a novel method of information discovery for multidimensional WSNs that can significantly increase network lifetime and minimize query processing latency, resulting in quality of service (QoS) improvements that are of immense benefit to missioncritical applications. We propose a distributed solution with multiple levels of resolution to enable fast query resolution. We present simulation results to show that the proposed approach to information discovery offers significant improvements on query resolution latency in comparison with current approaches. In addition, the results prove that the QoS improvements come with significant network-wide energy savings that will result in an increase of the network lifetime.

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An efficient data-centric storage method using time parameter for sensor networks

Cited by 11 publications

References 21 publications

An adaptive hybrid schema for data-centric storage in wireless sensor networks

An adaptive hybrid schema for data-centric storage in wireless sensor networks

An adaptive method for structured replication data-centric storage in wireless sensor networks

Information discovery in multidimensional wireless sensor networks

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