Data Dissemination with Temporal-Centric Storage in Wireless Sensor Networks
碩士 === 雲林科技大學 === 電機工程系碩士班 === 96 === In a wireless sensor network, sensor nodes are generally battery-powered with limited communication and computational capabilities. As far as the dissemination of sensing data is concerned, many schemes have been proposed to cater for energy efficient applicati...
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ndltd-TW-096YUNT54420522015-10-13T11:20:44Z http://ndltd.ncl.edu.tw/handle/27600339860353813257 Data Dissemination with Temporal-Centric Storage in Wireless Sensor Networks 在無線感測網路中使用以時間導向為主的資料散播 Heng-shou Liu 劉恆碩 碩士 雲林科技大學 電機工程系碩士班 96 In a wireless sensor network, sensor nodes are generally battery-powered with limited communication and computational capabilities. As far as the dissemination of sensing data is concerned, many schemes have been proposed to cater for energy efficient application. However, these schemes may suffer from hot-spot problems if certain sensing data are generated frequently, in particular when. Multidimensional range queries are issued to collect data of interest whose attributes exist within some range. This may cause large communication cost since diverse data are likely to be distributed over a widely-dispersed area of sensor networks. In this thesis we propose an approach with Temporal-Centric Storage (TCS) approach allowing for load balance, scalability and energy efficiency. In our architecture the detected sensing data are pushed to some storage node indexed on-line by a hash function of current time. These nodes act as rendezvous between sink and source nodes. We also provide a means to suppress frequent source updates so as to reduce traffic cost. Our design is arguably effective in practice. Simulation result show that the proposed approach mitigates the hot-spot problem and can thus improve overall system performance substantially. Kuang-hui Chi Ji-han Jiang 紀光輝 江季翰 2008 學位論文 ; thesis 63 en_US |
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碩士 === 雲林科技大學 === 電機工程系碩士班 === 96 === In a wireless sensor network, sensor nodes are generally battery-powered with limited communication and computational capabilities. As far as the dissemination of sensing data is concerned, many schemes have been proposed to cater for energy efficient application. However, these schemes may suffer from hot-spot problems if certain sensing data are generated frequently, in particular when. Multidimensional range queries are issued to collect data of interest whose attributes exist within some range. This may cause large communication cost since diverse data are likely to be distributed over a widely-dispersed area of sensor networks. In this thesis we propose an approach with Temporal-Centric Storage (TCS) approach allowing for load balance, scalability and energy efficiency. In our architecture the detected sensing data are pushed to some storage node indexed on-line by a hash function of current time. These nodes act as rendezvous between sink and source nodes. We also provide a means to suppress frequent source updates so as to reduce traffic cost. Our design is arguably effective in practice. Simulation result show that the proposed approach mitigates the hot-spot problem and can thus improve overall system performance substantially.
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Kuang-hui Chi |
author_facet |
Kuang-hui Chi Heng-shou Liu 劉恆碩 |
author |
Heng-shou Liu 劉恆碩 |
spellingShingle |
Heng-shou Liu 劉恆碩 Data Dissemination with Temporal-Centric Storage in Wireless Sensor Networks |
author_sort |
Heng-shou Liu |
title |
Data Dissemination with Temporal-Centric Storage in Wireless Sensor Networks |
title_short |
Data Dissemination with Temporal-Centric Storage in Wireless Sensor Networks |
title_full |
Data Dissemination with Temporal-Centric Storage in Wireless Sensor Networks |
title_fullStr |
Data Dissemination with Temporal-Centric Storage in Wireless Sensor Networks |
title_full_unstemmed |
Data Dissemination with Temporal-Centric Storage in Wireless Sensor Networks |
title_sort |
data dissemination with temporal-centric storage in wireless sensor networks |
publishDate |
2008 |
url |
http://ndltd.ncl.edu.tw/handle/27600339860353813257 |
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