Providing Virtual Memory Support for Sensor Networks with Mass Data Processing
With the development of sensor networks and emerging of various sensors, sensor networks are capable of acquiring mass data to achieve much more complex monitoring tasks than ever. For example, image sensor nodes take photos using cameras, and images are collected and processed or stored for further...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2013-03-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1155/2013/324641 |
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| _version_ | 1832547222999269376 |
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| author | Nan Lin Yabo Dong Dongming Lu |
| author_facet | Nan Lin Yabo Dong Dongming Lu |
| author_sort | Nan Lin |
| collection | DOAJ |
| description | With the development of sensor networks and emerging of various sensors, sensor networks are capable of acquiring mass data to achieve much more complex monitoring tasks than ever. For example, image sensor nodes take photos using cameras, and images are collected and processed or stored for further processing. So, mass data processing is required for these sensor networks. However, low-power resource-constrained sensor nodes are normally equipped with kilobytes of RAM which might be not enough for storing large data for processing. In this paper, we propose an optimized virtual memory mechanism for large data processing on low-power sensor nodes. We point out the major overhead of virtual memory for large data processing on sensor nodes and introduce efficient solutions to address these issues. Evaluation shows that the overhead of the proposed virtual memory is reduced to an affordable range. We further compare the energy consumption of data processing programs using virtual memory with other means that process or transmit data. Data processing using virtual memory can be significantly more energy efficient than data processing using rich-resource sensor nodes or transmitting data to powerful gateways for central processing. |
| format | Article |
| id | doaj-art-62afd0d9c5944b4abf996c7bf5180978 |
| institution | Kabale University |
| issn | 1550-1477 |
| language | English |
| publishDate | 2013-03-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj-art-62afd0d9c5944b4abf996c7bf51809782025-02-03T06:45:29ZengWileyInternational Journal of Distributed Sensor Networks1550-14772013-03-01910.1155/2013/324641Providing Virtual Memory Support for Sensor Networks with Mass Data ProcessingNan Lin0Yabo Dong1Dongming Lu2 School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China Cyrus Tang Center for Sensor Materials and Applications, Zhejiang University, Hangzhou 310027, China Cyrus Tang Center for Sensor Materials and Applications, Zhejiang University, Hangzhou 310027, ChinaWith the development of sensor networks and emerging of various sensors, sensor networks are capable of acquiring mass data to achieve much more complex monitoring tasks than ever. For example, image sensor nodes take photos using cameras, and images are collected and processed or stored for further processing. So, mass data processing is required for these sensor networks. However, low-power resource-constrained sensor nodes are normally equipped with kilobytes of RAM which might be not enough for storing large data for processing. In this paper, we propose an optimized virtual memory mechanism for large data processing on low-power sensor nodes. We point out the major overhead of virtual memory for large data processing on sensor nodes and introduce efficient solutions to address these issues. Evaluation shows that the overhead of the proposed virtual memory is reduced to an affordable range. We further compare the energy consumption of data processing programs using virtual memory with other means that process or transmit data. Data processing using virtual memory can be significantly more energy efficient than data processing using rich-resource sensor nodes or transmitting data to powerful gateways for central processing.https://doi.org/10.1155/2013/324641 |
| spellingShingle | Nan Lin Yabo Dong Dongming Lu Providing Virtual Memory Support for Sensor Networks with Mass Data Processing International Journal of Distributed Sensor Networks |
| title | Providing Virtual Memory Support for Sensor Networks with Mass Data Processing |
| title_full | Providing Virtual Memory Support for Sensor Networks with Mass Data Processing |
| title_fullStr | Providing Virtual Memory Support for Sensor Networks with Mass Data Processing |
| title_full_unstemmed | Providing Virtual Memory Support for Sensor Networks with Mass Data Processing |
| title_short | Providing Virtual Memory Support for Sensor Networks with Mass Data Processing |
| title_sort | providing virtual memory support for sensor networks with mass data processing |
| url | https://doi.org/10.1155/2013/324641 |
| work_keys_str_mv | AT nanlin providingvirtualmemorysupportforsensornetworkswithmassdataprocessing AT yabodong providingvirtualmemorysupportforsensornetworkswithmassdataprocessing AT dongminglu providingvirtualmemorysupportforsensornetworkswithmassdataprocessing |