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Exploration of tasks partitioning between hardware software and locality for a wireless camera based vision sensor node
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.ORCID iD: 0000-0002-6484-9260
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.ORCID iD: 0000-0003-1923-3843
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
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2011 (English)In: Proceedings - 6th International Symposium on Parallel Computing in Electrical Engineering, PARELEC 2011, IEEE conference proceedings, 2011, p. 127-132Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we have explored different possibilities for partitioning the tasks between hardware, software and locality for the implementation of the vision sensor node, used in wireless vision sensor network. Wireless vision sensor network is an emerging field which combines image sensor, on board computation and communication links. Compared to the traditional wireless sensor networks which operate on one dimensional data, wireless vision sensor networks operate on two dimensional data which requires higher processing power and communication bandwidth. The research focus within the field of wireless vision sensor networks have been on two different assumptions involving either sending raw data to the central base station without local processing or conducting all processing locally at the sensor node and transmitting only the final results. Our research work focus on determining an optimal point of hardware/software partitioning as well as partitioning between local and central processing, based on minimum energy consumption for vision processing operation. The lifetime of the vision sensor node is predicted by evaluating the energy requirement of the embedded platform with a combination of FPGA and micro controller for the implementation of the vision sensor node. Our results show that sending compressed images after pixel based tasks will result in a longer battery life time with reasonable hardware cost for the vision sensor node. © 2011 IEEE.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2011. p. 127-132
Keywords [en]
Hardware/Software Partioning, Image Processing, Reconfigurable Architecture, Vision Sensor Node, Wireless Vision Sensor Networks, Battery life time, Communication bandwidth, Compressed images, Embedded platforms, Energy requirements, Hardware cost, Hardware/software partitioning, Local processing, Minimum energy, Optimal points, Partioning, Processing power, Vision processing, Vision sensors, Wireless cameras, Work Focus, Computer hardware, Electrical engineering, Energy utilization, Engineering research, Field programmable gate arrays (FPGA), Parallel architectures, Sensors, Telecommunication equipment, Telecommunication systems, Wireless networks, Sensor nodes
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:miun:diva-14195DOI: 10.1109/PARELEC.2011.21Scopus ID: 2-s2.0-79958725347Local ID: STCISBN: 9780769543970 (print)OAI: oai:DiVA.org:miun-14195DiVA, id: diva2:431414
Conference
6th International Symposium on Parallel Computing in Electrical Engineering, PARELEC 2011; Luton; 4 April 2011 through 5 April 2011; Category number E4397; Code 85105
Available from: 2011-07-19 Created: 2011-07-19 Last updated: 2016-10-19Bibliographically approved
In thesis
1. Investigation of Architectures for Wireless Visual Sensor Nodes
Open this publication in new window or tab >>Investigation of Architectures for Wireless Visual Sensor Nodes
2011 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Wireless visual sensor network is an emerging field which has proveduseful in many applications, including industrial control and monitoring,surveillance, environmental monitoring, personal care and the virtual world.Traditional imaging systems used a wired link, centralized network, highprocessing capabilities, unlimited storage and power source. In manyapplications, the wired solution results in high installation and maintenancecosts. However, a wireless solution is the preferred choice as it offers lessmaintenance, infrastructure costs and greater scalability.The technological developments in image sensors, wirelesscommunication and processing platforms have paved the way for smartcamera networks usually referred to as Wireless Visual Sensor Networks(WVSNs). WVSNs consist of a number of Visual Sensor Nodes (VSNs)deployed over a large geographical area. The smart cameras can performcomplex vision tasks using limited resources such as batteries or alternativeenergy sources, embedded platforms, a wireless link and a small memory.Current research in WVSNs is focused on reducing the energyconsumption of the node so as to maximise the life of the VSN. To meet thischallenge, different software and hardware solutions are presented in theliterature for the implementation of VSNs.The focus in this thesis is on the exploration of energy efficientreconfigurable architectures for VSNs by partitioning vision tasks on software,hardware platforms and locality. For any application, some of the vision taskscan be performed on the sensor node after which data is sent over the wirelesslink to the server where the remaining vision tasks are performed. Similarly,at the VSN, vision tasks can be partitioned on software and the hardwareplatforms.In the thesis, all possible strategies are explored, by partitioning visiontasks on the sensor node and on the server. The energy consumption of thesensor node is evaluated for different strategies on software platform. It isobserved that performing some of the vision tasks on the sensor node andsending compressed images to the server where the remaining vision tasks areperformed, will have lower energy consumption.In order to achieve better performance and low power consumption,Field Programmable Gate Arrays (FPGAs) are introduced for theimplementation of the sensor node. The strategies with reasonable designtimes and costs are implemented on hardware-software platform. Based onthe implementation of the VSN on the FPGA together with micro-controller,the lifetime of the VSN is predicted using the measured energy values of theplatforms for different processing strategies. The implementation resultsprove our analysis that a VSN with such characteristics will result in a longerlife time.

Place, publisher, year, edition, pages
Sundsvall: Mid Sweden University, 2011. p. 80
Series
Mid Sweden University licentiate thesis, ISSN 1652-8948 ; 66
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-14388 (URN)STC (Local ID)978-91-86694-45-6 (ISBN)STC (Archive number)STC (OAI)
Presentation
2011-06-10, O102, Sundsvall, 10:27 (English)
Supervisors
Available from: 2011-08-24 Created: 2011-08-24 Last updated: 2016-10-19Bibliographically approved
2. Investigation of intelligence partitioning in wireless visual sensor networks
Open this publication in new window or tab >>Investigation of intelligence partitioning in wireless visual sensor networks
2011 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The wireless visual sensor network is an emerging field which is formed by deploying many visual sensor nodes in the field and in which each individual visual sensor node contains an image sensor, on board processor, memory and wireless transceiver. In comparison to the traditional wireless sensor networks, which operate on one dimensional data, the wireless visual sensor networks operate on two dimensional data which requires higher processing power and communication bandwidth. Research focus within the field of wireless visual sensor networks has been on two different extremes, involving either sending raw data to the central base station without local processing or conducting all processing locally at the visual sensor node and transmitting only the final results.This research work focuses on determining an optimal point of hardware/software partitioning at the visual sensor node as well as partitioning tasks between local and central processing, based on the minimum energy consumption for the vision processing tasks. Different possibilities in relation to partitioning the vision processing tasks between hardware, software and locality for the implementation of the visual sensor node, used in wireless visual sensor networks have been explored. The effect of packets relaying and node density on the energy consumption and implementation of the individual wireless visual sensor node, when used in a multi-hop wireless visual sensor networks have also been explored.The lifetime of the visual sensor node is predicted by evaluating the energy requirement of the embedded platform with a combination of the Field Programmable Gate Arrays (FPGA) and the micro-controller for the implementation of the visual sensor node and, in addition, taking into account the amount of energy required for receiving/forwarding the packets of other nodes in the multi-hop network.Advancements in FPGAs have been the motivation behind their choice as the vision processing platform for implementing visual sensor node. This choice is based on the reduced time-to-market, low Non-Recurring Engineering (NRE) cost and programmability as compared to ASICs. The other part of the architecture of the visual sensor node is the SENTIO32 platform, which is used for vision processing in the software implementation of the visual sensor node and for communicating the results to the central base station in the hardware implementation (using the RF transceiver embedded in SENTIO32).

Place, publisher, year, edition, pages
Sundsvall: Mid Sweden University, 2011. p. 108
Series
Mid Sweden University licentiate thesis, ISSN 1652-8948 ; 65
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-14445 (URN)STC (Local ID)978-91-86694-44-9 (ISBN)STC (Archive number)STC (OAI)
Supervisors
Available from: 2011-09-06 Created: 2011-09-05 Last updated: 2016-10-19Bibliographically approved
3. Investigation of intelligence partitioning and data reduction in wireless visual sensor network
Open this publication in new window or tab >>Investigation of intelligence partitioning and data reduction in wireless visual sensor network
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Sundsvall: Mid Sweden University, 2013. p. 208
Series
Mid Sweden University doctoral thesis, ISSN 1652-893X ; 150
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-20976 (URN)STC (Local ID)978-91-87103-75-9 (ISBN)STC (Archive number)STC (OAI)
Supervisors
Available from: 2014-01-08 Created: 2014-01-08 Last updated: 2016-10-20Bibliographically approved

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