Architecture exploration based on tasks partitioning between hardware, software and locality for a wireless vision sensor node

International Journal of Distributed Systems and Technologies

Volumn 3, Issue 2, 2012, Pages 58-71

  Imran, Muhammad ^a   Khursheed, Khursheed ^a   Malik, Abdul Waheed ^a   Ahmad, Naeem ^a   O'Nils, Mattias ^a   Lawal, Najeem ^a   Thörnberg, Benny ^a  

^a MID SWEDEN UNIVERSITY   (Sweden)

Author keywords

Hardware Software Partitioning; Image Processing; Reconfigurable Architecture; Vision Sensor Node; Wireless Vision Sensor Networks

Indexed keywords

ARCHITECTURE EXPLORATION; COMMUNICATION ENERGY CONSUMPTION; HARDWARE/SOFTWARE PARTITIONING; HIGH ENERGY CONSUMPTION; PROGRAMMABLE ARCHITECTURES; RECONFIGURABLE PLAT-FORMS; STATIC POWER CONSUMPTION; VISION SENSORS;

COMPUTER HARDWARE; ENERGY EFFICIENCY; ENERGY UTILIZATION; FIELD PROGRAMMABLE GATE ARRAYS (FPGA); HARDWARE; IMAGE PROCESSING; RECONFIGURABLE ARCHITECTURES; RECONFIGURABLE HARDWARE; SENSOR NETWORKS;

SENSOR NODES;

EID: 84880522514     PISSN: 19473532     EISSN: 19473540     Source Type: Journal    
DOI: 10.4018/jdst.2012040104     Document Type: Article

References (20)

1. Akyildiz, I. F., Melodia, T., & Chowdhury, K. R. (2007). A survey on wireless multimedia sensor networks. The International Journal of Computer and Telecommunications Networking, 51(4), 921-960.
2. Bianchi, A. C., & Reali-Costa, A. H. (2002). Implementing computer vision algorithms in hardware: An FPGA/VHDL-based vision system for a mobile robot. In Proceedings of the Robot Soccer World Cup, V, 281-286.
3. Curran, P., Buckley, J., O'Flynn, B., Li, X., Zhou, J., Lacey, G., & O'Mathuna, S. C. (2008). VAMP: A vision based sensor network for health care hygiene. In Proceedings of the 14th Nordic-Baltic Conference on Biomedical Engineering and Medical Physics, Riga, Latvia (Vol. 20, pp. 485-488).
4. Ferrigno, L., Marano, S., Paciello, V., & Pietrosanto, A. (2005). Balancing computational and transmission power consumption in wireless image sensor networks. In Proceedings of the IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurement Systems (p. 6).
5. Fredrik, L., Peng, C., & Oelmann, B. (2007). Analysis of the IEEE 802.15.4 standard for a wireless closed loop control system for heavy duty cranes. In Proceedings of the IEEE Second International Symposium on Industrial Embedded Systems, Lisbon, Portugal (pp. 164-169).
6. Imran, M., Khursheed, K., O'Nils, M., & Lawal, N. (2010). Exploration of target architecture for a wireless camera based sensor node. In Proceedings of the 28th Norchip Conference, Tampere, Finland (pp. 1-4).
7. Kerhet, A., Magno, M., Leonardi, F., Boni, A., & Benini, L. (2007). A low-power wireless video sensor node for distributed object detection. Journal of Real-Time Image Processing, 2, 331-342. doi:10.1007/s11554-007-0048-7
8. Khursheed, K., Imran, M., O'Nils, M., & Lawal, N. (2010). Exploration of local and central processing for a wireless camera based sensor node. In Proceedings of the IEEE International Conference on Signal & Electronic System, Gliwice, Poland (pp. 147-150).
9. Khursheed, K., Imran, M., O'Nils, M., Malik, A. W., O'Nils, M., Lawal, N., & Thornberg, B. (2011). Exploration of tasks partitioning between hardware software and locality for a wireless camera based vision sensor node. In Proceedings of the 6th International Symposium on Parallel Computing in Electrical Engineering, Luton, UK (pp. 127-132).
10. Kleihorst, R., Abbo, A., Schueler, B., & Danilin, A. (2007). Camera mote with a high-performance parallel processor for real-time frame-based video processing. In Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance, London, UK (pp. 69-74).
11. Kulkarni, P., Ganesan, D., Shenoy, P., & Lu, Q. (2005). Sens Eye, A multi-tier camera sensor network. In Proceedings of the 13th Annual ACM International Conference on Multimedia, Singapore (pp. 229-238).
12. Low, K. S., Win, W. N., & Er, M. J. (2006). Wireless sensor networks for industrial environments. In Proceedings of the International Conference on Intelligent Agents, Web Technologies and Internet Commerce, Vienna, Austria (pp. 271-276).
13. MacLean, W. J. (2005). An evaluation of the suitability of FPGAs for embedded vision systems. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, San Diego, CA (pp. 131-131).
14. Malik, A. W., Thörnberg, B., Cheng, X., & Lawal, N. (2011). Real-time component labelling with centre of gravity calculation on FPGA. In Proceedings of the Sixth International Conference on Systems, St. Maarten, French Caribbean. Microsemi. (n.d). The ACTEL Igloo. Retrieved from http://www.actel.com/products/igloo/default.aspx
15. Norell, H., Lawal, N., & O'Nils, M. (2007). Automatic generation of spatial and temporal memory architectures for embedded video processing systems. EURASIP Journal on Embedded Systems, (1): 32.
16. Rowe, A., Goel, D., & Rajkumar, R. (2007). Fire Fly Mosaic: A vision-enabled wireless sensor networking system. In Proceedings of the 28th IEEE International Real-Time Systems Symposium, Tucson, AZ (pp. 459-468).
17. Sen, M., Corretjer, I., Haim, F., Saha, S., Jason, S., & Lv, T. (2007). Dataflow-based mapping of computer vision algorithms onto FPGAs. EURASIP Journal on Embedded Systems, (1): 29.
18. Shang, L., Kaviani, A. S., & Bathala, K. (2002). Dynamic power consumption in Virtex-II FPGA family. In Proceedings of the ACM/SIGDA 10th International Symposium on Field-Programmable Gate Arrays (pp. 157-164).
19. Xilinx. (n.d). Spartan-6. Retrieved from http://www.xilinx.com/support/ documentation/spartan-6.htm
20. Zhiyong, C. H., Pan, L. Y., Zeng, Z., & Meng, M. Q.-H. (2009). A novel FPGA-based wireless vision sensor node. In Proceedings of the IEEE International Conference on Automation and Logistics, Shenyang, China (pp. 841-846).