Future scenarios of parallel computing: Distributed sensor networks

Over the past few years, motivated by the accelerating technological convergence of sensing, computing and communications, there has been a growing interest in potential and technological challenges of Wireless Sensor Network. This paper will introduce a wide range of current basic research lines dealing with ad hoc networks of spatially distributed systems, data rate requirements and constraints, real-time fusion and registration of data from distributed sensors, cooperative control, hypothesis generation, and network consensus filtering. This technical domain has matured to the point where a number of industrial products and systems have appeared. The presentation will also describe the state of the art regarding current and soon-to-appear applications.

[1]  Ivan Stojmenovic,et al.  Handbook of Sensor Networks: Algorithms and Architectures , 2005, Handbook of Sensor Networks.

[2]  Robert D. Nowak,et al.  Quantized incremental algorithms for distributed optimization , 2005, IEEE Journal on Selected Areas in Communications.

[3]  Srinivasan Seshan,et al.  IrisNet: An Architecture for Enabling Sensor-Enriched Internet Service , 2003 .

[4]  V. Michael Bove,et al.  The role of groups in smart camera networks , 2006 .

[5]  Yong Yao,et al.  The cougar approach to in-network query processing in sensor networks , 2002, SGMD.

[6]  Jeff Rose,et al.  MANTIS OS: An Embedded Multithreaded Operating System for Wireless Micro Sensor Platforms , 2005, Mob. Networks Appl..

[7]  Yu Hen Hu,et al.  Distance-Based Decision Fusion in a Distributed Wireless Sensor Network , 2004, Telecommun. Syst..

[8]  Kamran Eshraghian,et al.  SoC Emerging Technologies , 2006, Proceedings of the IEEE.

[9]  Wei Hong,et al.  TinyDB: an acquisitional query processing system for sensor networks , 2005, TODS.

[10]  Virginio Cantoni,et al.  Multiprocessor computing for images , 1988, Proc. IEEE.

[11]  Chenyang Lu,et al.  Mobile agent middleware for sensor networks: an application case study , 2005, IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005..

[12]  Richard M. Murray,et al.  Consensus problems in networks of agents with switching topology and time-delays , 2004, IEEE Transactions on Automatic Control.

[13]  Matt Welsh,et al.  Decentralized, adaptive resource allocation for sensor networks , 2005, NSDI.

[14]  Jeff Rose,et al.  Embedded Operating Systems for Wireless Microsensor Nodes , 2005, Handbook of Sensor Networks.

[15]  G. Amdhal,et al.  Validity of the single processor approach to achieving large scale computing capabilities , 1967, AFIPS '67 (Spring).

[16]  Robert D. Nowak,et al.  Backcasting: adaptive sampling for sensor networks , 2004, Third International Symposium on Information Processing in Sensor Networks, 2004. IPSN 2004.

[17]  Takashi Matsuyama,et al.  Real-time cooperative multi-target tracking by communicating active vision agents , 2002, Object recognition supported by user interaction for service robots.

[18]  Stefano Levialdi,et al.  Matching the task to an image processing architecture , 1983, Comput. Vis. Graph. Image Process..

[19]  David E. Culler,et al.  Mica: A Wireless Platform for Deeply Embedded Networks , 2002, IEEE Micro.

[20]  Ryan Newton,et al.  Region streams: functional macroprogramming for sensor networks , 2004, DMSN '04.

[21]  Sandeep K. S. Gupta,et al.  Research challenges in wireless networks of biomedical sensors , 2001, MobiCom '01.

[22]  Robert Szewczyk,et al.  System architecture directions for networked sensors , 2000, ASPLOS IX.

[23]  David E. Culler,et al.  System architecture directions for networked sensors , 2000, SIGP.

[24]  Virginio Cantoni,et al.  One long argument: Azriel Rosenfeld and the genesis of modern image systems , 2005, Pattern Recognit. Lett..

[25]  Virginio Cantoni New architectural solutions for computer vision systems , 2005, Machine Vision and Applications.