Driven by advances in MEMS micro-sensors, wireless networking, and embedded processing, ad-hoc networks of sensors are becoming increasingly available for commercial and military applications such as environmental monitoring (e.g., traffic, habitat, security), industrial sensing and diagnostics (e.g., factory, appliances), monitoring critical infrastructures (e.g., power grids, water distribution, waste disposal), and collecting data for battlefield awareness.
Information processing in sensor networks is an interdisciplinary research area, which spans the areas of signal processing/detection/estimation, networking and protocols, embedded systems, data bases and information management, as well as distributed algorithms. It opens up new research venues, which include sensor tasking and control, tracking and localization, probabilistic reasoning, sensor data fusion, distributed data bases, communication protocols and theory that address network coverage, connectivity, and capacity, as well as system/software architecture and design methodologies. Moreover, all these issues have to consider many cross-cutting requirements such as efficiency/cost tradeoff, robustness, self-organization, fault-tolerance, timeliness, scalability, and network longevity.
Topics of Interest
This special issue calls for articles that highlight technical issues from physical device design, signal processing, network protocols/algorithms, to revolutionary new applications enabled by sensor network technology. In particular, we are seeking contributions in all aspects of sensor networks. Of particular interests are:
(i)Articles that summarize the fundamental performance and behavior limits of sensor networks with respect to sensor network capacity, coverage, connectivity, and/or lifetime. As wireless sensor networks must operate under extreme resource constraints, an understanding of the fundamental performance limits of such networks will provide valuable insights into what designs make sense and can help identify areas in which theory promises performance much better than that attained by existing designs.
(ii)Articles that outline algorithms which realize certain sensor network operation, such as localization, time synchronization and target tracking, and their theoretical base. Articles of this type should focus on comparing alternative algorithms/approaches with respect to the various sensor network requirements outlined above.
(iii) Articles that deal with system implementations, experiments, and experiences in application domains. At an early stage of sensor network development, one can analyze and predict network behavior through simulation and theoretical reasoning. However, a true evaluation of system performance can only be obtained through implementation and direct measurement and experimentation of the prototype. Hence articles that report the system implementation issues with an emphasis on the cross-layer design tradeoffs will shed lights on how effective the overall system design is.
Example topical areas of interests include, but not limited to
Manuscript due: January 1st, 2004
Acceptance notification: March 1st, 2004
Final manuscript due: May 1st, 2004
Expected publication date: August 2004
Submission Instruction
All submissions should adhere to the style of IEEE Wireless Communications Magazine. Guidelines for prospective authors can be found on-line at http://www.comsoc.org/pubs/pcm/sub_guidelines.html. Electronic submissions are accepted only in Postscript and PDF formats and should be sent to sensornetworks@cs.uiuc.edu directly. If you have any questions, please contact any one of the guest editors.
Submissions must meet the following criteria:
Guest Editors
Paul Havinga
Department of Computer Science
University of Twente, the Netherlands
havinga@cs.utwente.nl
Jennifer C. Hou
Department of Computer Science
University of Illinois at Urbana Champaign
jhou@cs.uiuc.edu
Mani Srivastava
Department of Electrical and Computer Engineering
University of California at Los Angeles
mbs@ee.ucla.edu
Feng Zhao
Embedded Collaborative Computing
Palo Alto Research Center
zhao@parc.com