********************* CALL FOR PAPERS *********************

SUBMISSION DUE DATE: November 30, 2010


SPECIAL ISSUE ON Nature-Inspired Optimization for Wireless Sensor Networks
International Journal of Swarm Intelligence Research (IJSIR)

Guest Editors:
Professor Jun Zhang, E-mail: junzhang@ieee.org
Dr. Xiao-Min Hu, E-mail: xmhu@ieee.org


INTRODUCTION:
WSNs are research hotspots recently in that they use cheap and low-power sensors to perform surveillance tasks such as environmental monitoring, military surveillance, animal tracking, and home applications. Generally equipped with redundant sensors, a WSN also provides reliable and adaptive functions when some sensors become invalid. Because sensors are generally battery-powered and difficult to be recharged, how to control the operations of sensors so that the network can accomplish its task efficiently and continuously is a critical research topic in WSNs. New technologies for the areas such as intelligent node deployment, work mode scheduling, data aggregation, routing algorithms, and energy-efficient schemes, are needed in the further development of WSNs.

Nature-inspired (NI) optimization algorithms are a kind of techniques that simulate various biological behaviors in nature, such as foraging behaviors of ants and honey bees, bird flocking, animal herding, evolution of chromosomes, process of vertebrate immune system, and so on. The resulting ant colony optimization, particle swarm optimization, evolutionary algorithms, artificial immune systems, and many more have successfully solved a wide range of optimization problems. These algorithms are notable for using a population of simple individuals (ants, particles, chromosomes, etc.) interacting with each other to approach to the global optimum. Recently, there are also rapid growing research interests in NI algorithms, because the features of NI algorithms have shown to be able to adapt well in changing environments, especially suitable for the application of wireless sensor networks (WSNs). Research into using NI algorithms in WSNs is still at the beginning, many research issues are still open.

OBJECTIVE OF THE SPECIAL ISSUE:
The aim of this special issue is to highlight the most significant recent advances in the field, to identify future research directions, and increase the awareness of the computing and WSN community at large on taking advantage of NI optimization algorithms in the application of WSNs.

RECOMMENDED TOPICS:
Potential authors for this special issue should be researchers who are working with high quality NI optimization techniques applied to WSNs. Themes of the submitted articles should include the use of NI algorithms in WSNs. Authors are invited to submit their original and unpublished work in the areas including (but not limited to) the following:

• Theoretical studies of NI paradigms and algorithms for WSN applications
• Development/Survey of new NI paradigms and algorithms for WSN applications
• Swarm intelligence for applications in WSNs
• Knowledge-free and self-learning algorithms in WSNs
• Learning and adaptation for lifetime maximization in WSNs
• Intelligent coverage and surveillance in WSNs
• Efficient communication and traffic routing in WSNs
• Data aggregation and sensor clustering in WSNs
• Position location in WSNs
• Energy-efficient schemes for WSNs
• Representations for WSNs
• Heterogeneous WSNs
• Challenges for NI algorithms in WSNs
• Decentralized/distributed online NI algorithms in WSNs
• Modeling robust routing in dynamic/mobile sensors
• Optimization under uncertainty


SUBMISSION PROCEDURE:
Researchers and practitioners are invited to submit papers for this special theme issue on Nature-Inspired Optimization for Wireless Sensor Networks on or before November 30, 2010. All submissions must be original and may not be under review by another publication. INTERESTED AUTHORS SHOULD CONSULT THE JOURNAL’S GUIDELINES FOR MANUSCRIPT SUBMISSIONS at
http://www.igi-global.com/development/author_info/guidelines submission.pdf.
All submitted papers will be reviewed on a double-blind, peer review basis. Papers must follow APA style for reference citations.

IMPORTANT DATES:
30 November 2010: Deadline for full paper submission for special issue
31 January 2010: Acceptance notification sent to authors
28 February 2011: Deadline for final paper submission for special issue
June 2011: Target publication date of special issue

Please submit original manuscripts in WORD or PDF style through email to junzhang@ieee.org, indicating the submission for the IJSIR special issue.


ABOUT International Journal of Swarm Intelligence Research (IJSIR):
The mission of the IJSIR is to become a leading international and well-referred journal in swarm intelligence, nature-inspired optimization algorithms, and their applications. This journal publishes original and previously unpublished articles including research papers, survey papers, and application papers, to serve as a platform for facilitating and enhancing the information shared among researchers in swarm intelligence research areas ranging from algorithm developments to real-world applications

This journal is an official publication of the Information Resources Management Association
www.igi-global.com/IJSIR

Editor-in-Chief: Yuhui Shi
Published: Quarterly (both in Print and Electronic form)


PUBLISHER:
The International Journal of Swarm Intelligence Research (IJSIR) is published by IGI Global (formerly Idea Group Inc.), publisher of the “Information Science Reference” (formerly Idea Group Reference) and “Medical Information Science Reference” imprints. For additional information regarding the publisher, please visit www.igi-global.com.