Multifaceted Optimization of Energy Efficiency for Stationary WSN Applications
Loading...
URL
Journal Title
Journal ISSN
Volume Title
School of Science |
Doctoral thesis (article-based)
| Defence date: 2013-02-01
Checking the digitized thesis and permission for publishing
Instructions for the author
Instructions for the author
Unless otherwise stated, all rights belong to the author. You may download, display and print this publication for Your own personal use. Commercial use is prohibited.
Authors
Date
Major/Subject
Mcode
Degree programme
Language
en
Pages
61 + app. 67
Series
Aalto University publication series DOCTORAL DISSERTATIONS, 182/2012
Abstract
Stationary Wireless Sensor Networks (S-WSNs) consist of battery-powered and resource-constrained sensor nodes distributed at fixed locations to cooperatively monitor the environment or an object and provide persistent data acquisition. These systems are being practiced in many applications, ranging from disaster warning systems for instant event detection to structural health monitoring for effective maintenance. Despite the diversity of S-WSN applications, one common requirement is to achieve a long lifespan for a higher value-to-cost ratio. However, the variety of WSN deployment environments and use cases imply that there is no silver bullet to solve the energy issue completely. This thesis is a summary of six publications. Our contributions include four energy optimization techniques on three layers for S-WSN applications. From the bottom up, we designed an ultra-low power smart trigger to integrate environment perceptibility into the hardware. On the network layer, we propose a reliable clustering protocol and a cluster-based data aggregation scheme. This scheme offers topology optimization together with in-network data processing. On the application layer, we extend an industrial standard protocol XMPP to incorporate WSN characteristics for unified information dissemination. Our protocol extensions facilitate WSN application development by adopting IMPS on the Internet. In addition, we conducted a performance analysis of one lightweight security protocol for WSNs called HIP Diet Exchange, which is being standardized by IETF. We suggested a few improvements and potential applications for HIP DEX. In the process of improving energy efficiency, we explore modular and generic design for better system integration and scalability. Our hardware invention can extend features by adding new transducers onboard. The clustering protocol and data aggregation scheme provides a general self-adaptive method to increase information throughput per energy cost while tolerating network dynamics. The unified XMPP extensions aim to support seamless information flow for the Web of Things. The results presented in this thesis demonstrate the importance of multifaceted optimization strategy in WSN development. An optimal WSN system should comprehend multiple factors to boost energy efficiency in a holistic approach.Description
Supervising professor
Ylä-Jääski, Antti, Prof., Aalto University, FinlandThesis advisor
Lukyanenko, Andrey, Dr., Aalto University, FinlandKeywords
Other note
Parts
- [Publication 1]: Pin Nie and Zhihua Jin. Morph: Cognitive Clustering for Wireless Sensor Networks using Smart Materials. In European Workshop on Structural Health Monitoring (EWSHM’10), Proceedings of the 5th European Workshop on Structural Health Monitoring, Sorrento, Italy, June 2010.
- [Publication 2]: Pin Nie, Juho Salminen, Lukyanenko Andrey and Antti Ylä-Jääski. Smart Trigger for Ultralow Power and Time Critical WSN Applications. In International Conference on Internet of Things (iThings’12), Proceedings of IEEE International Conference on Internet of Things, Besançon, France, November 2012.
- [Publication 3]: Pin Nie, Juho Vähä-Herttua, Tuomas Aura and Andrei Gurtov. Performance Analysis of HIP Diet Exchange for WSN Security Establishment. In International Symposium on QoS and Security for Wireless and Mobile Networks (Q2SWinet’11), Proceedings of the 7th ACM International Symposium on QoS and Security for Wireless and Mobile Networks, Miami, USA, October 2011.
- [Publication 4]: Pin Nie, Zhihua Jin and Yi Gong. Mires++: A Reliable, Energy-aware Clustering Algorithm for Wireless Sensor Networks. In International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM’10), Proceedings of the ACM 13th International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, Bodrum, Turkey, October 2010.
- [Publication 5]: Pin Nie and Bo Li. A Cluster-based Data Aggregation Architecture in WSN for Structural Health Monitoring. In International Wireless Communications and Mobile Computing Conference (IWCMC’11), Proceedings of the 7th International Conference on Wireless Communications and Mobile Computing, Istanbul, Turkey, July 2011.
- [Publication 6]: Pin Nie and Jukka K. Nurminen. Integrate WSN to the Web of Things by using XMPP. International Conference on Sensor Systems and Software (S-Cube’12), Proceedings of the 3rd International Conference on Sensor Systems and Software, Lisbon, Portugal, June 2012.