Guoliang Xing
Chenyang Lu
Ying Zhang
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Abstract
This article proposes the minimum power configuration (MPC) approach to power management in wireless sensor networks. In contrast to earlier research that treats different radio states (i.e., transmission/reception/idle) in isolation, MPC integrates them in a joint optimization problem that depends on both the set of active nodes and the transmission power. We propose four approximation algorithms with provable performance bounds and two practical routing protocols. Simulations based on realistic radio models show that the MPC approach can conserve more energy than existing minimum power routing and topology control protocols. Furthermore, it can flexibly adapt to network workload and radio platforms.
- Alessio, F. 2004. Sensor networks: Performance measurements with motes technology. Tech. Rep., University of Pisa, Italy.Google Scholar
- Alzoubi, K., Li, X.-Y., Wang, Y., Wan, P.-J., and Frieder, O. 2003. Geometric spanners for wireless ad hoc networks. IEEE Trans. Parallel Distrib. Syst. 14. Google ScholarDigital Library
- Bertsekas, D. and Gallager, R. 1987. Data Networks. Prentice-Hall, Upper Saddle River, NJ. Google ScholarDigital Library
- Calinescu, G., Kapoor, S., Olshevsky, A., and Zelikovsky, A. 2003. Network lifetime and power assignment in ad-hoc wireless networks. In Proceedings of the Annual European Symposium on Algorithms (ESA).Google Scholar
- Chang, J.-H. and Tassiulas, L. 2000. Energy conserving routing in wireless ad hoc networks. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (InfoCom).Google Scholar
- Chen, B., Jamieson, K., Balakrishnan, H., and Morris, R. 2001. Span: An energy-efficient coordination algorithm for topology maintenance in ad hoc wireless networks. In Proceedings of the 7th Annual International Conference on Mobile Computing and Networking (MobiCom). Google ScholarDigital Library
- Chipara, O., He, Z., Xing, G., Chen, Q., Wang, X., Lu, C., Stankovic, J., and Abdelzaher, T. 2006. Real-Time power-aware routing in sensor networks. In Proceeding of the IEEE International Workshop on Quality of Service (IWQoS).Google Scholar
- Chipara, O., Lu, C., and Roman, G.-C. 2000. Efficient power management based on application timing semantics for wireless sensor networks. In Proceedings of the IEEE International Conference on Distributed Computing Systems (ICDCS). Google ScholarDigital Library
- Crossbow. 2003. Mica and mica2 wireless measurement system datasheets. http://72.14.209.104/searchPq=cache:uw-483FWGsUJ:www.xbow.com/Products/Product-pdf-Files/Wireless-pdf/MICA2-Datasheet.pdf+Crossbow+Micatandtmicaz+wireless+measurement+system+data+sheet&-hl=en&-ct=clnk&-cd=1&-gl=usGoogle Scholar
- Dukstra, E. W. 1959. A note on two problems in connexion with graphs. Numer. Math. 1, 269--271.Google ScholarDigital Library
- Dong, Q. 2005. Maximizing system lifetime in wireless sensor networks. In Proceedings of the 4th International Symposium on Information Processing in Sensor Networks (IPSN). Google ScholarDigital Library
- Dong, Q., Banerjee, S., Adler, M., and Misra, A. 2005. Minimum energy reliable paths using unreliable wireless links. In Proceedings of the 6th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc). Google ScholarDigital Library
- Doshi, S., Bhandare, S., and Brown, T. X. 2002. An on-demand minimum energy routing protocol for a wireless ad hoc network. SIGMOBILE Mob. Comput. Commun. Rev. 6, 3, 50--66. Google ScholarDigital Library
- Doshi, S. and Brown, T. X. 2002. Minimum energy routing schemes for a wireless ad hoc network. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (InfoCom).Google Scholar
- Ergen, S. C. 2002. Pedamacs: Power efficient and delay aware medium access protocol for sensor networks. M. S. thesis, University of California at Berkeley. Google ScholarDigital Library
- Garey, M. R. and Johnson, D. S. 1990. Computers and Intractability; A Guide to the Theory of NP-Completeness. W. H. Freeman. Google ScholarDigital Library
- Gilbert, E. N. and Pollak, H. O. 1968. Steiner minimal trees. SIAM J. Appl. Math. 16, 1--29.Google ScholarDigital Library
- He, T., Krishnamurthy, S., Stankovic, J. A., Abdelzaher, T., Luo, L., Stoleru, R., Yan, T., Gu, L., Hui, J., and Krogh, B. 2004. Energy-Efficient surveillance system using wireless sensor networks. In Proceedings of the 9th International Conference on Mobile System, Applications, and Services (MobiSys). Google ScholarDigital Library
- Hohlt, B., Doherty, L., and Brewer, E. 2004. Flexible power scheduling for sensor networks. In Proceedings of the 3rd International Symposium on Information Processing in Sensor Networks (IPSN). Google ScholarDigital Library
- IEEE. 1999. Wireless lan medium access control (mac) and physical layer (phy) specifications. IEEE Standard 802.11.Google Scholar
- Imase, M. and Waxman, B. 1991. Dynamic Steiner tree problem. SlAM J. Discrete Math. 4, 3, 369--384.Google ScholarCross Ref
- Kawadia, V. and Kumar, P. R. 2003. Power control and clustering in ad hoc networks. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (InfoCom).Google Scholar
- Kotz, D., Newport, C., Gray, R. S., Liu, J., Yuan, Y., and Elliott, C. 2004. Experimental evaluation of wireless simulation assumptions. In Proceedings of the 7th ACM International Symposium on Modeling, Analysis and Simulation of Wireless and Mobile Systems (MSWiM). Google ScholarDigital Library
- Li, L., Halpern, J. Y., Bahl, P., Wang, Y.-M., and Wattenhofer, R. 2001. Analysis of a cone-based distributed topology control algorithm for wireless multi-hop networks. In Proceedings of the 20th Annual ACM Symposium on Principles of Distributed Computing. Google ScholarDigital Library
- Li, N., Hou, J. C., and Sha, L. 2003. Design and analysis of an MST-based topology control algorithm. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (InfoCom).Google Scholar
- Li, Q., Aslam, J., and Rus, D. 2001. Online power-aware routing in wireless ad-hoc networks. In Proceedings of the Annual International Conference on Mobile Computing and Networking (MobiCom). Google ScholarDigital Library
- Mainwaring, A., Culler, D., Polastre, J., Szewczyk, R., and Anderson, J. 2002. Wireless sensor networks for habitat monitoring. In Proceeding of the 1st ACM International Workshop on Wireless Sensor Networks and Applications (WSNA). 88--97. Google ScholarDigital Library
- Meyerson, A., Munagala, K., and Plotkin, S. 2000. Cost-Distance: Two metric network design. In Proceedings of the 41st Annual Symposium on Foundations of Computer Science (FOCS). Google ScholarDigital Library
- Narayanaswamy, S., Kawadia, V., Sreenivas, R. S., and Kumar, P. R. 2002. Power control in ad-hoc networks: Theory, architecture, algorithm and implementation of the compow protocol. In Proceedings of the European Wireless Conference.Google Scholar
- Perkins, C. E. and Bhagwat, P. 1994. Highly dynamic destination-sequenced distance-vector routing (DSDV) for mobile computers. In Proceedings of the SIGCOMM Conference on Communications Architectures, Protocols and Applications. Google ScholarDigital Library
- Polastre, J., Hill, J., and Culler, D. 2004. Versatile low power media access for wireless sensor networks. In Proceedings of the 2nd International Conference on Embedded Networked Sensor System (SenSys). Google ScholarDigital Library
- Ramanathan, R. and Hain, R. 2000. Topology control of multihop wireless networks using transmit power adjustment. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (InfoCom).Google Scholar
- Robins, G. and Zelikovsky, A. 2000. Improved Steiner tree approximation in graphs. In SODA. Google ScholarDigital Library
- Rodoplu, V. and Meng, T. H. 1999. Minimum energy mobile wireless networks. IEEE J. Selected Areas in Commun. 17, 8. Google ScholarDigital Library
- Sankar, A. and Liu, Z. 2004. Maximum lifetime routing in wireless ad-hoc networks. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (InfoCom).Google Scholar
- Shnayder, V., Hempstead, M., rong Chen, B., Allen, G. W., and Welsh, M. 2004. Simulating the power consumption of large-scale sensor network applications. In Proceedings of the International Conference on Embedded Networked Sensor Systems (SenSys). Google ScholarDigital Library
- Simon, G. Probabilistic wireless network simulator. http://www.isis.vanderbilt.edu/projects/nest/prowler/.Google Scholar
- Singh, S., Woo, M., and Raghavendra, C. S. 1998. Power-Aware routing in mobile ad hoc networks. In Proceedings of the 4th Annual ACM-IEEE International Conference on Mobile Computing and Networking. Google ScholarDigital Library
- Stankovic, J. A., Abdelzaher, T., Lu, C., Sha, L., and Hou, J. 2003. Real-Time communication and coordination in embedded sensor networks. Proc. IEEE 91, 7.Google ScholarCross Ref
- Szewczyk, R., Mainwaring, A., Polastre, J., Anderson, J., and Culler, D. 2004. An analysis of a large scale habitat monitoring application. In Proceedings of the International Conference on Embedded Networked Sensor Systems (SenSys). Google ScholarDigital Library
- van Dam, T. and Langendoen, K. 2003. An adaptive energy-efficient mac protocol for wireless sensor networks. In Proceedings of the International Conference on Embedded Networked Sensor Systems (SenSys). Google ScholarDigital Library
- Wattenhofer, M. and Wattenhofer, R. 2004. Distributed weighted matching. In Proceedings of the 18th Annual Conference on Distributed Computing (DISC).Google Scholar
- Woo, A., Tong, T., and Culler, D. 2003. Taming the underlying challenges of reliable multihop routing in sensor networks. In Proceedings of the International Conference on Embedded Networked Sensor Systems (SenSys). Google ScholarDigital Library
- Xing, G., Lu, C., Zhang, Y., Huang, Q., and Pless, R. 2005. Minimum power configuration in wireless sensor networks. In Proceedings of the 6th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc). Google ScholarDigital Library
- Xing, G., Wang, X., Zhang, Y., Lu, C., Pless, R., and Gill, C. 2005. Integrated coverage and connectivity configuration for energy conservation in sensor networks. ACM Trans. on Senor Netw. 1, 1, 36--72. Google ScholarDigital Library
- Xu, N., Rangwala, S., Chintalapudi, K. K., Ganesan, D., Broad, A., Govindan, R., and Estrin, D. 2004. A wireless sensor network for structural monitoring. In Proceedings of the International Conference on Embedded Networked Sensor Systems (SenSys). Google ScholarDigital Library
- Xu, Y., Heidemann, J., and Estrin, D. 2000. Adaptive energy-conserving routing for multihop ad hoc networks. Res. Rep. 527, USC. October.Google Scholar
- Xu, Y., Heidemann, J., and Estrin, D. 2001. Geography-Informed energy conservation for ad hoc routing. In Proceedings of the Annual International Conference on Mobile Computing and Networking (MobiCom). Google ScholarDigital Library
- Ye, W., Heidemann, J., and Estrin, D. 2002. An energy-efficient MAC protocol for wireless sensor networks. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (InfoCom).Google Scholar
- Zhang, Y. 2007. Routing modeling application simulation environment. http://www2.parc.com/spl/projects/era/nest/Rmase/.Google Scholar
- Zhao, J. and Govindan, R. 2003. Understanding packet delivery performance in dense wireless sensor networks. In Proceedings of the International Conference on Embedded Networked Sensor Systems (SenSys) (Los Angeles, CA). Google ScholarDigital Library
- Zheng, R., Hou, J. C., and Sha, L. 2003. Asynchronous wakeup for ad hoc networks. In Proceedings of the 4th ACM International Symposium on Mobile Ad Hoc Networking and Computing. ACM Press, New York, 35--45. Google ScholarDigital Library
- Zheng, R. and Kravets, R. 2003. On-Demand power management for ad hoc networks. In Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (InfoCom).Google Scholar
- Zuniga, M. and Krishnamachari, B. 2004. Analyzing the transitional region in low power wireless links. In Proceedings of the 1st IEEE International Conference on Sensor and Ad Hoc Communications and Networks (SeCon).Google Scholar
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- Minimum power configuration for wireless communication in sensor networks
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