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Intelligent fluid infrastructure for embedded networks

Published: 06 June 2004 Publication History

Abstract

Computer networks have historically considered support for mobile devices as an extra overhead to be borne by the system. Recently however, researchers have proposed methods by which the network can take advantage of mobile components. We exploit mobility to develop a fluid infrastructure: mobile components are deliberately built into the system infrastructure for enabling specific functionality that is very hard to achieve using other methods. Built-in intelligence helps our system adapt to run time dynamics when pursuing pre-defined performance objectives. Our approach yields significant advantages for energy constrained systems, sparsely deployed networks, delay tolerant networks, and in security sensitive situations. We first show why our approach is advantageous in terms of network lifetime and data fidelity. Second, we present adaptive algorithms that are used to control mobility. Third, we design the communication protocol supporting a fluid infrastructure and long sleep durations on energy-constrained devices. Our algorithms are not based on abstract radio range models or idealized unobstructed environments but founded on real world behavior of wireless devices. We implement a prototype system in which infrastructure components move autonomously to carry out important networking tasks. The prototype is used to validate and evaluate our suggested mobility control methods.

References

[1]
G. J. Pottie and W. J. Kaiser. Wireless integrated network sensors. In Communications of the ACM, May 2000.
[2]
David Tennenhouse. Embedding the Internet: Proactive computing. In Communications of the ACM, May 2000.
[3]
Ya Xu and John Heidemann and Deborah Estrin. Geography-informed energy conservation for Ad Hoc routing. In Proc. ACM Mobicom July 2001.
[4]
Henri Dubois-Ferriere, Matthias Grossglauser, Martin Vetterli. Age Matters: Efficient Route Discovery in Mobile Ad Hoc Networks Using Encounter Ages. In ACM Mobihoc June 2003.
[5]
Rahul C Shah, Sumit Roy, Sushant Jain and Waylon Brunette. DataMULEs: Modelling a Three Tiered Architecture for Sparse Sensor Networks. In First IEEE International Workshop on Sensor Network Protocols and Applications (SNPA), May 2003.
[6]
Tara Small and Zygmunt J. Haas. The shared wireless infostation model: a new ad hoc networking paradigm (or where there is a whale, there is a way). In ACM Mobihoc, June 2003.
[7]
Philo Juang, Hidekazu Oki, Yong Wang, Margaret Martonosi, Li Shiuan Peh and Daniel Rubenstein. Energy-efficient computing for wildlife tracking: design tradeoffs and early experiences with ZebraNet. In Architectural Support for Programming Languages and Operating Systems (ASPLOS), October 2002.
[8]
A Chakrabarty, A Sabharwal and B Aazhang. Using Predictable Observer Mobility for Power Efficient Design of a Sensor Network. In Second International Workshop on Information Processing in Sensor Networks (IPSN), April 2003.
[9]
Alberto Cerpa, Jeremy Elson, Deborah Estrin, Lewis Girod, Michael Hamilton and Jerry Zhao. Habitat monitoring: Application driver for wireless communications technology. In ACM SIGCOMM Workshop on Data Communications in Latin America and the Caribbean, 2001.
[10]
Alan Mainwaring, Joseph Polastre, Robert Szewczyk, David Culler and John Anderson. Wireless Sensor Networks for Habitat Monitoring. In First ACM Workshop on Wireless Sensor Networks and Applications (SNPA), September 2002.
[11]
Delay Tolerant Networking Research Group. www.dtnrg.org.
[12]
Chalermek Intanagonwiwat, Ramesh Govindan and Deborah Estrin. Directed Diffusion: A Scalable and Robust Communication Paradigm for Sensor Networks. In Mobicom, August 2000.
[13]
Philip Levis, Nelson Lee, Matt Welsh, and David Culler. TOSSIM: Accurate and Scalable Simulation of Entire TinyOS Applications. In ACM SenSys, November 2003.
[14]
Mica2 motes. Product Datasheet. http://www.xbow.com/Products/Wireless_Sensor_Networks.htm.
[15]
A. LaMarca, W. Brunette, D. Koizumi, M. Lease, S. B. Sigurdsson, K. Sikorski, D. Fox, and G. Borriello. PlantCare: An Investigation in Practical Ubiquitous Systems. In Ubicomp, September 2002.
[16]
Packbot, The Next Step in Unmanned Tactical Mobile Robots. www.packbot.com.
[17]
iRobot. www.irobot.com.
[18]
ActivMedia Robotics. www.amigobot.com.
[19]
TinyOS: a Component-based OS for the networked sensor regime. http://webs.cs.berkeley.edu/tos/.
[20]
X-Scale Single Board Computer and Wireless Networking Platform. http://www.xbow.com/Products/XScale.htm.
[21]
Dragos Niculescu and Badri Nath. Trajectory based forwarding and its applications. In Mobicom, September 2003.
[22]
J Scott and M Hazas. User-Friendly Surveying Techniques for Location-Aware Systems. In Ubicomp, October 2003.
[23]
Curt Schurgers, Vlasios Tsiatsis, Saurabh Ganeriwal, Mani Srivastava. Optimizing Sensor Networks in the Energy-Latency-Density Design Space. In IEEE Transactions on Mobile Computing, January-March 2002.
[24]
Xiaorui Wang, Guoliang Xing, Yuanfang Zhang, Chenyang Lu, Robert Pless, and Christopher Gill. Integrated Coverage and Connectivity Configuration in Wireless Sensor Networks. In ACM SenSys, November 2003.
[25]
Benjie Chen, Kyle Jamieson, Hari Balakrishnan, Robert Morris. Span: An Energy-Efficient Coordination Algorithm for Topology Maintenance in Ad Hoc Wireless Networks. In ACM Mobicom, July 2001.
[26]
Alberto Cerpa and Deborah Estrin. ASCENT: Adaptive Self-Configuring sEnsor Networks Topologies. In Infocom, June 2002.
[27]
A.K. Salkintzis. A Survey of Mobile Data Networks. In IEEE Communication Surveys, 3rd Quarter 1999.
[28]
Kevin Fall. A Delay-Tolerant Network Architecture for Challenged Internets. In Sigcomm, August 2003.
[29]
Qun Li and Daniela Rus. Sending messages to mobile users in disconnected ad-hoc wireless networks. In ACM Mobicom, August 2000.
[30]
Matthias Grossglauser and David Tse. Mobility Increases the Capacity of Ad-hoc Wireless Networks. In Infocom, April 2001.
[31]
Jerry Zhao and Ramesh Govindan. Understanding Packet Delivery Performance in Dense Wireless Sensor Networks. In ACM Sensys, November 2003.
[32]
Mohammed Rahimi, Hardik Shah, Gaurav S. Sukhatme, John Heidemann and D. Estrin. Studying the Feasibility of Energy Harvesting in a Mobile Sensor Network. In IEEE Int'l Conference on Robotics and Automation, May 2003.
[33]
Deborah Estrin, Ramesh Govindan and John Heidemann. Embedding the Internet: introduction. In Communications of the ACM, May 2000.
[34]
V. Raghunathan, C. Schurgers, S. Park and M. Srivastava. Energy aware wireless microsensor networks. In IEEE Signal Processing Magazine, March 2002.
[35]
Jeremy Elson, Lewis Girod and Deborah Estrin. Fine-Grained Network Time Synchronization using Reference Broadcasts. In Proceedings of the Fifth Symposium on Operating Systems Design and Implementation (OSDI), February 2002.
[36]
S. Jain, R. Shah, W. Brunette, G. Borriello and S. Roy. Exploiting Mobility for Energy Efficient Data Collection in Sensor Networks. In IEEE Workshop on Modeling and Optimization in Mobile Ad hoc and Wireless Networks (WiOpt), March 2004.
[37]
M Srivastava, R. Muntz, and M. Potkonjak. Smart kindergarten: sensor-based wireless networks for smart developmental problem-solving enviroments. In Proceedings of the Seventh ACM Annual International Conference on Mobile Computing and Networking (MobiCom), pages 132--138, July 2001.
[38]
AS Pentland, R Fletcher, and A Hasson. Daknet: rethinking connectivity in developing nations. IEEE Computer, 37(1):78--83, January 2004.

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cover image ACM Conferences
MobiSys '04: Proceedings of the 2nd international conference on Mobile systems, applications, and services
June 2004
294 pages
ISBN:1581137931
DOI:10.1145/990064
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 06 June 2004

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Author Tags

  1. controlled mobility
  2. data gathering
  3. mobile router
  4. sensor networks

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MobiSys '04 Paper Acceptance Rate 22 of 162 submissions, 14%;
Overall Acceptance Rate 274 of 1,679 submissions, 16%

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  • (2023)Reinforcement Learning for Delay Tolerance and Energy Saving in Mobile Wireless Sensor NetworksIEEE Access10.1109/ACCESS.2023.324757611(19819-19835)Online publication date: 2023
  • (2021)Efficient Resource Allocation in Hybrid Wireless Networks Increase the CapacityInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology10.32628/CSEIT21715(41-48)Online publication date: 1-Jan-2021
  • (2021)Functioning Model of Long-Term Sensor NetworksInformatics and Cybernetics in Intelligent Systems10.1007/978-3-030-77448-6_27(282-289)Online publication date: 16-Jul-2021
  • (2020)Cluster Estimation in Terrestrial and Underwater Sensor NetworksWireless Personal Communications10.1007/s11277-020-07851-9Online publication date: 29-Oct-2020
  • (2019)A pattern for a UAV-aided wireless sensor networkProceedings of the 26th Conference on Pattern Languages of Programs10.5555/3492252.3492258(1-9)Online publication date: 7-Oct-2019
  • (2019)Delay Tolerance and Energy Saving in Wireless Sensor Networks with a Mobile Base StationWireless Communications & Mobile Computing10.1155/2019/39298762019Online publication date: 12-Feb-2019
  • (2019)Partitioned network with Adaptive Mobile Sinks2019 IEEE 10th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)10.1109/IEMCON.2019.8936226(1098-1103)Online publication date: Oct-2019
  • (2019)A comprehensive survey on trajectory schemes for data collection using mobile elements in WSNsJournal of Ambient Intelligence and Humanized Computing10.1007/s12652-019-01268-4Online publication date: 22-Mar-2019
  • (2018)Big Data Collection in Large-Scale Wireless Sensor NetworksSensors10.3390/s1812447418:12(4474)Online publication date: 18-Dec-2018
  • (2018)An Energy Efficient Tour Construction Using Restricted k-Means Clustering Algorithm for Mobile Sink in Wireless Sensor Networks2018 11th International Conference on Developments in eSystems Engineering (DeSE)10.1109/DeSE.2018.00022(100-107)Online publication date: Sep-2018
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