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Intelligent fluid infrastructure for embedded networks
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Source International Conference On Mobile Systems, Applications And Services archive
Proceedings of the 2nd international conference on Mobile systems, applications, and services table of contents
Boston, MA, USA
SESSION: Wireless sensor networks table of contents
Pages: 111 - 124  
Year of Publication: 2004
ISBN:1-58113-793-1
Authors
Aman Kansal  University of California, Los Angeles (UCLA)
Arun A. Somasundara  University of California, Los Angeles (UCLA)
David D. Jea  University of California, Los Angeles (UCLA)
Mani B. Srivastava  University of California, Los Angeles (UCLA)
Deborah Estrin  University of California, Los Angeles (UCLA)
Sponsors
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
USENIX: USENIX Association
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 4,   Downloads (12 Months): 84,   Citation Count: 32
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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

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY  32

Collaborative Colleagues:
Aman Kansal: colleagues
Arun A. Somasundara: colleagues
David D. Jea: colleagues
Mani B. Srivastava: colleagues
Deborah Estrin: colleagues