Our vision is to create an architecture, called Safari, that is able to provide network connectivity and basic network services in a self-organizing fashion, using available infrastructure when and where it exists, without depending on its availability. Our goals are to:
The wide spread usage of powerful mobile computing devices predict sizes for future Mobile Ad hoc Networks (MANETs), several magnitudes larger than current protocols can handle. Our research is targeted towards providing scalable ad hoc routing and enable conventional internet services like the DNS, DHCP and SMTP for such MANETs and eventually seamless integration of wired infrastructure, whenever available. To this end we have proposed an architecture called Safari which employs topology aware, hierarchical addressing for the mobile hosts through a proactive, self-organizing, hierarchical address assignment protocol. Topology awareness is implemented in a distributed fashion using a Distributed Hash Table (DHT). Novel to our approach are beacon broadcasts which are instrumental in creating an adaptive hierarchy and an overlay structure, and at the same time disseminate valuable routing information, thus drastically reducing overhead.
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and Higher Layer Protocols in Multihop Wireless Ad
Hoc Networks. Yih-Chun
Hu and David B. Johnson. In Proceedings of
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Adaptive Clock Synchronization in Sensor
PalChaudhuri, Amit Kumar Saha, and David B. Johnson. In Proceedings
of International Conference on Information Processing in Sensor Networks,
Modeling Mobility for Vehicular Ad Hoc
Kumar Saha and David B. Johnson. Poster
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Robust distributed estimation in sensor networks using the
embedded polygons algorithm. V. Delouille, R. Neelamani, and Richard G. Baraniuk. In International
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Alireza Keshavarz-Haddad, Vinay Ribeiro and Rudolf Riedi.
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Distributed wavelet transform for irregular sensor network grids. R. Wagner and V. Deloille and H. Choi and R. Baraniuk. In IEEE/SP 13th Workshop on Statistical Signal Processing, July 2005.
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Design of Adaptive Overlays for Multi-scale
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Wavelet Analysis and Processing in Sensor Networks. Raymond S. Wagner,
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Routing-Enhanced Duty-Cycle MAC Protocol for Wireless Sensor Networks. Shu Du, Amit Kumar Saha and David B.
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An Adaptive Scheduling Protocol for Multi-scale Sensor Network Architecture. Santashil PalChaudhuri and David B. Johnson. In Proceedings of the Third IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS 2007), pp. 386-403, IEEE, Santa Fe, NM, June 2007. Proceedings published as Lecture Notes in Computer Science (LNCS) 4549, Springer, 2007.
On non-scale-invariant infinitely divisible cascades. Pierre Chainais, Rudolf Riedi and Patrice Abry. In IEEE Transactions on Information Theory, 51 (3), pp 1063--1083, March 2005.
Diverging moments and parameter estimation. Paulo Goncalves and Rudolf Riedi. In Journal of the American Statistical Association, 100 (472), pp 1382-1393, December 2005.
Optimal sampling strategies for multiscale stochastic processes. Vinay J. Ribeiro, Rudolf Riedi and Richard G. Baraniuk. In IMS Lecture Notes–Monograph Series, 2nd Lehmann Symposium – Optimality 49, 266--290, 2006.
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Wireless Networks. Alireza Keshavarz-Haddad, Vinay
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on Mobile Computing and Networking (MobiCom),
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Interplay of Power, Density and Interference. Alireza
Keshavarz-Haddad and Rudolf Riedi. 4th Annual IEEE
Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and
Bounds for the Capacity of Wireless Multihop Networks imposed by Topology and Demand . Alireza Keshavarz-Haddad and Rudolf Riedi. 8th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), Montréal, Québec, Canada, September 2007.
Infinitely Divisible Shot-Noise: Modeling Fluctuations in Networking and Finance. Rudolf Riedi and Darrin Gershman.
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Multicast Capacity of Large Homogeneous Multihop Wireless Networks. Alireza Keshavarz-Haddad and Rudolf Riedi. 6th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt), Berlin, Germany, April 2008.
on the Benefit of Network Coding: Throughput and Energy Saving in Wireless
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This work is funded by the NSF under grant number ANI-0338856 and by Texas ATP.
This material is based upon work supported by the National Science Foundation under Grant No. 0338856. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
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