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Scalable Geographic Routing for Data-Centric Storage

Investigating scalable routing techniques for wireless sensor networks, enhancing data storage structures. Published work in ACM conferences, demonstrated implementations, and developed robust protocols. Overcoming challenges for accurate and practical data dissemination in sensor networks.

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Scalable Geographic Routing for Data-Centric Storage

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  1. Grant Number: 0330178 Institution of PI: University of Southern CaliforniaPIs: Ramesh Govindan, Scott Shenker, and Brad KarpTitle: Robust and Efficient Data Dissemination for Data-Centric Storage Our project is investigating scalable and robust routing techniques for wireless sensor networks. These techniques provide the underlying routing infrastructure for a variety of distributed data storage structures, such as hash tables and multi-dimensional index trees. • Published the work on routing without location information in ACM Mobicom 2003. • Posted a publication describing CLDP to ACM SenSys 2004. • Posted a publication describing the Routing using Hierarchical Localization Identifiers to ACM SenSys 2004. • Implemented GPSR on the Mica-2 motes. • Demonstrated our GPSR implementation, integrated with a data-centric storage scheme called DIM, at ACM SenSys 2003. • Investigated the robustness of geographic routing protocols to obstacles and localization errors. • Designed a geographic routing protocol that essentially works on arbitrary graphs. • Designed and evaluated a practical and scalable routing algorithm for sensor networks that uses location information. • Developed a scalable routing protocol for sensor networks that does not rely on location information. • Implemented GPSR and demonstrated its integration with a data-centric storage scheme. Previously, geographical routing suffers both the inaccuracy of the position and break of the unit disk graph assumption in a real radio network. Our work in CLDP makes the geographical routing possible in realistic radio network, such as sensor networks. Altogether, the data-centric storage systems will be possibly deployed in real applications due to our effort in providing scalable, robust and efficient routing in all cases. Figure: We have developed a new geographic routing protocol that is perfect on arbitrary graphs. Existing routing protocols do not have this property.

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