Next century challenges: scalable coordination in sensor networks
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
Directed diffusion: a scalable and robust communication paradigm for sensor networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Distributed computation on graphs: shortest path algorithms
Communications of the ACM
Degree-constrained multicasting in point-to-point networks
INFOCOM '95 Proceedings of the Fourteenth Annual Joint Conference of the IEEE Computer and Communication Societies (Vol. 1)-Volume - Volume 1
ICDCS '01 Proceedings of the The 21st International Conference on Distributed Computing Systems
Energy Efficient Data Collection in Distributed Sensor Environments
ICDCS '04 Proceedings of the 24th International Conference on Distributed Computing Systems (ICDCS'04)
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Many applications such as those for surveillance and target detection rely on a network of sensors to collect real-time data. These sensor applications may have to operate semi-autonomously under a diverse set of operating conditions. Often, several alternative algorithms are available for each service required by an application, and the performance of these algorithms may depend on several factors such as network topology, placement of sensor nodes, and the application structure. As a result, designers are often faced with the problem of identifying the best set of algorithms to use for an application. We study this problem in the context of rate-based data propagation. This problem involves constructing a data propagation tree to efficiently disseminate data from a sensor node at the required rate to each of its consumers. We identify a number of operating conditions that can influence the efficiency of data collection trees. We propose a set of algorithms to construct data propagation trees, and perform experimental evaluation to determine the operating conditions under which each algorithm outperforms the others. Based on these evaluations, we provide heuristics to choose the most appropriate algorithm for the given operating conditions.