Computer Networks and ISDN Systems - Selected papers of the 3rd international caching workshop
Summary cache: a scalable wide-area web cache sharing protocol
IEEE/ACM Transactions on Networking (TON)
Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
Exact and approximate membership testers
STOC '78 Proceedings of the tenth annual ACM symposium on Theory of computing
Space-code bloom filter for efficient traffic flow measurement
Proceedings of the 3rd ACM SIGCOMM conference on Internet measurement
Link-level measurements from an 802.11b mesh network
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
Informed content delivery across adaptive overlay networks
IEEE/ACM Transactions on Networking (TON)
Collecting the internet AS-level topology
ACM SIGCOMM Computer Communication Review
Efficient algorithms for large-scale topology discovery
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
An optimal Bloom filter replacement
SODA '05 Proceedings of the sixteenth annual ACM-SIAM symposium on Discrete algorithms
Sympathy for the sensor network debugger
Proceedings of the 3rd international conference on Embedded networked sensor systems
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Connectivity monitoring is useful in practical deployment of wireless sensor network. In order to understand the behavior and performance bottleneck, knowledge of the network connectivity is crucial. In this paper, we propose a flexible and efficient connectivity monitoring algorithm (H^2CM) that has three components and operates in a divide-and-conquer manner. The components include hop vector distance based filtering, Bloom filters and signature hashing and are designed to work with different combinations of network and neighbor set sizes. In simulation, communication cost reduction of H^2CM compare to maximal compression of neighborhood information varies from 65% to 85% for large networks (1000 nodes) and from 40% to 70% for a medium size network (a few hundred nodes). We have also implemented the algorithm in TinyOS and evaluated its performance on a testbed with 34 motes. Lastly, we study the problem of node failure detection - a simple application of connectivity monitoring. We show that by combining H^2CM with the concept of dominating set, the communication cost can be drastically reduced compare to traditional data collection method.