Name
Abstract | ||
|---|---|---|
Network patterns are based on generic algorithms that execute on tree-based overlays. A set of such patterns has been developed at KTH to support distributed monitoring in networks with non-trivial topologies. We consider the use of this approach in logical peer networks in cfengine as a way of scaling aggregation of data to large organizations. Use of 'deep' network structures can lead to temporal anomalies. We show how to minimize temporal fragmentation during data aggregation by using time offsets and what effect these choices might have on power consumption. We offer proof of concept for this technology to initiate either multicast or inverse multicast pulses through sensor networks. |
Year | Venue | Keywords |
|---|---|---|
2007 | LISA | network structure,non-trivial topology,scalable data aggregation,large organization,temporal fragmentation,temporal anomaly,sensor network,network pattern,data aggregation,inverse multicast pulse,generic algorithm |
Field | DocType | Citations |
Computer science,Computer network,Network topology,Proof of concept,Multicast,Overlay,Data aggregator,Wireless sensor network,Scalability,Network structure,Distributed computing | Conference | 3 |
PageRank | References | Authors |
0.45 | 7 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mark Burgess | 1 | 203 | 22.41 |
| Matthew Disney | 2 | 6 | 0.91 |
| Rolf Stadler | 3 | 706 | 70.88 |