Title
Gossiping for threshold detection
Abstract
We investigate the use of gossip protocols to detect threshold crossings of network-wide aggregates. Aggregates are computed from local device variables using functions such as SUM, AVERAGE, COUNT, MAX and MIN. The process of aggregation and detection is performed using a standard gossiping scheme. A key design element is to let nodes dynamically adjust their neighbor interaction rates according to the distance between the nodes' local estimate of the global aggregate and the threshold itself. We show that this allows considerable savings in communication overhead. In particular, the overhead becomes negligible when the aggregate is sufficiently far above or far below the threshold. We present evaluation results from simulation studies regarding protocol efficiency, quality of threshold detection, scalability, and controllability.
Year
DOI
Venue
2009
10.1109/INM.2009.5188818
Integrated Network Management
Keywords
Field
DocType
considerable saving,threshold detection,gossip protocol,key design element,local estimate,network-wide aggregate,communication overhead,threshold crossing,local device variable,global aggregate,network management,protocols,artificial neural networks,telecommunications,data mining,hysteresis,communication systems,computer networks,switches,tree graphs,scalability,computer science
Design elements and principles,Controllability,Computer science,Communications system,Computer network,Gossip,Gossip protocol,Artificial neural network,Network management,Distributed computing,Scalability
Conference
Citations 
PageRank 
References 
3
0.40
16
Authors
3
Name
Order
Citations
PageRank
Fetahi Wuhib118012.10
Rolf Stadler270670.88
Mads Dam375461.86