A scheme for dynamic monitoring and logging of topology information in Wireless Mesh Networks

Popi, Cristian; Festor, Olivier

doi:10.1109/noms.2008.4575207

Cited by 3 publications

(1 citation statement)

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“…Also in the static network setting, [29] solves the problem of locating monitoring nodes to get the maximum coverage on a static network given assumptions about the cost of allocation and benefit of monitoring (and possible budget constraints). In the dynamic network setting, [30] uses a DHT to monitor the topology of a wireless network -in this context every node is part of the monitoring effort rather than a subset. In the MANETs context, [31] looks at a very specific monitoring problem, that of developing video sensors -in this context all nodes are collectors of data (like our ICPs) and the equivalent of IAPs are also fixed nodes in the network with higher capabilities for upload and download.…”

Section: Introductionmentioning

confidence: 99%

On the Selection of Management/Monitoring Nodes in Highly Dynamic Networks

Clegg

Clayman

Pavlou

et al. 2013

IEEE Trans. Comput.

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This paper addresses the problem of provisioning management/monitoring nodes within highly dynamic network environments, particularly virtual networks. In a network where nodes and links may be spontaneously created and destroyed (perhaps rapidly) there is a need for stable and responsive management and monitoring which does not create a large load (in terms of traffic or processing) for the system. A subset of nodes has to be chosen for management/monitoring, each of which will manage a subset of the nodes in the network. A new, simple and locally optimal greedy algorithm called Pressure is provided for choice of node position to minimise traffic. This algorithm is combined with a system for predicting the lifespan of nodes, and a tunable parameter is also given so that a system operator could express a preference for elected nodes to be chosen to reduce traffic, to be "stable", or some compromise between these positions. The combined algorithm called PressureTime is lightweight and could be run in a distributed manner. The resulting algorithms are tested both in simulation and in a testbed environment of virtual routers. They perform well, both at reducing traffic and at choosing long lifespan nodes.

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Section: Introductionmentioning

confidence: 99%