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Projects > COMPUTER > 2019 > NON IEEE > APPLICATION
LNetwork tomography is the process of calculating fine-grained link metrics by using aggregated path measurements. It is an effective and efficient way to facilitate various network operations, such as network monitoring, load balancing, and fault diagnosis. Recently, there is a growing interest in the monitor placement problem that ensures link identifiability in a network with link failures. In this project the problem of placing a minimum number of monitors to identify additive link was studied from end-to-end measurements among monitors with considering both predictable and unpredictable link failures. A set of robust monitor placement algorithms was developed with different performance-complexity trade-offs to solve this tomography problem. In particular, the optimal (i.e., minimum) monitor placement is the solution to a hitting set problem, for which it provides a polynomial-time algorithm to construct the input. The proposed algorithms can guarantee network identifiability against failures based on the graph theory.
In the existing system, Optimal Monitor Assignment (OMA) algorithm was used.An optimal monitor assignment (OMA) algorithm for preferential link tomography in communication networks. OMA first partitions the graph representing the network topology into multiple graph components.
A set of robust monitor placement algorithms that place monitors to achieve network identifiability against predictable and unpredictable link failures, including: (i) two straightforward solutions that apply an existing algorithm for static networks with fixed topologies to a network with changing topologies. (ii) An incremental placement algorithm that sequentially places monitors in each predicted topology. (iii) a joint placement algorithm that jointly considers monitor requirements of all network topologies by casting the problem as a hitting set problem, and then removes the redundant monitors by a monitor removal method.
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