Decentralized Computation of Threshold Crossing Alerts

Threshold crossing alerts (TCAs) indicate to a management system that a management variable, associated with the state, performance or health of the network, has crossed a certain threshold. The timely detection of TCAs is essential to proactive management. This paper focuses on detecting TCAs for network-level variables, which are computed from device-level variables using aggregation functions, such as SUM, MAX, or AVERAGE. It introduces TCA-GAP, a novel protocol for producing network-wide TCAs in a scalable and robust manner. The protocol maintains a spanning tree and uses local thresholds, which adapt to changes in network state and topology, by allowing nodes to trade unused “threshold space”. Scalability is achieved through computing the thresholds locally and through distributing the aggregation process across all nodes. Fault-tolerance is achieved by a mechanism that reconstructs the spanning tree after node addition, removal or failure. Simulation results on an ISP topology show that the protocol successfully concentrates traffic overhead to periods where the aggregate is close to the given threshold.

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