Background: Traditional network management solutions suffer from scalability issues and delayed
fault reporting when monitoring large network topologies, as described in various patents. IntelliMon is an intelligent
polling engine which takes into account network baselining statistics, indicative of the past behavior of
the network and utilizes this information to dynamically formulate its polling strategies to achieve faster detection
of network faults, while regulating the amount of network management traffic that it generates. This leads
to lower Mean-Time-to-Detect (MTTD) for network faults compared to traditional network management solutions,
which employ static pre-configured polling strategies.
Method: Network baselining statistics are used to formulate dynamic polling strategies for nodes or areas of the
network which are prone to faults.
Results: Early simulation results of up to 5000 node network show that IntelliMon achieves significantly lower
MTTD, specifically 14-32% lower than traditional polling engines under different scenarios.
Conclusion: Heuristics combined with hard-statistics derived from network baselining are effective in formulating
adaptive polling strategies that are able to detect network faults quicker especially for large topologies.