Dynamic syslog mining for network failure monitoring
Syslog monitoring technologies have recently received vast attentions in the areas of network management and network monitoring. They are used to address a wide range of important issues including network failure symptom detection and event correlation discovery. Syslogs are intrinsically dynamic in the sense that they form a time series and that their behavior may change over time. This paper proposes a new methodology of dynamic syslog mining in order to detect failure symptoms with higher confidence and to discover sequential alarm patterns among computer devices. The key ideas of dynamic syslog mining are 1) to represent syslog behavior using a mixture of Hidden Markov Models, 2) to adaptively learn the model using an on-line discounting learning algorithm in combination with dynamic selection of the optimal number of mixture components, and 3) to give anomaly scores using universal test statistics with a dynamically optimized threshold. Using real syslog data we demonstrate the validity of our methodology in the scenarios of failure symptom detection, emerging pattern identification, and correlation discovery.
A humanitarian logistics model for disaster relief operation considering network failure and standard relief time: A case study on San Francisco district
We propose a multi-depot location-routing model considering network failure, multiple uses of vehicles, and standard relief time. The model determines the locations of local depots and routing for last mile distribution after an earthquake. The model is extended to a two-stage stochastic program with random travel time to ascertain the locations of distribution centers. Small instances have been solved to optimality in GAMS. A variable neighborhood search algorithm is devised to solve the deterministic model. Computational results of our case study show that the unsatisfied demands can be significantly reduced at the cost of higher number of local depots and vehicles.
Reliability and Survivability of Wireless and Mobile Networks
The world is becoming more dependent on wireless and mobile services, but the ability of wireless network infrastructures to handle the growing demand is questionable. As wireless and mobile services grow, weaknesses in network infrastructures become clearer. Failures not only affect current voice and data use but could also limit emerging wireless applications such as e-commerce and high-bandwidth Internet access. As wireless and mobile systems play greater roles in emergency response, including 911 and enhanced 911 services, network failures take on life-or-death significance. Therefore, in addition to directing some attention to designing survivable wireless and mobile networks, developers must also keep in mind that increasingly pervasive and demanding services will further escalate the importance of reliability and survivability requirements. The authors explain several options providers must consider to decrease the number of network failures and to cope with failures when they do occur.
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