On time and space decomposition of complex structures
Communications of the ACM
Stochastic catastrophe theory in computer performance modeling
Journal of the ACM (JACM)
Congestion avoidance and control
SIGCOMM '88 Symposium proceedings on Communications architectures and protocols
Path integral methods for computer performance analysis
Information Processing Letters
High-performance communication networks
High-performance communication networks
Decomposability, instabilities, and saturation in multiprogramming systems
Communications of the ACM
The Practical Performance Analyst: Performance-by-Design Techniques for Distributed Systems
The Practical Performance Analyst: Performance-by-Design Techniques for Distributed Systems
Performance Modeling of Distributed Hybrid Architectures
IEEE Transactions on Parallel and Distributed Systems
Disaster avoidance mechanism for content-delivering service
Computers and Operations Research
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Failures in communication networks have become all too familiar. The AT&T phone system was brought to its knees in 1990 and their frame-relay network shut down west coast bank ATMs in 1998. These were hard network failures. Less obvious is the congestive failure of packet networks even without hard errors. This spontaneous collapse in performance is observed as orders-of-magnitude drop in packets/second delivered or increased packet delay. Such effects were seen on the Internet in 1986 and led to the implementation of the TCP/IP "slow-start" congestion avoidance algorithm. That same algorithm is now responsible for latency overhead in HTTP traffic on the World Wide Web. This paper outlines an approach developed by the author based on the surprising observation that the degree of instability in computer networks is logically equivalent to estimating the rate of decay in an unstable (radioactive) atom and suggests the application of the Feynman path integral from quantum mechanics. The advantage of this approach is threefold: (a) it makes the dynamics of large transients intuitively clear, (b) it furnishes an estimator for the mean time to collapse, and (c) it provides corrections to other estimators (e.g., Catastrophe Theory and the Theory of Large Deviations).