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Agrawala, A. K.

Publications and source records attributed to Agrawala, A. K..

Efficient decentralized consensus protocols

Decentralized consensus protocols are characterized by successive rounds of message interchanges. Protocols which achieve a consensus in one round of message interchange require O(N-squared) messages, where N is the number of participants. In this paper, a communication scheme, based on finite projective planes, which requires only O(N sq rt N) messages for each round is presented. Using this communication scheme, decentralized consensus protocols which achieve a consensus within two rounds of message interchange are developed. The protocols are symmetric, and the communication scheme does not impose any hierarchical structure. The scheme is illustrated using blocking and nonblocking commit protocols, decentralized extrema finding, and computation of the sum function.

Lakshman, T. V.

Control of a heterogeneous two-server exponential queueing system

A dynamic control policy known as 'threshold queueing' is defined for scheduling customers from a Poisson source on a set of two exponential servers with dissimilar service rates. The slower server is invoked in response to instantaneous system loading as measured by the length of the queue of waiting customers. In a threshold queueing policy, a specific queue length is identified as a 'threshold,' beyond which the slower server is invoked. The slower server remains busy until it completes service on a customer and the queue length is less than its invocation threshold. Markov chain analysis is employed to analyze the performance of the threshold queueing policy and to develop optimality criteria. It is shown that probabilistic control is suboptimal to minimize the mean number of customers in the system. An approximation to the optimum policy is analyzed which is computationally simple and suffices for most operational applications.

Larsen, R. L.

Parametric instabilities in computer system performance prediction

Results found by applying a predictive model to a particular system (University of Maryland Computer Center's Univak 1100/42) are presented. Given the correct model parameters, the system performance from the model closely matches the actual system observed performance. However, the major application of system modeling is the prediction of performance when the system configuration is altered. The prediction results presented are disappointing but useful with the major problem traced to parametric instabilities. The interactions between the user demands, overhead activities, and device characteristics must be considered in developing system models.

Dowdy, L. W.

Predicting the workload of a computer system

A technique based on clustering is described for characterizing the current workload of a computer system and for predicting future workload. The technique was applied to predicting the load for an installation operating two machines processing about 20,000 job steps per month.

Agrawala, A. K.

Learning with a probabilistic teacher

Learning scheme for solving unsupervised learning problems with correct estimate convergence and for state estimates of Gauss-Markov sequences with additive and multiplicative observed noise

Agrawala, A. K.