Modelling and analysis of the variance in parallelism in parallel computations

In this paper, we introduce an analytical technique based on queueing networks and Petri nets for making a performance analysis of dataflow computations when executed on the Manchester machine. This technique is also applicable for the analysis of parallel computations on multiprocessors. We characterize the parallelism in dataflow computations through a four-parameter characterization, namely, the minimum parallelism, the maximum parallelism, the average parallelism and the variance in parallelism. We observe through detailed investigation of our analytical models that the average parallelism is a good characterization of the dataflow computations only as long as the variance in parallelism is small. However, significant difference in performance measures will result when the variance in parallelism is comparable to or higher than the average parallelism

e-Procurement using goal programming

e-Procurement is an Internet-based business process for obtaining materials and services and managing their inflow into the organization. In this paper we develop multiattribute e-Procurement systems with configurable bids and formulate the bid evaluation problem as a linear integer multiple criteria optimization problem. Configurable bids allow multiple values for each attribute and for each value the bidder can specify price as a piecewise linear function of quantity. The suppliers can express volume discount bargaining strategy and economies of scale, using the above price function. The buyer can include several business rules and purchasing policies as side constraints in the optimization problem to evaluate the winning bids. We propose the use of goal programming techniques to solve the bid evaluation problem