Abstract: Resource allocations in stream data processing systems are performed to allocate the resources in a cost-effective manner by formulating the resource allocation problem as a linear program. For a problem with a single output, a backward algorithm or method is used that produces an optimal solution in linear time. For a problem with multiple outputs and the network has a tree structure, a backward shrink algorithm or method is used to provide an optimal solution in linear time. These algorithms are fully distributed, they require only local exchange of parameters between neighboring nodes, and are adaptive to the dynamic changes in network conditions and flow rate fluctuations.

Abstract: A system and method for performance modeling for an information technology (IT) system having a server(s) for performing a number of types of transactions includes receiving data for system topology and transaction flows and receiving performance measurement data for the IT system. The measurement data is clustered into multiple regimes based on similarities. Service demand and network delay parameters may be inferred based on clustered data.

Abstract: Resource allocations in stream data processing systems are performed to allocate the resources in a cost-effective manner by formulating the resource allocation problem as a linear program. For a problem with a single output, a backward algorithm or method is used that produces an optimal solution in linear time. For a problem with multiple outputs and the network has a tree structure, a backward shrink algorithm or method is used to provide an optimal solution in linear time. These algorithms are fully distributed, they require only local exchange of parameters between neighboring nodes, and are adaptive to the dynamic changes in network conditions and flow rate fluctuations.

Abstract: Techniques are provided for determining a capacity allocation in a multi-tiered computing system. In one aspect of the invention, a technique for designing capacity allocation for a multi-tiered computing system, each tier of the computing system having one or more computing devices (e.g., servers), comprises the following steps/operations. Input parameters relating to capacity allocation are obtained. A capacity allocation is computed based on at least a portion of the input parameters, the capacity allocation being computable such that one or more end-to-end performance measures are substantially satisfied for multiple service classes. The capacity allocation computation may minimize a cost function.

Abstract: In one embodiment, the present invention is a method and apparatus for automatic system parameter configuration for performance improvement. One embodiment of the inventive method involves formulating a black box optimization problem, and solving the optimization problem using an enhanced smart hill climbing method. The smart hill climbing method includes both a global and a more precise local search to identify an optimal solution.