Abstract: A multi-grid mechanism using peer-to-peer (P2P) platform protocols. An autonomic grid computing mechanism may be used to implement a multi-grid grid computing system. In the multi-grid grid computing system, there may be multiple master nodes, and thus multiple smaller grids (or grid cells) each including one or more compute nodes, in a single (larger) grid. A job submitter node may use one or more P2P platform protocols to discover the master nodes and to obtain information about the grid cells, including information that may be used by the job submitter to automatically select one of the grid cells that is suitable to execute a particular job. After selecting the grid cell, the job submitter may submit the particular job to the master node of the grid cell using the P2P platform protocols.

Abstract: There are provided mechanisms and methods for automating management of Scalable Distributed Persistent Applications (SDPA) in a grid computing environment. These mechanisms and methods make it possible for physical and operating system resources in the grid to be dynamically allocated and/or de-allocated based upon the results of monitoring performance and monitoring usage of physical and operating system resources.

Abstract: A mechanism for automating the process of establishing a resource grid is provided. First, a grid establishment component (GEC) is communicatively coupled to a plurality of nodes, wherein each node provides zero or more resources. Next, the GEC selects which of the nodes to include in a resource grid and establishes the resource grid by configuring each selected node (i.e., grid node) to participate as part of the resource grid. In addition, the GEC establishes one or more grid masters to manage access to the resources provided by the grid nodes. Once the grid nodes are configured, and one or more grid masters are established, the resource grid is ready for regular operation. By automating the grid establishment process, the GEC removes a significant burden from a system administrator, and greatly simplifies and accelerates the process of establishing a resource grid.

Abstract: An autonomic grid computing mechanism. In embodiments, peer-to-peer platform protocols may be integrated with a grid computing system. Embodiments may use peer-to-peer platform protocols as the transport for the grid computing system. Embodiments may provide one or more of, but not limited to, the following capabilities to grid computing systems: self-deployment and self-configuration, self-updating, self-healing, node removal, master node backup, monitoring, administration, load balancing, grid brokering, decentralized grid, and multi-grid support. Peer-to-peer platform protocols may be used to automatically configure compute nodes. When a node comes up, the node searches for a master node using the peer-to-peer platform. When the node finds a master node, it provides node information to the master node using the peer-to-peer platform. The master node may send the node grid configuration information using the peer-to-peer platform and the node may self-configure as a compute node.

Abstract: A computer-implemented method and system for controlled optimization of enterprise planning models is provided. This is accomplished by first defining an auxiliary objective function, which depends on the same variables as the model, or a subset thereof. An effective objective function is then constructed from the primary objective function by subtracting the auxiliary objective function multiplied by a weighting factor. The effective objective function is then optimized for a whole range of weighting values, yielding a table that describes how the primary objective function varies according to different values of the weighting factor. Optimization of the effective objective function with a given value of the weighting factor results in a particular value for the auxiliary objective. Thus, this computed table essentially provides a relationship between different realized values of the primary objective, the auxiliary objective, and all the variables of the enterprise planning model.

Abstract: A method for incorporating psychological effects into a demand model for pricing. First the original demand model is modified to include a mechanism to convert actual prices into perceived prices, thus causing the demand model to predict higher demand for certain prices. The user specifies the function that converts from real prices to perceived prices. This modified demand function is then fitted to a sales history to yield the parameters appropriate to its particular form. Also, the demand model can be modified to account for promotional effects. The user defines a visibility model, which gives the relative increase in demand for an item caused by a promotion, and the cost of the promotion. The demand model is modified to include the effect of increased demand based on the visibility, and a profit model is modified to account for the added cost due to the added visibility. The profit model is then optimized with respect to both prices and promotions.

Abstract: A method for tuning a demand model in manner that is stable with respect to fluctuations in the sales history used for the tuning is provided. A market model is selected, which predicts how a subset of the parameters in the demand model depends upon information external to the sales history; this model may itself have a number of parameters. An effective figure-of-merit function is defined, consisting of a standard figure-of-merit function based upon the demand model and the sales history, plus a function that attains a minimum value when the parameters of the demand model are closest to the predictions of the market model. This effective figure-of-merit function is minimized with respect to the demand model and market model parameters. The resulting demand model parameters conform to the portions of the sales history data that show a strong trend, and conform to the external market information when the corresponding portions of the sales history data show noise.