Abstract: A system, method and computer program product for managing sensors. One example of embodiment includes a data reader to receive sensor measurements from sensors. A user value collector receives user values from users representing a user's measurement of an abstract concept. A data store saves the sensor measurements and the user values in computer readable memory. The system further includes a virtual sensor generator. The virtual sensor generator determines a mapping function based on the stored sensor measurements and user values. Furthermore, given a new set of sensor measurements from the sensors, the virtual sensor generator employs the mapping function to generate a new virtual sensor value.

Abstract: In one embodiment, the present invention is a method for allocation of finite computational resources amongst multiple entities, wherein the method is structured to optimize the business value of an enterprise providing computational services. One embodiment of the inventive method involves establishing, for each entity, a service level utility indicative of how much business value is obtained for a given level of computational system performance. The service-level utility for each entity is transformed into a corresponding resource-level utility indicative of how much business value may be obtained for a given set or amount of resources allocated to the entity. The resource-level utilities for each entity are aggregated, and new resource allocations are determined and executed based upon the resource-level utility information. The invention is thereby capable of making rapid allocation decisions, according to time-varying need or value of the resources by each of the entities.

Abstract: Managing readiness states of a plurality of computing devices. A programmed processor unit operates, upon receipt of a request, to: provide one or more computing devices from an inactive pool to an active pool, or accept one or more active computing devices into the inactive pool. The system proactively manages the inactive states of each computing device by: determining the desired number (and identities) of computing devices to be placed in each inactive state of readiness by solving a constraint optimization problem that describes a user-specified trade-off between expected readiness (estimated time to be able to activate computing devices when they are needed next) and conserving energy; generating a plan for changing the current set of inactive states to the desired set; and, executing the plan. Multiple alternative ways of quantifying the desired responsiveness to surges in demand are provided.

Abstract: A mechanism is provided for automatically detecting and locating equipment within an intelligent equipment rack. The intelligent equipment rack comprises a rack controller that determines whether a signal has been received indicating that a rack space in a plurality of rack spaces in the intelligent equipment rack has been occupied by a piece of electronic equipment. Responsive to receiving the signal indicating that the rack space has been occupied by the piece of electronic equipment, the rack controller updates a rack information table in the memory with occupation information related to the rack space occupied by the piece of electronic equipment.

Abstract: Techniques are described for controlling the climate in a data center. Using the input of an administrator, multiple desired attributes of a data center (e.g., temperature, energy consumption, costs, or system performance) may be balanced using a utility function that maximizes the utility of the computing systems in the data center according to the administrator's preferences. Additionally, a cooling model is generated that represents the affect of a control parameter (e.g., the fan speed of a CRAC) on the desire attributes of the data center. The cooling model may then be substituted into the utility function to replace the desired attributes. Using this new utility function, the control parameters may be varied such that the maximum utility is achieved.

Abstract: Techniques for organizing information in a user-interactive system based on user interest are provided. In one aspect, a method for operating a system having a plurality of resources through which a user can navigate is provided. The method includes the following steps. When the user accesses the system, the resources are presented to the user in a particular order. Interests of the user in the resources presented are determined. The interests of the user are compared to interests of other users to find one or more subsets of users to which the user belongs by virtue of having similar interests. Upon one or more subsequent accesses to the system by the user, the order in which the resources are presented to the user is based on interests common to the one or more subsets of users to which the user belongs.

Abstract: One or more embodiments manage emergency response services. An emergency event is determined to have occurred. A set of civilian responders currently available to respond to the emergency event is selected from a plurality of civilian responders in response to determining that the emergency event has occurred. Each civilian responder in the set of civilian responders is associated with at least one wireless communication device. The set of civilian responders is notified that the emergency event has occurred. A set of emergency event information associated with the emergency event is transmitted to at least one wireless communication device associated with each civilian responder in the set of civilian responders.

Abstract: A system method and computer program product for managing readiness states of a plurality of computing devices. A programmed processor unit operates, upon receipt of a request, to either: provide one or more computing devices from an inactive pool to an active pool, or accept one or more active computing devices into the inactive pool. An Inactive Pool Manager proactively manages the inactive states of each computing device by: determining the desired number (and identities) of computing devices to be placed in each inactive state of readiness by solving a constraint optimization problem that describes a user-specified trade-off between expected readiness (estimated time to be able to activate computing devices when they are needed next) and conserving energy; generating a plan for changing the current set of inactive states to the desired set; and, executing the plan.

Abstract: Systems, apparatuses, methods, and software that implement power budget allocation optimization algorithms in multi-processor systems, such as server farms. The algorithms are derived from a queuing theoretic model that minimizes the mean response time of the system to the jobs in the workload while accounting for a variety of factors. These factors include, but are not necessarily limited to, the type of power (frequency) scaling mechanism(s) available within the processors in the system, the power-to-frequency relationship(s) of the processors for the scaling mechanism(s) available, whether or not the system is an open or closed loop system, the arrival rate of jobs incoming into the system, the number of jobs within the system, and the type of workload being processed.

Abstract: Techniques for energy and environmental leak detection in an indoor environment using one or more mobile robots are provided. An energy leak detection system is provided. The energy leak detection system includes one or more mobile robots configured to move throughout at least a portion of a building and to take temperature and air flow measurements at a plurality of locations within the building. An environmental leak detection system is also provided. The environmental leak detection system includes one or more mobile robots configured to move throughout at least a portion of a building and to take airborne matter measurements at a plurality of locations within the building.

Abstract: The present invention is a method and an apparatus for reward-based learning of management policies. In one embodiment, a method for reward-based learning includes receiving a set of one or more exemplars, where at least two of the exemplars comprise a (state, action) pair for a system, and at least one of the exemplars includes an immediate reward responsive to a (state, action) pair. A distance measure between pairs of exemplars is used to compute a Non-Linear Dimensionality Reduction (NLDR) mapping of (state, action) pairs into a lower-dimensional representation, thereby producing embedded exemplars, wherein one or more parameters of the NLDR are tuned to minimize a cross-validation Bellman error on a holdout set taken from the set of one or more exemplars. The mapping is then applied to the set of exemplars, and reward-based learning is applied to the embedded exemplars to obtain a learned management policy.

Abstract: A method and system performs dynamic online multi-parameter optimization for autonomic computing systems. A simplex is maintained. The system's performance is measured for the particular setting of configuration parameters associated with each point in the simplex. A new sample point is determined using the geometric transformations of the simplex. A current best point in the simplex can be resampled to determine if the environment has changed. If a sufficiently different utility value is obtained from a previously sampled utility value for the point in the simplex, the simplex is expanded. If the difference is not sufficient enough, then contraction of the simplex is performed.

Abstract: Techniques for organizing information in a user-interactive system based on user interest are provided. In one aspect, a method for operating a system having a plurality of resources through which a user can navigate is provided. The method includes the following steps. When the user accesses the system, the resources are presented to the user in a particular order. Interests of the user in the resources presented are determined. The interests of the user are compared to interests of other users to find one or more subsets of users to which the user belongs by virtue of having similar interests. Upon one or more subsequent accesses to the system by the user, the order in which the resources are presented to the user is based on interests common to the one or more subsets of users to which the user belongs.

Abstract: In one embodiment, the present invention is a method for reward-based learning of improved systems management policies. One embodiment of the inventive method involves obtaining a decision-making entity and a reward mechanism. The decision-making entity manages a plurality of application environments supported by a data processing system, where each application environment operates on data input to the data processing system. The reward mechanism generates numerical measures of value responsive to actions performed in states of the application environments. The decision-making entity and the reward mechanism are applied to the application environments, and results achieved through this application are processed in accordance with reward-based learning to derive a policy. The reward mechanism and the policy are then applied to the application environments, and the results of this application are processed in accordance with reward-based learning to derive a new policy.

Abstract: A method, computer program product, and data processing system for providing an improved directory service for storing information about hardware and software components is disclosed. The directory service stores not only the information that other hardware and software components require to locate, and make use of, the components listed in the directory, but is also able to dynamically construct ‘meta services’ that fulfill a client's functionality requirements.

Abstract: The present invention is a method and an apparatus for reward-based learning of policies for managing or controlling a system or plant. In one embodiment, a method for reward-based learning includes receiving a set of one or more exemplars, where at least two of the exemplars comprise a (state, action) pair for a system, and at least one of the exemplars includes an immediate reward responsive to a (state, action) pair. A distance measure between pairs of exemplars is used to compute a Non-Linear Dimensionality Reduction (NLDR) mapping of (state, action) pairs into a lower-dimensional representation. The mapping is then applied to the set of exemplars, and reward-based learning is applied to the transformed exemplars to obtain a management policy.

Abstract: In one embodiment, the present invention is a method for reward-based learning of improved systems management policies. One embodiment of the inventive method involves supplying a first policy and a reward mechanism. The first policy maps states of at least one component of a data processing system to selected management actions, while the reward mechanism generates numerical measures of value responsive to particular actions (e.g., management actions) performed in particular states of the component(s). The first policy and the reward mechanism are applied to the component(s), and results achieved through this application (e.g., observations of corresponding states, actions and rewards) are processed in accordance with reward-based learning to derive a second policy having improved performance relative to the first policy in at least one state of the component(s).

Abstract: In one embodiment, the present invention is a method for allocation of finite computational resources amongst multiple entities, wherein the method is structured to optimize the business value of an enterprise providing computational services. One embodiment of the inventive method involves establishing, for each entity, a service level utility indicative of how much business value is obtained for a given level of computational system performance. The service-level utility for each entity is transformed into a corresponding resource-level utility indicative of how much business value may be obtained for a given set or amount of resources allocated to the entity. The resource-level utilities for each entity are aggregated, and new resource allocations are determined and executed based upon the resource-level utility information. The invention is thereby capable of making rapid allocation decisions, according to time-varying need or value of the resources by each of the entities.

Abstract: An improved method and system for performing dynamic online multi-parameter optimization for autonomic computing systems are provided. With the method and system of the present invention, a simplex, i.e. a set of points in the parameter space that has been directly sampled, is maintained. The system's performance with regard to a particular utility value is measured for the particular setting of configuration parameters associated with each point in the simplex. A new sample point is determined using the geometric transformations of the simplex. The method and system provide mechanisms for limiting the size of the simplex that is generated through these geometric transformations so that the present invention may be implemented in noisy environments in which the same configuration settings may lead to different results with regard to the utility value. In addition, mechanisms are provided for resampling a current best point in the simplex to determine if the environment has changed.

Abstract: A method, computer program product, and data processing system for providing an improved directory service for storing information about hardware and software components is disclosed. The directory service stores not only the information that other hardware and software components require to locate, and make use of, the components listed in the directory, but is also able to dynamically construct ‘meta services’ that fulfill a client's functionality requirements.