An instrumentation analysis system processes data streams by executing instructions specified using a data stream language program. The data stream language allows users to specify a search condition using a find block for identifying the set of data streams processed by the data stream language program. The set of identified data streams may change dynamically. The data stream language allows users to group data streams into sets of data streams based on distinct values of one or more metadata attributes associated with the input data streams. The data stream language allows users to specify a threshold block for determining whether data values of input data streams are outside boundaries specified using low/high thresholds. The elements of the set of data streams input to the threshold block can dynamically change. The low/high threshold values can be specified as data streams and can dynamically change.

A method of providing a distributed scheme for executing a RAM program, without revealing any information regarding the program, the data and the results, according to which the instructions of the program are simulated using SUBLEQ instructions and the execution of the program is divided among a plurality of participating computational resources such as one or more clouds, which do not communicate with each other, while secret sharing all the program's SUBLEQ instructions, to hide their nature of operation and the sequence of operations. Private string matching is secretly performed by comparing strings represented in secret shares, for ensuring the execution of the right instruction sequence. Then arithmetic operations are performed over secret shared bits and branch operations are performed according to the secret shared sign bit of the result.

Provided a management apparatus including a maintenance mode setting unit that transitions a first virtualization infrastructure (NFVI0) to a maintenance mode, a mobility control unit that at least instructs a virtualization deployment unit (VDU) on the first virtualization infrastructure in the maintenance mode to move to a second virtualization infrastructure (NFVI1), and a maintenance mode release unit that releases the maintenance mode of the first virtualization infrastructure (NFVI0).

Systems and methods for reducing data movement in a computer system. The systems and methods use information or knowledge about the structure of an algorithm, operations to be executed at a receiving processing unit, variables or subsets or groups of variables in a distributed algorithm, or other forms of contextual information, for reducing the number of bits transmitted from at least one transmitting processing unit to at least one receiving processing unit or storage device.

Systems and methods for reducing data movement in a computer system. The systems and methods use information or knowledge about the structure of an algorithm, operations to be executed at a receiving processing unit, variables or subsets or groups of variables in a distributed algorithm, or other forms of contextual information, for reducing the number of bits transmitted from at least one transmitting processing unit to at least one receiving processing unit or storage device.

Methods and apparatus to execute a workload in an edge environment are disclosed. An example apparatus includes a node scheduler to accept a task from a workload scheduler, the task including a description of a workload and tokens, a workload executor to execute the workload, the node scheduler to access a result of execution of the workload and provide the result to the workload scheduler, and a controller to access the tokens and distribute at least one of the tokens to at least one provider, the provider to provide a resource to the apparatus to execute the workload.

Writing data to storage utilizing a diverged thread for asynchronous write operations is provided. On a first thread, an analysis engine analyzes and identifies changed information to write to storage and an I/O manager copies the writes into buffers and places the buffers into a queue, while on a second thread, a flushless transactional layer (FTL) drive executes the writes to storage. By allowing the analysis to continue and enqueue writes on a first thread while the writes are written to storage on a second thread, the CPU and I/O of the system are utilized in parallel. Accordingly, efficiency of the computing device is improved.

The present approach relates to systems and methods for facilitating run time predictions for cloud-computing automated tasks (e.g., automated tasks), and using the predicted run time to schedule resource locking. A predictive model may predict the automated task run time based on historical run time to completion, and the run time may be updated using machine learning. Resource lock schedules may be determined for a queue of automated tasks utilizing the resource based on the predicted run time for the various types of automated tasks. The predicted run time may be used to reserve a resource for the given duration, such that the resource is not available for use for another task.

A method for sorting a data table is provided. The method may include providing a plurality of attribute value information for each data block of the data table. The method may also include receiving a query requiring a sorting on the first attribute of the data table. The method may further include determining a plurality of sequences of a plurality of data blocks having disjoint value ranges of the first attribute based on the provided plurality of attribute value information. The method may also include, for each determined sequence of the plurality of data blocks, reading a plurality of data, sorting the read plurality of data from each data block, and concatenating the sorted plurality of data from the plurality of data blocks within the determined sequence, thereby providing a sorted plurality of sequences. The method may further include merging the sorted plurality of sequences.

The present disclosure describes transaction-enabling systems and methods. A system can include a controller and a fleet of machines, each having at least one of a compute task requirement, a networking task requirement, and an energy consumption task requirement. The controller may include a resource requirement circuit to determine an amount of a resource for each of the machines to service the task requirement for each machine, a forward resource market circuit to access a forward resource market, and a resource distribution circuit to execute an aggregated transaction of the resource on the forward resource market.