247results about How to "Shorten completion time" patented technology

Liquefied natural gas is used as a fracturing fluid to stimulate production of hydrocarbons from and/or injectability of fluids into subterranean formations. Proppants may be blended with the LNG prior to pumping the liquefied natural gas into the well. Optionally, the liquefied natural gas is heated after it is pumped and before it is introduced into the subterranean formation.

A RAID system access a physical disk and perform Rebuild/Copy back processing according to a host I/O request, so as to implement high-speed Rebuild/Copy back processing without interfering with the processing of a normal I/O. When one disk device fails, out of a plurality of disk devices constituting a RAID configuration, the controller performs Rebuild/Copy back processing to reconstruct the RAID. In Rebuild/Copy back, the controller reads the data from one disk and writes the data to another disk, so the presence of a normal I/O is judged, and when a normal I/O is absent, read and write of these different disk drives are executed simultaneously. By this, the Rebuild/Copy back time can be decreased.

The invention provides a method for high-efficiency task scheduling of a heterogeneous multi-core processor. The method comprises the following steps of: clustering certain special tasks which are large in communication overhead and easy to cluster in a task image to a precursor node of the tasks by adopting a linear task clustering method; starting from a topological structure of the whole task image, selecting parameters capable of comprehensively reflecting the importance of the task in the whole task image as priority weights; selecting a free critical path node to perform allocation first, and if multiple free critical path nodes exist, allocating the free critical path nodes in a sequence from high to low according to the node priority weights, and allocating all non-critical path free nodes in a sequence from high to low according to the priority weights; performing redundancy judgment, and deleting redundant tasks in a scheduling result; and performing adjustment according to the scheduling result after deleting the redundant tasks, and recalculating the earliest finish time of each task. According to the method, the efficiency of the task scheduling of the heterogeneous multi-core processor is improved, the power consumption of the processor is reduced, and the performance of the multi-core processor is promoted.

The invention discloses a dispatching method and a system of a distributed system. The method comprises the following steps: a dispatching request comprising data reading operation is received by a data dispatcher, and data is stored in at least one entity providing data service in the distributed system; status of each data service corresponding to the dispatching request is determined by the data dispatcher, dispatching response consenting to conduct reading operation on each data service is sent by the data dispatcher when each data service is in an idle/reading status; and each data service is at least one same data service. The invention can effectively solve the defects of resource waste, low task processing efficiency and the like in the distributed dispatching method in the prior art, realizes reasonable resource utilization, and improves task processing efficiency.

The invention provides a Lyapunov optimization-based multi-server mobile edge computing unloading method and device, and the method comprises: building a task cache queue for a task generated by eachmobile device, and building a virtual task cache queue for a task which needs to be unloaded and is not processed by each mobile device; establishing a terminal power consumption model, a bandwidth model and a QoE model; collecting task cache queue information and virtual cache queue information of the mobile device and the bandwidth condition of the server at each preset time slice; constructinga Lyapunov drift and penalty function according to the collected information; and based on Lyapunov drift and a penalty function, a calculation unloading decision in the current time slice is solved.The technical effects of calculating and unloading based on the multi-server MEC, effectively reducing the task completion time and reducing the energy consumption of the mobile device are achieved.

A metal-stamping die or tool is provided. Another aspect uses an additive manufacturing machine and material to create a die. A further aspect provides a method of making a die from an additive manufacturing process and/or using such a die to stamp a metal part, such as a fastener or clip.

Computerised automatic translation method characterised by the use of multi-tasking with two processors or a dual core that duplicates the system into two twins, one becoming server of the other and instructing the first to send a remaining part that is less than half to the second while the first begins the translation of the first part to then, on completion of its work, pick up the text translated by the second and joint it to the first part that has already been translated.

The invention relates to an interference-prevention-based multi-automatic-guided-vehicle (AVG) path planning method for a logistics storage system. On the basis of analyses of arrival and departure times of multiple AGVs at and from all road sections and nodes in a logistics storage system, driving overlapping frequencies of the AGVs on the road sections and nodes are calculated. With combination of an interference threshold value, a multi-AGV shortest path planning model with an interference prevention constraint is established by using multi-AGV operation time as a target. With a frame of an ant colony algorithm, an interference-prevention-based multi-automatic-guided-vehicle path planning method with inducing ant colony and particle swarm fusion for a logistics storage system is designed by keeping a pheromone factor is kept, removing a visibility factor, and adding a A <*> factor and an inducing factor. Road features of typical logistics storage systems like a dock, a warehouse, a distribution center, a container station and various storage yards are combined and a multi-automatic-guided-vehicle path planning method is provided. Therefore, the interference can be avoided effectively; the AGVs can arrive at destinations according to respective shortest paths; and thus the working efficiency and security of the logistics storage system can be improved.

The invention discloses a method for constraining workflow scheduling in a cloud environment based on the ant colony optimization algorithm through deadline. The method comprises the steps: employing an ant colony system with a candidate list; respectively searching a workflow scheduling scheme in the cloud environment through a plurality of ants; carrying out the communication of a workflow scheduling result among the ants in a pheromone mode, thereby guiding the deciding of the subsequent search direction of ants and the workflow scheduling scheme. Compared with a conventional workflow scheduling method, the method can reduce the cost of the workflow scheduling in the cloud environment and improves the service quality for cloud users under the condition of meeting the deadline time QoS requirements of users.

The invention relates to a bidirectional stepped grid resource scheduling method based on QoS constraints, which includes: 1. QoS service is offered to all available machines for testing according to QoS request provided by the task and the testing results are recorded in a matrix form, if the request is executable, the execution time is recorded and if the request is non-executable corresponding signs are made; 2. the matrix of the testing results is deformed according to the designated principle and the deformed matrix is accumulated according to the horizontal and vertical directions, thus calculating two vectors; 3. the tasks and the resources are grouped in a non-descending order according to the two vectors; 4. the priority scheduling is conducted according to the task grouping results, wherein, the group with small value has high priority and is firstly scheduled and the interior of the grouping is scheduled according to Min-min algorithm principle; 5. if the task has the same minimum completion time with different resources in the scheduling, the scheduling is conducted according to the resource grouping results and the group with small value has high priority and is firstly scheduled; 6. the fourth step and the fifth step are repeatedly executed until the scheduling of all tasks is completed.

A novel solution for converting a walk behind floor scrubber into a sit and ride behind floor scrubber. The present invention consists of a chassis frame to which five wheels are attached. Two of the front wheels pivot and the up-front safety wheel does not. The wheels that are attached to the rear of the frame, are non-pivotal. A person sits on the cushioned seat. Upon grabbing the floor scrubber's control handles and rotating them forward the floor scrubber, as it propells forward, pulls the present invention behind it in tandem. This allows the operator for the floor scrubber to sit and rid instead of walking, while cleaning large commercial size floors. This new procedure saves enormous time and the person controlling the scrubber will be less fatigued from hours of walking. The Scrub-mate is new to the floor cleaning industry, because it eliminates walking of the operator while using a battery-powered walk behind floor scrubber.

The invention discloses a distributed assembly type permutation flow shop scheduling optimization method and system. The efficiency of a distributed permutation flow shop is increased; and the completion time and the energy consumption are reduced. The method comprises the steps of: with the purpose of reducing the minimum weight value of the completion time and the total energy consumption, constructing a distributed assembly type permutation flow shop optimization problem model with a crane; solving the distributed assembly type permutation flow shop optimization problem model with the craneby adopting an improved whale swarm algorithm, so that a scheduling optimization scheme is obtained; and scheduling work-pieces of various factories in the distributed assembly type permutation flowshop by utilizing the obtained scheduling optimization scheme.

An auxiliary capacitance line and a terminal portion of a liquid crystal display device are made of an Al or Al alloy layer and an Mo layer. The edge portions of a lower auxiliary capacitance electrode and the terminal portion are sequentially coated with a first insulating film, a second insulating film that is thinner than the first insulating film, and a third insulating film. The lower auxiliary capacitance electrode is coated with the second insulating film, and an upper auxiliary capacitance electrode is laid on the surface of the second insulating film on the lower auxiliary capacitance electrode.

The embodiment of the invention discloses a data distribution method and device based on MapReduce as well as a computer readable storage medium. The method can comprise the following steps; running apreset Map function on an input to-be-processed document, and obtaining a key value pair set; calculating a type number of keys in the key value pair set by utilizing a preset counting method; calculating a standard numerical value corresponding to each key by utilizing a preset algorithm; carrying out reminder calculation on the standard numerical values and the type number, so as to divide keyvalue pairs with the same type number in the key value pair set into one partition, thus at least one partition is obtained, and the number of at least one partition is the same with the type number;and based on a quantity of the key value pairs, corresponding to at least one partition, of at least one partition and a quantity of at least one to-be-distributed key value pair corresponding to at least one Reduce task, establishing corresponding relationship between at least one partition and at least one Reduce task, so that processing can be carried out on the key value pairs of at least onepartition by at least one Reduce task.

The invention discloses a transmission control method for a DCN (Data Center Network) based on multilevel congestion feedback. The method comprises the steps of setting a switch cache queue length threshold which comprises a first-level queue marking threshold 1 and a second-level queue marking threshold 2; monitoring a current queue length by each switch in a transmission path when multiple sending parties send data concurrently; comparing the current queue length with the first-level queue marking threshold 1 and the second-level queue marking threshold 2, and feeding back a current network congestion state; reducing a window increasing speed in a slow start stage according to first-level congestion feedback; and timely logging out the slow start stage, and entering a congestion avoiding stage according to the second-level congestion feedback. According to the method, the throughput breakdown phenomenon resulting from the fact that the window increasing speed is too fast in the slow start stage when DCN concurrent transmission is carried out can be effectively avoided. The network throughput is greatly improved, and the integrated performance of a network application is improved.

The invention discloses a cloud service workflow scheduling method based on budget constraint, and belongs to the technical field of cloud computing scheduling. In the method, cost of renting cloud service by a user does not exceed capital budget of the user is used as a constraint condition, and workflow makespan minimization is used as a goal, and a corresponding virtual machine is distributed to each task in the workflow. The method further respectively performs initial scheduling and rescheduling through two constructed weights, so that an algorithm simpler and faster. The method realizes efficient supply of cloud environment resources, under the condition that workflow of the user is ensured to be completed in the user budget, time of completion of the workflow is minimized. The algorithm is simple and easy to realize.

A method for reducing time in performing an imaging function by an imaging device. The method includes receiving at least one media sheet against an image capture window of the imaging device, detecting whether a lid for covering the image capture window is closed, capturing an image of the at least one media sheet in the image capture window in response to detecting a closed lid, receiving a start signal indicative of a user request to start an image capture operation after capturing the image, and sending a final image based upon the captured image to a destination.

The invention belongs to the technical field of data processing, and discloses a resource scheduling method and system based on a multi-dimensional constraint genetic algorithm, and the method comprises the steps: carrying out the initialization of a prediction model, a task matrix, and a node matrix, and building a dual-fitness function; formulating an option-Copying operator, a cross operator and a variation operator; and after multiple iterations, obtaining a globally optimal resource allocation mode. In order to seek a better resource allocation scheme, the invention provides a Hadoop resource scheduling algorithm based on a multi-dimensional constraint genetic algorithm, and a Hadoop resource scheduler is realized through the algorithm; by the adoption of the algorithm, the cluster resource distribution efficiency can be effectively improved, and the overall completion time of cluster tasks is shortened by about 20%.

The invention discloses an information imperceptible Coflow scheduling system capable of automatically adjusting a queue threshold and a scheduling method thereof. The scheduling system comprises a monitoring system (MS) and a central controller (CC), wherein the monitoring system and the CC are distributed on a terminal host; the monitoring system is used for collecting Coflow information on a terminal host. And the central controller adjusts a set of degradation thresholds according to the information of the Coflow, observes a scheduling result of the Coflow as an award of a reinforcement learning algorithm, and further optimizes the degradation threshold of the queue through the award.