740 results about "Storage pool" patented technology

The invention relates to the technical field of geographic information systems, in particular to a map tile data efficient access method and system based on hybrid storage and intelligent layering, and the method comprises the following steps: constructing a multi-level storage architecture, carrying out dynamic heat analysis, carrying out intelligent layering scheduling, preloading and space prediction, and carrying out transmission and access optimization. The method has the beneficial effects that the multi-level storage pool is constructed by combining the advantages of object storage and a distributed file system; adopting a dynamic tile popularity analysis model to realize hot data cache acceleration and cold data hierarchical archiving; and meanwhile, a tile request preloading mechanism is introduced, and an access path is optimized in combination with a spatial locality prediction algorithm. According to the method, the storage cost can be remarkably reduced, the tile request delay is reduced, quick response in a high-concurrency scene is supported, and the method is suitable for application scenes such as Internet map services and smart cities.

A method of optimizing a set of oil producing wells to be drilled in a reservoir includes receiving a base reservoir simulation representative of a geological oil reservoir, clustering the reservoir, and generating, in a first process, a possible pool of well positions in the reservoir, where each well position satisfies plausibility and respects operational constraints. The method further includes, in a second process, optimizing the pool of well positions, the second process maximizing a dynamic variable of the reservoir, and outputting the optimized pool of wells to a user. In embodiments, the second process further includes training a DNN surrogate model to forecast the production of the reservoir; and using the trained DNN surrogate model, optimizing the pool of wells.

Disclosed in the embodiments of the present application are a method and apparatus for inference in a large language model, which are used for reducing the bandwidth consumption of inference in a large language model. The method in the embodiments of the present application comprises: a computing device acquiring input data of a large language model running on a plurality of processors, wherein the input data comprises input text of a user and reference information generated on the basis of the input text, and the reference information comprises domain-related knowledge corresponding to the input text and timeliness information corresponding to the input text; on the basis of the input data, matching historical key-value cache data in a shared storage pool, so as to determine key-value cache data corresponding to the input data, wherein the historical key-value cache data is used for indicating intermediate data generated when the large language model processes different historical input data, the shared storage pool is used for storing historical key-value cache data generated by the plurality of processors, and the different historical input data comprises historical input text and reference information corresponding to the historical input text; and on the basis of the key-value cache data, generating an output result corresponding to the input data.

The invention discloses a request path generation method and device, electronic equipment and a storage medium, and relates to the technical field of data storage, and the method comprises the steps: receiving a client request, and obtaining hardware configuration information of a storage cluster; dividing the storage pool into different speed levels based on hardware performance differences; positioning a target cache node through topology perception and obtaining the state of the target cache node; in combination with request features and cache node states, intelligently scheduling request data to a storage pool of a matching speed level; and finally generating and executing an optimized target storage path. According to the method and the device, the problem of poor request path generation performance caused by insufficient intelligent and efficient resource scheduling in related technologies in a heterogeneous hardware storage environment is solved, and the technical effects of improving the utilization efficiency of storage resources, reducing request processing delay and optimizing end-to-end storage access performance are achieved.

The invention discloses a storage space optimization method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the space utilization rate of a full-flash storage pool in real time, and determining the space utilization rate of the full-flash storage pool based on the actual space balance proportion of the last period and the target space balance proportion of the current period under the condition that the space utilization rate reaches a recovery threshold value; and determining the proportion between the number of first metadata operations generated by writing data into the all-flash storage pool in the current period and the number of second metadata operations generated by recovering the data in the all-flash storage pool. Therefore, the space consumption speed and the space recovery speed of the all-flash storage pool are adjusted, accurate regulation and control of the storage space are realized, and the storage performance of the all-flash storage system is improved. By means of the method, the technical problems that in the related technology, the adjustment efficiency of the storage space is low, and the granularity is rough are solved, and the technical effect of improving the storage performance of the all-flash storage system is achieved.

The invention relates to the technical field of wastewater treatment, and provides a pretreatment device and method for wastewater containing heavy metal ions, and the pretreatment device comprises a water inlet unit, a multi-stage reaction unit, a solid-liquid separation unit, a deep adsorption unit and an intelligent control unit; the water inlet unit comprises a wastewater storage pool and a pH adjusting pool, and the pH adjusting pool is provided with a pH sensor and a dosing device; the multi-stage reaction unit consists of three rotational flow reaction tanks which are connected in series, and spiral guide plates are arranged in the tanks to enhance mixing; the solid-liquid separation unit comprises an inclined plate sedimentation tank and a centrifugal filter; a sludge return pipe is arranged at the bottom of the inclined plate sedimentation tank and extends to the reaction tank; the deep adsorption unit is filled with a modified zeolite-activated carbon composite adsorbent, and a heavy metal ion concentration online monitor is arranged at the rear end; the intelligent control unit dynamically adjusts the dosage and the reaction time based on pH and concentration data. The device has the beneficial effects that the mixing efficiency of wastewater treatment is enhanced, the pH application range of wastewater treatment is widened, and the cost is reduced.

The invention discloses a storage node cluster access method and a cloud management platform, which not only can enable a plurality of applications to share the same storage pool, but also can ensure the data security among the applications. The method comprises the steps that a tenant can input an identifier of an application of the tenant and an identifier of a computing node of the tenant to a binding interface provided by a cloud management platform; and then, the cloud management platform can create a binding relationship among the identifier of the application, the identifier of the computing node and the identifier of the storage space serving the application, and enables the computing node to run the application. The cloud management platform may then deploy the binding relationship in the proxy node. And then, when the agent node receives an access request from the computing node, the agent node can detect the access request based on the binding relationship, and if information carried by the access request conforms to the binding relationship, the agent node creates a storage space in the storage node cluster or completes data processing in the storage space.

The invention relates to a method, a system and equipment for online upgrading of a storage system and a medium, and belongs to the technical field of distributed storage, and the method comprises the following steps: determining at least one node to be upgraded in the storage system; any node to be upgraded is selected as a control node to receive the mirror image file package, and a mirror image source is created based on the mirror image file package; and determining at least one node cluster according to the node cluster category to which the to-be-upgraded node belongs, determining the upgrading sequence of each node cluster according to the upgrading priority of the node cluster, and simultaneously upgrading the plurality of to-be-upgraded nodes which belong to the same node cluster and belong to the same storage pool. Through the upgrading method provided by the invention, rapid and reliable upgrading iteration can be realized on the premise of not influencing service operation.

The embodiment of the invention provides a data processing method and device, equipment and a storage medium, which are used for realizing rapidness and stability of distributed storage. The method is applied to the fields of block chains, big data, cloud technologies, artificial intelligence and the like, and comprises the steps that a data writing request sent by a client is received, and the data writing request is used for indicating data modification of N copies of target data; a consistency rule of the target storage pool is obtained, the consistency rule is used for indicating that the execution of the feedback data write request to the client is successful when response replies returned by M storage nodes are received, and M is a positive integer smaller than or equal to N; sending a data writing request to the N storage nodes to enable the N storage nodes to execute a writing operation of the target data; counting response replies fed back by the N storage nodes; when the response reply meets the consistency rule of the target storage pool, a response message is replied to the client side, and the response message is used for indicating that the data writing request is executed successfully.

The invention discloses a fault recovery method of a storage pool, computer equipment, a storage medium and a product, and relates to the technical field of computers, and the method comprises the following steps: preferentially identifying and scanning a metadata area after the storage pool is offline, screening persistent effective metadata before offline, and storing the effective metadata in a database; metadata reconstruction is taken as a core to preferentially complete integration and restoration of a mapping relation between a logic address and a physical address instead of waiting for synchronous reconstruction of business data, so that the dilemma of long-time logic unavailability of a storage pool caused by synchronous processing of the metadata and the business data in a traditional restoration scheme is effectively broken through; according to the method, the target mapping relation table is quickly generated through conflict resolution and deletion completion processing, so that the interruption duration of the storage pool from offline to online can be remarkably shortened while the mapping accuracy is guaranteed, and the service access delay caused by unready metadata can be avoided.

The invention relates to a method and device for creating a cloud host, electronic equipment and a storage medium. The method comprises the following steps: in response to a received creation instruction, obtaining an IP address, a subnet mask, a first cluster list and a basic network list of a to-be-created cloud host; filtering the basic network list according to the IP address and the subnet mask to obtain an available network list and a first host list; filtering the first cluster list through the first host list to obtain a second cluster list and a storage pool; determining a target storage pool, a second host list and a third cluster list from the storage pools; obtaining an intersection of the second cluster list and the third cluster list to obtain a fourth cluster list and a target cluster; and determining a target host according to the second host list and the target cluster, and creating the to-be-created cloud host according to the available network list, the target storage pool, the target cluster and the target host. By adopting the method, the cloud host can be efficiently and conveniently created, and the high availability of the cloud host is improved.

The technology disclosed herein enables a higher-level process to perform storage volume management with knowledge of a physical storage backend underlying a storage volume. In a particular example, a method includes mounting a storage volume to a computing node of the computing nodes. The storage volume is stored in a storage pool of a plurality of underlying storage pools. The method further includes determining an identifier for the storage pool, receiving a request to duplicate the storage volume, and determining a second identifier for a second storage pool of the plurality of underlying storage pools to which the storage volume will be duplicated. When the second identifier matches the identifier, creating a clone of the storage volume rather than copying the storage volume to the second storage pool.

The invention discloses a heat supply system and method for a water source heat pump coupled seasonal water pool synergistic municipal heat supply network. In the system, a solar heat collector is connected with a seasonal heat storage water pool through a pipeline via a heat exchanger; the seasonal heat storage water tank and the municipal heat supply network are connected with a heat consumer through a pipeline via a heat exchanger; and the water source heat pump is connected with the seasonal heat storage water tank and the heat consumers through pipelines. According to the system, a multi-source complementary framework with solar energy as a main source, heat pump synergism and municipal administration as a bottom is constructed. In the heat supply season, the system adopts a temperature difference lag control strategy, according to seasonal temperature changes of the heat storage pool, a direct heat supply mode, a water source heat pump coupling heat storage pool heat supply mode and a municipal heat supply network heat compensation mode are automatically switched, and stable transition from high-temperature direct heat supply to low-temperature water pump auxiliary heat supply and then to municipal heat supply network bottom heat supply is achieved. It is guaranteed that the building can obtain continuous and stable heat supply all the time in the heat supply season, and meanwhile, clean energy is utilized in a larger range, and heat supply quality is accurately controlled.

The invention discloses a backup method and device, a storage medium and electronic equipment. Relates to the field of big data, and comprises the following steps: obtaining a current operation state of a storage pool, the storage pool comprising N storage addresses, the N storage addresses respectively corresponding to different storage performances, and N being a positive integer; based on the current running state, a target model is adopted to determine a target address from the N storage addresses, the target model is obtained through training on the basis of historical backup feedback information of the storage pool, and the historical backup feedback information is obtained on the basis of the historical storage success rate and the historical backup rate of the storage pool; and storing the business data to be backed up to the target address. Through the data backup control method and device, the problem that the accuracy of data backup control is not ideal in the prior art is solved.

A data storage method is provided. The method includes generating a plurality of data blocks based on data to be stored and determining a target storage layer for the plurality of data blocks in a storage pool of at least one storage device. The storage pool has a multi-layer architecture including a plurality of storage layers. Each of the plurality of storage layers in the storage pool corresponds to a plurality of storage units, each storage unit in each storage layer contains a plurality of storage units in a next storage layer of the storage layer. The target storage layer is a storage layer in the storage pool that satisfies a first preset condition. The method further includes determining a plurality of target storage units from the storage pool based on the target storage layer and storing the plurality of data blocks based on the plurality of target storage units.

The invention discloses a data centralized control platform intelligent hierarchical storage system based on a distributed architecture, and relates to the field of data storage. According to the data centralized control platform intelligent hierarchical storage system based on the distributed architecture, key index characteristics of data are continuously collected through an intelligent hierarchical engine, a corresponding quantification mode is independently designed for each type of characteristics of the data for quantification processing, quantification results are normalized, then a comprehensive value score calculation formula is introduced, and a comprehensive value score is obtained. By designing a heterogeneous storage pool and integrating various storage rear ends, a logical storage hierarchy is formed, grading is carried out according to access characteristics of the data, and threshold division association is carried out on the data and the comprehensive value score of the data, so that the data can be automatically subjected to data grading storage according to a scoring rule; the data storage scheme is simplified, and meanwhile it is ensured that the high-value data has the advantages of being high in speed, low in delay and rapid in response during access.

The invention relates to the technical field of artificial intelligence infrastructure, in particular to a large-model high-concurrency reasoning storage hierarchical acceleration system, which comprises an access popularity acquisition module, a pressure analysis module, a migration execution module and a heterogeneous storage pool, the access popularity acquisition module is used for acquiring the access frequency A and the access delay D of model parameters in real time. The effects of sensing system pressure in real time and accurately triggering migration are achieved by arranging the access popularity acquisition module and the pressure analysis module, the access popularity acquisition module continuously monitors the access frequency and delay of model parameters, and the pressure analysis module calculates and stores a pressure index based on a historical peak value and a dynamic threshold value. When the index exceeds the preset threshold value, migration operation is triggered immediately, the problem that delay exceeds the standard due to storage I / O bottleneck in the financial transaction peak period is solved, the system can still keep millisecond-level response under tens of thousands of concurrent requests per second, and risk misinformation and missing report caused by delay jitter are avoided.

The invention provides an intelligent detection method and system for multiple pollutants in the urban solid waste incineration process, and belongs to the technical field of artificial intelligence. Inputting the input variables into the multi-module echo state network model to obtain predicted concentrations corresponding to the to-be-detected pollutants output by the multi-module echo state network model; wherein the multi-module echo state network model comprises two sub-modules, each sub-module is constructed for one pollutant, and each sub-module is provided with an independent input layer, a reserve pool and an output layer. According to the method, the multi-pollutant collaborative detection model based on the multi-module echo state network is constructed, and the concentration of various pollutants in the urban solid waste incineration process is accurately predicted through state sharing among the sub-modules.

The invention discloses a far-end caching device and method for sample loading in model distributed training, relates to the technical field of deep learning, and solves the problem that a traditional cache cannot play a role due to failure of a locality principle in a completely random access mode. The method comprises the steps that a client sends a sample request; the server side responds to the sample request; wherein the server side comprises a storage pool used for storing a training sample; the buffer pool is used for outputting training samples according to the sample request and storing the training samples randomly extracted from the storage pool; according to the method, the time delay of training sample loading in the model training process can be reduced, and the memory cache utilization rate of the storage nodes in the model training scene is improved.

The invention discloses a Kubernetes-based multi-tenant resource dynamic isolation method, which comprises the following steps of: constructing a CPU (Central Processing Unit) resource control group by utilizing cgropsv2, and realizing dynamic allocation of CPU resources in combination with a dynamic binding engine; constructing a physically isolated storage pool based on the Ceph distributed file system; the network namespace and eBPF flow control technology is utilized, and LWTunnel packaging is combined to realize tenant network complete isolation and QoS speed limitation; constructing an LSTM neural network prediction model to pre-judge a resource demand; a multi-level security system is constructed through AES-256 encryption, Seccomp / BPF container limitation and other technologies; and defining a dynamic strategy object by utilizing CRD to realize strategy management. Through dynamic adaptive resource scheduling, multi-level security protection and highly flexible customization capability, the cluster resource utilization rate can be improved, the CPU cross-NUMA access delay can be reduced, the malicious traffic interception rate can be improved, and the high-performance and high-security requirements of multi-industry and multi-tenant scenes such as finance and e-commerce can be met.

Methods and systems for a networked storage system are provided. One method includes predicting an IOPS limit for a plurality of storage pools based on a maximum allowed latency of each storage pool, the maximum allowed latency determined from a relationship between the retrieved latency and a total number of IOPS from a resource data structure; identifying a storage pool whose utilization has reached a threshold value, the utilization based on a total number of IOPS directed towards the storage pool and a predicted IOPS limit; detecting a bully workload based on a numerical value determined from a total number of IOPS issued by the bully workload for the storage pool and a rising step function; and implementing a corrective action to reduce an impact of the bully workload on a victim workload.

The invention relates to the technical field of regulation and storage pool operation management, in particular to an interactive control method and system for urban regulation and storage pool operation management. The method comprises the following steps: acquiring geometric structure parameters of the storage tank; setting dynamic boundary parameters based on the geometric structure parameters; wherein the dynamic boundary parameters comprise a safe water storage upper limit, a suggested emptying water level and a forced emptying water level; constructing a three-dimensional interactive visual interface containing a space-time constraint relation according to the dynamic boundary parameters; and in response to an interactive working condition switching instruction input in the three-dimensional interactive visual interface, performing virtual execution verification, and after the virtual execution verification is passed, converting the equipment linkage rehearsal sequence into a control instruction and issuing the control instruction so as to realize operation management of the urban regulation and storage pool. By constructing the three-dimensional water level dynamic boundary mapping and equipment linkage virtual rehearsal mechanism, visual perception of working condition switching and water hammer resistance safety verification are achieved, and the problems that the operation opportunity is difficult to judge and the hidden danger of misoperation is caused are solved.

The utility model relates to the technical field of excrement air-drying sterilization, and discloses a novel excrement sterilization dryer which comprises a storage pool used for storing excrement, a draw-off pump, a draw-off pipe, an output pipe, a crushing mechanism, a centrifugal separation mechanism, a transmission mechanism, a conical spiral dry-wet separator, an excrement air-drying collection box and a baffle. The draw-off pump is located at the top of the storage pool, the draw-off pipe is located on the left side of the draw-off pump and fixedly communicated with the left side of the draw-off pump, the output pipe is located on the right side of the draw-off pump and fixedly communicated with the right side of the draw-off pump, and the bottom of the draw-off pipe is communicated with an inner cavity of the storage pool in an inserted mode. And the bottom of the output pipe is horizontally aligned with the top of the crushing mechanism. The problems that in the using process of an excrement dryer, there is no assembly capable of rapidly crushing, separating and sterilizing excrement, the excrement treatment effect is reduced in the air drying process, and therefore the excrement dryer is not convenient for a user to use are solved.

The invention discloses a data copy storage method and system, a medium, electronic equipment and a program product, and relates to the technical field of server hyper-convergence, and the method comprises the steps: determining N distributed nodes corresponding to M virtual machines supported by a hyper-convergence architecture application; in a disk formatting process, dividing a to-be-allocated storage space associated with the super fusion architecture application according to the N distributed nodes so as to equally divide the to-be-allocated storage space into N storage areas; determining a corresponding relationship between the N storage areas and the N distributed nodes; wherein each storage area at least corresponds to one distributed node; and performing storage indication on the data copies generated by the M virtual machines according to the corresponding relationship, thereby solving the problem that a cluster storage pool cannot realize IO localization in an HCI scene, and realizing the technical effect of efficient localization storage of the data copies in the HCI scene.

The invention provides a multi-level tenant management method. A tree-shaped hierarchical structure with a root tenant as a vertex is constructed, dynamic association of sub-tenants and automatic increasing of hierarchical depth values are realized by utilizing parent tenant identifiers, and a depth-extensible architecture is constructed as required. The root tenant independently configures the function permission and the resource permission for each sub-tenant, and a rigid mechanism depending on a static strategy table or a fixed permission distribution mode is replaced. Meanwhile, by binding an attribution tenant identifier for a system resource and clearly distinguishing the resource attribute as a private resource or a controllable resource, dual verification based on a hierarchical relationship and the resource attribute can be carried out, a resource boundary between tenants is implemented at a resource access source, the risk of data leakage caused by no isolation of a shared storage pool mode is solved, and the system performance is improved. And the problem of low efficiency caused by manual configuration required by cross-level collaboration in a physical resource direct binding mode is solved, so that efficient and safe resource collaboration operation within an authorization range is supported while data security isolation is guaranteed.

The utility model discloses an exosome protein concentration detection device, including: a stirring mechanism, a vacuum mechanism, and a detection mechanism; the characteristics are: the stirring mechanism: a sample tank, a motor, and a stirring fan blade; the vacuum mechanism includes: a plurality of sample temporary storage balls, a vacuum pump, and a sample temporary storage tube; the plurality of sample temporary storage balls are distributed along a circumferential array, and connecting tubes are provided between adjacent sample temporary storage balls, and the connecting tubes are respectively fixedly connected to adjacent sample temporary storage balls; the detection mechanism includes: a sample storage pool, a plurality of sample detection blocks, and an electrochemical sensor; a second delivery tube is provided on the sample detection block, and the two ends of the second delivery tube are respectively fixedly connected to the sample detection block and the sample temporary storage ball. The utility model is provided with a vacuum mechanism, and a low-pressure environment is created by a vacuum pump, so that the sample solution is more easily sucked into the sample temporary storage ball; the design of the vacuum mechanism of the utility model accelerates the sample transmission process and improves the detection efficiency.

The invention provides a multi-type storage cluster dynamic nano-management method based on a cloud platform, and belongs to the technical field of cloud platform storage resource management, a storage pool is used as a minimum management unit, a configuration center provides a unified nano-management entrance and is associated with a platform initialization process, and initialization of standardized parameters such as a storage cluster IP, an account and the like is automatically completed; after management, block storage, file storage or object storage types and exclusive parameters thereof are configured for the storage pool according to business requirements, and available storage pools are screened according to binding relations when storage services are created, so that resource mismatching is avoided. Bidirectional synchronization is carried out between the operation and maintenance resource management module and the storage module through a full life cycle by using an equipment SN number, so that state consistency and traceability are realized; expansion of newly added storage pools, unbinding of the storage pools and resource recovery are supported, and the resource utilization rate and the operation and maintenance efficiency are improved.

The invention discloses an image-based urban solid waste (MSW) calorific value prediction method. According to the method, on the basis of a monitoring video of a garbage storage pool, an in-furnace garbage image is captured and screened manually, and an efficient multi-module fusion learning framework is developed by using a deep learning technology. According to the framework, through extracting time sequence features and image visual features of calorific value labels and introducing a variational auto-encoder to process high-dimensional combined features, dynamic prediction of the incineration calorific value of the garbage entering the furnace can be realized. According to the actual working condition, two different time sequence information input strategies are explored, one strategy is that the real heat value at the previous moment is used as input, the other strategy is that the predicted heat value at the previous moment is used as input, and effective information reference and decision support can be provided for incineration intelligent control of the waste incineration power plant.

The starch slurry and residue separation and dehydration system comprises a slurry storage pool arranged on a mounting frame, a slurry discharging opening is formed in the bottom of the slurry storage pool, a screen assembly is obliquely arranged above the slurry storage pool, a driving mechanism used for driving the screen assembly to swing is further arranged on the mounting frame, and the driving mechanism is arranged at the higher end of the screen assembly. A discharging opening is formed in the lower end of the screen assembly, a screw extruder is arranged at the lower end of the discharging opening, a liquid collecting barrel is further arranged, a liquid discharging opening of the screw extruder is communicated with the liquid collecting barrel through a water pipe, starch milk is formed after starch raw pulp is filtered through the screen assembly and then enters the pulp storage pool, and the starch milk in the pulp storage pool is discharged out of the pulp discharging opening. Solid residues formed after starch primary pulp discharged from the discharge port passes through the screw extruder are discharged from the tail end of the screw extruder, formed liquid is discharged into the liquid collecting barrel through the liquid discharge port, and the problems that in the prior art, when a vertical centrifugal screen is adopted for filtering, efficiency is low, and cost is high are solved.

The invention discloses a metadata space management method, device and equipment and a readable storage medium, and relates to the technical field of computers, the method comprises the following steps: selecting a target metadata service as a default metadata service; the default metadata service is used for distributing the logic space of the management storage pool; when the metadata spaces of other metadata services except the target metadata service are lower than a lower use limit threshold value, sending a space application instruction to the target metadata service; and after the target metadata service responds to the space application instruction and distributes part of logic space of the storage pool to other metadata services, the other metadata services store the distributed space as own metadata space. In this way, the metadata service manages the metadata space, management of the metadata service space of multiple nodes is achieved only through one storage pool, and no longer depends on an object storage daemon process and reliable and automatic distributed object storage.