Abstract: A system for achieving non-interruptive data reconstruction is disclosed. The system includes a source storage, a target storage, a server, a traffic modeling unit and at least one data moving service unit. With the help of traffic modeling unit, a period of time of low access can be estimated. Data reconstruction (copying or moving) can be carried on during the period of time. Thus, non-interruptive data reconstruction can be done.

Abstract: A hybrid backup and recovery management system for database versioning and virtualization with data transformation is disclosed. The hybrid backup and recovery management system includes at least one original storage device, at least one target storage device, a database managing sub-system, and a conversion module. The present invention takes advantages of fast speed of data transmitting in volume level format while let DBAs see the procedure and interface of backup and recovery are the same as what they are used to (file level format). Current database management system can be kept just with some modules plugged in. Fast backup and recovery can be achieved.

Abstract: A workload-aware I/O scheduler in a Software-Defined Hybrid Storage (SDHS) system is disclosed. The scheduler includes a queue managing module, a workload property database, a traffic monitoring module, and a traffic modeling module. The queue managing module further has a request receiving sub-module, a request controlling sub-module, and a request dispatching sub-module. With the operations of the queue managing module, requests for accesses of HDDs and SSDs can be separately queued. Thus, performance of the SDHS can be improved. Meanwhile, the scheduler can be used for requests from a number of workloads at the same time while meet performance requirement of each workload.

Abstract: A storage system having nodes with light weight containers is disclosed by the present invention. The storage system includes: at least one cluster, having a number of nodes linked to one another, each node having: a node host, operated by a storage operating system, and installed with a number of service containers, which are used for providing specific services to clients and/or operations of the node out of the service containers; and at least one node storage device, operated by the storage operating system, for providing storing and accessing of data for the service containers; and a messaging module, linked to each node host, for bridging the node hosts and/or node hosts in different clusters. Coarse-grained REST APIs are used for communication between any two service containers to reduce chatty communication in the storage system.

Abstract: A workload-aware I/O scheduler in a Software-Defined Hybrid Storage (SDHS) system is disclosed. The scheduler includes a queue managing module, a workload property database, a traffic monitoring module, and a traffic modeling module. The queue managing module further has a request receiving sub-module, a request controlling sub-module, and a request dispatching sub-module. With the operations of the queue managing module, requests for accesses of HDDs and SSDs can be separately queued. Thus, performance of the SDHS can be improved. Meanwhile, the scheduler can be used for requests from a number of workloads at the same time while meet performance requirement of each workload.

Abstract: A system for database, application, and storage security in a Software Defined Network (SDN) is disclosed. The system includes: a SDN control server, a database monitoring server, a storage installation, and a storage security gateway server. The storage security gateway server can share loadings of the database monitoring server by watching the operating situation of the storage devices where the database monitoring server can not touch. Thus, security breach issues can be screened out. Storage security or even network security can be achieved. In addition, since the security breach issue screening jobs are distributed to one or more storage security gateway server, the architecture can work well even the SDN becomes larger and more and more nodes join in. Scalability is not an issue for the SDN.

Abstract: An adaptive fuzzy rule controlling system for a software defined storage (SDS) system to control performance parameters in a storage node is disclosed. The system includes: a traffic monitoring module, for acquiring observed values of performance parameters in the storage node; an adaptive neural fuzzy inference module, for learning a dynamic relationship between configurations of a plurality of storage devices in the storage node and the performance parameters during a period of time, and outputting fuzzy rules which is built according to the dynamic relationship; a traffic forecasting module, for providing forecasted values of the performance parameters in a particular point in time in the future; and a fuzzy rule control module, for arranging the configuration of the storage devices in the storage node in the particular point in time in the future according to the fuzzy rules and the forecasted values.

Abstract: A SSD caching system for hybrid storages is disclosed. The caching system for hybrid storages includes: a Solid State Drive (SSD) for storing cached data, separated into a Repeated Pattern Cache (RPC) area and a Dynamical Replaceable Cache (DRC) area; and a caching managing module, including: an Input/output (I/O) profiling unit, for detecting I/O requests for accesses of blocks in a Hard Disk Drive (HDD) during a number of continuously detecting time intervals, and storing first data corresponding to first blocks being repeatedly accessed at least twice in individual continuously detecting time intervals to the RPC area sequentially; and a hot data searching unit, for detecting I/O requests for accesses of a HDD during a independently detecting time interval, and storing second data corresponding to second blocks being accessed at least twice in the independently detecting time interval to the DRC area sequentially.

Abstract: A system and a method for data transformation for cloud-based archiving and backup are disclosed. The system includes an original disk storage, an object storage and a Data Transformation and Virtualization Module (DTVM). The DTVM can transform an original data in the original disk storage into an archiving data which has objects, pointers, and a metadata including an environmental information, and store the archiving data to the object storage by a storing means. Thus, in addition to restoring of the archiving data which is available, with the drivers for booting added to objects, pointers, and a metadata, recovery of the original disk storage with booting function can be available.

Abstract: A method for optimizing storage configuration for future demand and a system applying the method are disclosed. The system includes a monitoring module, a storage recording module, a traffic modeling module, a rule-based decision module, and a storage management module. With performance values and utilization values provided from the monitoring module, a traffic status of data access in a particular time in the future can be generated. Then, a storage configuration with the workload requirement according to some rules can be available. The storage configuration is implemented to fulfill the requirement of the traffic status of data access.

Abstract: A system for achieving non-interruptive data reconstruction is disclosed. The system includes a source storage, a target storage, a server, a traffic modeling unit and at least one data moving service unit. With the help of traffic modeling unit, a period of time of low access can be estimated. Data reconstruction (copying or moving) can be carried on during the period of time. Thus, non-interruptive data reconstruction can be done.

Abstract: A method and system for storage traffic modeling in a Software Defined Storage (SDS) is disclosed. The method includes the steps of: collecting observed values of at least one performance parameter in a period of time from a storage node; learning a trend structure of the at least one performance parameter varying with time from the observed values; and providing a predicted value of one performance parameter in a particular point in time in the future. The storage node is operated by SDS software. The trend structure is adjusted based on observed values collected after the period of time. The predicted value is an output of the trend structure which has been adjusted.

Abstract: An adaptive fuzzy rule controlling system for a software defined storage (SDS) system to control performance parameters in a storage node is disclosed. The system includes: a traffic monitoring module, for acquiring observed values of performance parameters in the storage node; an adaptive neural fuzzy inference module, for learning a dynamic relationship between configurations of a plurality of storage devices in the storage node and the performance parameters during a period of time, and outputting fuzzy rules which is built according to the dynamic relationship; a traffic forecasting module, for providing forecasted values of the performance parameters in a particular point in time in the future; and a fuzzy rule control module, for arranging the configuration of the storage devices in the storage node in the particular point in time in the future according to the fuzzy rules and the forecasted values.

Abstract: An adaptive quick response controlling system for a software defined storage (SDS) system to improve a performance parameter is disclosed. The system includes: a traffic monitoring module, for acquiring an observed value of the performance parameter in a storage node; an adaptive dual neural module, for learning best configurations of a plurality of storage devices in the storage node under various difference values between the observed values and a specified value of the performance parameter from historical records of configurations of the storage devices and associated observed values, and providing the best configurations when a current difference value is smaller than a threshold value; and a quick response control module, for changing a current configuration of the storage devices in the storage node as the best configuration of the storage devices provided from the adaptive dual neural module if the current difference value is not smaller than the threshold value.

Abstract: A method for encapsulating functions for application programming interface in a cloud environment is disclosed. The method includes the steps of: A. providing an API supported by a driver; B inheriting the API as a new class if the API is usable for a service device in a computing node environment; C. augmenting extending function(s) for the service device to the driver; and D. repackaging the driver to conform to the inherited API.

Abstract: In one example, a method to transmit data to one or more devices is provided. One or more data files are transmitted cyclically via one or more respective channels, such as a radio-frequency channel, a request for at least one desired data file is received from a device, and a message identifying a respective channel associated with the at least one desired data file is transmitted to the device. The at least one desired data file may be transmitted cyclically via at least one selected channel. The at least one desired data file may comprise one or more software applications, such as an operating system. Other systems and methods of assembly and data transmission are also described.

Abstract: A method and a system for storing and/or retrieving data which can be implemented using a storage area network. The system includes a client computer having data to store or desiring data to retrieve, a storage server in communication with the client computer and able to read storage-related requests from the client computer, a high-speed network running at least one data communication protocol for communicating between the client computer and the storage server, a storage device, which has data to retrieve and is used to store data, in communication with the storage server, and a storage manager for allocating and authorizing the storage device. Preferably, the data communication protocol includes at least one of the Internet protocols, including Internet Protocol (“IP”), Transmission Control Protocol (“TCP”), and User Datagram Protocol (“UDP”). Preferably, the system also includes a high-speed switch for communicating between the client computer and the storage server.