Abstract:
The invention is an improvement to a storage virtualization system that enables the system to determine a class of service for potential storage devices and allows a user, administrator, or application to select a minimum class of service for any given type of data. The class of service is based upon factors that reflect a potential storage device&#39;s reliability, such as the device type and historical uptime data. In a P2P environment, the class of service also includes additional factors, such as the type of attached processing unit and the type of operating system running the attached processing unit.

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
       [0001]    The present invention is related to the subject matter of U.S. patent application Ser. No. 10/922,281, incorporated herein by reference. 
     
    
     FIELD OF THE INVENTION 
       [0002]    The invention is related generally to data processing apparatus and corresponding methods for storing data as computer files, wherein the apparatus comprises a plurality of spatially distributed computers and storage devices, and wherein the methods include transferring the data between spatially distributed computers and storage devices to effect the storage. 
       BACKGROUND OF THE INVENTION 
       [0003]    Most data processing systems in use today include some form of storage sub-system. In a personal computer, the storage sub-system often consists of nothing more than a single storage medium, such as a magnetic disk, attached to a circuit board in the central processing unit, which controls access to the storage medium. In more complex enterprise data processing systems, the storage sub-system may comprise numerous, diverse storage devices. For many years it was common practice for each such storage device to be attached to and controlled by a single processing unit, or “server,” which serviced other units through a network connection. Such a network of storage servers is commonly referred to as a storage area network, or SAN. Although other units could potentially access any given storage device through the attached server, this architecture creates many single points of failure and physically limits storage expansion. In recent years, though, storage virtualization techniques have emerged that allow a data processing system to divorce storage devices from the bonds of a single processing unit. In a virtual storage system, dedicated software assumes storage management responsibilities traditionally reserved for the operating system of an attached processing unit. But this dedicated software also assumes additional responsibilities, including responsibility for creating and managing “logical storage volumes.” Hence, this dedicated software is sometimes referred to as a “storage volume controller (SVC).” Unlike conventional storage devices, a logical storage volume may span many physical storage devices, even if no constituent storage device is attached to a central processing unit. The SVC implements a virtual interface so that a logical storage volume looks like any other conventional storage device to the other components of a data processing system, regardless of the composition or configuration of the underlying physical storage hardware. Moreover, the composition and configuration of the underlying physical storage hardware can change at any time, while the virtual interface insulates the other components from the physical changes. And while most of the preceding discussion presumes that the SVC&#39;s virtual interface replaces a server in a SAN, U.S. patent application Ser. No. 10/922,281 clearly demonstrates that storage virtualization technology also can be applied to peer-to-peer (P2P) networks. 
         [0004]    Advanced storage virtualization technologies also attempt to manage network bandwidth to provide a predictable quality of service for priority users, and some provide additional storage to the data processing system on demand. To take advantage of such features, though, an administrator must specify threshold requirements and reserve resources in advance. An administrator also must update storage requirements manually, and must add storage to the SAN manually before the storage virtualization system can provide storage on demand. These auto-provisioning techniques are not suitable for SVCs in a P2P network, since such a network is decentralized and no single user has sufficient access or control to administer the auto-provisioning requirements. 
         [0005]    The cost and reliability of storage devices can vary widely, but all inevitably fail at some point during their service life. In practice, particularly in an enterprise context, some types of data often are deemed more critical than other types, and resources can be maximized by balancing the importance of the data with the cost and reliability of potential storage devices. Current storage virtualization technologies provide an effective means for integrating numerous, diverse storage devices into a coherent and robust storage system, but no available system yet addresses this need to match data with a storage device that is appropriate to the importance of the data. 
       SUMMARY OF THE INVENTION 
       [0006]    The invention is an improvement to a storage virtualization system that enables the system to determine a class of service for potential storage devices and allows a user, administrator, or application to select a minimum class of service for any given type of data. The class of service is based upon factors that reflect a potential storage device&#39;s reliability, such as the device type and historical uptime data. In a P2P environment, the class of service also includes additional factors, such as the type of attached processing unit and the type of operating system running the attached processing unit. 
     
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         [0007]    The novel features believed characteristic of the invention are set forth in the appended claims. The invention itself, however, as well as a preferred mode of use, further objectives and advantages thereof, will be understood best by reference to the following detailed description of an illustrative embodiment when read in conjunction with the accompanying drawings, wherein: 
           [0008]      FIG. 1  represents an exemplary network of hardware devices, with which the present invention may operate; 
           [0009]      FIG. 2  is a schematic of an exemplary memory having the components of the present invention stored therein; 
           [0010]      FIG. 3  provides a general overview of functions implemented in the present invention that locate one or more storage devices on a network that satisfy a given class of service requirement; 
           [0011]      FIG. 4  is an exemplary data structure that classifies service levels based upon selected characteristics of a storage device; and 
           [0012]      FIG. 5  illustrates the functions implemented in the present invention that manage the data storage after initial placement. 
       
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT 
       [0013]    The principles of the present invention are applicable to a variety of computer hardware and software configurations. The term “computer hardware” or “hardware,” as used herein, refers to any machine or apparatus that is capable of accepting, performing logic operations on, storing, or displaying data, and includes without limitation processors and memory; the term “computer software” or “software,” refers to any set of instructions operable to cause computer hardware to perform an operation. A “computer,” as that term is used herein, includes without limitation any useful combination of hardware and software, and a “computer program” or “program” includes without limitation any software operable to cause computer hardware to accept, perform logic operations on, store, or display data. A computer program may, and often is, comprised of a plurality of smaller programming units, including without limitation subroutines, modules, functions, methods, and procedures. Thus, the functions of the present invention may be distributed among a plurality of computers and computer programs. 
         [0014]    The invention is described best, though, as a single computer program that configures and enables one or more general-purpose computers to implement the novel aspects of the invention. For illustrative purposes, the inventive computer program will be referred to as the “class of service manager (COSM).” 
         [0015]    Additionally, COSM is described below with reference to an exemplary network of hardware devices, as depicted in  FIG. 1 , through which COSM can transfer data from one hardware device to another. A “network” comprises any number of hardware devices coupled to and in communication with each other through a communications medium, such as the Internet. A “communications medium” includes without limitation any physical, optical, electromagnetic, or other medium through which hardware or software can transmit data. For descriptive purposes, exemplary network  100  has only a limited number of nodes, including workstation computer  105 , workstation computer  110 , server computer  115 , and persistent storage nodes  120 - 123 . Persistent storage nodes  120 - 123  collectively represent a storage area network (SAN), labeled as SAN  124  in  FIG. 1 . Although not visible in  FIG. 1 , workstation computers  105  and  110 , as well as server computer  115 , each have a storage sub-system directly attached. Network connection  125  comprises all hardware, software, and communications media necessary to enable communication between network nodes  105 - 120 . Unless otherwise indicated in context below, all network nodes use publicly available protocols or messaging services to communicate with each other through network connection  125 . 
         [0016]    COSM  200  typically is stored in a memory, represented schematically as memory  220  in  FIG. 2 . The term “memory,” as used herein, includes without limitation any volatile or persistent medium, such as an electrical circuit, magnetic disk, or optical disk, in which a computer can store data or software for any duration. A single memory may encompass and be distributed across a plurality of media and network nodes. Thus,  FIG. 2  is included merely as a descriptive expedient and does not necessarily reflect any particular physical embodiment of memory  220 . As depicted in  FIG. 2 , though, memory  220  may include additional data and programs. Of particular importance to COSM  200 , memory  220  may include storage volume controller (SVC)  225 , operating system  230  and application program  240 , with which COSM  200  may interact. 
         [0017]      FIG. 3  provides a general overview of functions implemented in the present invention, including novel functions that locate one or more storage devices on a network that satisfy a given class of service (COS) requirement. In a P2P network environment, these functions preferably are implemented as a P2P agent that cooperates with the infrastructure described in U.S. patent application Ser. No. 10/922,281, but in a conventional client/server architecture, these functions alternatively may be distributed between a client and a SAN server. For the sake of clarity, the following discussion disregards the particular distribution of code associated with the various implementations and focuses on the functions that are implemented, which are common to all implementations. Typically, COSM  200  is activated when an application program, such as application program  240 , initiates an operation to save data to a persistent storage medium ( 305 ). When activated, COSM  200  first acquires the required COS ( 310 ). There are many techniques known in the art for acquiring input for a program, any of which are suitable for use in acquiring the COS requirement. Examples, though, include dialog boxes in which the operator can select or enter a required COS, acquiring the COS requirement from policy-driven logic in the application program itself, or simply using a default COS stored in a file by the operator in advance. After acquiring the COS requirement, COSM  200  polls the storage devices in the network to acquire COS characteristics from each device ( 315 ), and classifies each storage device according to the characteristics discovered in the polling process ( 320 ). Polling is a process known in the art and need not be described in detail here, but it should be clear that COSM  200  may poll all storage devices before classifying each device&#39;s service level, or may poll and classify each device individually until a satisfactory storage device is located. In yet another alternative embodiment, the storage devices themselves could be adapted to internally evaluate their own COS and provide it to COSM  200  in response to the poll, thereby shifting some of the processing load from COSM  200  and distributing it among a number of devices. Whether the processing load is placed on COSM  200  or individual storage devices, though, the classifying procedure is substantially the same. In one embodiment of the invention, an administrator or other operator provides a table or other data structure that classifies service levels based upon selected characteristics of a storage device. An example of such a table is provided in  FIG. 4 . Table  400  of  FIG. 4  consists of a first column (“COS”) that provides a label for the COS defined by the characteristics in each row of the table, and additional columns that identify the selected characteristics that define a COS. The labels included in  FIG. 4  are illustrative only, and any system of labels, classes, or categories that distinguish and prioritize service levels is suitable. In table  400 , the selected characteristics include the operating system (“OS”), the percentage of uninterrupted service availability (“% Uptime”), and the storage device&#39;s hardware type. The characteristics selected in table  400  are merely illustrative, and not exhaustive of the types of characteristics that can be selected. Such characteristics may vary with operator preference or network environment. An additional column in table  400  (“RAID Level”) indicates the type of RAID algorithm that should be used to store data that requires the associated COS. RAID (“Redundant Array of Independent Disks”) is a system of using multiple storage devices to share or replicate data among the devices. RAID is a system that is well-known in the art and need not be described in detail here. Moreover, U.S. patent application Ser. No. 10/922,281, which is incorporated herein by reference, describes in detail how to apply RAID to a P2P storage virtualization technology. Assuming for descriptive purposes that COSM  200  is responsible for classifying the storage devices, for each storage device polled, COSM  200  matches the characteristics of the storage device discovered during the polling process with a COS in the table and then assigns that COS to the storage device. For example, given table  400  in  FIG. 4 , if a storage device reports that it is running a LINUX operating system on INTEL hardware with a 95%-99% uptime (i.e. uninterrupted service availability), then COSM  200  would assign a “gold” COS to the storage device. Finally, after classifying the storage devices, storage is allocated on one or more of the storage devices that satisfy (i.e. meet or exceed) the COS requirement ( 325 ), where the number of storage devices depends upon the quantity of data that must be stored and the available capacity of each storage device. Storage allocation is a function that currently is implemented in SVCs. Thus, conventional SVCs may be adapted to allocate storage only on storage devices that satisfy the COS requirement, as determined by COSM  200 , or this function may be shifted to COSM  200 . 
         [0018]      FIG. 3  and the accompanying description illustrate the initial placement of data in one or more storage devices that satisfy a given COS requirement, but in practice COSM  200  operates in a dynamic environment where the COS of a storage device fluctuates and the COS requirements may change. Accordingly, COSM  200  also implements functions that manage the data storage in this dynamic environment, after the initial placement. These functions are illustrated in  FIG. 5  and described below. After a given time interval ( 505 ), which may be programmed into COSM  200  or may be specified by an administrator or operator, COSM  200  again polls the storage devices in which the data was initially placed ( 510 ). If any of the selected COS characteristics have changed, COSM  200  re-classifies the storage devices ( 515 ), as described above with reference to  FIGS. 3 and 4 . If the COS is unchanged, then COSM  200  takes no further action until the given time interval elapses again. If the COS changes, then COSM  200  determines if the COS is lower than the original COS ( 520 ). If the COS has improved, then the storage device still satisfies the COS requirement and COSM  200  takes no further action. But if the COS has degraded, then COSM  200  polls other storage devices, classifies them, and allocates storage, as described above with reference to  FIG. 3 . COSM  200  then moves the data to the newly allocated storage device or devices that satisfy the COS requirement ( 525 ). Alternatively, an administrator or other operator may change the COS requirement itself ( 530 ), which also causes COSM  200  to re-poll, re-classify, and allocate storage on one or more storage devices that satisfy the new COS requirement, as depicted in  FIGS. 3 and 5 . 
         [0019]    A preferred form of the invention has been shown in the drawings and described above, but variations in the preferred form will be apparent to those skilled in the art. The preceding description is for illustration purposes only, and the invention should not be construed as limited to the specific form shown and described. The scope of the invention should be limited only by the language of the following claims.