AUTONOMIC STORAGE PROVISIONING TO ENHANCE STORAGE VIRTUALIZATION INFRASTRUCTURE AVAILABILITY

Field of the Invention

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

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. While most of the preceding discussion presumes that the SVCs virtual interface replaces a server in a SAN, storage virtualization technology also can be applied to peer-to-peer (P2P) networks.

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.

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

In accordance with an aspect of the present invention there is provided a method of storing data in a storage virtualization system comprised of at least two storage devices, the method comprising: acquiring a class of service requirement from an operator; steps for classifying the service level of each storage device; comparing the service level of each storage device with the class of service requirement; and storing the data in one or more storage devices having a service level that satisfies the class of service requirement. Thus there

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'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.

Preferable the steps for classifying the storage level of each storage device comprise the technical features of: providing a data structure that associates service levels with a storage device type and uninterrupted service time; determining the type of each storage device; determining the uninterrupted service time of each storage device; and assigning a service level that is associated in the data structure with the determined type of storage device and the determined uninterrupted service time.

Brief Description of Drawings

A preferred embodiment of the present invention will now be described by way of example only with reference to the following drawings in which:

Figure 1 illustrates an exemplary network of hardware devices, with which embodiments of the present invention may operate;

Figure 2 is a schematic of an exemplary memory having components of a preferred embodiment of the present invention stored therein;

Figure 3 provides a general overview of functions implemented in a preferred embodiment of the present invention that locate one or more storage devices on a network that satisfy a given class of service requirement;

Figure 4 is an exemplary data structure that classifies service levels based upon selected characteristics of a storage device in accordance with a preferred embodiment of the present invention; and Figure 5 illustrates the functions implemented in a preferred embodiment of the present invention that manage the data storage after initial placement.

Detailed Description of the Preferred Embodiment

The principles of embodiments 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 embodiments of the present invention may be distributed among a plurality of computers and computer programs. In alternative embodiments a single computer program that configures and enables one or more general-purpose computers could be employed. For illustrative purposes, the inventive method which can be embodied as a computer program will be referred to as the "class of service manager (COSM) ."

Additionally, COSM is described below with reference to an exemplary network of hardware devices, as depicted in Figure 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 Figure 1. Although not visible in Figure 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.

COSM 200 typically is stored in a memory, represented schematically as memory 220 in Figure 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, Figure 2 is included merely as a descriptive expedient and does not necessarily reflect any particular physical embodiment of memory 220. As depicted in Figure 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.

Figure 3 provides a general overview of functions implemented in a preferred embodiment of 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 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'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 Figure 4. Table 400 of Figure 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 Figure 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'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 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 Figure 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.

Figure 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 Figure 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 reclassifies the storage devices (515) , as described above with reference to Figures 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 Figure 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, reclassify, and allocate storage on one or more storage devices that satisfy the new COS requirement, as depicted in Figures 3 and 5.

A preferred embodiment of the present 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.