System for global and local data resource management for service guarantees

• US 20020194324A1
• Filed: 04/26/2002
• Published: 12/19/2002
• Est. Priority Date: 04/26/2001
• Status: Abandoned Application

• Current Assignee: CreekPath Systems, Inc. (HP Inc.)
• Original Assignee: CreekPath Systems, Inc. (HP Inc.)
• Inventors: Guha, Aloke
• Application Number:
  US10/132,715
• Publication Number:
  US 20020194324A1
• Time in Patent Office: Days
• US Class Current: 709/223
• CPC Class Codes: H04L 41/0896 Bandwidth or capacity management, i.e. automatically increasing or decreasing capacities flow or congestion control using dynamic resource allocation, e.g. in-call renegotiation, H04L47/76
• CPC Class Codes: H04L 41/5003 Managing SLA; Interaction between SLA and QoS
• CPC Class Codes: H04L 41/5019 Ensuring fulfilment of SLA
• CPC Class Codes: H04L 43/00 Arrangements for monitoring or testing data switching networks
• CPC Class Codes: H04L 43/0817 by checking functioning
• CPC Class Codes: H04L 47/24 Traffic characterised by specific attributes, e.g. priority or QoS
• CPC Class Codes: H04L 67/1001 for accessing one among a plurality of replicated servers
• CPC Class Codes: H04L 67/1008 based on parameters of servers, e.g. available memory or workload monitoring of computer activity G06F11/30
• CPC Class Codes: H04L 67/1029 using data related to the state of servers by a load balancer
• CPC Class Codes: H04L 67/1095 Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes
• CPC Class Codes: H04L 67/563 Data redirection of data network streams
• CPC Class Codes: H04L 67/568 Storing data temporarily at an intermediate stage, e.g. caching
• CPC Class Codes: H04L 67/63 Routing a service request depending on the request content or context
• CPC Class Codes: H04L 69/329 in the application layer [OSI layer 7]
• CPC Class Codes: H04L 9/40 Network security protocols

Abstract

An end-to-end content management and delivery architecture is disclosed which provided for end-to-end content management from a data storage facility to an requestor remotely located. An End-to-End Content I/O Management (ECIM) contains a Global Infrastructure Control (GIC) that monitors the composite load levels at data centers across network servers, and identifies the best data center from which content request is met. Each data center has a QoS enforcer that monitors content arriving at the data center and controls the entry of all traffic at the data center. Each data center also has a controller, which controls the end-to-end I/O in the local data center. The ECIM allows end-to-end control of the content delivery, scalability provisioning of the application content storage pool to meet service level agreements; dynamic load balancing of the content, and optimization of the I/O resources both locally and across data centers so as to maximize the service level guarantees with minimum resource usage from application servers to storage.

Claims

1. A system for global and local data management comprising:

a plurality of data storage centers, each data storage center including;

a QoS enforcer that monitors content requests at an individual data storage center;

a local controller which controls an individual data storage center and determines status information of an individual storage center; and

a global infrastructure (GIC) control which controls the plurality of data storage centers,

wherein said GIC receives status information from the local controller of each data storage center of the multiple data storage centers and determines from which data storage centers of the multiple data storage centers to provide data to meet a content request, and wherein said GIC initiates replication of data between data storage centers to improve data availability and data access performance.

2. The system of claim 1, wherein said QoS enforcer contains a rule engine containing a predetermined QoS policy, and said GIC determines from which data storage centers of the multiple data storage centers to provide data to meet a content request according to said QoS policy and the status information.

3. The system of claim 1, wherein said QoS enforcer includes a load balancing network device.

4. The system of claim 1, wherein each data storage center further includes:

at least one server device which communicates with the QoS enforcer;

a network switch which communicates with the at least one server device; and

at least one storage device which communicates with the network switch.

5. The system of claim 4, wherein a content controller communicates with the network switch and the at least one storage device.

6. The system of claim 1, wherein the GIC provides end-to-end control of content delivery to the end client over the Internet or intranet.

7. The system of claim 1, wherein provisioning of the application of a content storage pool is scaled to meet service level guarantees.

8. The system of claim 1, wherein content storage and I/O loads on the plurality of storage centers are dynamically balanced.

9. A method of managing data on a network having a plurality of data storage centers, each data storage center including:

a QoS enforcer that monitors content requests at an individual data storage center; and

local controller which controls an individual data storage center and determines status information of an individual storage center; and

a global infrastructure (GIC) control which controls the plurality of data storage centers, the method comprising the steps of;

receiving a content request at the QoS enforcer;

applying QoS enforcer rules to the content request and acting on the content request according to the QoS enforcer rules;

updating a content request traffic profile in a local content controller; and

applying QoS policy based load balancing by the local content controller.

10. The method of claim 9, wherein the step of applying QoS enforcer rules to the content request and acting on the content request according to the QoS enforcer rules includes dropping the content request or delaying the content request when a QoS associated with the request is not high and a remote load of architecture needed to comply with the request is high.

11. The method of claim 9, wherein the step of applying QoS enforcer rules to the content request and acting on the content request according to the QoS enforcer rules includes rotating the content request to an optimal data storage center to comply with the content request when a QoS associated with the request is not high and a remote load of architecture needed to comply with the request is low.

12. The method of claim 9, further comprising the steps of:

providing load information to the GIC from at least one data storage center indicative of a load on the respective data storage center; and

determining an optimal data storage center of the plurality of data storage centers from which to deliver content.

13. The method of claim 12, wherein the step of determining an optimal data storage center of the plurality of data storage centers from which to deliver content, determines the optimal data storage center based on the ability of the storage centers to meet a service level agreement.

15. The computer readable medium of claim 14, wherein the step of applying QoS enforcer rules to the content request and acting on the content request according to the QoS enforcer rules includes dropping the content request or delaying the content request when a QoS associated with the request is not high and a remote load of the architecture needed to comply with the request is high.

16. The computer readable medium of claim 14, wherein the step of applying QoS enforcer rules to the content request and acting on the content request according to the QoS enforcer rules includes routing the content request to the optimal data storage center to comply with the content request when a QoS associated with the request is not high and a remote load of the architecture needed to comply with the request is low.

17. The computer readable medium of claim 14, wherein the instruction further cause the computer to further performs the steps of:

providing load information to the GIC from at least one data storage center indicative of a load on the respective data storage center;

determining the optimal data storage center of the plurality of data storage centers from which to deliver content; and

controlling the replication of data between data storage centers to improve access performance and availability of data, in the case of failures in a data center containing the content.

18. The computer readable medium of claim 17, wherein the step of determining the optimal data storage center of the plurality of data storage centers from which to deliver content, determines the optimal data storage center based on the ability of the storage centers to meet a service level agreement.

14. A computer readable medium carrying instructions for a computer to manage data on a network having a plurality of data storage centers, each data storage center including:

a QoS enforcer that monitors content requests at an individual data storage center; and

local controller which controls an individual data storage center and determines status information of an individual storage center; and

a global infrastructure (GIC) control which controls the plurality of data storage centers, the instructions instructing the computer to perform the method comprising the steps of;

receiving a content request at the QoS enforcer;

applying QoS enforcer rules to the content request and acting on the content request according to the QoS enforcer rules;

updating a content request traffic profile in a local content controller; and

applying QoS policy based load balancing by the local content controller.