Data processing: generic control systems or specific application – Generic control system – apparatus or process – Plural processors
Reexamination Certificate
2000-08-02
2003-07-22
Patel, Ramesh (Department: 2121)
Data processing: generic control systems or specific application
Generic control system, apparatus or process
Plural processors
C700S099000, C700S101000, C709S241000, C709S241000, C709S208000, C709S209000, C712S031000
Reexamination Certificate
active
06597956
ABSTRACT:
FIELD OF THE INVENTION
The present invention relates generally to data processing. The invention relates more specifically to a method and apparatus for controlling a computing grid.
BACKGROUND OF THE INVENTION
Builders of Web sites and other computer systems today are faced with many challenging systems planning issues. These issues include capacity planning, site availability and site security. Accomplishing these objectives requires finding and hiring trained personnel capable of engineering and operating a site, which may be potentially large and complicated. This has proven to be difficult for many organizations because designing, constructing and operating large sites is often outside their core business.
One approach has been to host an enterprise Web site at a third party site, co-located with other Web sites of other enterprises. Such outsourcing facilities are currently available from companies such as Exodus, AboveNet, GlobalCenter, etc. These facilities provide physical space and redundant network and power facilities shared by multiple customers.
Although outsourcing web site hosting greatly reduces the task of establishing and maintaining a web site, it does not relieve a company of all of the problems associated with maintaining a web site. Companies must still perform many tasks relating to their computing infrastructure in the course of building, operating and growing their facilities. Information technology managers of the enterprises hosted at such facilities remain responsible for manually selecting, installing, configuring, and maintaining their own computing equipment at the facilities. The managers must still confront difficult issues such as resource planning and handling peak capacity. Specifically, managers must estimate resource demands and request resources from the outsourcing company to handle the demands. Many managers ensure sufficient capacity by requesting substantially more resources than are needed to provide a cushion against unexpected peak demands. Unfortunately, this often results in significant amounts of unused capacity that increases companies' overhead for hosting their web sites.
Even when outsourcing companies also provide complete computing facilities including servers, software and power facilities, the facilities are no easier to scale and grow for the outsourcing company, because growth involves the same manual and error-prone administrative steps. In addition, problems remain with capacity planning for unexpected peak demand. In this situation, the outsourcing companies often maintain significant amounts of unused capacity.
Further, Web sites managed by outsourcing companies often have different requirements. For example, some companies may require the ability to independently administer and control their Web sites. Other companies may require a particular type or level of security that isolates their Web sites from all other sites that are co-located at an outsourcing company. As another example, some companies may require a secure connection to an enterprise Intranet located elsewhere.
Also, various Web sites differ in internal topology. Some sites simply comprise a row of Web servers that are load balanced by a Web load balancer. Suitable load balancers are Local Director from Cisco Systems, Inc., BigIP from F5Labs, Web Director from Alteon, etc. Other sites may be constructed in a multi-tier fashion, whereby a row of Web servers handle Hypertext Transfer Protocol (HTTP) requests, but the bulk of the application logic is implemented in separate application servers. These application servers in turn may need to be connected back to a tier of database servers.
Some of these different configuration scenarios are shown in
FIG. 1A
,
FIG. 1B
, and FIG.
1
C.
FIG. 1A
is a block diagram of a simple Web site, comprising a single computing element or machine
100
that includes a CPU
102
and disk
104
. Machine
100
is coupled to the global, packet-switched data network known as the Internet
106
, or to another network. Machine
100
may be housed in a co-location service of the type described above.
FIG. 1B
is a block diagram of a 1-tier Web server farm
110
comprising a plurality of Web servers WSA, WSB, WSC. Each of the Web servers is coupled to a load-balancer
112
that is coupled to Internet
106
. The load balancer divides the traffic between the servers to maintain a balanced processing load on each server. Load balancer
112
may also include or may be coupled to a firewall for protecting the Web servers from unauthorized traffic.
FIG. 1C
shows a 3-tier server farm
120
comprising a tier of Web servers W
1
, W
2
, etc., a tier of application servers A
1
, A
2
, etc., and a tier of database servers D
1
, D
2
, etc. The Web servers are provided for handling HTTP requests. The application servers execute the bulk of the application logic. The database servers execute database management system (DBMS) software.
Given the diversity in topology of the kinds of Web sites that need to be constructed and the varying requirements of the corresponding companies, it may appear that the only way to construct large-scale Web sites is to physically custom build each site. Indeed, this is the conventional approach. Many organizations are separately struggling with the same issues, and custom building each Web site from scratch. This is inefficient and involves a significant amount of duplicate work at different enterprises.
Still another problem with the conventional approach is resource and capacity planning. A Web site may receive vastly different levels of traffic on different days or at different hours within each day. At peak traffic times, the Web site hardware or software may be unable to respond to requests in a reasonable time because it is overloaded. At other times, the Web site hardware or software may have excess capacity and be underutilized. In the conventional approach, finding a balance between having sufficient hardware and software to handle peak traffic, without incurring excessive costs or having over-capacity, is a difficult problem. Many Web sites never find the right balance and chronically suffer from under-capacity or excess capacity.
Yet another problem is failure induced by human error. A great potential hazard present in the current approach of using manually constructed server farms is that human error in configuring a new server into a live server farm can cause the server farm to malfunction, possibly resulting in loss of service to users of that Web site.
Based on the foregoing, there is a clear need in this field for improved methods and apparatuses for providing a computing system that is instantly and easily extensible on demand without requiring custom construction.
There is also a need for a computing system that supports creation of multiple segregated processing nodes, each of which can be expanded or collapsed as needed to account for changes in traffic throughput.
There is a further need for a method and apparatus for controlling such an extensible computing system and its constituent segregated processing nodes. Other needs will become apparent from the disclosure provided herein.
SUMMARY OF THE INVENTION
According to one aspect of the invention, the foregoing needs, and other needs and that will become apparent from the following description, are achieved by a method and apparatus for controlling and managing a highly scalable, highly available and secure data processing sites, based on a wide scale computing fabric (“computing grid”). The computing grid is physically constructed once, and then logically divided up for various organizations on demand. The computing grid comprises a large plurality of computing elements that are coupled to one or more VLAN switches and to one or more storage area network (SAN) switches. A plurality of storage devices are coupled to the SAN switches and may be selectively coupled to one or more of the computing elements through appropriate switching logic and commands. One port of the VLAN switch is coupled to an external network, such as the Inter
Aziz Ashar
Gray Mark
Markson Tom
Patterson Martin
Becker Edward A.
Hickman Palermo & Truong & Becker LLP
Patel Ramesh
Pham Thomas
Terraspring, Inc.
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