1. Field of the Invention
The invention relates in general to a distributed computing system, particularly to a system that allows dynamic allocation of computing tasks.
2. Description of Related Art
In the 1990's, the “Internet,” a connection system that links computers worldwide in a network, has grown from mainly an academic usage to a widespread medium for the transfer of information. The Internet has been termed the so called “information superhighway.” As more and more computers are connected via the Internet or a network such as an intranet or wide-area-network (WAN), information is not the only resource that is shared within a network of computers. A network will also be utilized in distributing computing tasks such as mathematical calculations, word processing, graphic design, and etc. Since tasks and files are distributed among various computers, a system is required to balance the computing tasks among a plurality of servers.
Presently, various load-balancing methods have been developed to address the problem of overloading computing tasks on one particular server. For example, for a web site having several servers but operating under a single uniform resource locator (“URL”), a domain name server (“DNS”) will send information requests for a specific URL to specific IP addresses corresponding to the servers. In a round-robin DNS, load balancing is achieved by routing requests to these servers in sequential rotation based on their IP addresses. However, since the DNS just routes requests sequentially, this method does not consider the load of the servers and a request can be routed to a server that has failed or does not have the load to perform the request.
Another method is to dedicate a hardware device such as proxy gateways or an IP redirector to perform load balancing. The proxy gateway receives all the requests, queries the servers to determine their respective loads, and then distribute the requests accordingly. Responses from the servers are routed back to the network through the proxy gateway. Unlike the DNS-based method, all requests resolve to the IP address of the proxy server, which avoids the problem of failed servers. However, dedicated load balancers also have a drawback of relying on “old information” as the proxy gateway can only query the servers so often without creating undesirable overhead on the network. Also, these hardware devices only route tasks based on requests and do not consider other important aspects of a computing tasks. For example, in an Application Service Provider (ASP) model, client attributes, such as memory space and computing power, need to be matched up with the fulfillment server attributes, such as data format and size of the output. If the computing task is to produce a video image by the fulfillment server, the output of the server needs to be in a specific format that the client can visualize. Thus, there is a need for a load-balancer that can track the differing capabilities of various servers in fulfilling a client's need.
U.S. Pat. No. 6,128,279, to O'Neil et al., solves the old information problem by teaching a peer-to-peer load balancing method in which a server in a plurality of servers determines whether it can serve the request or whether it should direct the request to another server. Although the information is real-time, the redirecting of the request is accomplished by the server itself, which creates a problem with scalability. As server number increases, each server needs to track the load of other servers and thus, diverts the server's computing power from its main task of fulfilling requests. Also, like the previous methods mentioned, the peer-to-peer load balancing tracks only load and neglects various attributes of a client, a server, and a request.
Therefore, it is advantageous to have a scalable system to distribute computing tasks that considers attributes of the client, the server, and the request.
The invention enables distribution of computing task according to various attributes of a client, a server, and a computing task. The infrastructure for this system is a network, which enables a set of distributor servers to manage client requests and distribute such client requests to a set of fulfillment servers.
The preferred embodiments of this system would enable a client to distribute its computing tasks to a suitable fulfillment server that has all the required client attributes, computing task attributes, and server attributes. The system is scalable as additional sets of distributor servers can be added to manage the fulfillment servers. In addition, new distributor servers can be added to manage pre-existing distributor servers. Also, the distributor servers can be programmed to consider various attributes according to the usage of the system. In an alternative embodiment, the system can be used to parse a highly intense computing task into components and distribute said components to fulfillment servers that have idle computing power.
a is a block diagram of a computing task allocation system having a client component 10, distributor components 5060, and fulfillment components 100200300400 in accordance with the present invention.
b illustrates the scalability of the system, wherein a plurality of clients 102030 is coupled to one set of distributor servers, which manages a subsequent set of distributor servers that manages a set of fulfillment servers.
The elements of the computing task allocation system in accordance with the invention can essentially be divided into three distinct components: client component 10, distributor component comprising of distributor servers 5060, and fulfillment component comprising of application servers 100200300400, as illustrated in
The system enables a user to access a suitable network resource, such as one of the application servers 100200300400, to fulfill its computing task. The term “computing task” as described herein is defined as tasks that are performed by a microprocessor machine, such as word processing, graphic design, file sharing, printing, mathematical calculations, and etc. In the preferred embodiment, the system is used in an Application Service Provider (ASP) model, in which software applications A1 A2 A3 reside on fulfillment servers 100200300400. Clients share and access the applications from the servers via a network. However, one skilled in the art should realize that the fulfillment servers could be software or microprocessor machines that can execute a computing task, such as a printer, a web-content server, or a database.
All components of the system (client, distributor servers, and fulfillment servers) are connected to the system via registration through an administration module 40 and stored in a system database 42. In addition to the registration of each component to the system, each fulfillment server is registered with a specific distributor server, as illustrated in
After registration of the fulfillment servers, the client is able to distribute its computing tasks among the plurality of fulfillment servers. The client component 10 consists an input module 11 to request a computing task, a client manager 12 to track input and output data, and an output module 13 to present a result of the computing task. Client 10 communicates to the other components of the system via a network such as the Internet, a local area network (LAN) and/or wide area network (WAN), wireless and/or wired, or other network communication infrastructure.
The client 10 communicates computing tasks to a virtual Internet Protocol (IP) box 500 that sequentially redirects the computing tasks among the distributor servers 5060. Once the computing task reaches the distributor manager 5262, the distributor manager will search a corresponding server database 5464. For example, distributor manager 52 will search the server database 54 to find a fulfillment server from the plurality of fulfillment servers 100200300400 that match the attributes of the computing task and the client. If no suitable fulfillment server is found, a server selector 56 will re-direct the computing task to another distributor server 60. If a suitable server is found, the server selector 56 sends the corresponding IP address of the suitable server to the client 10 and the client 10 directly access the suitable fulfillment server via the IP address.
b illustrates the scalability of the system, as shown by a plurality of clients 102030 communicating requests via a virtual IP box 500 to a set of distributor servers 8090, which redirects the request to a distributor server in a second set of distributor server 506070 that manages the fulfillment servers 100200300400. As shown in
After application sever attributes are recorded in the system database 2200, the application server sends 2300 its attributes to a virtual IP box 520, which redirects 2400 the information to a distributor server 50. In step 2500, the distributor manager 52 registers the information in its server database 54 and sends 2600 its “distributor server IP address” to the application server 100. After completion of registration 2700, the application server 100 sends 2800 its attributes to distributor server 50 directly via the “distributor IP address,” and attributes in the server database 54 is dynamically updated accordingly 3000, as illustrated in
The above embodiments are only illustrative of the principles of this invention and are not intended to limit the invention to the particular embodiments described. One skilled in the art should recognize that computing tasks could include all types of tasks such as printing, word processing, project management, graphic design, mathematic calculations, and etc. In particular, it is contemplated that functional implementation of the invention described herein may be implemented equivalently in hardware, software, firmware, and/or other available functional components or building blocks. Accordingly, various modifications, adaptations, and combinations of various features of the described embodiments can be practiced without departing from the scope of the invention as set forth in the appended claims.
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