[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

EP1057101A2 - Procede et appareil de calcul reparti dynamique sur un reseau - Google Patents

Procede et appareil de calcul reparti dynamique sur un reseau

Info

Publication number
EP1057101A2
EP1057101A2 EP99908442A EP99908442A EP1057101A2 EP 1057101 A2 EP1057101 A2 EP 1057101A2 EP 99908442 A EP99908442 A EP 99908442A EP 99908442 A EP99908442 A EP 99908442A EP 1057101 A2 EP1057101 A2 EP 1057101A2
Authority
EP
European Patent Office
Prior art keywords
server
task
client
results
code
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP99908442A
Other languages
German (de)
English (en)
Inventor
Kenneth C. R. C. Arnold
James H. Waldo
Ann M. Wollrath
Peter C. Jones
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Sun Microsystems Inc
Original Assignee
Sun Microsystems Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from US09/030,840 external-priority patent/US6446070B1/en
Application filed by Sun Microsystems Inc filed Critical Sun Microsystems Inc
Publication of EP1057101A2 publication Critical patent/EP1057101A2/fr
Withdrawn legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F15/00—Digital computers in general; Data processing equipment in general
    • G06F15/16—Combinations of two or more digital computers each having at least an arithmetic unit, a program unit and a register, e.g. for a simultaneous processing of several programs
    • G06F15/163—Interprocessor communication
    • G06F15/173—Interprocessor communication using an interconnection network, e.g. matrix, shuffle, pyramid, star, snowflake
    • G06F15/17306—Intercommunication techniques
    • G06F15/17318—Parallel communications techniques, e.g. gather, scatter, reduce, roadcast, multicast, all to all
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • G06F9/505—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering the load
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F8/00—Arrangements for software engineering
    • G06F8/30—Creation or generation of source code
    • G06F8/31—Programming languages or programming paradigms
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/445—Program loading or initiating
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/445—Program loading or initiating
    • G06F9/44568—Immediately runnable code
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
    • G06F9/5044—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering hardware capabilities
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/52—Program synchronisation; Mutual exclusion, e.g. by means of semaphores
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/54—Interprogram communication
    • G06F9/547—Remote procedure calls [RPC]; Web services
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/46—Multiprogramming arrangements
    • G06F9/54—Interprogram communication
    • G06F9/547—Remote procedure calls [RPC]; Web services
    • G06F9/548—Object oriented; Remote method invocation [RMI]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
    • H04L12/42—Loop networks
    • H04L12/427—Loop networks with decentralised control
    • H04L12/433—Loop networks with decentralised control with asynchronous transmission, e.g. token ring, register insertion
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2209/00—Indexing scheme relating to G06F9/00
    • G06F2209/54—Indexing scheme relating to G06F9/54
    • G06F2209/549—Remote execution

Definitions

  • This invention generally relates to distributed computing systems and more particularly, to a method and apparatus for performing dynamic distributed computing over a network.
  • a distributed computing network users can harness the processing capabilities of numerous computers coupled to the network. Tasks with many different independent calculations can be quickly processed in parallel by dividing the processing among different computers on the network. Further, specialized tasks can be computed more quickly by locating a computer on the network most suitable for processing the data. For example, a task executing on a client system which performs an intense floating point calculation may execute faster on a server system coupled to the network which has specialized floating point hardware suitable for the particular calculations.
  • scripting based systems are an improvement over some conventional distributed computing systems.
  • scripting based systems eliminate the need to recompile code, but are still very inefficient.
  • a scripting based distributed system can execute the same instructions on multiple platforms because the language is interpreted by an interpreter located on each system. Consequently, most scripting languages are slow since they must translate high level scripting instructions into low level native instructions in real time.
  • scripting languages are hard to optimize and can waste storage space since they are not generally compressed.
  • a method and apparatus for dynamic distributed computing is provided.
  • the client selects a server from the network to process the task. This selection can be based on the availability of the server or the specialized processing capabilities of the server.
  • a client stub marshals the parameters and data into a task request.
  • the client sends the task request to the server which invokes a generic compute method.
  • the server automatically determines if the types associated with the task are available on the server and downloads the task types from the network as necessary. Information in the task types are used to extract parameters and data stored in the particular task request.
  • the generic compute method is used to execute the task request on the selected server.
  • the client receives the results, or the computed task, back from the selected server.
  • a method and apparatus for dynamic distributed computing is provided.
  • the server will automatically determine which task types are available on the server and will download task types from the network as necessary. These task types help the server unmarshal parameters and data from a task request and generate a local task.
  • the server invokes a generic compute method capable of processing all types of compute tasks or subtypes of a compute task.
  • the generic compute method is used to execute the task request on the selected server. If a subsequent task will use the results, the server stores the results from the computed tasks in a local cache. Once the task has completed, the server returns the results, or the computed task, to the client.
  • FIG. 1. illustrates a network suitable for use with method and systems consistent with the present invention
  • FIG. 2 is block diagram of a computer system suitable for use with Method and Systems consistent with the present invention
  • FIG. 3 is a block diagram representation of a client-server networking environment suitable for use with a Method and System consistent with the present invention
  • FIG. 4 is a flow chart of the steps a client performs in accordance with Methods and Systems consistent with the present invention.
  • FIG. 5 is a flow chart the steps performed by a server in accordance with Methods and Systems consistent with the present invention. INTRODUCTION
  • Systems consistent with the present invention address shortcomings of the prior art and provide a dynamic distributed computing system used over a network of server computers.
  • This dynamic distributed computing system is particular useful in heterogenous computer networks having computers with different processors, different operating systems, and combinations thereof.
  • Such a system allows a client application to select a server computer at runtime to execute a particular task.
  • the task is an object having a particular type or class definition.
  • the server can generally defer knowing the actual class definition until the parameters and data associated with the object task are received on the server. Consequently, the particular type is downloaded by the server if it is not available on the server. For example, if an object instance of an unknown class is transmitted to the server, the server downloads the unknown class. The server then uses this class to process the object.
  • RMI Remote Method Invocation
  • Sun Microsystems, Inc. of Mountain View, California For more information on Remote Method Invocation (RMI) see co-pending U.S. Patent Application, "System and Method For Facilitating Loading of "Stub” Information to Enable a Program Operating in One Address Space to Invoke Processing of a Remote Method or Procedure in Another Address Space” having serial number 08/636,706, filed April 23, 1996 by Ann M. Wolrath, James Waldo, and Roger Riggs assigned to the assignees of the present invention and incorporated by reference herein. Also, RMI is also described in further detail on the JavaSoft WebPage at
  • a task in the dynamic distributed system consistent with the present invention can be written once and executed on any server computer in a network. This capability is particularly advantageous in a heterogeneous network because the task does not have to be ported to every platform before it is executed. Instead, a generic compute task designed in accordance with the present invention is loaded on each system. This generic compute task is capable of executing a wide variety of tasks specified by the client at runtime. For example, one can develop a type called "Compute" and a generic compute task which accepts the "Compute" type in an object oriented language, such as Java.
  • Java is described in many texts, including one that is entitled “The Java Language Specification” by James Gosling, Bill Joy, and Guy Steele, Addison- Wesley, 1996, which is incorporated by reference herein.
  • the client creates a task having a subtype of the type "Compute” and passes an object corresponding to task to the generic compute task on the server.
  • a remote procedure call mechanism downloads the object to the server and the generic compute task which executes the task.
  • Java the task transmitted by the client is actually an object including a series of bytecodes. These bytes codes can be executed immediately as long as the server implements a Java Virtual Machine (JVM).
  • JVM Java Virtual Machine
  • the JVM can be implemented directly in hardware or efficiently simulated in a software layer running on top of the native operating system.
  • the Java language was designed to run on computing systems with characteristics that are specified by the Java Virtual Machine (JVM) Specification.
  • JVM Java Virtual Machine
  • the JVM specification is described in greater detail in a text entitled The Java Virtual Machine Specification. Addison Wesley, which is incorporated by reference herein.
  • This uniform JVM environment allows homogeneous execution of tasks even though the computer systems are heterogenous and have different processors, different operating systems, and combinations thereof.
  • Combining a powerful remote procedure call subsystem with a generic compute task on the server, designed in accordance with the present invention results in a powerful dynamic distributed computing environment.
  • a compute server using bytecodes can process a task much faster than systems using conventional text based scripting languages or other character based languages.
  • Each bytecode is compact (8 bits) and is in a numeric format. Consequently, the server computer does not spend compute cycles parsing the characters and arguments at run time.
  • the bytecodes can be optimized on the client before transporting them to the server.
  • the server optionally can convert the bytecodes to native instructions for execution directly on the hardware at run time using a processing mechanism such as a Just-in-Time (JIT) compiler.
  • JIT Just-in-Time
  • a system designed in accordance with the present invention assumes that each client is capable of communicating to each server over a common networking protocol such as TCP/IP. Also, it is assumed that there is a remote procedure call (RPC) subsystem on the client and server which is capable of receiving remote requests from a client and executing them on the server. This RPC system also automatically downloads code and related information needed for performing the task at run time.
  • RPC remote procedure call
  • RMI developed by Sun Microsystems, Inc. is a suitable RPC subsystem providing these features.
  • RPC subsystems such as DCOM/COM from Microsoft, Inc., may be used in lieu of RMI. COMPUTER NETWORK
  • Fig. 1 illustrates a network 100 in which one embodiment of the present invention can be implemented.
  • Network 100 includes Local Area Network (LAN) 101, backbone or Wide Area Network (WAN) 112, and Local Area Network (LAN) 116 in its essential configuration.
  • LAN 101 includes a series of work stations and server computers 102, 104, 106, and 108.
  • LAN 116 includes a series of work stations and server computers 118, 120, 122, and 124. These computer systems 102-108 and 118-124 are coupled together to share information, transmit data, and also share computational capabilities.
  • LAN 101 is coupled to the larger overall network using a network interconnect device 110.
  • the specific type of network interconnect device can be a router, a switch, or a hub depending on the particular network configuration.
  • network interconnect device 110 includes routers, switches, hubs or any other network interconnect device capable of coupling together a LAN 101, a WAN 112, and LAN 116 with user terminals into an integrated network.
  • Network interconnect device 114 can also include routers, switches, hubs, or any other network interconnect device capable of coupling the computers on LAN 116 with user terminals into an integrated network.
  • a dynamic distributed computing system designed in accordance with the present invention is typically located on each computer system coupled to network 100 . Accordingly, each computer may operate as either a client or a server depending on the particular request being made and the services being provided. Typically, the client requests that a task is computed on a server computer and the server computer will process the task. COMPUTER SYSTEM
  • Fig. 2 the system architecture for a computer system suitable for practicing methods and systems consistent with the present invention is illustrated.
  • the exemplary computer system is for descriptive purposes only. Although the description may refer to terms commonly used in describing particular computer systems, such as in IBM PS/2 personal computer, the description and concepts equally apply to other computer systems, such as network computers, workstation, and even mainframe computers having architectures dissimilar to Fig. 1.
  • the implementation is described with reference to a computer system implementing the Java programming language and Java Virtual Machine specifications, although the invention is equally applicable to other computer systems having similar requirements. Specifically, the present invention may be implemented with both object oriented and nonobject-oriented programming systems.
  • Computer system 200 includes a central processing unit (CPU) 105, which may be implemented with a conventional microprocessor, a random access memory (RAM) 210 for temporary storage of information, and a read only memory (ROM) 215 for permanent storage of information.
  • a memory controller 220 is provided for controlling RAM 210.
  • a bus 230 interconnects the components of computer system 200.
  • a bus controller 225 is provided for controlling bus 230.
  • An interrupt controller 235 is used for receiving and processing various interrupt signals from the system components.
  • Mass storage may be provided by diskette 242, CD ROM 247, or hard drive 252. Data and software may be exchanged with computer system 200 via removable media such as diskette 242 and CD ROM 247.
  • Diskette 242 is insertable into diskette drive 241 which is, in turn, connected to bus 230 by a controller 240.
  • CD ROM 247 is insertable into CD ROM drive 246 which is, in turn, connected to bus 230 by controller 245.
  • Hard disk 252 is part of a fixed disk drive 251 which is connected to bus 230 by controller 250.
  • Computer system 200 may be provided by a number of devices.
  • a keyboard 256 and mouse 257 are connected to bus 230 by controller 255.
  • controller 255 It will be obvious to those reasonably skilled in the art that other input devices, such as a pen and/or tablet may be connected to bus 230 and an appropriate controller and software, as required.
  • DMA controller 260 is provided for performing direct memory access to RAM 210
  • a visual display is generated by video controller 265 which controls video display 270.
  • Computer system 200 also includes a communications adaptor 290 which allows the system to be interconnected to a local area network (LAN) or a wide area network (WAN), schematically illustrated by bus 291 and network 295.
  • LAN local area network
  • WAN wide area network
  • Operation of computer system 200 is generally controlled and coordinated by operating system software.
  • the operating system controls allocation of system resources and performs tasks such as processing scheduling, memory management, networking, and services, among things.
  • Dynamic distributed computing is generally a client server process.
  • the client-server relationship is established for each call being made and generally the roles can change.
  • the client is defined as the process making a call to request resources located or controlled by the server.
  • the computer or processor executing the requesting process may also be referred to as a client.
  • these roles may change depending on the context of information and particular processing which is taking place.
  • Fig. 3 is a block diagram representation of a client-server networking environment used to implement one embodiment of the present invention. This diagram includes those subsystems closely related to the present invention to emphasize one embodiment of the present invention. Additional subsystems, excluded in Fig. 3, may be necessary depending on the actual implementation.
  • Fig. 3 includes a client 302, a server 316, and an object/method repository 314 which are all operatively coupled to a network 312.
  • Client 302 includes an application 304 which makes a remote compute call 306 to process a task on a remote server computer.
  • a remote stub 310 typically generated using a remote procedure call subsystem as described in the RMI specification, is used to package parameters and data associated with the specific remote compute call 306.
  • the typical client can also includes a collection of local objects/methods 308 which may contain the type of task client 302 calls remote compute call 306 to execute.
  • the tasks can be located in object method repository 314 and are accessed by compute method 320 as needed.
  • Server 316 includes a remote skeleton 322 to unmarshal the parameters and data transmitted from the client.
  • Remote skeleton 322 prepares information for use by compute method 320.
  • a local objects/methods 324 also includes tasks client 302 can ask the server 316 to process.
  • remote compute call 306 makes a call to a compute method 320 to process a particular task.
  • a remote stub 310 marshals information on the calling method so that a compute method 320 on server 316 can execute the task.
  • Remote stub 310 may also marshal basic parameters used as arguments by compute method 320 on server 302.
  • Remote skeleton 322 receives the task and unmarshals data and parameters received over the network and provides them to compute method 320. If the task and related types are not available on server 316, the skeleton downloads the types from client 302, object/method repository 314, or some other safe and reliable source of the missing types.
  • the type information maps the location of data in the object and allows the remote skeleton to complete processing the object.
  • RMI is one remote procedure call (RPC) system capable of providing remote stub 310 and remote skeleton 322.
  • RPC remote procedure call
  • Fig. 4 is a flow chart of the steps performed by a client when utilizing the dynamic distributed computing system and method consistent with the present invention.
  • the client selects a suitable server from the network to process the task (step 402).
  • the selection criteria can be based upon the overall processing load distribution among the collection of server computers or the specialized computing capabilities of each server computer. For example, load balancing techniques may be used to automatically determine which computer has the least load at a given moment.
  • some computers having specialized hardware, such as graphic accelerators or math co-processors may be selected by the client because the task has intense graphic calculations, such as rendering three dimensional wireframes, or must perform many floating point calculations.
  • the client invokes a remote compute method on the selected server (step 404).
  • An RPC system such as RMI, facilitates invoking the remote compute method on a server computer.
  • the client need only know that the remote compute method can be used as a conduit to process a particular task on a remote computer. For example, in Java the remote instruction "Server.runTask(new PI(1000))" executed on a client causes a remote method "runTask" to be invoked on a remote server "Server" of type "ComputeServer".
  • This step provides the task (in this case the task is a type task object instantiated by the "new PI(1000)) as a parameter to the generic compute method through the remote method "runTask".
  • the "runTask” method on the server implements a Compute remote interface.
  • this instruction can indicate to the server that results from the computed task should be stored in a result cache on the selected server. This enables subsequent tasks to share the results between iterations. For example, the results from calculating "PI” may be used later by another remote method to compute the volume of a sphere or perform another precise calculation using the value of "PI".
  • a stub is used to marshal parameters and data into a task request.
  • the task request is then provided to the selected server.
  • the task request includes data and parameters for the task as well as a network location for the type or class if it is not present on the server.
  • a skeleton on the server uses the type or class information to process the object and unmarshall data and parameters.
  • the task request is an object and the class location information is contained in a codebase URL (universal record locator) parameter. Further details on this are contained in the RMI Specification.
  • the server can schedule the task for execution immediately or whenever the server finds a suitable time for executing the task. After the server performs the computation, the client receives the results from the computed task (step 408).
  • Fig. 5 is a flow chart of the steps performed by the dynamic distributed computing system and methods consistent with the present invention.
  • a skeleton on the server unmarshalls parameters and data from a task request and recreates the original task as transmitted (step 504). Unmarshalling these parameters may include downloading several additional types.
  • the skeleton determines if the types related to the task request are available on the server (step 506). If the types associated with the task request are not available, the skeleton must download the tasks from one of the areas on the network (step 509). For example, if a "PI()" class is not on the server, the skeleton server will down load this type from the client. The type or class is used by the skeleton to map data in the object and marshall parameters and data..
  • the client will indicate in the request package where the particular type is located.
  • the skeleton can download the requested type from a object/method repository and can cache the type for future server requests.
  • the requested type could also be located on the client.
  • the class containing the particular type is located in the given codebase URL (universal record locator) transmitted by the client.
  • Dynamic class loading features in RMI facilitate the automatic downloading of the class using the codebase.
  • the skeleton invokes the generic compute method (step 508).
  • the generic compute method on the server then executes the specific task requested by the client (step 510). For example, assume the client calls "Computes erver.runTask(new PI(1000))". The skeleton will invoke the generic compute method "runTask” on the server. The “runTask” method calls the “run()” method embedded in the task called by the client. Further, the "runTask' method implements the remote interface "Compute" which maintains the remote connection with the client.
  • the skeleton stores results from the computed tasks in a cache if a subsequent task will use the results.
  • the computed task or results are returned to the client by executing "return t.run()" on the server (step 512).
  • the server can include the following Java code: THE TASK public interface Task extends Serializable ⁇
  • Java code can be used on a client performing dynamic distributed computing consistent with the present invention.
  • ComputerServer server getAComputerServer(); // Select a server from
  • Double pi server.runTask(new PI(1000)); // implement abstract remote // to execute a "pi"computation // defined in "PF'class. System. out.println("PI seems to be "+pi); // return results in "pi” variable

Landscapes

  • Engineering & Computer Science (AREA)
  • Software Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Hardware Design (AREA)
  • Signal Processing (AREA)
  • Mathematical Physics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Computing Systems (AREA)
  • Computer And Data Communications (AREA)
  • Multi Processors (AREA)

Abstract

Dans un environnement client-serveur, il est souhaitable de disposer d'un certain nombre de serveurs capables de traiter une large gamme d'applications telles que des applications de calcul intensif ou des opérations graphiques telles que des rendus. Dans un environnement client-serveur hétérogène, des systèmes classiques stockent de manière statique des exécutables sur un serveur en vue d'une exécution ultérieure. Ce stockage requiert une mémoire importante ainsi que de nombreuses heures de programmation de portage d'applications vers la machine de serveur à partir de machines de clients comportant différents modules objets. La présente invention permet de résoudre ces problèmes par la création d'un environnement d'exécution homogène à l'intérieur d'un réseau client-serveur hétérogène: le système télécharge de façon dynamique un code sur un serveur de calcul, exécute le code sur le serveur de calcul, et retourne les résultats traités au client appelant. Cette technique ne nécessite pas de téléchargement ni de compilation de multiples copies de code, puisque le code de serveur peut être exécuté sur tous les différents systèmes. Un système conçu selon cette technique est également efficace. Le code de serveur est généralement compilé localement chez le client, téléchargé vers le serveur comme codes de multiplets, puis exécuté.
EP99908442A 1998-02-26 1999-02-25 Procede et appareil de calcul reparti dynamique sur un reseau Withdrawn EP1057101A2 (fr)

Applications Claiming Priority (5)

Application Number Priority Date Filing Date Title
US7604898P 1998-02-26 1998-02-26
US09/030,840 US6446070B1 (en) 1998-02-26 1998-02-26 Method and apparatus for dynamic distributed computing over a network
US76048P 1998-02-26
US30840 1998-02-26
PCT/US1999/004064 WO1999044121A2 (fr) 1998-02-26 1999-02-25 Procede et appareil de calcul reparti dynamique sur un reseau

Publications (1)

Publication Number Publication Date
EP1057101A2 true EP1057101A2 (fr) 2000-12-06

Family

ID=26706519

Family Applications (1)

Application Number Title Priority Date Filing Date
EP99908442A Withdrawn EP1057101A2 (fr) 1998-02-26 1999-02-25 Procede et appareil de calcul reparti dynamique sur un reseau

Country Status (6)

Country Link
EP (1) EP1057101A2 (fr)
JP (1) JP2002505462A (fr)
KR (1) KR20010034542A (fr)
CN (1) CN1292118A (fr)
AU (1) AU2787699A (fr)
WO (1) WO1999044121A2 (fr)

Families Citing this family (25)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6460082B1 (en) 1999-06-17 2002-10-01 International Business Machines Corporation Management of service-oriented resources across heterogeneous media servers using homogenous service units and service signatures to configure the media servers
US7783695B1 (en) * 2000-04-19 2010-08-24 Graphics Properties Holdings, Inc. Method and system for distributed rendering
WO2001090883A2 (fr) * 2000-05-09 2001-11-29 Sun Microsystems, Inc. Appel de fonction a distance au moyen de messages dans un environnement informatique distribue
JP2001344199A (ja) * 2000-06-02 2001-12-14 Nec Corp 分散型処理システム及び方法並びに記録媒体
JP2002095071A (ja) * 2000-09-13 2002-03-29 Sanyo Electric Co Ltd ネットワークシステム及び機器制御方法
EP1229436B1 (fr) 2001-01-31 2008-08-06 Hewlett-Packard Company, A Delaware Corporation Méthode et dispositif de mise en oeuvre de documents
KR20030021114A (ko) * 2001-09-05 2003-03-12 주식회사 미리텍 부하분산기
GB2380911B (en) * 2001-10-13 2004-09-08 Hewlett Packard Co Performance of a multi-stage service within an information technology network
KR100497353B1 (ko) * 2002-03-26 2005-06-23 삼성전자주식회사 영상 처리 장치 및 처리된 영상을 수신하는 장치 및 방법
CN100450256C (zh) * 2002-10-28 2009-01-07 中兴通讯股份有限公司 移动通信网络规划中小区覆盖文件的分布式处理方法
SE0203297D0 (sv) * 2002-11-05 2002-11-05 Ericsson Telefon Ab L M Remote service execution in an heterogenous network
US20040122950A1 (en) * 2002-12-20 2004-06-24 Morgan Stephen Paul Method for managing workloads in an autonomic computer system for improved performance
US7975270B2 (en) * 2004-03-10 2011-07-05 International Business Machines Corporation Facilitating allocation of resources in a heterogeneous computing environment
JP2006004008A (ja) * 2004-06-15 2006-01-05 Sony Computer Entertainment Inc 処理管理装置、コンピュータ・システム、分散処理方法及びコンピュータプログラム
CN101176079B (zh) * 2005-03-16 2011-12-07 航空照片技术有限公司 在服务器和客户机之间分配计算的方法以及分布式计算机系统
CN101146116B (zh) * 2006-09-11 2010-11-10 河南科技大学 一种基于网络的cad图形处理系统
JP5368687B2 (ja) * 2007-09-26 2013-12-18 キヤノン株式会社 演算処理装置および方法
CN101140525B (zh) * 2007-10-17 2010-12-08 中兴通讯股份有限公司 分布式编译方法
WO2009052529A1 (fr) * 2007-10-20 2009-04-23 Citrix Systems, Inc. Procédés et systèmes permettant d'afficher à distance de données graphiques en trois dimensions
US8169436B2 (en) * 2008-01-27 2012-05-01 Citrix Systems, Inc. Methods and systems for remoting three dimensional graphics
US8751844B2 (en) 2009-09-24 2014-06-10 Citrix Systems, Inc. Systems and methods for attributing an amount of power consumption to a workload
US8539080B1 (en) * 2012-12-18 2013-09-17 Microsoft Corporation Application intelligent request management based on server health and client information
US10776325B2 (en) * 2013-11-26 2020-09-15 Ab Initio Technology Llc Parallel access to data in a distributed file system
CN104794095B (zh) * 2014-01-16 2018-09-07 华为技术有限公司 分布式计算处理方法及装置
CN107194490B (zh) * 2016-03-14 2022-08-12 商业对象软件有限公司 预测建模优化

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
ATE151183T1 (de) * 1989-02-24 1997-04-15 Digital Equipment Corp Makler für die auswahl von rechnernetzwerkservern
US5515536A (en) * 1992-11-13 1996-05-07 Microsoft Corporation Method and system for invoking methods of an object through a dispatching interface
US5742848A (en) * 1993-11-16 1998-04-21 Microsoft Corp. System for passing messages between source object and target object utilizing generic code in source object to invoke any member function of target object by executing the same instructions
US5630066A (en) * 1994-12-20 1997-05-13 Sun Microsystems, Inc. System and method for locating object view and platform independent object
US5928323A (en) * 1996-05-30 1999-07-27 Sun Microsystems, Inc. Apparatus and method for dynamically generating information with server-side software objects
US6360256B1 (en) * 1996-07-01 2002-03-19 Sun Microsystems, Inc. Name service for a redundant array of internet servers

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
See references of WO9944121A2 *

Also Published As

Publication number Publication date
JP2002505462A (ja) 2002-02-19
KR20010034542A (ko) 2001-04-25
CN1292118A (zh) 2001-04-18
WO1999044121A3 (fr) 1999-10-21
WO1999044121A2 (fr) 1999-09-02
AU2787699A (en) 1999-09-15

Similar Documents

Publication Publication Date Title
US6446070B1 (en) Method and apparatus for dynamic distributed computing over a network
EP1057101A2 (fr) Procede et appareil de calcul reparti dynamique sur un reseau
US6493870B1 (en) Methods and apparatus for packaging a program for remote execution
US6877163B1 (en) Method and system for dynamic proxy classes
US6393497B1 (en) Downloadable smart proxies for performing processing associated with a remote procedure call in a distributed system
EP0735470B1 (fr) Dispositif et procédé pour la détermination du type d'un objet dans un système d'objet distribué
US7490330B2 (en) Using a virtual machine instance as the basic unit of user execution in a server environment
US6622175B1 (en) System and method for communications in a distributed processing environment
US7971210B2 (en) Interface for processing client-server method calls within a single virtual machine
US6199196B1 (en) Methods and apparatus for linking a program for remote execution
US6947965B2 (en) System and method for communications in a distributed computing environment
US6253256B1 (en) Deferred reconstruction of objects and remote loading in a distributed system
US20020078255A1 (en) Pluggable instantiable distributed objects
KR20010041293A (ko) 원격 메소드 호출을 위한 방법 및 장치
US6842894B1 (en) Dynamic Compiling
WO2003065206A2 (fr) Repartition et integration dynamiques d'objets de code informatiques
WO1999044123A1 (fr) Serveurs mandataires chargeables executant des traitements associes a une procedure de teleappel
EP1057113B1 (fr) Reconstitution differee d'objets et telechargement de notifications d'evenements dans un systeme decentralise
Fritsche et al. A Java distributed computation library
Janson et al. CORBA vs. DCOM
Zhang A comparative study of DCOM/CORBA and. NET/J2EE
Diehl et al. Implementing Multi-User Worlds with CORBA
Kerry et al. Service Management in DISCWorld using CORBA and Java
Guide PV-WAVE®
Nooren et al. JAVA & Parallelism/Real-time systems

Legal Events

Date Code Title Description
PUAI Public reference made under article 153(3) epc to a published international application that has entered the european phase

Free format text: ORIGINAL CODE: 0009012

17P Request for examination filed

Effective date: 20000907

AK Designated contracting states

Kind code of ref document: A2

Designated state(s): DE FR GB IE NL SE

17Q First examination report despatched

Effective date: 20001222

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE APPLICATION IS DEEMED TO BE WITHDRAWN

18D Application deemed to be withdrawn

Effective date: 20030902