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    • 1. 发明授权
    • Method for determining load balancing weights using application instance topology information
    • 使用应用实例拓扑信息确定负载均衡权重的方法
    • US07493380B2
    • 2009-02-17
    • US10725635
    • 2003-12-02
    • Jeffrey David AmanJohn E. ArweMichael Edward BaskeyJohn Alan Bivens, IIDavid Vincent BostjancicDonna N. DillenbergerPeter Bergersen Yocom
    • Jeffrey David AmanJohn E. ArweMichael Edward BaskeyJohn Alan Bivens, IIDavid Vincent BostjancicDonna N. DillenbergerPeter Bergersen Yocom
    • G06F15/16
    • H04L67/1008H04L67/1002H04L67/101H04L67/1023
    • An apparatus and method for distributing traffic across a group of machines using application instance statistics. In order to perform load balancing in accordance with the present invention, a method of generating weights to bias load balancing distributions is provided. The application instances to which traffic is being distributed, or the application middleware, are instrumented to establish certain metrics about the application while running. The application instance instrumentation will provide application statistics such as number of successful transactions, application response times, application topology, importance of transactions being processed, time the application is blocked waiting for resources, resource consumption data, and the like. These metrics are collected, processed, and then presented as a set of weights to the load balancing apparatus to govern its distribution of traffic. With such application metrics available, traffic can be disbursed based on the current state of the application instances and other application instances in the transaction's path, the application instance's likelihood to complete the request, or even higher level business-oriented goals.
    • 一种用于使用应用程序实例统计信息在一组机器上分配流量的装置和方法。 为了根据本发明执行负载平衡,提供了一种产生权重以偏置负载均衡分布的方法。 要分发流量的应用程序实例或应用程序中间件被运行,以便在运行时建立应用程序的某些指标。 应用程序实例仪器将提供应用程序统计信息,例如成功事务的数量,应用程序响应时间,应用程序拓扑,正在处理的事务的重要性,应用程序被阻止等待资源的时间,资源消耗数据等。 这些度量被收集,处理,然后作为一组权重呈现给负载平衡装置以管理其流量分布。 通过这种应用指标,可以根据交易路径中应用程序实例和其他应用程序实例的当前状态,应用程序实例完成请求的可能性,甚至更高级别的面向业务的目标来支付流量。
    • 2. 发明授权
    • Method and apparatus for managing resource contention in a multisystem cluster
    • 用于管理多系统集群中的资源争用的方法和装置
    • US07228351B2
    • 2007-06-05
    • US10334203
    • 2002-12-31
    • John E. Arwe
    • John E. Arwe
    • G06F15/173
    • G06F9/52
    • A method and apparatus for managing contention among users for access to serialized resources in a system cluster containing multiple systems. Each user has an assigned need that is independent of contention of the user for a resource and may be either a holder or a waiter for a resource it is seeking to access. A local system stores local cluster data indicating a grouping of the resources into local clusters on the basis of contention on the local system and indicating for each local cluster the assigned need of a waiter for resources in the cluster. The local system receives remote cluster data from remote systems in the system cluster, which it combines with the local cluster data to generate composite cluster data. A holder on the local system of a resource in a composite cluster is managed in accordance with the composite cluster data for the cluster.
    • 一种用于管理用户访问包含多个系统的系统集群中的序列化资源的竞争的方法和装置。 每个用户具有独立于资源的用户争用的分配需求,并且可以是其正在寻求访问的资源的持有者或服务者。 本地系统基于本地系统上的争用,将指示资源分组的本地集群数据存储到本地集群中,并且为每个本地集群指示分配了服务器对集群中的资源的需求。 本地系统从系统集群中的远程系统接收远程集群数据,它与本地集群数据结合,生成复合集群数据。 根据集群的复合集群数据管理复合集群中资源的本地系统上的持有者。
    • 3. 发明授权
    • Method and apparatus for controlling the number of servers in a multisystem cluster
    • US06230183B1
    • 2001-05-08
    • US09038573
    • 1998-03-11
    • Peter B. YocomCatherine K. EilertJohn E. Arwe
    • Peter B. YocomCatherine K. EilertJohn E. Arwe
    • G06F1300
    • G06F9/5061G06F9/5083G06F2209/505
    • A method and apparatus for controlling the number of servers in a multisystem cluster. Incoming work requests are organized into service classes, each of which has a queue serviced by servers across the cluster. Each service class has defined for it a local performance index for each particular system of the cluster and a multisystem performance index for the cluster as a whole. Each system selects one service class as a donor class for donating system resources and another service class as a receiver class for receiving system resources, based upon how well the service classes are meeting their goals. Each system then determines the resource bottleneck causing the receiver class to miss its goals. If the resource bottleneck is the number of servers, each system determines whether and how many servers should be added to the receiver class, based upon whether the positive effect of adding such servers on the performance index for the receiver class outweighs the negative effect of adding such servers on the performance measure for the donor class. If a system determines that servers should be added to the receiver class, it then determines the system in the cluster to which the servers should be added, based upon the effect on other work on that system. To make this latter determination, each system first determines whether another system has enough idle capacity and, if so, lets that system add servers. If no system has sufficient idle capacity, each system then determines whether the local donor class will miss its goals if servers are started locally. It not, the servers are started on the local system. Otherwise, each system determines where the donor class will be hurt the least and acts accordingly. To ensure the availability of a server capable of processing each of the work requests in the queue, each system determines whether there is a work request in the queue with an affinity only to a subset of the cluster that does not have servers for the queue and, if so, starts a server for the queue on a system in the subset to which the work request has an affinity.