Abstract:
The method of the present invention provides an automatic and optimised selection of the network topology for distributing scheduling of jobs on the computers of the modified network topology. The automatic and optimised selection of the network topology starts from the current topology and a desired number of additional connections. In this way the method of the present invention provides a higher convergence speed for the modified consensus algorithm in comparison e.g. to a simple ring network. The method exploits the so called small-world networks. Small-world networks are more robust to perturbations than other network architectures. The preferred embodiment provides a workload scheduling system which is highly scalable to accommodate increasing workloads within a heterogeneous distributed computing environment. A modified average consensus algorithm is used to distribute network traffic and jobs amongst a plurality of computers.
Abstract:
A solution is proposed for controlling a distributed application. A corresponding method (400) comprises the steps of detecting (404-422) an indication of a computational capability of a client computing machine and/or of a server computing machine, building (424-440) at least part of a page in response to a request received by the server computing machine from the client computing machine, the page comprising a set of commands each one for submitting a next request on the client computing machine, a processing logic for serving each next request being split between a client processing component and/or a server processing component, returning (442-456) the page with the client processing component for each command to the client computing machine for causing the client computing machine to load the page and execute each client processing component in response to the corresponding next request, and executing (458-464,424-440) each server processing component in response to the corresponding next request.
Abstract:
A mechanism is provided for performing secure system access by a requesting user without sharing a password of a credential owner. A database stores system information for resources. The owner of super user authority for a resource provides system information to the database including a credential for accessing the resource. When a user wishes to access the system, client software of the requestor sends an access request to client software of the owner. The client software of the owner prompts the owner to authorize or deny access. Responsive to the owner authorizing the access, the client software of the owner returns authorization to the client software of the requestor, which then uses the credential in the system information database to access the resource. The client software of the requestor does not cache or store the credential or present the credential to the user.
Abstract:
Das Verfahren der vorliegenden Erfindung stellt eine automatische und optimierte Auswahl der Netztopologie für die verteilte Steuerung von Jobs auf den Computern der modifizierten Netztopologie bereit. Die automatische und optimierte Auswahl der Netztopologie geht von der aktuellen Topologie und einer gewünschten Anzahl zusätzlicher Verbindungen aus. Auf diese Weise bietet das Verfahren der vorliegenden Erfindung im Vergleich beispielsweise zu einem einfachen Ringnetz eine höhere Konvergenzgeschwindigkeit für den modifizierten Konsensalgorithmus. Das Verfahren bedient sich der so genannten Kleine-Welt-Netzwerke. Kleine-Welt-Netzwerke sind wesentlich störfester als andere Netzarchitekturen. Die bevorzugte Ausführungsart stellt ein Laststeuersystem bereit, das in hohem Maße skalierbar ist und innerhalb einer heterogenen verteilten Rechnerumgebung wachsende Arbeitsbelastungen bewältigt. Es findet ein modifizierter Durchschnittskonsensalgorithmus Anwendung, um Netzwerkverkehr und Jobs auf eine Vielzahl von Computern zu verteilen.
Abstract:
Disclosed is a computer-implemented method of predicting the required number of servers for a future computing workload. The method comprises determining the number of servers in three classes of servers and predicting the future number of servers in the different classes based on a Susceptible-Infected-Recovered-Algorithm. The three classes are, class S are servers that are adapted to deploy the application, class I are servers that deploy the application and class R are servers that are disconnected from the network. The algorithm is based on the deployment rate, un-deployment rate and a removal rate. The deployment rate is the number of servers leaving class S moving to class I, the un-deployment rate is the number of servers leaving class I moving to class S, and the removal rate is the number of servers leaving class I and moving to class R, all in unit time. Such that the total number of servers required in the topology of the computer network in the data centre at a future time t is calculated.