Ciena Corporation

Marc Lyonnais

Gauravdeep Singh Shami

Rodney G Wilson

Abdullah Bittar

Ziqiang Wang

Systems and methods are provided for predicting how tasks should be allocated to available network resources. A method, according to one implementation, includes the step of receiving resource utilization metrics from each of a plurality of nodes arranged in a cluster, wherein the resource utilization metrics of each node include information related to utilization of one or more resources of the respective node over a plurality of time periods. The method also includes the step of predicting current and forthcoming resource availability of each node based on patterns of resource utilization over past and current time periods. In response to receiving a job request having multiple workload responsibilities, the method includes the step of allocating the workload responsibilities to one or more nodes based on the predicted current and forthcoming resource availability of each node in order to fulfill the job request.

Predictive resource allocation and scheduling for a distributed workload

Systems and methods for creating and updating data transfer strategies for massive amounts of data are provided. A method, according to one implementation, includes obtaining a first set of parameters pertaining to a data source configured as a first node in a communications system, obtaining a second set of parameters pertaining to a data sink configured as a second node in the communications system, and obtaining a third set of parameters pertaining to a plurality of network elements and links configured along one or more data paths between the data source and data sink. The method also includes the step of automatically creating a high-bandwidth data transfer strategy for transferring a massive amount of data from the data source to the data sink based on the first, second, and third sets of parameters.

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Ottawa, Canada

Marc Lyonnais