公开(公告)号：US20240314747A1

公开(公告)日：2024-09-19

申请号：US18323126

申请日：2023-05-24

申请人： Microsoft Technology Licensing, LLC

发明人： Behnaz ARZANI ,  Pooria NAMYAR ,  Srikanth KANDULA ,  Umesh KRISHNASWAMY ,  Himanshu RAJ ,  Santiago Martin SEGARRA ,  Daniel Stopol CRANKSHAW

IPC分类号： H04W72/044 ,  H04W72/512

CPC分类号： H04W72/044 ,  H04W72/512

摘要： A method for allocating a plurality of network resources to a plurality of network-access demands of a plurality of network guests comprises (a) receiving the plurality of network-access demands; (b) for each of the plurality of network-access demands (i) dynamically computing, from among the plurality of network resources, a resorted order of resources associated with the network-access demand, and (ii) for each network resource associated with the network-access demand, increasing, in the re-sorted order, an allocation of the network resource to the network-access demand until the network-access demand is saturated, and freezing the allocation of each of the plurality of network resources to the saturated demand; and (c) outputting the frozen allocation of each of the plurality of network resources for each of the plurality of network-access demands.

公开(公告)号：US20240080255A1

公开(公告)日：2024-03-07

申请号：US17929503

申请日：2022-09-02

申请人： Microsoft Technology Licensing, LLC

发明人： Behnaz ARZANI ,  Pooria NAMYAR ,  Ryan Andrew BECKETT ,  Srikanth KANDULA ,  Santiago Martin SEGARRA ,  Himanshu RAJ

IPC分类号： H04L45/02

CPC分类号： H04L45/08

摘要： A computing device is provided, including a processor that receives a network graph. The processor further receives a specification of a network traffic control heuristic for a network traffic routing problem over the network graph. The processor further constructs a gap maximization problem that has, as a maximization target, a difference between an exact solution to the network traffic routing problem and a heuristic solution generated using the network traffic control heuristic. The processor further generates a Lagrange multiplier formulation of the gap maximization problem. At a convex solver, the processor further computes an estimated maximum gap as an estimated solution to the Lagrange multiplier formulation of the gap maximization problem. The processor further performs a network traffic control action based at least in part on the estimated maximum gap.