2,913 research outputs found
An Efficient Decomposition Algorithm for Large-Scale Network Slicing
In this paper, we consider the network slicing (NS) problem which attempts to
map multiple customized virtual network requests to a common shared network
infrastructure and allocate network resources to meet diverse service
requirements. We propose an efficient decomposition algorithm for solving this
NP-hard problem. The proposed algorithm decomposes the large-scale hard NS
problem into two relatively easy function placement (FP) and traffic routing
(TR) subproblems and iteratively solves them enabling information feedback
between each other, which makes it particularly suitable to solve large-scale
problems. Specifically, the FP subproblem is to place service functions into
cloud nodes in the network, and solving it can return a function placement
strategy based on which the TR subproblem is defined; and the TR subproblem is
to find paths connecting two nodes hosting two adjacent functions in the
network, and solving it can either verify that the solution of the FP
subproblem is an optimal solution of the original problem, or return a valid
inequality to the FP subproblem that cuts off the current infeasible solution.
The proposed algorithm is guaranteed to find the global solution of the NS
problem. We demonstrate the effectiveness and efficiency of the proposed
algorithm via numerical experiments.Comment: 5 pages, 4 figures, accepted for publication in IEEE SPAWC 202
Tillage condition effects on soil/plow-breast flow interaction of a horizontally reversible plow
Abstract : The horizontally reversible plow (HRP) is commonly utilized because of higher performances than the regular mold-board plow. Soil/plow surface flow interaction during HRP tillage trends to incur so severe pressure on the plow-breast as to reduce the plow life. This paper numerically characterized the soil/plow-breast flow interaction and subsequently assessed tillage-condition effects on the plow-breast surface. These tillage conditions herein involved tool speed and operation-al depth. The simulations showed that for either tool speed or operational depth the maximum pressure appeared at the plow-shank of the plow-breast and that the soil pressures were increased with them. The computational fluid dynamics (CFD) based predictions qualitatively agreed with the preliminary experimental results at the identified settings with scanning electronic microscopy. Once again, CFD analysis is demonstrated to be feasible and effective enough to provide insight into improve the horizontally reversible plow by predicting real soil behaviors
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