Distributed resource allocation

A resource allocation and resource technology, applied in resource allocation, multi-program device, program control design, etc., can solve problems such as consumption, excessive computing resources and time

Pending Publication Date: 2020-12-25
ADVANCED NEW TECH CO LTD
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  • Abstract
  • Description
  • Claims
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Problems solved by technology

Existing resource allocation solutions perform poorly at such large scales as they consume excessive computational resources and time

Method used

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Embodiment Construction

[0029] This article describes techniques for resource allocation. These techniques generally involve solving the large-scale knapsack problem (KP) in a scalable distributed paradigm via synchronized coordinate descent (SCD). In some embodiments, the described techniques can help solve the knapsack problem on a scale of billions or more with multiple global constraints. In some embodiments, the described techniques can help solve such large-scale knapsack problems without compromising the optimality of the solution or violating constraints. In some embodiments, techniques may be implemented using off-the-shelf distributed computing frameworks (eg, MPI, Hadoop, Spark). In some embodiments, these techniques can save storage space, reduce computational complexity, and improve the speed of solving the knapsack problem. In some embodiments, these techniques can solve resource allocation problems on an unprecedented scale (e.g., the knapsack problem with billions of decision and co...

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Abstract

Disclosed methods, systems, and apparatus, include computer programs encoded on computer storage media, for performing allocation of M resources among N users into K pools by solving a knapsack problem (KP) using a distributed computing system. The method includes: receiving data representing K global constraints and L local constraints of the KP; transforming the KP into a dual problem using K dual multipliers; decomposing the dual problem into N sub-problems; performing two or more iterations in solving the dual problem, wherein in one iteration, for each dual multiplier corresponding to a global constraint corresponding to a pool: determining an updated dual multiplier for the global constraint corresponding to the pool to be a non-negative threshold; and computing M decision variablesof each of the N users corresponding to the updated dual multiplier in solving each of the N sub-problems corresponding to the each of the N users.

Description

technical field [0001] This article deals with resource allocation. Background technique [0002] The knapsack problem (KP) can often be used to model resource allocation applications in real-world decision-making processes. Examples of knapsack problems include asset management, portfolio selection, and budget allocation, among others. For example, solve the knapsack problem to determine the amount of notifications per user to optimize long-term user engagement. Real-world resource allocation applications are often achieved by solving the knapsack problem, but they are only tractable at relatively small scales. Several variants of the knapsack problem have been studied in the literature, such as the multidimensional knapsack problem (MDKP), the multiple option knapsack problem (MCKP), and the multidimensional multiple option knapsack problem (MMKP). In MDKP, there are multiple backpack constraints and resource items (also called items), which when selected will consume r...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F9/50
CPCG06F17/11G06F9/3891G06F9/5011G06F2209/5011G06F17/12G06F9/5061
Inventor 张兴文奇峰华致刚杨双红
Owner ADVANCED NEW TECH CO LTD
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