Introducing a Distributed Cloud Architecture with Efficient Resource Discovery and Optimal Resource Allocation

Author(s):  
Praveen Khethavath ◽  
Johnson Thomas ◽  
Eric Chan-Tin ◽  
Hong Liu
2010 ◽  
Vol 29-32 ◽  
pp. 1100-1108
Author(s):  
Jun Xie ◽  
Ji Guang Li

The paper presents a market oriented resource allocation strategy for grid resource. The proposed model uses the utility functions for calculating the utility of a resource allocation. This paper is target to solve above issues by using utility-based optimization scheme. We firstly point out the factors that influence the resources’ prices; then make out the trading flow for resource consumer agents and provider agents. By doing these, the two trading agents can decide their price due to the dynamic changes of the Grid environment without any manmade interferences. Total user benefit of the computational grid is maximized when the equilibrium prices are obtained through the consumer’s market optimization and provider’s market optimization. The economic model is the basis of an iterative algorithm that, given a finite set of requests, is used to perform optimal resource allocation.


Algorithms ◽  
2020 ◽  
Vol 13 (3) ◽  
pp. 55
Author(s):  
Natsumi Oyamaguchi ◽  
Hiroyuki Tajima ◽  
Isamu Okada

Although exploring the principles of resource allocation is still important in many fields, little is known about appropriate methods for optimal resource allocation thus far. This is because we should consider many issues including opposing interests between many types of stakeholders. Here, we develop a new allocation method to resolve budget conflicts. To do so, we consider two points—minimizing assessment costs and satisfying allocational efficiency. In our method, an evaluator’s assessment is restricted to one’s own projects in one’s own department, and both an executive’s and mid-level executives’ assessments are also restricted to each representative project in each branch or department they manage. At the same time, we develop a calculation method to integrate such assessments by using a multi-branch tree structure, where a set of leaf nodes represents projects and a set of non-leaf nodes represents either directors or executives. Our method is incentive-compatible because no director has any incentive to make fallacious assessments.


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