Competitive proportional resource allocation policy for computational grid

Li, Chunlin; Layuan, Li

doi:10.1016/j.future.2003.11.029

Cited by 53 publications

(24 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is a simple rule commonly used in semiconductor manufacturing (Mallik and Harker, 2004), computing resources (Li and Li, 2004), and communication networks (Kelly, 1997 …”

Section: Capacity Allocation Gamementioning

confidence: 99%

Modeling Bounded Rationality in Capacity Allocation Games with the Quantal Response Equilibrium

2012

View full text Add to dashboard Cite

We consider a supply chain with a single supplier and two retailers. The retailers choose their orders strategically, and if their orders exceed the supplier's capacity, quantities are allocated proportionally to the orders. We experimentally study the capacity allocation game using subjects motivated by financial incentives. We find that the Nash equilibrium, which assumes that players are perfectly rational, substantially exaggerates retailers' tendency to strategically order more than they need. We propose a model of bounded rationality based on the quantal response equilibrium, in which players are not perfect optimizers and they face uncertainty in their opponents' actions. We structurally estimate model parameters using the maximumlikelihood method. Our results confirm that retailers exhibit bounded rationality, become more rational through repeated game play, but may not converge to perfect rationality as assumed by the Nash equilibrium. Finally, we consider several alternative behavioral theories and show that they do not explain our experimental data as well as our bounded rationality model. Abstract:We consider a supply chain with a single supplier and two retailers. The retailers choose their orders strategically and if their orders exceed the supplier's capacity, quantities are allocated proportionally to the orders. We experimentally study the capacity allocation game using subjects motivated by financial incentives. We find that the Nash Equilibrium, which assumes that players are perfectly rational, substantially exaggerates retailers' tendency to strategically order more than they need.We propose a model of bounded rationality based on the Quantal Response Equilibrium, in which players are not perfect optimizers and they face uncertainty in their opponents' actions. We structurally estimate model parameters using the maximum likelihood method. Our results confirm that retailers exhibit bounded rationality, become more rational through repeated game play, but may not converge to perfect rationality as assumed by the Nash equilibrium. Finally, we consider several alternative behavioral theories and show that they do not explain our experimental data as well as our bounded rationality model.

show abstract

“…This is a simple rule commonly used in semiconductor manufacturing (Mallik and Harker, 2004), computing resources (Li and Li, 2004), and communication networks (Kelly, 1997 …”

Section: Capacity Allocation Gamementioning

confidence: 99%

Modeling Bounded Rationality in Capacity Allocation Games with the Quantal Response Equilibrium

2012

View full text Add to dashboard Cite

show abstract

“…In this paper, a market-based mechanism is proposed, which uses a three layer system model [79]. The lower layer is composed of Grid resources that are owned and allocated by Grid resource agents residing at the nodes within the system.…”

Section: Price Directed Proportional Resource Allocation Mechanismmentioning

confidence: 99%

Survey on Grid Resource Allocation Mechanisms

et al. 2014

View full text Add to dashboard Cite

Grid is a distributed high performance computing paradigm that offers various types of resources (like computing, storage, communication) to resource-intensive user tasks. These tasks are scheduled to allocate available Grid resources efficiently to achieve high system throughput and to satisfy A. Y. Zomaya University of Sydney, Sydney, Australia user requirements. The task scheduling problem has become more complex with the ever increasing size of Grid systems. Even though selecting an efficient resource allocation strategy for a particular task helps in obtaining a desired level of service, researchers still face difficulties in choosing a suitable technique from a plethora of existing methods in literature. In this paper, we explore and discuss existing resource allocation mechanisms for resource allocation problems employed in Grid systems. The work comprehensively surveys Gird resource allocation mechanisms for different architectures (centralized, distributed, static or dynamic). The paper also compares these resource allocation mechanisms based on their common features such as time complexity, searching mechanism, allocation strategy, optimality, operational environment and objective function they adopt for solving computing-and data-intensive applications. The comprehensive analysis of cutting-edge research in the Grid domain presented in this work provides readers with an understanding of essential concepts of resource allocation mechanisms in Grid systems and helps them identify important and outstanding issues for further investigation. It also helps readers to choose the most appropriate mechanism for a given system/application.

show abstract

“…More importantly they are geographically distributed with different time zones. To manage such complex grid environments, market is appropriate because once a currency exchange protocol is established, negotiations can occur simultaneously at various nodes without the necessity of a central authority [20]. Therefore, we explore the usage of an economics-based paradigm for managing resource allocation in computational grid environment.…”

Section: Backgrounds and Motivationmentioning

confidence: 99%