Dynamic resource allocation for shared data centers using online measurements
SIGMETRICS '03 Proceedings of the 2003 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
An analytical model for multi-tier internet services and its applications
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Utility Functions in Autonomic Systems
ICAC '04 Proceedings of the First International Conference on Autonomic Computing
Dynamic Provisioning of Multi-tier Internet Applications
ICAC '05 Proceedings of the Second International Conference on Automatic Computing
Resource Allocation for Autonomic Data Centers using Analytic Performance Models
ICAC '05 Proceedings of the Second International Conference on Automatic Computing
Provisioning servers in the application tier for e-commerce systems
ACM Transactions on Internet Technology (TOIT)
Tycoon: An implementation of a distributed, market-based resource allocation system
Multiagent and Grid Systems
Model-based resource provisioning in a web service utility
USITS'03 Proceedings of the 4th conference on USENIX Symposium on Internet Technologies and Systems - Volume 4
Agile dynamic provisioning of multi-tier Internet applications
ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Generating Adaptation Policies for Multi-tier Applications in Consolidated Server Environments
ICAC '08 Proceedings of the 2008 International Conference on Autonomic Computing
The complexity of computing a Nash equilibrium
Communications of the ACM - Inspiring Women in Computing
Colocation games: and their application to distributed resource management
HotCloud'09 Proceedings of the 2009 conference on Hot topics in cloud computing
A game-theoretic method of fair resource allocation for cloud computing services
The Journal of Supercomputing
A Cost-Aware Elasticity Provisioning System for the Cloud
ICDCS '11 Proceedings of the 2011 31st International Conference on Distributed Computing Systems
Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference
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Cloud computing is a newly emerging reliable and scalable paradigm in which customers pay for cloud resources they use on demand. However, current auto-scaling mechanisms in cloud lack the critical self-adaption policy which helps application providers decide on when and how to reallocate resources. Furthermore, virtualization techniques can not ensure an absolute isolation between multiple virtual machines sharing the same physical resource, which leads to some customers paying unfairly for heavy-loaded resource under a widely-adopted fixed pricing scheme. In this paper, we present a global performance-to-price model based on game theory, in which each application is considered as a selfish player attempting to guarantee QoS requirements and simultaneously minimize the resource cost. Then we apply the idea of Nash equilibrium to obtain the appropriate allocation, and an approximated solution is proposed to obtain the Nash equilibrium, ensuring that each player is charged fairly for their desired performance. First, each player maximizes its utility independently without considering the placement of virtual machines. Then based on the initial allocation, each player reaches its optimal placement solely without considering others' interference. Finally we propose an evolutionary algorithm which step by step updates the global resource allocation based on the initial optimal allocation and placement.