A Microeconomic Approach to Optimal Resource Allocation in Distributed Computer Systems
IEEE Transactions on Computers
Spawn: A Distributed Computational Economy
IEEE Transactions on Software Engineering
Economic models for allocating resources in computer systems
Market-based control
Mariposa: a wide-area distributed database system
The VLDB Journal — The International Journal on Very Large Data Bases
User-Centric Performance Analysis of Market-Based Cluster Batch Schedulers
CCGRID '02 Proceedings of the 2nd IEEE/ACM International Symposium on Cluster Computing and the Grid
Market-based Proportional Resource Sharing for Clusters
Market-based Proportional Resource Sharing for Clusters
The application of microeconomics to the design of resource allocation and control algorithms
The application of microeconomics to the design of resource allocation and control algorithms
The utility business model and the future of computing services
IBM Systems Journal
Libra: a computational economy-based job scheduling system for clusters
Software—Practice & Experience
Balancing Risk and Reward in a Market-Based Task Service
HPDC '04 Proceedings of the 13th IEEE International Symposium on High Performance Distributed Computing
OnCall: Defeating Spikes with a Free-Market Application Cluster
ICAC '04 Proceedings of the First International Conference on Autonomic Computing
Profitable services in an uncertain world
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Markets are dead, long live markets
ACM SIGecom Exchanges
Tycoon: An implementation of a distributed, market-based resource allocation system
Multiagent and Grid Systems
A break in the clouds: towards a cloud definition
ACM SIGCOMM Computer Communication Review
The Proportional-Share Allocation Market for Computational Resources
IEEE Transactions on Parallel and Distributed Systems
Tradeoffs Between Profit and Customer Satisfaction for Service Provisioning in the Cloud
Proceedings of the 20th international symposium on High performance distributed computing
Ontology-based resource management for cloud computing
ACIIDS'11 Proceedings of the Third international conference on Intelligent information and database systems - Volume Part II
Profit-driven scheduling for cloud services with data access awareness
Journal of Parallel and Distributed Computing
SLA-based admission control for a Software-as-a-Service provider in Cloud computing environments
Journal of Computer and System Sciences
SLA - driven dynamic resource allocation on clouds
ADCONS'11 Proceedings of the 2011 international conference on Advanced Computing, Networking and Security
A coordinator for scaling elastic applications across multiple clouds
Future Generation Computer Systems
Optimal resource provisioning for cloud computing environment
The Journal of Supercomputing
Configurable performance analysis and evaluation framework for cloud systems
International Journal of Information and Communication Technology
Scheduling data processing flows under budget constraint on the cloud
Proceedings of the 2013 Research in Adaptive and Convergent Systems
SLA-driven dynamic capacity forecasting and resource allocation with risk analysis on clouds
International Journal of Communication Networks and Distributed Systems
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A primary driving force of the recent cloud computing paradigm is its inherent cost effectiveness. As in many basic utilities, such as electricity and water, consumers/clients in cloud computing environments are charged based on their service usage, hence the term ‘pay-per-use’. While this pricing model is very appealing for both service providers and consumers, fluctuating service request volume and conflicting objectives (e.g., profit vs. response time) between providers and consumers hinder its effective application to cloud computing environments. In this paper, we address the problem of service request scheduling in cloud computing systems. We consider a three-tier cloud structure, which consists of infrastructure vendors, service providers and consumers, the latter two parties are particular interest to us. Clearly, scheduling strategies in this scenario should satisfy the objectives of both parties. Our contributions include the development of a pricing model—using processor-sharing—for clouds, the application of this pricing model to composite services with dependency consideration (to the best of our knowledge, the work in this study is the first attempt), and the development of two sets of profit-driven scheduling algorithms.