Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Automatically classifying database workloads
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Value-based scheduling in real-time database systems
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
Handbook of Scheduling: Algorithms, Models, and Performance Analysis
Handbook of Scheduling: Algorithms, Models, and Performance Analysis
Balancing Risk and Reward in a Market-Based Task Service
HPDC '04 Proceedings of the 13th IEEE International Symposium on High Performance Distributed Computing
SLA based profit optimization in autonomic computing systems
Proceedings of the 2nd international conference on Service oriented computing
Web server QoS models: applying scheduling rules from production planning
Computers and Operations Research
Profitable services in an uncertain world
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Efficient scheduling of heterogeneous continuous queries
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Understanding internet video sharing site workload: a view from data center design
Proceedings of the 17th international conference on World Wide Web
Column-stores vs. row-stores: how different are they really?
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Performance Analysis of Queuing and Computer Networks (Chapman & Hall/Crc Computer & Information Science Series)
Fair, effective, efficient and differentiated scheduling in an enterprise data warehouse
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Predicting Multiple Metrics for Queries: Better Decisions Enabled by Machine Learning
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Resilient workload manager: taming bursty workload of scaling internet applications
ICAC '09 Proceedings of the 6th international conference on Autonomic computing
Rethinking cost and performance of database systems
ACM SIGMOD Record
An evaluation of alternative architectures for transaction processing in the cloud
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Extreme scale with full SQL language support in microsoft SQL Azure
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
iCBS: incremental cost-based scheduling under piecewise linear SLAs
Proceedings of the VLDB Endowment
Performance evaluation of scheduling algorithms for database services with soft and hard SLAs
Proceedings of the second international workshop on Data intensive computing in the clouds
Scalable real time data management for smart grid
Proceedings of the Middleware 2011 Industry Track Workshop
A mechanism to measure quality-of-service in a federated cloud environment
Proceedings of the 2012 workshop on Cloud services, federation, and the 8th open cirrus summit
PMAX: tenant placement in multitenant databases for profit maximization
Proceedings of the 16th International Conference on Extending Database Technology
A platform for seamless context transfers in the mobile cloud
Proceedings of the 12th International ACM Workshop on Data Engineering for Wireless and Mobile Acess
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As cloud computing becomes increasingly important in database systems, many new challenges and opportunities have arisen. One challenge is that in cloud computing, business profit plays a central role. Hence, it is very important for a cloud service provider to quickly make profit-oriented decisions. In this paper, we propose a novel data structure, called SLA-tree, to efficiently support profit-oriented decision making. SLA-tree is built on two pieces of information: (1) a set of buffered queries waiting to be executed, which represents the scheduled events that will happen in the near future, and (2) a service level agreement (SLA) for each query, which indicates the different profits for the query for varying query response times. By constructing the SLA-tree, we efficiently support the answering of certain profit-oriented "what if" questions. Answers to these questions in turn can be applied to different profit-oriented decisions in cloud computing such as profit-aware scheduling, dispatching, and capacity planning. Extensive experimental results based on both synthetic and real-world data demonstrate the effectiveness and efficiency of our SLA-tree framework.