Automated SLA Monitoring for Web Services
DSOM '02 Proceedings of the 13th IFIP/IEEE International Workshop on Distributed Systems: Operations and Management: Management Technologies for E-Commerce and E-Business Applications
Improving web server performance by caching dynamic data
USITS'97 Proceedings of the USENIX Symposium on Internet Technologies and Systems on USENIX Symposium on Internet Technologies and Systems
CASCON '08 Proceedings of the 2008 conference of the center for advanced studies on collaborative research: meeting of minds
MACE: A Dynamic Caching Framework for Mashups
ICWS '09 Proceedings of the 2009 IEEE International Conference on Web Services
Dynamic SLA Template Adjustments Based on Service Property Monitoring
CLOUD '09 Proceedings of the 2009 IEEE International Conference on Cloud Computing
Comprehensive QoS monitoring of Web services and event-based SLA violation detection
Proceedings of the 4th International Workshop on Middleware for Service Oriented Computing
Data caching as a cloud service
Proceedings of the 4th International Workshop on Large Scale Distributed Systems and Middleware
Elastic Cloud Caches for Accelerating Service-Oriented Computations
Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis
Workload analysis of a large-scale key-value store
Proceedings of the 12th ACM SIGMETRICS/PERFORMANCE joint international conference on Measurement and Modeling of Computer Systems
Online Scheduling for Cloud Computing and Different Service Levels
IPDPSW '12 Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum
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Cloud computing encourages application to migrate into it for economic of scale, where they rent shared resources to deliver services. Service Level Agreements(SLA) plays an important role in assisting various applications providing high-quality services to end users in cloud's complex and uncertain environments. Most of the existing work tries to support application claimed quality by help cloud make decisions of computing resources allocation during runtime. In this paper, we propose an approach for applications to maintain quality requirements by runtime cache adjustment in consideration of service level objectives (SLOs) and unpredictable workload in cloud, which can be taken as a complement to the existing work. Our approach includes application SLO modeling and mapping to monitor metrics during runtime, and an algorithm to adapting caches according to runtime status and SLOs. The approach has been applied to a real-world SNS application which proves effectiveness of our approach.