Time Series Analysis
Feedback Control of Computing Systems
Feedback Control of Computing Systems
Low-overhead memory leak detection using adaptive statistical profiling
ASPLOS XI Proceedings of the 11th international conference on Architectural support for programming languages and operating systems
HPCA '05 Proceedings of the 11th International Symposium on High-Performance Computer Architecture
Cork: dynamic memory leak detection for garbage-collected languages
Proceedings of the 34th annual ACM SIGPLAN-SIGACT symposium on Principles of programming languages
C-JDBC: flexible database clustering middleware
ATEC '04 Proceedings of the annual conference on USENIX Annual Technical Conference
Precise memory leak detection for java software using container profiling
Proceedings of the 30th international conference on Software engineering
IT Professional
An adaptive feedback controller for SIP server memory overload protection
ICAC '09 Proceedings of the 6th international conference on Autonomic computing
Automated control in cloud computing: challenges and opportunities
ACDC '09 Proceedings of the 1st workshop on Automated control for datacenters and clouds
Performance model driven QoS guarantees and optimization in clouds
CLOUD '09 Proceedings of the 2009 ICSE Workshop on Software Engineering Challenges of Cloud Computing
Adaptive Distributed Load Balancing Algorithm Based on Live Migration of Virtual Machines in Cloud
NCM '09 Proceedings of the 2009 Fifth International Joint Conference on INC, IMS and IDC
A Comparative Experiment in Distributed Load Balancing
DESE '09 Proceedings of the 2009 Second International Conference on Developments in eSystems Engineering
CLOUD '10 Proceedings of the 2010 IEEE 3rd International Conference on Cloud Computing
Resource provisioning with budget constraints for adaptive applications in cloud environments
Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing
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We consider a cloud data center in which a set of application servers is hosted. Each server runs in a virtual machine in the cloud, subjected to a session-oriented workload, whereby session data of one server is replicated on other servers for purposes of high availability. In such an environment, we are concerned with the memory resource usage due to the application servers. In particular, our goal is to prevent memory overload by managing the session load admitted to each of the application servers. Little interest has been given to load management in the cloud based on memory usage, although memory is a crucial and valuable resource. We introduce a dynamic memory overload protection solution that is based on adaptive feedback controller techniques. In particular, we have designed and implemented a self-configurable memory controller, which is automatically tuned based on an analytical model of the system under control. Our proposed solution consists of a set of independent controllers and, hence, is a scalable architecture. Challenged by actual correlation among application servers due to session replication, we validate our solution on commercially available servers in the cloud environment. Our experimental results illustrate good performance in the presence of load fluctuations and session replication.