Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Modelling Producer/Consumer Constraints
CP '95 Proceedings of the First International Conference on Principles and Practice of Constraint Programming
Entropy: a consolidation manager for clusters
Proceedings of the 2009 ACM SIGPLAN/SIGOPS international conference on Virtual execution environments
Algorithmica
Search spaces for min-perturbation repair
CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
A constraint programming approach for the service consolidation problem
CPAIOR'10 Proceedings of the 7th international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
An energy aware framework for virtual machine placement in cloud federated data centres
Proceedings of the 3rd International Conference on Future Energy Systems: Where Energy, Computing and Communication Meet
Weibull-Based benchmarks for bin packing
CP'12 Proceedings of the 18th international conference on Principles and Practice of Constraint Programming
A scalable sweep algorithm for the cumulative constraint
CP'12 Proceedings of the 18th international conference on Principles and Practice of Constraint Programming
Modeling response times in the Google ROADEF/EURO challenge
ACM SIGMETRICS Performance Evaluation Review
Higher SLA satisfaction in datacenters with continuous VM placement constraints
Proceedings of the 9th Workshop on Hot Topics in Dependable Systems
UCC '13 Proceedings of the 2013 IEEE/ACM 6th International Conference on Utility and Cloud Computing
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A datacenter can be viewed as a dynamic bin packing system where servers host applications with varying resource requirements and varying relative placement constraints. When those needs are no longer satisfied, the system has to be reconfigured. Virtualization allows to distribute applications into Virtual Machines (VMs) to ease their manipulation. In particular, a VM can be freely migrated without disrupting its service, temporarily consuming resources both on its origin and destination. We introduce the Bin Repacking Scheduling Problem in this context. This problem is to find a final packing and to schedule the transitions from a given initial packing, accordingly to new resource and placement requirements, while minimizing the average transition completion time. Our CP-based approach is implemented into Entropy, an autonomous VM manager which detects reconfiguration needs, generates and solves the CP model, then applies the computed decision. CP provides the awaited flexibility to handle heterogeneous placement constraints and the ability to manage large datacenters with up to 2,000 servers and 10,000 VMs.