Amortized efficiency of list update and paging rules
Communications of the ACM
An optimal on-line algorithm for metrical task system
Journal of the ACM (JACM)
A polylog(n)-competitive algorithm for metrical task systems
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Online computation and competitive analysis
Online computation and competitive analysis
Approximation algorithms
Live migration of virtual machines
NSDI'05 Proceedings of the 2nd conference on Symposium on Networked Systems Design & Implementation - Volume 2
A Primal-Dual Randomized Algorithm for Weighted Paging
FOCS '07 Proceedings of the 48th Annual IEEE Symposium on Foundations of Computer Science
The Design of Competitive Online Algorithms via a Primal: Dual Approach
Foundations and Trends® in Theoretical Computer Science
Cutting the electric bill for internet-scale systems
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
Managing the cost, energy consumption, and carbon footprint of internet services
Proceedings of the ACM SIGMETRICS international conference on Measurement and modeling of computer systems
INFOCOM'10 Proceedings of the 29th conference on Information communications
Energy Efficient Resource Management in Virtualized Cloud Data Centers
CCGRID '10 Proceedings of the 2010 10th IEEE/ACM International Conference on Cluster, Cloud and Grid Computing
Optimality analysis of energy-performance trade-off for server farm management
Performance Evaluation
Towards the randomized k-server conjecture: a primal-dual approach
SODA '10 Proceedings of the twenty-first annual ACM-SIAM symposium on Discrete Algorithms
Metrical task systems and the k-server problem on HSTs
ICALP'10 Proceedings of the 37th international colloquium conference on Automata, languages and programming
ACM Journal on Emerging Technologies in Computing Systems (JETC)
Properties of energy-price forecasts for scheduling
CP'12 Proceedings of the 18th international conference on Principles and Practice of Constraint Programming
Proceedings of the ACM SIGMETRICS/international conference on Measurement and modeling of computer systems
SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
ACM SIGMETRICS Performance Evaluation Review - Special issue on the 31st international symposium on computer performance, modeling, measurements and evaluation (IFIPWG 7.3 Performance 2013)
Proceedings of the Ninth IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis
Hi-index | 0.00 |
Energy costs are becoming the fastest-growing element in datacenter operation costs. One basic approach to reduce these costs is to exploit the spatiotemporal variation in electricity prices by moving computation to datacenters in which energy is available at a cheaper price. However, injudicious job migration between datacenters might increase the overall operation cost due to the bandwidth costs of transferring application state and data over the wide-area network. To address this challenge, we propose novel online algorithms for migrating batch jobs between datacenters, which handle the fundamental tradeoff between energy and bandwidth costs. A distinctive feature of our algorithms is that they consider not only the current availability and cost of (possibly multiple) energy sources, but also the future variability and uncertainty thereof. Using the framework of competitive-analysis, we establish worst-case performance bounds for our basic online algorithm. We then propose a practical, easy-to-implement version of the basic algorithm, and evaluate it through simulations on real electricity pricing and job workload data. The simulation results indicate that our algorithm outperforms plausible greedy algorithms that ignore future outcomes. Notably, the actual performance of our approach is significantly better than the theoretical guarantees, within 6% of the optimal offline solution.