Scheduling under dynamic speed-scaling for minimizing weighted completion time and energy consumption

Since a few years there is an increasing interest in minimizing the energy consumption of computing systems. However in a shared computing system, users want to optimize their experienced quality of service, at the price of a high energy consumption. In this work, we address the problem of optimizing and designing mechanisms for a linear combination of weighted completion time and energy consumption on a single machine with dynamic speed-scaling. We show that minimizing linear combination reduces to a unit speed scheduling problem under a polynomial penalty function. In the mechanism design setting, we define a cost share mechanism and study its properties, showing that it is truthful and the overcharging of total cost share is bounded by a constant.

[1]  H. Varian A Solution to the Problem of Externalities When Agents Are Well-Informed , 1994 .

[2]  An Auction Mechanism for the Commons: Some Extensions , 2007 .

[3]  Kirk Pruhs,et al.  Speed scaling to manage energy and temperature , 2007, JACM.

[4]  Evripidis Bampis,et al.  Energy Aware Scheduling for Unrelated Parallel Machines , 2012, 2012 IEEE International Conference on Green Computing and Communications.

[5]  F. Frances Yao,et al.  A scheduling model for reduced CPU energy , 1995, Proceedings of IEEE 36th Annual Foundations of Computer Science.

[6]  Nicole Megow,et al.  Dual Techniques for Scheduling on a Machine with Varying Speed , 2013, ICALP.

[7]  Erik D. Demaine,et al.  Energy-Efficient Algorithms , 2016, ITCS.

[8]  T. Groves,et al.  Optimal Allocation of Public Goods: A Solution to the 'Free Rider Problem' , 1977 .

[9]  Kirk Pruhs,et al.  Getting the best response for your erg , 2004, TALG.

[10]  Susanne Albers,et al.  Energy-efficient algorithms for flow time minimization , 2006, STACS.

[11]  Sandy Irani,et al.  Algorithmic problems in power management , 2005, SIGA.

[12]  Lap-Kei Lee,et al.  Non-clairvoyant Speed Scaling for Weighted Flow Time , 2010, ESA.

[13]  Christoph Dürr,et al.  Order constraints for single machine scheduling with non-linear cost , 2014, ALENEX.

[14]  Kirk Pruhs,et al.  Improved Bounds for Speed Scaling in Devices Obeying the Cube-Root Rule , 2009, ICALP.

[15]  Lukasz Jez,et al.  Mechanism Design for Aggregating Energy Consumption and Quality of Service in Speed Scaling Scheduling , 2013, WINE.

[16]  John Duggan,et al.  Implementing the Efficient Allocation of Pollution , 2002 .