Scheduling to Minimize Power Consumption using Submodular Functions
We develop logarithmic approximation algorithms for extremely general formulations of multiprocessor multi-interval offline task scheduling to minimize power usage. Here each processor has an arbitrary specified power consumption to be turned on for each possible time interval, and each job has a sp...
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Association for Computing Machinery (ACM)
2012
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| Online Access: | http://hdl.handle.net/1721.1/72589 https://orcid.org/0000-0003-3803-5703 |
| _version_ | 1811090730988339200 |
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| author | Demaine, Erik D. Zadimoghaddam, Morteza |
| author2 | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science |
| author_facet | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Demaine, Erik D. Zadimoghaddam, Morteza |
| author_sort | Demaine, Erik D. |
| collection | MIT |
| description | We develop logarithmic approximation algorithms for extremely general formulations of multiprocessor multi-interval offline task scheduling to minimize power usage. Here each processor has an arbitrary specified power consumption to be turned on for each possible time interval, and each job has a specified list of time interval/processor pairs during which it could be scheduled. (A processor need not be in use for an entire interval it is turned on.) If there is a feasible schedule, our algorithm finds a feasible schedule with total power usage within an O(log n) factor of optimal, where n is the number of jobs.(Even in a simple setting with one processor, the problem is Set-Cover hard.) If not all jobs can be scheduled and each job has a specified value, then our algorithm finds a schedule of value at least (1-ε) Z and power usage within an O(log(1/ε)) factor of the optimal schedule of value at least Z, for any specified Z and ε > 0. At the foundation of our work is a general framework for logarithmic approximation to maximizing any submodular function subject to budget constraints. |
| first_indexed | 2024-09-23T14:51:04Z |
| format | Article |
| id | mit-1721.1/72589 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T14:51:04Z |
| publishDate | 2012 |
| publisher | Association for Computing Machinery (ACM) |
| record_format | dspace |
| spelling | mit-1721.1/725892022-10-01T22:54:24Z Scheduling to Minimize Power Consumption using Submodular Functions Demaine, Erik D. Zadimoghaddam, Morteza Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Demaine, Erik D. Demaine, Erik D. Zadimoghaddam, Morteza We develop logarithmic approximation algorithms for extremely general formulations of multiprocessor multi-interval offline task scheduling to minimize power usage. Here each processor has an arbitrary specified power consumption to be turned on for each possible time interval, and each job has a specified list of time interval/processor pairs during which it could be scheduled. (A processor need not be in use for an entire interval it is turned on.) If there is a feasible schedule, our algorithm finds a feasible schedule with total power usage within an O(log n) factor of optimal, where n is the number of jobs.(Even in a simple setting with one processor, the problem is Set-Cover hard.) If not all jobs can be scheduled and each job has a specified value, then our algorithm finds a schedule of value at least (1-ε) Z and power usage within an O(log(1/ε)) factor of the optimal schedule of value at least Z, for any specified Z and ε > 0. At the foundation of our work is a general framework for logarithmic approximation to maximizing any submodular function subject to budget constraints. 2012-09-10T14:53:19Z 2012-09-10T14:53:19Z 2010-06 Article http://purl.org/eprint/type/ConferencePaper 978-1-4503-0079-7 http://hdl.handle.net/1721.1/72589 Erik D. Demaine and Morteza Zadimoghaddam. 2010. Scheduling to minimize power consumption using submodular functions. In Proceedings of the 22nd ACM symposium on Parallelism in algorithms and architectures (SPAA '10). ACM, New York, NY, USA, 21-29. https://orcid.org/0000-0003-3803-5703 en_US http://dx.doi.org/10.1145/1810479.1810483 Proceedings of the 22nd ACM Symposium on Parallelism in Algorithms and Architectures (SPAA '10) Creative Commons Attribution-Noncommercial-Share Alike 3.0 http://creativecommons.org/licenses/by-nc-sa/3.0/ application/pdf Association for Computing Machinery (ACM) MIT web domain |
| spellingShingle | Demaine, Erik D. Zadimoghaddam, Morteza Scheduling to Minimize Power Consumption using Submodular Functions |
| title | Scheduling to Minimize Power Consumption using Submodular Functions |
| title_full | Scheduling to Minimize Power Consumption using Submodular Functions |
| title_fullStr | Scheduling to Minimize Power Consumption using Submodular Functions |
| title_full_unstemmed | Scheduling to Minimize Power Consumption using Submodular Functions |
| title_short | Scheduling to Minimize Power Consumption using Submodular Functions |
| title_sort | scheduling to minimize power consumption using submodular functions |
| url | http://hdl.handle.net/1721.1/72589 https://orcid.org/0000-0003-3803-5703 |
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