Stochastic Resource Allocation for Energy-Constrained Systems
<p/> <p>Battery-powered wireless systems running media applications have tight constraints on energy, CPU, and network capacity, and therefore require the careful allocation of these limited resources to maximize the system's performance while avoiding resource overruns. Usually, re...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2009-01-01
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| Series: | EURASIP Journal on Wireless Communications and Networking |
| Online Access: | http://jwcn.eurasipjournals.com/content/2009/246439 |
| _version_ | 1811292642676310016 |
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| author | Sachs DanielGrobe Jones DouglasL |
| author_facet | Sachs DanielGrobe Jones DouglasL |
| author_sort | Sachs DanielGrobe |
| collection | DOAJ |
| description | <p/> <p>Battery-powered wireless systems running media applications have tight constraints on energy, CPU, and network capacity, and therefore require the careful allocation of these limited resources to maximize the system's performance while avoiding resource overruns. Usually, resource-allocation problems are solved using standard knapsack-solving techniques. However, when allocating <it>conservable</it> resources like energy (which unlike CPU and network remain available for later use if they are not used immediately) knapsack solutions suffer from excessive computational complexity, leading to the use of suboptimal heuristics. We show that use of Lagrangian optimization provides a fast, elegant, and, for convex problems, optimal solution to the allocation of energy across applications as they enter and leave the system, even if the exact sequence and timing of their entrances and exits is not known. This permits significant increases in achieved utility compared to heuristics in common use. As our framework requires only a stochastic description of future workloads, and not a full schedule, we also significantly expand the scope of systems that can be optimized.</p> |
| first_indexed | 2024-04-13T04:49:22Z |
| format | Article |
| id | doaj.art-0c7c2a999d7e40598616a5910039e26a |
| institution | Directory Open Access Journal |
| issn | 1687-1472 1687-1499 |
| language | English |
| last_indexed | 2024-04-13T04:49:22Z |
| publishDate | 2009-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Wireless Communications and Networking |
| spelling | doaj.art-0c7c2a999d7e40598616a5910039e26a2022-12-22T03:01:44ZengSpringerOpenEURASIP Journal on Wireless Communications and Networking1687-14721687-14992009-01-0120091246439Stochastic Resource Allocation for Energy-Constrained SystemsSachs DanielGrobeJones DouglasL<p/> <p>Battery-powered wireless systems running media applications have tight constraints on energy, CPU, and network capacity, and therefore require the careful allocation of these limited resources to maximize the system's performance while avoiding resource overruns. Usually, resource-allocation problems are solved using standard knapsack-solving techniques. However, when allocating <it>conservable</it> resources like energy (which unlike CPU and network remain available for later use if they are not used immediately) knapsack solutions suffer from excessive computational complexity, leading to the use of suboptimal heuristics. We show that use of Lagrangian optimization provides a fast, elegant, and, for convex problems, optimal solution to the allocation of energy across applications as they enter and leave the system, even if the exact sequence and timing of their entrances and exits is not known. This permits significant increases in achieved utility compared to heuristics in common use. As our framework requires only a stochastic description of future workloads, and not a full schedule, we also significantly expand the scope of systems that can be optimized.</p>http://jwcn.eurasipjournals.com/content/2009/246439 |
| spellingShingle | Sachs DanielGrobe Jones DouglasL Stochastic Resource Allocation for Energy-Constrained Systems EURASIP Journal on Wireless Communications and Networking |
| title | Stochastic Resource Allocation for Energy-Constrained Systems |
| title_full | Stochastic Resource Allocation for Energy-Constrained Systems |
| title_fullStr | Stochastic Resource Allocation for Energy-Constrained Systems |
| title_full_unstemmed | Stochastic Resource Allocation for Energy-Constrained Systems |
| title_short | Stochastic Resource Allocation for Energy-Constrained Systems |
| title_sort | stochastic resource allocation for energy constrained systems |
| url | http://jwcn.eurasipjournals.com/content/2009/246439 |
| work_keys_str_mv | AT sachsdanielgrobe stochasticresourceallocationforenergyconstrainedsystems AT jonesdouglasl stochasticresourceallocationforenergyconstrainedsystems |