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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 conservable 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.
Yuan W, Nahrstedt K, Adve SV, Jones DL, Kravets RH: Design and evaluation of a cross-layer adaptation framework for mobile multimedia systems. Multimedia Computing and Networking, January 2003, Proceedings of SPIE 5019: 1-13.
Moser M, Jokanovic D, Shiratori N: An algorithm for the multidimensional multiple-choice knapsack problem. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences 1997, 80(3):582-589.
Lee C, Lehoczky J, Siewiorek D, Rajkumar R, Hansen J: A scalable solution to the multi-resource QoS problem. Proceedings of the 20th IEEE Real-Time Systems Symposium, December 1999 315-326.
Yuan W, Nahrstedt K: ReCalendar: calendaring and scheduling applications with CPU and energy resource guarantees for mobile devices. Proceedings of the IEEE Pervasive Computing and Communications (PerCom '03), March 2003
Krongold BS, Ramchandran K, Jones DL: Computationally efficient optimal power allocation algorithms for multicarrier communication systems. IEEE Transactions on Communications 2000, 48(1):23-27. 10.1109/26.818869 CrossRef
Ramchandran K, Vetterli M: Best wavelet packet bases in a rate-distortion sense. IEEE Transactions on Image Processing 1993, 2(2):160-175. 10.1109/83.217221 CrossRef
Kelly F: Charging and rate control for elastic traffic. European Transactions on Telecommunications 1997, 8(1):33-37. 10.1002/ett.4460080106 CrossRef
Goel M, Shanbhag NR: Dynamic algorithm transforms for low-power reconfigurable adaptive equalizers. IEEE Transactions on Signal Processing 1999, 47(10):2821-2832. 10.1109/78.790662 CrossRef
Vardhan V, et al.: Integrating fine-grained application adaptation with global adaptation for saving energy. Proceedings of the 2nd International Workshop on Power-Aware Real-Time Computing (PARC '05), September 2005, Jersey City, NJ, USA
Sachs DG: A new framework for hierarchical cross-layer adaptation, Ph.D. dissertation. University of Illinois at Urbana-Champaign, Urbana-Champaign, Ill, USA; May 2006.
Sachs DG, Adve SV, Jones DL: Cross-layer adaptive video coding to reduce energy on general-purpose processors. Proceedings of IEEE International Conference on Image Processing, September 2003, Barcelona, Spain 3: 109-112.
- Stochastic Resource Allocation for Energy-Constrained Systems
Douglas L. Jones
- Springer International Publishing
EURASIP Journal on Wireless Communications and Networking
Elektronische ISSN: 1687-1499
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