Voltage scheduling problem for dynamically variable voltage processors
ISLPED '98 Proceedings of the 1998 international symposium on Low power electronics and design
Energy efficient fixed-priority scheduling for real-time systems on variable voltage processors
Proceedings of the 38th annual Design Automation Conference
Proceedings of the 14th international symposium on Systems synthesis
Task scheduling and voltage selection for energy minimization
Proceedings of the 39th annual Design Automation Conference
A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Energy-Efficient Mapping and Scheduling for DVS Enabled Distributed Embedded Systems
Proceedings of the conference on Design, automation and test in Europe
Proceedings of the conference on Design, automation and test in Europe - Volume 1
Scheduling and Mapping of Conditional Task Graphs for the Synthesis of Low Power Embedded Systems
DATE '03 Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
Proceedings of the 2004 IEEE/ACM International conference on Computer-aided design
Minimizing Multi-resource Energy for Real-Time Systems with Discrete Operation Modes
ECRTS '10 Proceedings of the 2010 22nd Euromicro Conference on Real-Time Systems
Dynamic voltage and frequency scaling: the laws of diminishing returns
HotPower'10 Proceedings of the 2010 international conference on Power aware computing and systems
IEEE Transactions on Computers
Mobile cloud computing: A survey
Future Generation Computer Systems
Optimal DPM and DVFS for frame-based real-time systems
ACM Transactions on Architecture and Code Optimization (TACO) - Special Issue on High-Performance Embedded Architectures and Compilers
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To reduce the energy consumption in mobile devices, intricate applications are divided into several interconnected partitions like Task Interaction Graph (TIG) and are of floaded to cloud resources or nearby surrogates. Dynamic Voltage and Frequency Scaling (DVFS) is an effective technique to reduce the power consumption during mapping and scheduling stages. Most of the existing research works proposed several task scheduling solutions by considering the voltage/frequency scaling at the scheduling stage alone. But, the efficacy of these solutions can be improved by applying the DVFS in both mapping as well as scheduling stages. This research work attempts to apply DVFS in mapping as well as scheduling stages by combining both the task-resource and resource-frequency assignments in a single problem. The idea is to estimate the worst-case global slack time for each task-resource assignment, distributes it over the TIG and slowing down the execution of tasks using dynamic voltage and frequency scaling. This optimal slowdown increases the computation time of TIG without exceeding its worst-case completion time. Further, the proposed work models the code offloading as a Quadratic Assignment Problem (QAP) in Matlab-R2012b and solves it using two-level Genetic Algorithm (GA) of the global optimization toolbox. The effectiveness of the proposed model is assessed by a simulation and the results conclude that there is an average energy savings of 35% in a mobile device.