Resource allocation problems: algorithmic approaches
Resource allocation problems: algorithmic approaches
Data driven signal processing: an approach for energy efficient computing
ISLPED '96 Proceedings of the 1996 international symposium on Low power electronics and design
Power optimization of variable voltage core-based systems
DAC '98 Proceedings of the 35th annual Design Automation Conference
A resource allocation model for QoS management
RTSS '97 Proceedings of the 18th IEEE Real-Time Systems Symposium
Practical Solutions for QoS-Based Resource Allocation
RTSS '98 Proceedings of the IEEE Real-Time Systems Symposium
Synthesis Techniques for Low-Power Hard Real-Time Systems on Variable Voltage Processors
RTSS '98 Proceedings of the IEEE Real-Time Systems Symposium
System Synthesis of Synchronous Multimedia Applications
Proceedings of the 12th international symposium on System synthesis
Scheduling for quality of service guarantees via service curves
ICCCN '95 Proceedings of the 4th International Conference on Computer Communications and Networks
High-level power modeling, estimation, and optimization
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Quality of service guarantees in virtual circuit switched networks
IEEE Journal on Selected Areas in Communications
Optimisation problems for dynamic concurrent task-based systems
Proceedings of the 2001 IEEE/ACM international conference on Computer-aided design
Voltage-Clock-Scaling Adaptive Scheduling Techniques for Low Power in Hard Real-Time Systems
IEEE Transactions on Computers
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Energy is one of the limited resources for modern systems, especially the battery-operated devices and personal digital assistants. The backlog in new technologies for more powerful battery is changing the traditional system design philosophies. For example, due to the limitation on battery life, it is more realistic to design for the optimal benefit from limited resource rather than design to meet all the applications' requirement. We consider the following problem: a system achieves a certain amount of utility from a set of applications by providing them certain levels of quality of service(QoS). We want to allocate the limited system resources to get the maximal system utility. We formulate this utility maximization problem, which is NP-hard in general, and propose heuristic algorithms that are capable of finding solutions provably arbitrarily close to the optimal. We have also derived explicit formulae to guide the allocation of resources to actually achieve such solutions. Simulation shows that our approach can use 99.9% of the given resource to achieve 25.6% and 32.17% more system utilities over two other heuristics, while providing QoS guarantees to the application program.