Title :
An overview of the competitive and adversarial approaches to designing dynamic power management strategies
Author :
Irani, Sandy ; Singh, Gaurav ; Shukla, Sandeep K. ; Gupta, Rajesh K.
Author_Institution :
Sch. of Inf. & Comput. Sci., Univ. of California, Irvine, CA, USA
Abstract :
Dynamic power management (DPM) refers to the problem of judicious application of various low-power techniques based on runtime conditions in an embedded system to minimize the total energy consumption. To be effective, often such decisions take into account the operating conditions and the system-level design goals. DPM has been a subject of intense research in the past decade driven by the need for low power consumption in modern embedded devices. We present a comprehensive overview of two closely related approaches to designing DPM strategies, namely, competitive analysis approach and model checking approach based on adversarial modeling. Although many other approaches exist for solving the system-level DPM problem, these two approaches are closely related and are based on a common theme. This commonality is in the fact that the underlying model is that of a competition between the system and an adversary. The environment that puts service demands on devices is viewed as an adversary, or to be in competition with the system to make it burn more energy, and the DPM strategy is employed by the system to counter that.
Keywords :
embedded systems; integrated circuit design; integrated circuit modelling; low-power electronics; reviews; adversarial modeling; competitive analysis; dynamic power management strategies; low-power design; model checking; online algorithm; probabilistic model checking; stochastic policy; Algorithm design and analysis; Computer science; Embedded computing; Energy consumption; Energy management; Operating systems; Power system management; Power system modeling; Runtime; Stochastic processes; Competitive analysis; dynamic power management; low-power design; online algorithm; probabilistic model checking; stochastic policy;
Journal_Title :
Very Large Scale Integration (VLSI) Systems, IEEE Transactions on
DOI :
10.1109/TVLSI.2005.862725