Architecture of Computing Systems (Lecture Notes in Computer ...

Hierarchical Distributed Control of Power and Performances 39
[12] or are based on complex models to be build off-line and thus not easily
portable across different platforms [13]. In this class we can find also some Linux
kernel framework, but they resulted to be too much simple (QoSPM) or with
scalability limits (DPM [14]).
3 Constrained Power Management
The design of a cost-effective solution, for system-wide power and performances
optimization, requires to tackle the problem at all the abstraction levels, considering
both low-level architectural details and high-level application requirements.
The proposed approach supports the identification of an optimal trade-off
between expected performances and reduce power consumptions, especially focusing
on mobile multimedia embedded systems. Our technique is based on the
concept of Constrained Power Management (CPM) presented in this section.
3.1 Hierarchical Distributed Control
The CPM is an optimization technique based on a hierarchical distributed
control model. An overall view of the proposed solution is depicted in Fig. 1.
To overcame the complexity of centralized approaches, our solution splits the
system-wide control problem into two different sub-problems: low-level devices
local controls and an higher-level distributed agreement control. Drivers run a
device specific fine-tune policy, based on the system requirements and working
conditions, which exploits the detailed knowledge on the specific device capabilities.
The global optimization policy instead is implemented at a higher abstraction
level and exploits both low-level informations, related to resource availability
and hardware capabilities, and high-level informations related to application’s
QoS requirements.
Among the high-level global optimization policy and the multiple low-level
local optimization policies, we focused our attention on the upper layer. This
choice has a double motivation, on one hand it is the more interesting part, the
other many local optimization policies have already been investigated. The upper
layer is the more interesting because being the more abstract layer, the designed
solution will be completely platform independent and thus it can be directly
implemented within a portable framework. Instead, lower layer’s policies must
be strictly related to the devices and thus they require a detailed analysis of each
specific device class, which could itself require a complete study. Moreover, as
described in the prior-art, many researches have already focused on the definition
of local optimization policies for different classes of peripherals.
3.2 Cross-Layer Framework Design
From a design perspective CPM is a cross-layer technique which involves three
different levels: a low-level abstraction layer, a middle-level modeling layer and
finally an high-level optimization layer. The first two layers allow respectively to