关于电源管理的几篇paper

wangyu82725

关于电源管理的几篇paper，还有一些

semico_ljj

Abstract！

cupt000

00000

yangfunc

dddddddddddddddddddddddd

megafit

A Stream-Oriented Power Management Protocol for Low Duty Cycle Sensor Network Applications

Abstract
Most power management protocols are packet-based and optimize
for applications with mostly asynchronous (i.e. unexpected)
traffic. We present AppSleep, a stream-oriented power
management protocol for latency tolerant sensor network applications.
For this class of applications, AppSleep demonstrates
an over 3x lifetime gain over B-MAC and SMAC. AppSleep leverages
application characteristics in order to take advantage of
periods of high latency tolerance to put the network to sleep for
extended periods of time, while still facilitating low latency responses
when required. AppSleep also gives applications the
flexibility to efficiently and effectively trade latency for energy
when desired, and enables energy efficient multi-fragment unicast
communication by only keeping the active route awake. We
also present Adaptive AppSleep, an application driven addition
to AppSleep which supports varying latency requirements while
still maximizing energy efficiency. Our evaluation demonstrates
that for an overlooked class of applications, stream-oriented
power management protocols such as AppSleep outperform
packet-based protocols such as B-MAC and S-MAC.

megafit

A Task-Specific Approach to Dynamic Device Power Management for Embedded System

Abstract
One of the major challenges of dynamic device
power management lies in the uncertain length of the
idle periods of devices. In this paper, we focus on the
problem of the accuracy of prediction when tasks
change their request modes, leading the change of the
device idle periods. We notice that there are some
reasons causing the change of the idle periods. In
order to capture these reasons, we first establish a
two-level power management mechanism in the
operating system. Then we provide a task-specific
approach, which is based on the relationship between
tasks and devices and takes dynamic weight of
predictive value and actual value. Experiments show
that our approach could save more than 40% power
consumption and was more efficient and accurate than
previous predictive policies.

megafit

Adaptive power management for mobile agent-based information retrieval

Abstract
Mobile agent technology has been used in wireless distributed
information retrieval for many years. However,
the energy-efficiency issue in such systems remains unexplored.
In this paper, we proposed an adaptive application-
driven power management (AADPM) protocol for mobile
agent-based applications within the IEEE 802.11b
infrastructure WLAN environment. Our goal is to minimize
energy while achieving low round trip time (RTT)
delay. We discuss the protocol and evaluate its effectiveness
using the network simulator NS2. We also draw horizontal
comparisons among a variety of PM methods reported
in the literature. Experimental results show that,
compared to the power save mode supported by 802.11b,
AADPM reduces the network interface card energy consumption
by 65% while only introducing 3% RTT delay.

megafit

Adaptive power management in software radios using resolution adaptive analog to digital converters

Abstract
The popularity of Software Radios is increasing, as
they have become one of the important emerging
technologies in mobile communications. One of the
major challenges during development of mobile
communications hardware is the inevitable low power
requirement. In this paper, we investigate power
management for software radios. The use of resolution
adaptive analog to digital converters as well as the
flexibility of the modulation schemes that a reconfigurable
radio provides is investigated. The
concept of a resolution adaptive analog to digital
converter is to trade performance for energy efficiency.
The energy delay product is used to evaluate the
performance versus energy tradeoffs and an adaptive
power management method is proposed.

w123456

good,

bluebaby

ghjgjjfjjghjg