30-05-2012, 12:27 PM
RESOURCE MANAGEMENT FOR SOFTWARE-DEFINED RADIO CLOUDS
[attachment=23493]
Wireless communications are
virtually omnipresent today. Radio transmitters
and receivers encode and decode signals
such that huge data amounts reach their destinations
in real time and at the desired quality.
Wireless communications links are
therefore established between mobile terminals
and base stations of cellular communications
systems.
Maximizing the capacity of wireless communications
systems under the given technological
and physical constraints led to the
concept of spectral efficiency. A higher spectral
efficiency is usually achieved through
advanced signal-processing techniques, including
adaptive modulation, orthogonal frequency
division multiplexing (OFDM),
channel estimation and equalization, iterative
decoding, and sophisticated channel access.
The SDR cloud
Base stations are the core elements of
today’s wireless communications systems.
Traditionally, they’re dimensioned offline
for a predetermined number of users and
radio resources. During large periods of low
radio traffic,5 however, computing resources
remain idle and can hardly
Resource management requirements and approach
Today’s wireless subscribers access communications
services anywhere, anytime,
and under different circumstances. An
SDR application’s real-time processing and
data-flow demands are a function of the
communications service, QoS, and channel
conditions. The wireless communications
channel highly degrades transmitted signals.
Yet, weak or corrupted signals can still be
recovered, and the QoS target (bit error
rate, video or image resolution, and so
forth) can still be achieved through sophisticated
signal processing.
ALOE enabling technologies
The Abstraction Layer and Operating Environment
(http://flexnets.upc.edu/trac/wiki/
ALOE) is a lightweight, platform-independent
execution environment for SDRs. ALOE
is implemented in plain C. Its modular
design consists of three layers: the hardware
API, software daemons, and the software
API.
Resource management
Using the available computing resources,
the resource manager must satisfy real-time
computing-resource requirements. Generalpurpose
computing clouds or grids often
apply best effort or other types of resourcemanagement
policies11 without the strict timing
constraints of wireless communications.
The ALOE resource manager accounts for the
SDR-specific computing constraints. It models
SDR platforms as interconnected processing
cores, and SDR applications as directed acyclic
graphs of continuous data flow demands.
[attachment=23493]
Wireless communications are
virtually omnipresent today. Radio transmitters
and receivers encode and decode signals
such that huge data amounts reach their destinations
in real time and at the desired quality.
Wireless communications links are
therefore established between mobile terminals
and base stations of cellular communications
systems.
Maximizing the capacity of wireless communications
systems under the given technological
and physical constraints led to the
concept of spectral efficiency. A higher spectral
efficiency is usually achieved through
advanced signal-processing techniques, including
adaptive modulation, orthogonal frequency
division multiplexing (OFDM),
channel estimation and equalization, iterative
decoding, and sophisticated channel access.
The SDR cloud
Base stations are the core elements of
today’s wireless communications systems.
Traditionally, they’re dimensioned offline
for a predetermined number of users and
radio resources. During large periods of low
radio traffic,5 however, computing resources
remain idle and can hardly
Resource management requirements and approach
Today’s wireless subscribers access communications
services anywhere, anytime,
and under different circumstances. An
SDR application’s real-time processing and
data-flow demands are a function of the
communications service, QoS, and channel
conditions. The wireless communications
channel highly degrades transmitted signals.
Yet, weak or corrupted signals can still be
recovered, and the QoS target (bit error
rate, video or image resolution, and so
forth) can still be achieved through sophisticated
signal processing.
ALOE enabling technologies
The Abstraction Layer and Operating Environment
(http://flexnets.upc.edu/trac/wiki/
ALOE) is a lightweight, platform-independent
execution environment for SDRs. ALOE
is implemented in plain C. Its modular
design consists of three layers: the hardware
API, software daemons, and the software
API.
Resource management
Using the available computing resources,
the resource manager must satisfy real-time
computing-resource requirements. Generalpurpose
computing clouds or grids often
apply best effort or other types of resourcemanagement
policies11 without the strict timing
constraints of wireless communications.
The ALOE resource manager accounts for the
SDR-specific computing constraints. It models
SDR platforms as interconnected processing
cores, and SDR applications as directed acyclic
graphs of continuous data flow demands.