This paper presents the VMedia multimedia virtualization framework, for sharing media devices among multiple
virtual machines (VMs). The framework provides logical media devices, exported via a well defined, higher level,
multimedia access interface, to the applications and operating system running in a VM. By using semantically
meaningful information, rather than low-level raw data, within the VMedia framework, efficient virtualization
solutions can be created for physical devices shared by multiple VMs. Experimental results demonstrate that the
base cost of virtual device access via VMedia is small compared to native physical device access, and in addition,
that these costs scale well with an increasing number of guest VMs. Here, VMedia's MediaGraph abstraction is
a key contributor, since it also allows the framework to support dynamic restructuring, in order to adapt device
accesses to changing requirements. Finally, VMedia permits platforms to offer new and enhanced logical device
functionality at lower costs than those achievable with alternative solutions.
KEYWORDS: Multimedia, Operating systems, Video, Computing systems, Algorithm development, Systems modeling, Solid state electronics, Digital photography, Data storage, Manufacturing
Mobile multimedia computers require large amounts of data storage, yet must consume low power in order to
prolong battery life. Solid-state storage offers low power consumption, but its capacity is an order of magnitude
smaller than the hard disks needed for high-resolution photos and digital video. In order to create a device with
the space of a hard drive, yet the low power consumption of solid-state storage, hardware manufacturers have
proposed using flash memory as a write buffer on mobile systems. This paper evaluates the power savings of such
an approach and also considers other possible flash allocation algorithms, using both hardware- and software-level
flash management. Its contributions also include a set of typical multimedia-rich workloads for mobile systems
and power models based upon current disk and flash technology. Based on these workloads, we demonstrate
an average power savings of 267 mW (53% of disk power) using hardware-only approaches. Next, we propose
another algorithm, termed Energy-efficient Virtual Storage using Application-Level Framing (EVS-ALF), which
uses both hardware and software for power management. By collecting information from the applications and
using this metadata to perform intelligent flash allocation and prefetching, EVS-ALF achieves an average power
savings of 307 mW (61%), another 8% improvement over hardware-only techniques.
The computation and communication abilities of modern platforms are enabling increasingly capable cooperative
distributed mobile systems. An example is distributed multimedia processing of sensor data in robots deployed
for search and rescue, where a system manager can exploit the application's cooperative nature to optimize the
distribution of roles and tasks in order to successfully accomplish the mission. Because of limited battery capacities,
a critical task a manager must perform is online energy management. While support for power management
has become common for the components that populate mobile platforms, what is lacking is integration and explicit
coordination across the different management actions performed in a variety of system layers. This papers
develops an integration approach for distributed multimedia applications, where a global manager specifies both
a power operating point and a workload for a node to execute. Surprisingly, when jointly considering power and
QoS, experimental evaluations show that using a simple deadline-driven approach to assigning frequencies can
be non-optimal. These trends are further affected by certain characteristics of underlying power management
mechanisms, which in our research, are identified as groupings that classify component power management as
"compatible" (VFC) or "incompatible" (VFI) with voltage and frequency scaling. We build on these findings
to develop CompatPM, a vertically integrated control strategy for power management in distributed mobile
systems. Experimental evaluations of CompatPM indicate average energy improvements of 8% when platform
resources are managed jointly rather than independently, demonstrating that previous attempts to maximize
battery life by simply minimizing frequency are inappropriate from a platform-level perspective.
KEYWORDS: Video, Cameras, RGB color model, Data modeling, Video surveillance, Sensors, Remote sensing, Instrument modeling, Local area networks, Performance modeling
New applications like remote surveillance and online environmental or traffic monitoring are making it increasingly
important to provide flexible and protected access to remote video sensor devices. Current systems use application-level
codes like web-based solutions to provide such access. This requires adherence to user-level APIs provided by such
services, access to remote video information through given application-specific service and server topologies, and that
the data being captured and distributed is manipulated by third party service codes. CameraCast is a simple, easily used
system-level solution to remote video access. It provides a logical device API so that an application can identically
operate on local vs. remote video sensor devices, using its own service and server topologies. In addition, the
application can take advantage of API enhancements to protect remote video information, using a capability-based
model for differential data protection that offers fine grain control over the information made available to specific codes
or machines, thereby limiting their ability to violate privacy or security constraints. Experimental evaluations of
CameraCast show that the performance of accessing remote video information approximates that of accesses to local
devices, given sufficient networking resources. High performance is also attained when protection restrictions are
enforced, due to an efficient kernel-level realization of differential data protection.
Modern mobile processors offer dynamic voltage and frequency scaling, which can be used to reduce the energy requirements of embedded and real-time applications by exploiting idle CPU resources, while still maintaining all applications' real-time characteristics. However, accurate predictions of task run-times are key to computing the frequencies and voltages that ensure that all tasks' real-time constraints are met. Past work has used feedback-based approaches, where applications' past CPU utilizations are used to predict future CPU requirements. Inaccurate predictions in these approaches can lead to missed deadlines, less than expected energy savings, or large overheads due to frequent voltage and frequency changes. Previous solutions ignore other `indicators' of future CPU requirements, such as the frequency of I/O operations, memory accesses, or interrupts. This paper addresses this shortcoming for memory-intensive applications, where measured task run-times and cache miss rates are used as feedback for accurate run-time predictions. Cache miss rates indicate the frequency of memory accesses and enable us to derive the latencies introduced by these operations. The results shown in this paper indicate improvements in the number of deadlines met and the amount of energy saved.
KEYWORDS: Visualization, Human-machine interfaces, Computer simulations, Data modeling, Visual analytics, Binary data, Device simulation, 3D modeling, Data communications, Data visualization
This paper presents a structure and set of tools to address the needs of groups of scientists working on large, time- dependent simulations. It describes a direct manipulation, 3D steering environment that is integrated with a controller for instrumenting parallel computations, collecting output, and passing it in binary mode between heterogeneous machines. The instrumentation allows collection of data at chosen points in the model and control of the computation through changes of parameters of insertion of alternate data. The steering interface and controller are joined with a library of collaborative communication tools. With these tools a user may steer a simulation and share visualization tools within the group. In addition a time-dependent steering interface has been introduced. Here time is treated on exactly the same basis as the spatial dimensions so there is a 4D environment, 3 shown spatially and one through animation. The steering interface is built upon a flexible visualization/analysis system. This permits the immediate display of time-dependent results from the dynamic simulations and refined interaction with the results to bring out the character and correlations of multivariate data. The user can then launch new simulations at any stage in this exploration using the visualization to define and focus the simulation parameters, region of interest, and time frame.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.