25,656 research outputs found
Multi-View Video Packet Scheduling
In multiview applications, multiple cameras acquire the same scene from
different viewpoints and generally produce correlated video streams. This
results in large amounts of highly redundant data. In order to save resources,
it is critical to handle properly this correlation during encoding and
transmission of the multiview data. In this work, we propose a
correlation-aware packet scheduling algorithm for multi-camera networks, where
information from all cameras are transmitted over a bottleneck channel to
clients that reconstruct the multiview images. The scheduling algorithm relies
on a new rate-distortion model that captures the importance of each view in the
scene reconstruction. We propose a problem formulation for the optimization of
the packet scheduling policies, which adapt to variations in the scene content.
Then, we design a low complexity scheduling algorithm based on a trellis search
that selects the subset of candidate packets to be transmitted towards
effective multiview reconstruction at clients. Extensive simulation results
confirm the gain of our scheduling algorithm when inter-source correlation
information is used in the scheduler, compared to scheduling policies with no
information about the correlation or non-adaptive scheduling policies. We
finally show that increasing the optimization horizon in the packet scheduling
algorithm improves the transmission performance, especially in scenarios where
the level of correlation rapidly varies with time
Promote-IT: An efficient Real-Time Tertiary-Storage Scheduler
Promote-IT is an efficient heuristic scheduler that provides QoS guarantees for accessing data from tertiary storage. It can deal with a wide variety of requests and jukebox hardware. It provides short response and confirmation times, and makes good use of the jukebox resources. It separates the scheduling and dispatching functionality and effectively uses this separation to dispatch tasks earlier than scheduled, provided that the resource constraints are respected and no task misses its deadline. To prove the efficiency of Promote-IT we implemented alternative schedulers based on different scheduling models and scheduling paradigms. The evaluation shows that Promote-IT performs better than the other heuristic schedulers. Additionally, Promote-IT provides response-times near the optimum in cases where the optimal scheduler can be computed
A QoS-Aware Scheduling Algorithm for High-Speed Railway Communication System
With the rapid development of high-speed railway (HSR), how to provide the
passengers with multimedia services has attracted increasing attention. A key
issue is to develop an effective scheduling algorithm for multiple services
with different quality of service (QoS) requirements. In this paper, we
investigate the downlink service scheduling problem in HSR network taking
account of end-to-end deadline constraints and successfully packet delivery
ratio requirements. Firstly, by exploiting the deterministic high-speed train
trajectory, we present a time-distance mapping in order to obtain the highly
dynamic link capacity effectively. Next, a novel service model is developed for
deadline constrained services with delivery ratio requirements, which enables
us to turn the delivery ratio requirement into a single queue stability
problem. Based on the Lyapunov drift, the optimal scheduling problem is
formulated and the corresponding scheduling service algorithm is proposed by
stochastic network optimization approach. Simulation results show that the
proposed algorithm outperforms the conventional schemes in terms of QoS
requirements.Comment: 6 pages, 3 figures, accepted by IEEE ICC 2014 conferenc
Using Dedicated and Opportunistic Networks in Synergy for a Cost-effective Distributed Stream Processing Platform
This paper presents a case for exploiting the synergy of dedicated and
opportunistic network resources in a distributed hosting platform for data
stream processing applications. Our previous studies have demonstrated the
benefits of combining dedicated reliable resources with opportunistic resources
in case of high-throughput computing applications, where timely allocation of
the processing units is the primary concern. Since distributed stream
processing applications demand large volume of data transmission between the
processing sites at a consistent rate, adequate control over the network
resources is important here to assure a steady flow of processing. In this
paper, we propose a system model for the hybrid hosting platform where stream
processing servers installed at distributed sites are interconnected with a
combination of dedicated links and public Internet. Decentralized algorithms
have been developed for allocation of the two classes of network resources
among the competing tasks with an objective towards higher task throughput and
better utilization of expensive dedicated resources. Results from extensive
simulation study show that with proper management, systems exploiting the
synergy of dedicated and opportunistic resources yield considerably higher task
throughput and thus, higher return on investment over the systems solely using
expensive dedicated resources.Comment: 9 page
Adaptive Network Coding for Scheduling Real-time Traffic with Hard Deadlines
We study adaptive network coding (NC) for scheduling real-time traffic over a
single-hop wireless network. To meet the hard deadlines of real-time traffic,
it is critical to strike a balance between maximizing the throughput and
minimizing the risk that the entire block of coded packets may not be decodable
by the deadline. Thus motivated, we explore adaptive NC, where the block size
is adapted based on the remaining time to the deadline, by casting this
sequential block size adaptation problem as a finite-horizon Markov decision
process. One interesting finding is that the optimal block size and its
corresponding action space monotonically decrease as the deadline approaches,
and the optimal block size is bounded by the "greedy" block size. These unique
structures make it possible to narrow down the search space of dynamic
programming, building on which we develop a monotonicity-based backward
induction algorithm (MBIA) that can solve for the optimal block size in
polynomial time. Since channel erasure probabilities would be time-varying in a
mobile network, we further develop a joint real-time scheduling and channel
learning scheme with adaptive NC that can adapt to channel dynamics. We also
generalize the analysis to multiple flows with hard deadlines and long-term
delivery ratio constraints, devise a low-complexity online scheduling algorithm
integrated with the MBIA, and then establish its asymptotical
throughput-optimality. In addition to analysis and simulation results, we
perform high fidelity wireless emulation tests with real radio transmissions to
demonstrate the feasibility of the MBIA in finding the optimal block size in
real time.Comment: 11 pages, 13 figure
A Survey of Techniques For Improving Energy Efficiency in Embedded Computing Systems
Recent technological advances have greatly improved the performance and
features of embedded systems. With the number of just mobile devices now
reaching nearly equal to the population of earth, embedded systems have truly
become ubiquitous. These trends, however, have also made the task of managing
their power consumption extremely challenging. In recent years, several
techniques have been proposed to address this issue. In this paper, we survey
the techniques for managing power consumption of embedded systems. We discuss
the need of power management and provide a classification of the techniques on
several important parameters to highlight their similarities and differences.
This paper is intended to help the researchers and application-developers in
gaining insights into the working of power management techniques and designing
even more efficient high-performance embedded systems of tomorrow
A cross-layer approach to enhance QoS for multimedia applications over satellite
The need for on-demand QoS support for communications over satellite is of primary importance for distributed multimedia applications. This is particularly true for the return link which is often a bottleneck due to the large set of end-users accessing a very limited uplink resource. Facing this need, Demand Assignment Multiple Access (DAMA) is a classical technique that allows satellite operators to offer various types of services, while managing the resources of the satellite system efficiently. Tackling the quality degradation and delay accumulation issues that can result from the use of these techniques, this paper proposes an instantiation of the Application Layer Framing (ALF) approach, using a cross-layer interpreter(xQoS-Interpreter). The information provided by this interpreter is used to manage the resource provided to a terminal by the satellite system in order to improve the quality of multimedia presentations from the end users point of view. Several experiments are carried out for different loads on the return link. Their impact on QoS is measured through different application as well as network level metrics
The design and implementation of a multimedia storage server tosupport video-on-demand applications
In this paper we present the design and implementation of a client/server based multimedia architecture for supporting video-on-demand applications. We describe in detail the software architecture of the implementation along with the adopted buffering mechanism. The proposed multithreaded architecture obtains, on one hand, a high degree of parallelism at the server side, allowing both the disk controller and the network card controller work in parallel. On the other hand; at the client side, it achieves the synchronized playback of the video stream at its precise rate, decoupling this process from the reception of data through the network. Additionally, we have derived, under an engineering perspective, some services that a real-time operating system should offer to satisfy the requirements found in video-on-demand applications.This research has been supported by the Regional Research Plan of the Autonomus Community of Madrid under an F.P.I. research grant.Publicad
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