2,029 research outputs found
Backlog and Delay Reasoning in HARQ Systems
Recently, hybrid-automatic-repeat-request (HARQ) systems have been favored in
particular state-of-the-art communications systems since they provide the
practicality of error detections and corrections aligned with repeat-requests
when needed at receivers. The queueing characteristics of these systems have
taken considerable focus since the current technology demands data
transmissions with a minimum delay provisioning. In this paper, we investigate
the effects of physical layer characteristics on data link layer performance in
a general class of HARQ systems. Constructing a state transition model that
combines queue activity at a transmitter and decoding efficiency at a receiver,
we identify the probability of clearing the queue at the transmitter and the
packet-loss probability at the receiver. We determine the effective capacity
that yields the maximum feasible data arrival rate at the queue under
quality-of-service constraints. In addition, we put forward non-asymptotic
backlog and delay bounds. Finally, regarding three different HARQ protocols,
namely Type-I HARQ, HARQ-chase combining (HARQ-CC) and HARQ-incremental
redundancy (HARQ-IR), we show the superiority of HARQ-IR in delay robustness
over the others. However, we further observe that the performance gap between
HARQ-CC and HARQ-IR is quite negligible in certain cases. The novelty of our
paper is a general cross-layer analysis of these systems, considering
encoding/decoding in the physical layer and delay aspects in the data-link
layer
Markov Decision Process Based Energy-Efficient On-Line Scheduling for Slice-Parallel Video Decoders on Multicore Systems
We consider the problem of energy-efficient on-line scheduling for
slice-parallel video decoders on multicore systems. We assume that each of the
processors are Dynamic Voltage Frequency Scaling (DVFS) enabled such that they
can independently trade off performance for power, while taking the video
decoding workload into account. In the past, scheduling and DVFS policies in
multi-core systems have been formulated heuristically due to the inherent
complexity of the on-line multicore scheduling problem. The key contribution of
this report is that we rigorously formulate the problem as a Markov decision
process (MDP), which simultaneously takes into account the on-line scheduling
and per-core DVFS capabilities; the power consumption of the processor cores
and caches; and the loss tolerant and dynamic nature of the video decoder's
traffic. In particular, we model the video traffic using a Direct Acyclic Graph
(DAG) to capture the precedence constraints among frames in a Group of Pictures
(GOP) structure, while also accounting for the fact that frames have different
display/decoding deadlines and non-deterministic decoding complexities. The
objective of the MDP is to minimize long-term power consumption subject to a
minimum Quality of Service (QoS) constraint related to the decoder's
throughput. Although MDPs notoriously suffer from the curse of dimensionality,
we show that, with appropriate simplifications and approximations, the
complexity of the MDP can be mitigated. We implement a slice-parallel version
of H.264 on a multiprocessor ARM (MPARM) virtual platform simulator, which
provides cycle-accurate and bus signal-accurate simulation for different
processors. We use this platform to generate realistic video decoding traces
with which we evaluate the proposed on-line scheduling algorithm in Matlab
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
Energy-efficient wireless communication
In this chapter we present an energy-efficient highly adaptive network interface architecture and a novel data link layer protocol for wireless networks that provides Quality of Service (QoS) support for diverse traffic types. Due to the dynamic nature of wireless networks, adaptations in bandwidth scheduling and error control are necessary to achieve energy efficiency and an acceptable quality of service. In our approach we apply adaptability through all layers of the protocol stack, and provide feedback to the applications. In this way the applications can adapt the data streams, and the network protocols can adapt the communication parameters
Renegotiation based dynamic bandwidth allocation for selfsimilar VBR traffic
The provision of QoS to applications traffic depends heavily on how different traffic types are categorized and classified, and how the prioritization of these applications are managed. Bandwidth is the most scarce network resource. Therefore, there is a need for a method or system that distributes an available bandwidth in a network among different applications in such a way that each class or type of traffic receives their constraint QoS requirements.
In this dissertation, a new renegotiation based dynamic resource allocation method for variable bit rate (VBR) traffic is presented. First, pros and cons of available off-line methods that are used to estimate selfsimilarity level (represented by Hurst parameter) of a VBR traffic trace are empirically investigated, and criteria to select measurement parameters for online resource management are developed. It is shown that wavelet analysis based methods are the strongest tools in estimation of Hurst parameter with their low computational complexities, compared to the variance-time method and R/S pox plot. Therefore, a temporal energy distribution of a traffic data arrival counting process among different frequency sub-bands is considered as a traffic descriptor, and then a robust traffic rate predictor is developed by using the Haar wavelet analysis. The empirical results show that the new on-line dynamic bandwidth allocation scheme for VBR traffic is superior to traditional dynamic bandwidth allocation methods that are based on adaptive algorithms such as Least Mean Square, Recursive Least Square, and Mean Square Error etc. in terms of high utilization and low queuing delay. Also a method is developed to minimize the number of bandwidth renegotiations to decrease signaling costs on traffic schedulers (e.g. WFQ) and networks (e.g. ATM). It is also quantified that the introduced renegotiation based bandwidth management scheme decreases heavytailedness of queue size distributions, which is an inherent impact of traffic self similarity.
The new design increases the achieved utilization levels in the literature, provisions given queue size constraints and minimizes the number of renegotiations simultaneously. This renegotiation -based design is online and practically embeddable into QoS management blocks, edge routers and Digital Subscriber Lines Access Multiplexers (DSLAM) and rate adaptive DSL modems
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