6,722 research outputs found
Scheduling Packets with Values and Deadlines in Size-bounded Buffers
Motivated by providing quality-of-service differentiated services in the
Internet, we consider buffer management algorithms for network switches. We
study a multi-buffer model. A network switch consists of multiple size-bounded
buffers such that at any time, the number of packets residing in each
individual buffer cannot exceed its capacity. Packets arrive at the network
switch over time; they have values, deadlines, and designated buffers. In each
time step, at most one pending packet is allowed to be sent and this packet can
be from any buffer. The objective is to maximize the total value of the packets
sent by their respective deadlines. A 9.82-competitive online algorithm has
been provided for this model (Azar and Levy. SWAT 2006), but no offline
algorithms have been known yet. In this paper, We study the offline setting of
the multi-buffer model. Our contributions include a few optimal offline
algorithms for some variants of the model. Each variant has its unique and
interesting algorithmic feature. These offline algorithms help us understand
the model better in designing online algorithms.Comment: 7 page
Bounded Delay Scheduling with Packet Dependencies
A common situation occurring when dealing with multimedia traffic is having
large data frames fragmented into smaller IP packets, and having these packets
sent independently through the network. For real-time multimedia traffic,
dropping even few packets of a frame may render the entire frame useless. Such
traffic is usually modeled as having {\em inter-packet dependencies}. We study
the problem of scheduling traffic with such dependencies, where each packet has
a deadline by which it should arrive at its destination. Such deadlines are
common for real-time multimedia applications, and are derived from stringent
delay constraints posed by the application. The figure of merit in such
environments is maximizing the system's {\em goodput}, namely, the number of
frames successfully delivered.
We study online algorithms for the problem of maximizing goodput of
delay-bounded traffic with inter-packet dependencies, and use competitive
analysis to evaluate their performance. We present competitive algorithms for
the problem, as well as matching lower bounds that are tight up to a constant
factor. We further present the results of a simulation study which further
validates our algorithmic approach and shows that insights arising from our
analysis are indeed manifested in practice
Energy Efficient Multiuser Scheduling: Statistical Guarantees on Bursty Packet Loss
In this paper, we consider energy efficient multiuser scheduling. Packet loss
tolerance of the applications is exploited to minimize average system energy.
There is a constraint on average packet drop rate and maximum number of packets
dropped successively (bursty loss). A finite buffer size is assumed. We propose
a scheme which schedules the users opportunistically according to the channel
conditions, packet loss constraints and buffer size parameters. We assume
imperfect channel state information at the transmitter side and analyze the
scheme in large user limit using stochastic optimization techniques. First, we
optimize system energy for a fixed buffer size which results in a corresponding
statistical guarantee on successive packet drop. Then, we determine the minimum
buffer size to achieve a target (improved) energy efficiency for the same (or
better) statistical guarantee. We show that buffer size can be traded
effectively to achieve system energy efficiency for target statistical
guarantees on packet loss parameters.Comment: Proc. Physcomnet in conjunction with WIOPT 201
Energy and bursty packet loss tradeoff over fading channels: a system-level model
Energy efficiency and quality of service (QoS) guarantees are the key design goals for the 5G wireless communication systems. In this context, we discuss a multiuser scheduling scheme over fading channels for loss tolerant applications. The loss tolerance of the application is characterized in terms of different parameters that contribute to quality of experience (QoE) for the application. The mobile users are scheduled opportunistically such that a minimum QoS is guaranteed. We propose an opportunistic scheduling scheme and address the cross-layer design framework when channel state information (CSI) is not perfectly available at the transmitter and the receiver. We characterize the system energy as a function of different QoS and channel state estimation error parameters. The optimization problem is formulated using Markov chain framework and solved using stochastic optimization techniques. The results demonstrate that the parameters characterizing the packet loss are tightly coupled and relaxation of one parameter does not benefit the system much if the other constraints are tight. We evaluate the energy-performance tradeoff numerically and show the effect of channel uncertainty on the packet scheduler design
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