380 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
An Optimal Lower Bound for Buffer Management in Multi-Queue Switches
In the online packet buffering problem (also known as the unweighted FIFO
variant of buffer management), we focus on a single network packet switching
device with several input ports and one output port. This device forwards
unit-size, unit-value packets from input ports to the output port. Buffers
attached to input ports may accumulate incoming packets for later transmission;
if they cannot accommodate all incoming packets, their excess is lost. A packet
buffering algorithm has to choose from which buffers to transmit packets in
order to minimize the number of lost packets and thus maximize the throughput.
We present a tight lower bound of e/(e-1) ~ 1.582 on the competitive ratio of
the throughput maximization, which holds even for fractional or randomized
algorithms. This improves the previously best known lower bound of 1.4659 and
matches the performance of the algorithm Random Schedule. Our result
contradicts the claimed performance of the algorithm Random Permutation; we
point out a flaw in its original analysis
A 4/3-competitive randomized algorithm for online scheduling of packets with agreeable deadlines
In 2005 Li et al. gave a phi-competitive deterministic online algorithm for
scheduling of packets with agreeable deadlines with a very interesting
analysis. This is known to be optimal due to a lower bound by Hajek. We claim
that the algorithm by Li et al. can be slightly simplified, while retaining its
competitive ratio. Then we introduce randomness to the modified algorithm and
argue that the competitive ratio against oblivious adversary is at most 4/3.
Note that this still leaves a gap between the best known lower bound of 5/4 by
Chin et al. for randomised algorithms against oblivious adversary.Comment: 11 pages, 3-4 figures; new version due to STACS submissio
Datacenter Traffic Control: Understanding Techniques and Trade-offs
Datacenters provide cost-effective and flexible access to scalable compute
and storage resources necessary for today's cloud computing needs. A typical
datacenter is made up of thousands of servers connected with a large network
and usually managed by one operator. To provide quality access to the variety
of applications and services hosted on datacenters and maximize performance, it
deems necessary to use datacenter networks effectively and efficiently.
Datacenter traffic is often a mix of several classes with different priorities
and requirements. This includes user-generated interactive traffic, traffic
with deadlines, and long-running traffic. To this end, custom transport
protocols and traffic management techniques have been developed to improve
datacenter network performance.
In this tutorial paper, we review the general architecture of datacenter
networks, various topologies proposed for them, their traffic properties,
general traffic control challenges in datacenters and general traffic control
objectives. The purpose of this paper is to bring out the important
characteristics of traffic control in datacenters and not to survey all
existing solutions (as it is virtually impossible due to massive body of
existing research). We hope to provide readers with a wide range of options and
factors while considering a variety of traffic control mechanisms. We discuss
various characteristics of datacenter traffic control including management
schemes, transmission control, traffic shaping, prioritization, load balancing,
multipathing, and traffic scheduling. Next, we point to several open challenges
as well as new and interesting networking paradigms. At the end of this paper,
we briefly review inter-datacenter networks that connect geographically
dispersed datacenters which have been receiving increasing attention recently
and pose interesting and novel research problems.Comment: Accepted for Publication in IEEE Communications Surveys and Tutorial
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