137 research outputs found
Shortest Path versus Multi-Hub Routing in Networks with Uncertain Demand
We study a class of robust network design problems motivated by the need to
scale core networks to meet increasingly dynamic capacity demands. Past work
has focused on designing the network to support all hose matrices (all matrices
not exceeding marginal bounds at the nodes). This model may be too conservative
if additional information on traffic patterns is available. Another extreme is
the fixed demand model, where one designs the network to support peak
point-to-point demands. We introduce a capped hose model to explore a broader
range of traffic matrices which includes the above two as special cases. It is
known that optimal designs for the hose model are always determined by
single-hub routing, and for the fixed- demand model are based on shortest-path
routing. We shed light on the wider space of capped hose matrices in order to
see which traffic models are more shortest path-like as opposed to hub-like. To
address the space in between, we use hierarchical multi-hub routing templates,
a generalization of hub and tree routing. In particular, we show that by adding
peak capacities into the hose model, the single-hub tree-routing template is no
longer cost-effective. This initiates the study of a class of robust network
design (RND) problems restricted to these templates. Our empirical analysis is
based on a heuristic for this new hierarchical RND problem. We also propose
that it is possible to define a routing indicator that accounts for the
strengths of the marginals and peak demands and use this information to choose
the appropriate routing template. We benchmark our approach against other
well-known routing templates, using representative carrier networks and a
variety of different capped hose traffic demands, parameterized by the relative
importance of their marginals as opposed to their point-to-point peak demands
Merlin: A Language for Provisioning Network Resources
This paper presents Merlin, a new framework for managing resources in
software-defined networks. With Merlin, administrators express high-level
policies using programs in a declarative language. The language includes
logical predicates to identify sets of packets, regular expressions to encode
forwarding paths, and arithmetic formulas to specify bandwidth constraints. The
Merlin compiler uses a combination of advanced techniques to translate these
policies into code that can be executed on network elements including a
constraint solver that allocates bandwidth using parameterizable heuristics. To
facilitate dynamic adaptation, Merlin provides mechanisms for delegating
control of sub-policies and for verifying that modifications made to
sub-policies do not violate global constraints. Experiments demonstrate the
expressiveness and scalability of Merlin on real-world topologies and
applications. Overall, Merlin simplifies network administration by providing
high-level abstractions for specifying network policies and scalable
infrastructure for enforcing them
Measuring and Understanding Throughput of Network Topologies
High throughput is of particular interest in data center and HPC networks.
Although myriad network topologies have been proposed, a broad head-to-head
comparison across topologies and across traffic patterns is absent, and the
right way to compare worst-case throughput performance is a subtle problem.
In this paper, we develop a framework to benchmark the throughput of network
topologies, using a two-pronged approach. First, we study performance on a
variety of synthetic and experimentally-measured traffic matrices (TMs).
Second, we show how to measure worst-case throughput by generating a
near-worst-case TM for any given topology. We apply the framework to study the
performance of these TMs in a wide range of network topologies, revealing
insights into the performance of topologies with scaling, robustness of
performance across TMs, and the effect of scattered workload placement. Our
evaluation code is freely available
Sampling cluster endurance for peer-to-peer based content distribution networks
Several types of Content Distribution Networks are being deployed over the Internet today, based on different architectures to meet their requirements (e.g., scalability, efficiency and resiliency). Peer-to-peer (P2P) based Content Distribution Networks are promising approaches that have several advantages. Structured P2P networks, for instance, take a proactive approach and provide efficient routing mechanisms. Nevertheless, their maintenance can increase considerably in highly dynamic P2P environments. In order to address this issue, a two-tier architecture called Omicron that combines a structured overlay network with a clustering mechanism is suggested in a hybrid scheme. In this paper, we examine several sampling algorithms utilized in the aforementioned hybrid network that collect local information in order to apply a selective join procedure. Additionally, we apply the sampling algorithms on Chord in order to evaluate sampling as a general information gathering mechanism. The algorithms are based mostly on random walks inside the overlay networks. The aim of the selective join procedure is to provide a well balanced and stable overlay infrastructure that can easily overcome the unreliable behavior of the autonomous peers that constitute the network. The sampling algorithms are evaluated using simulation experiments as well as probabilistic analysis where several properties related to the graph structure are reveale
A Fringe Projection System for Measurement of Condensing Fluid Films in Reduced Gravity
The thesis describes the design of a fringe projection system to study the dynamics of condensation with potential application in a reduced gravity environment. The concept is that an optical system for imaging the condensation layer enables extraction of valuable data from the image because of the ability of the optical system to image the perturbations in the condensation films. By acquiring a sequence of images of the deformed fringe pattern, the change in the surface topology can be observed over time, giving greater understanding of condensation dynamics in reduced gravity
Using holography to measure particle extinction and surface topography
Master of ScienceDepartment of PhysicsMatthew J. BergSince its conception, holography has been applied to everything from microscopy and interferometry to art and security. Two separate applications of holography are discussed in detail. In the first project, holography is used to obtain a measurement of the extinction cross section of various micron sized particles, which are compared to the discrete dipole approximation (DDA) cross sectional values. We are also interested in the structure of ``fairy castles'', a model developed to explain the photometric behavior of the surface of the moon. A holographic solution in conjunction with phase unwrapping is obtained, and the basics of phase unwrapping are discussed
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