2,477 research outputs found
PACE: Simple Multi-hop Scheduling for Single-radio 802.11-based Stub Wireless Mesh Networks
IEEE 802.11-based Stub Wireless Mesh Networks (WMNs) are a cost-effective and flexible solution to extend wired network infrastructures. Yet, they suffer from two major problems: inefficiency and unfairness. A number of approaches have been proposed to tackle these problems, but they are too restrictive, highly complex, or require time synchronization and modifications to the IEEE 802.11 MAC.
PACE is a simple multi-hop scheduling mechanism for Stub WMNs overlaid on the IEEE 802.11 MAC that jointly addresses the inefficiency and unfairness problems. It limits transmissions to a single mesh node at each time and ensures that each node has the opportunity to transmit a packet in each network-wide transmission round. Simulation results demonstrate that PACE can achieve optimal network capacity utilization and greatly outperforms state of the art CSMA/CA-based solutions as far as goodput, delay, and fairness are concerned
Overlapping of Communication and Computation and Early Binding: Fundamental Mechanisms for Improving Parallel Performance on Clusters of Workstations
This study considers software techniques for improving performance on clusters of workstations and approaches for designing message-passing middleware that facilitate scalable, parallel processing. Early binding and overlapping of communication and computation are identified as fundamental approaches for improving parallel performance and scalability on clusters. Currently, cluster computers using the Message-Passing Interface for interprocess communication are the predominant choice for building high-performance computing facilities, which makes the findings of this work relevant to a wide audience from the areas of high-performance computing and parallel processing. The performance-enhancing techniques studied in this work are presently underutilized in practice because of the lack of adequate support by existing message-passing libraries and are also rarely considered by parallel algorithm designers. Furthermore, commonly accepted methods for performance analysis and evaluation of parallel systems omit these techniques and focus primarily on more obvious communication characteristics such as latency and bandwidth. This study provides a theoretical framework for describing early binding and overlapping of communication and computation in models for parallel programming. This framework defines four new performance metrics that facilitate new approaches for performance analysis of parallel systems and algorithms. This dissertation provides experimental data that validate the correctness and accuracy of the performance analysis based on the new framework. The theoretical results of this performance analysis can be used by designers of parallel system and application software for assessing the quality of their implementations and for predicting the effective performance benefits of early binding and overlapping. This work presents MPI/Pro, a new MPI implementation that is specifically optimized for clusters of workstations interconnected with high-speed networks. This MPI implementation emphasizes features such as persistent communication, asynchronous processing, low processor overhead, and independent message progress. These features are identified as critical for delivering maximum performance to applications. The experimental section of this dissertation demonstrates the capability of MPI/Pro to facilitate software techniques that result in significant application performance improvements. Specific demonstrations with Virtual Interface Architecture and TCP/IP over Ethernet are offered
Dynamic load balancing for the distributed mining of molecular structures
In molecular biology, it is often desirable to find common properties in large numbers of drug candidates. One family of
methods stems from the data mining community, where algorithms to find frequent graphs have received increasing attention over the
past years. However, the computational complexity of the underlying problem and the large amount of data to be explored essentially
render sequential algorithms useless. In this paper, we present a distributed approach to the frequent subgraph mining problem to
discover interesting patterns in molecular compounds. This problem is characterized by a highly irregular search tree, whereby no
reliable workload prediction is available. We describe the three main aspects of the proposed distributed algorithm, namely, a dynamic
partitioning of the search space, a distribution process based on a peer-to-peer communication framework, and a novel receiverinitiated
load balancing algorithm. The effectiveness of the distributed method has been evaluated on the well-known National Cancer
Instituteâs HIV-screening data set, where we were able to show close-to linear speedup in a network of workstations. The proposed
approach also allows for dynamic resource aggregation in a non dedicated computational environment. These features make it suitable
for large-scale, multi-domain, heterogeneous environments, such as computational grids
Getting routers out of the core: Building an optical wide area network with "multipaths"
We propose an all-optical networking solution for a wide area network (WAN)
based on the notion of multipoint-to-multipoint lightpaths that, for short, we
call "multipaths". A multipath concentrates the traffic of a group of source
nodes on a wavelength channel using an adapted MAC protocol and multicasts this
traffic to a group of destination nodes that extract their own data from the
confluent stream. The proposed network can be built using existing components
and appears less complex and more efficient in terms of energy consumption than
alternatives like OPS and OBS. The paper presents the multipath architecture
and compares its energy consumption to that of a classical router-based ISP
network. A flow-aware dynamic bandwidth allocation algorithm is proposed and
shown to have excellent performance in terms of throughput and delay
System Support for Bandwidth Management and Content Adaptation in Internet Applications
This paper describes the implementation and evaluation of an operating system
module, the Congestion Manager (CM), which provides integrated network flow
management and exports a convenient programming interface that allows
applications to be notified of, and adapt to, changing network conditions. We
describe the API by which applications interface with the CM, and the
architectural considerations that factored into the design. To evaluate the
architecture and API, we describe our implementations of TCP; a streaming
layered audio/video application; and an interactive audio application using the
CM, and show that they achieve adaptive behavior without incurring much
end-system overhead. All flows including TCP benefit from the sharing of
congestion information, and applications are able to incorporate new
functionality such as congestion control and adaptive behavior.Comment: 14 pages, appeared in OSDI 200
High performance subgraph mining in molecular compounds
Structured data represented in the form of graphs arises in
several fields of the science and the growing amount of available data makes distributed graph mining techniques particularly relevant. In this paper, we present a distributed approach to the frequent subgraph mining
problem to discover interesting patterns in molecular compounds. The problem is characterized by a highly irregular search tree, whereby no reliable workload prediction is available. We describe the three main
aspects of the proposed distributed algorithm, namely a dynamic partitioning of the search space, a distribution process based on a peer-to-peer communication framework, and a novel receiver-initiated, load balancing
algorithm. The effectiveness of the distributed method has been evaluated on the well-known National Cancer Instituteâs HIV-screening dataset, where the approach attains close-to linear speedup in a network
of workstations
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