88,272 research outputs found
GeoLoc: Robust Resource Allocation Method for Query Optimization in Data Grid Systems
International audienceResource allocation (RA) is one of the key stages of distributed query processing in the Data Grid environment. In the last decade were published a number of works in the field that deals with different aspects of the problem. We believe that in those studies authors paid less attention to such important aspects as definition of allocation space and criterion of parallelism degree determination. In this paper we propose a method of RA that extends existing solutions in those two points of interest and resolves the problem in the specific conditions of the large scale heterogeneous environment of Data Grids. Firstly, we propose to use a geographical proximity of nodes to data sources to define the Allocation Space (AS). Secondly, we present the principle of execution time parity between scan and join (build and probe) operations for determination of parallelism degree and for generation of load balanced query execution plans. We conducted an experiment that proved the superiority of our GeoLoc method in terms of response time over the RA method that we chose for the comparison. The present study provides also a brief description of existing methods and their qualitative comparison with respect to proposed method
Voice Service Support in Mobile Ad Hoc Networks
Mobile ad hoc networks are expected to support voice traffic. The requirement
for small delay and jitter of voice traffic poses a significant challenge for
medium access control (MAC) in such networks. User mobility makes it more
complex due to the associated dynamic path attenuation. In this paper, a MAC
scheme for mobile ad hoc networks supporting voice traffic is proposed. With
the aid of a low-power probe prior to DATA transmissions, resource reservation
is achieved in a distributed manner, thus leading to small delay and jitter.
The proposed scheme can automatically adapt to dynamic path attenuation in a
mobile environment. Simulation results demonstrate the effectiveness of the
proposed scheme.Comment: To appear in the Proceedings of the IEEE Global Communications
Conference (GLOBECOM), Washington, DC, November 26 - 30, 200
Joint Channel Probing and Proportional Fair Scheduling in Wireless Networks
The design of a scheduling scheme is crucial for the efficiency and
user-fairness of wireless networks. Assuming that the quality of all user
channels is available to a central controller, a simple scheme which maximizes
the utility function defined as the sum logarithm throughput of all users has
been shown to guarantee proportional fairness. However, to acquire the channel
quality information may consume substantial amount of resources. In this work,
it is assumed that probing the quality of each user's channel takes a fraction
of the coherence time, so that the amount of time for data transmission is
reduced. The multiuser diversity gain does not always increase as the number of
users increases. In case the statistics of the channel quality is available to
the controller, the problem of sequential channel probing for user scheduling
is formulated as an optimal stopping time problem. A joint channel probing and
proportional fair scheduling scheme is developed. This scheme is extended to
the case where the channel statistics are not available to the controller, in
which case a joint learning, probing and scheduling scheme is designed by
studying a generalized bandit problem. Numerical results demonstrate that the
proposed scheduling schemes can provide significant gain over existing schemes.Comment: 26 pages, 8 figure
Using Dedicated and Opportunistic Networks in Synergy for a Cost-effective Distributed Stream Processing Platform
This paper presents a case for exploiting the synergy of dedicated and
opportunistic network resources in a distributed hosting platform for data
stream processing applications. Our previous studies have demonstrated the
benefits of combining dedicated reliable resources with opportunistic resources
in case of high-throughput computing applications, where timely allocation of
the processing units is the primary concern. Since distributed stream
processing applications demand large volume of data transmission between the
processing sites at a consistent rate, adequate control over the network
resources is important here to assure a steady flow of processing. In this
paper, we propose a system model for the hybrid hosting platform where stream
processing servers installed at distributed sites are interconnected with a
combination of dedicated links and public Internet. Decentralized algorithms
have been developed for allocation of the two classes of network resources
among the competing tasks with an objective towards higher task throughput and
better utilization of expensive dedicated resources. Results from extensive
simulation study show that with proper management, systems exploiting the
synergy of dedicated and opportunistic resources yield considerably higher task
throughput and thus, higher return on investment over the systems solely using
expensive dedicated resources.Comment: 9 page
Similarity-Based Classification in Partially Labeled Networks
We propose a similarity-based method, using the similarity between nodes, to
address the problem of classification in partially labeled networks. The basic
assumption is that two nodes are more likely to be categorized into the same
class if they are more similar. In this paper, we introduce ten similarity
indices, including five local ones and five global ones. Empirical results on
the co-purchase network of political books show that the similarity-based
method can give high accurate classification even when the labeled nodes are
sparse which is one of the difficulties in classification. Furthermore, we find
that when the target network has many labeled nodes, the local indices can
perform as good as those global indices do, while when the data is sparce the
global indices perform better. Besides, the similarity-based method can to some
extent overcome the unconsistency problem which is another difficulty in
classification.Comment: 13 pages,3 figures,1 tabl
Morphological diagram of diffusion driven aggregate growth in plane: competition of anisotropy and adhesion
Two-dimensional structures grown with Witten and Sander algorithm are
investigated. We analyze clusters grown off-lattice and clusters grown with
antenna method with and 8 allowed growth directions. With
the help of variable probe particles technique we measure fractal dimension of
such clusters as a function of their size . We propose that in the
thermodynamic limit of infinite cluster size the aggregates grown with high
degree of anisotropy () tend to have fractal dimension equal
to 3/2, while off-lattice aggregates and aggregates with lower anisotropy
() have . Noise-reduction procedure results in the
change of universality class for DLA. For high enough noise-reduction value
clusters with have fractal dimension going to when
.Comment: 6 pages, 8 figures, conference CCP201
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