1414584
Broadcast program generation for unordered queries with data replication
We study in this paper the problem of broadcasting dependent data for unordered queries. However, most prior studies on dependent data broadcasting are limited to the premise of no data replication. Different from other prior studies, we investigate the effect of data replication in this paper. Specifically, we first derive several theoretical properties for the average access time by analyzing the model of dependent data broadcasting. On the basis of the theoretical results, we develop a genetic algorithm to generate broadcast programs with replication. In order to compare the performance of the proposed algorithm and the prior studies, several experiments are conducted. Our experimental results show that with the analytical results derived, the theoretical results derived are able to guide the search of the genetic algorithm very effectively, and lead to solution broadcast programs of higher quality than those of the prior studies.
12270343
SIFA: a scalable file system with intelligent file allocation
In this paper we propose and evaluate a new NAS based system which is a consolidated file system in a network environment. The consolidated file system utilizes storage boxes cooperating as peers to provide all file system services, and presents itself to its NFS clients as a unified storage server. We have prototyped several key operations in this system. To provide more performance insights, we build a comprehensive system simulator and conduct extensive performance studies for the system via the simulator This simulator has been run against a workload of a real Web server and the system behavior of this workload is studied. In light of the experimental results, a consolidated file system is being implemented in full scale.
6920930
Data Broadcast on a Multi-System Heterogeneous Overlayed Wireless Network
We propose in this paper a two-phase algorithm, named algorithm layered-cutting, to address the problem of broadcast program generation in a multisystem heterogeneous overlayed wireless network. The experimental results show that algorithm layered-cutting is able to efficiently generate broadcast programs of high quality for a multisystem heterogeneous overlayed wireless network
14327978
On Exploring the Power-Law Relationship in the Itemset Support Distribution
We identify and explore in this paper an important phenomenon which points out that the power-law relationship appears in the distribution of itemset supports. Characterizing such a relationship will benefit many applications such as providing the direction of tuning the performance of the frequent-itemset mining. Nevertheless, due to the explosive number of itemsets, it will be prohibitively expensive to retrieve characteristics of the power-law relationship in the distribution of itemset supports. As such, we also propose in this paper a valid and cost-effective algorithm, called algorithm PPL, to extract characteristics of the distribution without the need of discovering all itemsets in advance. Experimental results demonstrate that algorithm PPL is able to efficiently extract the characteristics of the power-law relationship with high accuracy.
7193109
An object-oriented architecture supporting Web application testing
The flexibility and rich application frameworks of the Web model make Web applications more prevalent in both Internet and intranet environments. Programmers enjoy various Web application frameworks with support ranging from simple user interactions based on the plain client-server model, to complicated distributed-object computations based on CORBA. The variety gives users the flexibility to decide a proper framework, and leads to demands for new support tools and a testing framework to test and maintain Web applications. This paper presents an architecture containing several supporting tools which enhance traditional software testing architecture to fit common Web application frameworks. The architecture suits current Web models and reuses several software patterns and architectures from traditional testing environments. In addition, a prototype Web application testing environment is constructed for demonstration.
15941775
Exploring Regression for Mining User Moving Patterns in a Mobile Computing System
In this paper, by exploiting the log of call detail records, we present a solution procedure of mining user moving patterns in a mobile computing system. Specifically, we propose algorithm LS to accurately determine similar moving sequences from the log of call detail records so as to obtain moving behaviors of users. By exploring the feature of spatial-temporal locality, we develop algorithm TC to group call detail records into clusters. In light of the concept of regression, we devise algorithm MF to derive moving functions of moving behaviors. Performance of the proposed solution procedure is analyzed and sensitivity analysis on several design parameters is conducted. It is shown by our simulation results that user moving patterns obtained by our solution procedure are of very high quality and in fact very close to real user moving behaviors.
4333882
Linear-Time Representation Algorithms for Proper Circular-Arc Graphs and Proper Interval Graphs
Our main result is a linear-time (that is, time $O(m+n)$) algorithm to recognize and represent proper circular-arc graphs. The best previous algorithm, due to A. Tucker, has time complexity $O(n^2)$. We take advantage of the fact that (among connected graphs) proper circular-arc graphs are precisely the graphs orientable as local tournaments, and we use a new characterization of local tournaments. The algorithm depends on repeated representation of portions of the input graph as proper interval graphs. Thus we also find it useful to give a new linear-time algorithm to represent proper interval graphs. This latter algorithm also depends on an orientation characterization of proper interval graphs. It is conceptually simple and does not use complex data structures. As a byproduct of the correctness proof of the algorithm, we also obtain a new proof of a characterization of proper interval graphs by forbidden subgraphs.
14767737
Dynamic co-scheduling of distributed computation and replication
We are interested in developing the infrastructural tools that allow a distributed data intensive computing environment to be shared by a group of collaborating but geographically separated researchers in an interactive manner, as opposed to a batch mode of operation. However, without advanced reservation, it is difficult to assure a certain level of performance on a large number of shared and heterogeneous servers. To achieve scalable parallel speedups in this scenario, we must closely integrate the management of computation and runtime data movement. In this paper, we first define the canonical scheduling problem for datasets distributed with k-way replication in the wide area. We then develop a dynamic co-scheduling algorithm that integrates the scheduling of computation and data movement. Using time-varying visualization as the driving application, we demonstrate that our co-scheduling approach improves not only application performance but also server utilization at a very reasonable cost.
14698607
Statistical Multiplexing Over DSL Networks
Most previous work in statistical multiplexing only considered the case where the link transmission rates are fixed. In this paper, we consider statistical multiplexing in networks with adaptive transmission rates, with focus on DSL broadband access networks. This requires a jointly optimized allocation of buffer space and transmission bandwidth to traffic flows, which takes the flow traffic characteristics, the user QoS requirements, and the user interactions at the physical layer into consideration. Using the effective bandwidth concept, we propose a class of alternate maximization (AM) algorithms (AM-D and AM-M), which solve the statistical multiplexing problem for both delay insensitive data traffic and delay sensitive multimedia traffic. With low complexity as a design goal, the AM algorithms incorporate our recently proposed autonomous spectrum balancing (ASB) algorithm, which was originally designed for DSL physical layer spectrum management. Our numerical results show that the AM algorithms combines the gain due to statistical multiplexing and that due to spectrum management.
6888787
Distributed data management for large volume visualization
We propose a distributed data management scheme for large data visualization that emphasizes efficient data sharing and access. To minimize data access time and support users with a variety of local computing capabilities, we introduce an adaptive data selection method based on an "enhanced time-space partitioning" (ETSP) tree that assists with effective visibility culling, as well as multiresolution data selection. By traversing the tree, our data management algorithm can quickly identify the visible regions of data, and, for each region, adaptively choose the lowest resolution satisfying user-specified error tolerances. Only necessary data elements are accessed and sent to the visualization pipeline. To further address the issue of sharing large-scale data among geographically distributed collaborative teams, we have designed an infrastructure for integrating our data management technique with a distributed data storage system provided by logistical networking (LoN). Data sets at different resolutions are generated and uploaded to LoN for wide-area access. We describe a parallel volume rendering system that verifies the effectiveness of our data storage, selection and access scheme.
2569639
Visibility culling for time-varying volume rendering using temporal occlusion coherence
Typically there is a high coherence in data values between neighboring time steps in an iterative scientific software simulation; this characteristic similarly contributes to a corresponding coherence in the visibility of volume blocks when these consecutive time steps are rendered. Yet traditional visibility culling algorithms were mainly designed for static data, without consideration of such potential temporal coherency. We explore the use of temporal occlusion coherence (TOC) to accelerate visibility culling for time-varying volume rendering. In our algorithm, the opacity of volume blocks is encoded by means of plenoptic opacity functions (POFs). A coherence-based block fusion technique is employed to coalesce time-coherent data blocks over a span of time steps into a single, representative block. Then POFs need only be computed for these representative blocks. To quickly determine the subvolumes that do not require updates in their visibility status for each subsequent time step, a hierarchical "TOC tree" data structure is constructed to store the spans of coherent time steps. To achieve maximal culling potential, while remaining conservative, we have extended our previous POP into an optimized POP (OPOP) encoding scheme for this specific scenario. To test our general TOC and OPOF approach, we have designed a parallel time-varying volume rendering algorithm accelerated by visibility culling. Results from experimental runs on a 32-processor cluster confirm both the effectiveness and scalability of our approach.