ppxscal/embedding_network huggingface dataset:
Large deviations and importance sampling for a tandem network with slow-down
Authors: Paul Dupuis, Kevin Leder, Hui Wang
Venue: Queueing Systems: Theory and Applications (2007)

We consider a variant of the two-node tandem Jackson network where the upstream server reduces its service rate when the downstream queue exceeds some prespecified threshold. The rare event of interest is the overflow of the downstream queue. Based on a game/subsolution approach, we rigorously identify the exponential decay rate of the rare event probabilities and construct asymptotically optimal importance sampling schemes.
An Improved Attribute Selection Measure for Decision Tree Induction
Authors: Dianhong Wang, Liangxiao Jiang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 04 (2007)

Decision tree learning is one of the most widely used and practical methods for inductive inference. A fundamental issue in it is the attribute selection measure. The informa- tion gain measure is the most popular one for addressing this issue. However, a notable disadvantage of it is that it is biased towards selecting attributes with many values. Motivated by this fact, the gain ratio measure penalizes the attributes with many values by incorporating a term called split information. Unfortunately, the gain ratio measure suf- fers from another inevitable practical issue that the denom- inator sometimes is zero or very small. In this paper, we single out an improved attribute selection measure called average gain, which penalizes the attributes with many val- ues by dividing the number of attribute values. We experi- mentally tested its effectiveness using 36 UCI data sets.
BDT
Authors: Montserrat Vaqué, Anna Arola, Carles Aliagas, Gerard Pujadas
Venue: Bioinformatics (2006)

Motivation: AutoGrid/AutoDock is one of the most popular software packages for docking, but its automation is not trivial for tasks such as (1) the virtual screening of a library of ligands against a set of possible receptors; (2) the use of receptor flexibility and (3) making a blind-docking experiment with the whole receptor surface. This is an obstacle for research teams in the fields of Chemistry and the Life Sciences who are interested in conducting this kind of experiment but do not have enough programming skills. To overcome these limitations, we have designed BDT, an easy-to-use graphic interface for AutoGrid/AutoDock. Availability: BDT is available for free, upon request, for non-commercial research. Supplementary information: Contact: gerard.pujadas@urv.cat
Numerical algorithm for the time fractional Fokker-Planck equation
Authors: Weihua Deng
Venue: Journal of Computational Physics (2007)

Anomalous diffusion is one of the most ubiquitous phenomena in nature, and it is present in a wide variety of physical situations, for instance, transport of fluid in porous media, diffusion of plasma, diffusion at liquid surfaces, etc. The fractional approach proved to be highly effective in a rich variety of scenarios such as continuous time random walk models, generalized Langevin equations, or the generalized master equation. To investigate the subdiffusion of anomalous diffusion, it would be useful to study a time fractional Fokker-Planck equation. In this paper, firstly the time fractional, the sense of Riemann-Liouville derivative, Fokker-Planck equation is transformed into a time fractional ordinary differential equation (FODE) in the sense of Caputo derivative by discretizing the spatial derivatives and using the properties of Riemann-Liouville derivative and Caputo derivative. Then combining the predictor-corrector approach with the method of lines, the algorithm is designed for numerically solving FODE with the numerical error O(k^m^i^n^{^1^+^2^@a^,^2^})+O(h^2), and the corresponding stability condition is got. The effectiveness of this numerical algorithm is evaluated by comparing its numerical results for @a=1.0 with the ones of directly discretizing classical Fokker-Planck equation, some numerical results for time fractional Fokker-Planck equation with several different fractional orders are demonstrated and compared with each other, moreover for @a=0.8 the convergent order in space is confirmed and the numerical results with different time step sizes are shown.
A Feasibility Study of a Virtual Storage System for Large Organizations
Authors: H. Howie Huang, John F. Karpovich, Andrew S. Grimshaw
Venue: Proceedings of the 2nd International Workshop on Virtualization Technology in Distributed Computing (2006)

The average PC contains increasingly large amounts of storage with an ever greater amount left unused. There is an opportunity for organizations to harness the vast unused storage capacity on their PCs to create a very large, low cost, shared storage system. What is needed is a virtual storage system to exploit and manage the unused portions of existing PC storage devices and make it reliably accessible to users and applications. We call our vision of such a virtual storage system Storage@desk (SD). This paper describes a study of machine characteristics and usage in a model organization as a first step towards exploring the feasibility of Storage@desk. This paper presents the results of our data collection efforts, our analysis of the data, our simulation results, and our conclusion that a Storage@desk system is indeed feasible and holds promise as a cost effective way to create massive storage systems.
Dynamic workload management for very large data warehouses: juggling feathers and bowling balls
Authors: Stefan Krompass, Harumi Kuno, Umeshwar Dayal, Alfons Kemper
Venue: Proceedings of the 33rd international conference on Very large data bases (2007)

Workload management for business intelligence (BI) queries poses different challenges than those addressed in the online transaction processing (OLTP) context. The fundamental problem is that the execution times of BI queries can range from milliseconds to hours, and it is difficult to estimate these times accurately. Key challenges raised by this problem are how to identify queries that are not performing properly and what to do about them. We propose here a workload management system for controlling the execution of individual queries based on realistic customer service level objectives. In order to validate our proposal, we have implemented an experimental system that includes a dynamic execution controller that leverages fuzzy logic. We present results from a number of experiments that we ran using workloads based on actual industrial workloads and customer objectives that we gathered by interviewing industry practitioners. Our experiments show that even a handful of moderately mis-behaving problem queries can have a significant impact on a workload consisting of thousands of queries. We were surprised when our experiments also demonstrated that false positives -- incorrectly identifying a normal query as a problem -- can also have significant consequences. For those reasons, it is very important that an execution controller be as accurate as possible -- avoiding both false positives and false negatives. Our experiments also validate that our execution controller can markedly improve the execution of a workload that includes problem queries.
Multi-user data sharing in radar sensor networks
Authors: Ming Li, Tingxin Yan, Deepak Ganesan, Eric Lyons, Prashant Shenoy, Arun Venkataramani, Michael Zink
Venue: Proceedings of the 5th international conference on Embedded networked sensor systems (2007)

The emerging of rich sensor networks poses very different design challenges from traditional "mote-class" sensor networks. One important challenge is that these networks are designed to handle the diverse requirements of multiple users. In this work, we demonstrate how multiple end user needs are handled in rich sensor networks using a utility-driven architecture. We instantiate this architecture in the context of geographically distributed wireless radar sensor networks for weather, and demonstrate the real-time operation of the prototype on a radar testbed in Okalahoma.
On k-domination and minimum degree in graphs
Authors: Odile Favaron, Adriana Hansberg, Lutz Volkmann
Venue: Journal of Graph Theory (2008)

A subset S of vertices of a graph G is k-dominating if every vertex not in S has at least k neighbors in S. The k-domination number $\gamma_k(G)$ is the minimum cardinality of a k-dominating set of G. Different upper bounds on $\gamma_{k}(G)$ are known in terms of the order n and the minimum degree $\delta$ of G. In this self-contained article, we present an Erd&ouml;s-type result, from which some of these bounds follow. In particular, we improve the bound $\gamma_{k}(G) \le (2k- \delta - 1)n/(2k -\delta)$ for $(\delta +3)/2 \le k \le \delta - 1$, proved by Chen and Zhou in 1998. Furthermore, we characterize the extremal graphs in the inequality $\gamma_{k}(G) \le kn/(k +1)$, if $k \le \delta$, of Cockayne et al. This characterization generalizes that of graphs realizing $\gamma_1(G) = \gamma(G) = n/2$. &copy; 2007 Wiley Periodicals, Inc. J Graph Theory 57: 33&ndash;40, 2008
Assessment and enhancement of meta-schedulers for multi-site job sharing
Authors: G. Sabin, Vishvesh Sahasrabudhe, P. Sadayappan
Venue: Proceedings of the High Performance Distributed Computing, 2005. HPDC-14. Proceedings. 14th IEEE International Symposium (2005)

Meta-schedulers such as the LSF MultiCluster scheduler and the Moab meta-scheduler (Silver) are being deployed on clusters interconnected over the grid. A primary goal of such meta-schedulers is to share jobs amongst the individual local sites, balancing the load and improving utilization and turnaround time. This work focuses on current methodologies used in implemented meta-schedulers, such as LSF MultiCluster and Silver. The benefits and disadvantages of both centralized and delegated modes are evaluated. Focusing on the negative impact of meta-schedulers to jobs originating from lightly loaded sites, enhancements are proposed and evaluated via trace-driven simulation. It is shown that it is feasible to reduce the detrimental impact on lightly loaded sites while maintaining excellent overall performance.
Learning to control the program evolution process with cultural algorithms
Authors: Elena Zannoni, Robert G. Reynolds
Venue: Evolutionary Computation (1997)

Traditional software engineering dictates the use of modular and structured programming and top-down stepwise refinement techniques that reduce the amount of variability arising in the development process by establishing standard procedures to be followed while writing software. This focusing leads to reduced variability in the resulting products, due to the use of standardized constructs. Genetic programming (GP) performs heuristic search in the space of programs. Programs produced through the GP paradigm emerge as the result of simulated evolution and are built through a bottom-up process, incrementally augmenting their functionality until a satisfactory level of performance is reached. Can we automatically extract knowledge from the GP programming process that can be useful to focus the search and reduce product variability, thus leading to a more effective use of the available resources? An answer to this question is investigated with the aid of cultural algorithms. A new system, cultural algorithms with genetic programming (CAGP), is presented. The system has two levels. The first is the pool of genetic programs (population level), and the second is a knowledge repository (belief set) that is built during the GP run and is used to guide the search process. The microevolution within the population brings about potentially meaningful characteristics of the programs for the achievement of the given task, such as properties exhibited by the best performers in the population. CAGP extracts these features and represents them as the set of the current beliefs. Beliefs correspond to constraints that all the genetic operators and programs must follow. Interaction between the two levels occurs in one direction through the extraction process and, in the other, through the modulation of an individual's program parameters according to which, and how many, of the constraints it follows. CAGP is applied to solve an instance of the symbolic regression problem, in which a function of one variable needs to be discovered. The results of the experiments show an overall improvement on the average performance of CAGP over GP alone and a significant reduction of the complexity of the produced solution. Moreover, the execution time required by CAGP is comparable with the time required by GP alone.
Agent-oriented Petri Net based Modeling of Dynamic Behavior for Wide-area Backup Protection
Authors: Xiaoyang Tong, Xiaoru Wang
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 02 (2007)

The study of Agent-based Wide-Area Backup Protection (WABP) in power system has become a hot. An improved agent-oriented Petri net (AOPN) is proposed to simulate dynamic behaviors of multi-agent system. The general architecture of improved AOPN is set up, as well as formalized definitions, structural properties and theorems to describe Petri net. Agent-oriented Petri net for WABP is constructed; autonomy, corporation, concurrency and robustness characters of WABP agent are designed. The analysis of L3-liveness and consistency of Petri net are given. The reasoning results of three samples illustrate the accurateness of Petri net for WABP and effectiveness of capturing dynamic behaviors. Design errors can be found to make the system being robust and reliable.
Adaptive Scheduling of Parallel Jobs on Functionally Heterogeneous Resources
Authors: Yuxiong He, Hongyang Sun, Wen-Jing Hsu
Venue: Proceedings of the 2007 International Conference on Parallel Processing (2007)

A parallel program usually incurs operations on multiple processing resources, interleaving computations, I/Os, and communications, where each task can only be executed on a processor of a matching category. Many parallel systems also embed special-purpose processors like vector units, floating-point co-processors, and various I/O processors. Presently, there is no provably good scheduling algorithm that ensures efficient use of multiple resources with functional heterogeneity. This paper presents K-RAD, an algorithm that adaptively schedules parallel jobs on multiple processing resources without requiring prior information about the jobs, such as their release times and parallelism profiles. Let K denote the number of categories of heterogenous resources and P_max denote the maximum number of processors among all categories. We show that, for any set of jobs with arbitrary release times, K-RAD is (K +1-1/P_max)- competitive with respect to the makespan. This competitive ratio is provably the best possible for any non-clairvoyant deterministic algorithms for K-resource scheduling. We also show that K-RAD is (4K + 1 - 4K/(|J | + 1))- competitive with respect to the mean response time for any batched job set J . For the special case of K = 1, i.e., scheduling on homogeneous resources, the best existing mean response time bound for online non-clairvoyant algorithm is 2 + \sqrt 3 \approx 3.73 proved by Edmonds et al. in STOC'97. We show that K-RAD is 3-competitive with respect to the mean response time when K = 1, which offers the best competitive ratio to date.
Evaluation of Feature Extraction Methods on Software Cost Estimation
Authors: Burak Turhan, Onur Kutlubay, Ayse Bener
Venue: Proceedings of the First International Symposium on Empirical Software Engineering and Measurement (2007)

This research investigates the effects of linear and non-linear feature extraction methods on the cost estimation performance. We use Principal Component Analysis (PCA) and Isomap for extracting new features from observed ones and evaluate these methods with support vector regression (SVR) on publicly available datasets. Our results for these datasets indicate there is no significant difference between the performances of these linear and non-linear feature extraction methods.
A modified correlation coefficient based similarity measure for clustering time-course gene expression data
Authors: Young Sook Son, Jangsun Baek
Venue: Pattern Recognition Letters (2008)

Gene expression levels are often measured consecutively in time through microarray experiments to detect cellular processes underlying regulatory effects observed and to assign functionality to genes whose function is yet unknown. Clustering methods allow us to group genes that show similar time-course expression profiles and that are thus likely to be co-regulated. The correlation coefficient, the most well-liked similarity measure in the context of gene expression data, is not very reliable in representing the association of two temporal profile patterns. Moreover, the clustering methods with the correlation coefficient generate the same clustering result even when the time points are permuted arbitrarily. We propose a new similarity measure for clustering time-course gene expression data. The proposed measure is based on the correlation coefficient and the two indices representing the concordance of temporal profile patterns and that of the time points at which maximum and minimum expression levels are measured between two profiles, respectively. We applied the hierarchical clustering method with the proposed similarity measure to both synthetic and breast cancer cell line data. We observed favorable results compared to the correlation coefficient based method. The proposed similarity measure is simple to implement, and it is much more consistent for clustering than the correlation coefficient based method according to the cross-validation criterion.
Guest Editors' Introduction: On-Chip Interconnects for Multicores
Authors: Partha Kundu, Li-Shiuan Peh
Venue: IEEE Micro (2007)

This special issue of IEEE Micro brings readers the latest advances in the field of on-chip interconnects for multicores. The guest editors specifically selected articles to focus on novel on-chip networks realized on actual silicon--partly to showcase a few silicon prototypes of on-chip networks being used in multicore processors and SoCs; partly to bring to attention the implementation issues facing architects and designers. Along with six articles that gather insights from the designers of actual on-chip interconnects for multicores, the special issue includes two articles that delve into the design infrastructure support for on-chip networks and an article that summarizes the grand research challenges for realizing next-generation on-chip networks and multicores.
Adaptive Allocation of Independent Tasks to Maximize Throughput
Authors: Bo Hong, Viktor Prasanna
Venue: IEEE Transactions on Parallel and Distributed Systems (2007)

In this paper, we consider the task allocation problem for computing a large set of equal-sized independent tasks on a heterogeneous computing system where the tasks initially reside on a single computer (the root) in the system. This problem represents the computation paradigm for a wide range of applications such as SETI@home and Monte Carlo simulations. We consider the scenario where the systems have a general graph-structured topology, and the computers are capable of concurrent communications and overlapping communications with computation. We show that the maximization of system throughput reduces to a standard network flow problem. We then develop a decentralized adaptive algorithm that solves a relaxed form of the standard network flow problem and maximizes the system throughput. This algorithm is then approximated by a simple decentralized protocol to coordinate the resources adaptively. Simulations are conducted to verify the effectiveness of the proposed approach. For both uniformly distributed and power law distributed systems, close-to-optimal throughput is achieved and improved performance over a bandwidth-centric heuristic is observed. The adaptivity of the proposed approach is also verified through simulations.
Information Fusion Based on Fuzzy Neural Networks in Application of Monitoring Management
Authors: Jiren Xu, Jiasong Cheng, Changbao Wang, Jihai Liu, Xiaofen Yu
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02 (2007)

This paper set up monitoring management of fuzzy neural networks based on number type,semantic type and indefinite information character through the combination of fuzzy classification and neural networks. If general neural networks is given to fuzzy input signal or fuzzy authority value, fuzzy neural networks, which is the system including language computation,logic inference,distributed processing and nonlinear whose performance are just satisfied with processing demand of multi-sensor information fusionmapping, show complementation of fuzzy system and neural networks. This model is applied to monitoring management of plant unit of submarine vapor, and it demonstrate the system can give right judgement of work position.
Assessment of MANET broadcast schemes in the application context of multiplayer video games
Authors: Ahmad Sardouk, Sidi Mohammed Senouci, Nadjib Achir, Khaled Boussetta
Venue: Proceedings of the 6th ACM SIGCOMM workshop on Network and system support for games (2007)

Taking into consideration the popularity of multiplayer games and the tremendous success of wireless networks, we strongly believe that future game engines will benefit from the integration of MANET (Mobile Ad hoc NETworks) technology [1]. Indeed, in addition to the social interests of playing with close located persons, MANET technology will allow players, like a group of kids in a playground, to easily improvise a LAN multiplayer party without any need for an existing wireless network infrastructure. In order to make such scenario a common based reality, several issues still have to be addressed. Among which is the MANET's broadcast problem. In fact, broadcast is a fundamental network service for multiplayer LAN mode. But up to now, the most used scheme for broadcasting in MANET relies on flooding. Unfortunately, this simple scheme leads to high redundancy and collisions. In the context of a multiplayer party supported by mobile terminals, this broadcast storm problem [10], could result into a dramatic reduction of the network energy-based lifetime and to a high variability of the transmission delay. The latter one is know to be a crucial QoS parameter which can significantly affect the game play. In this paper, we evaluate the performance of different MANET broadcast schemes in the context of multiplayer video games. We analyze the capacity of simple flooding, distance based, probability based and self pruning broadcast schemes to satisfy the QoS constraints required by multiplayer games like FPS. Assessment simulations are conducted for both Client/Server and P2P network game architectures.