Engineering Commons^™

Parallelization Of Geant4 Using Top-C And Marshalgen, Gene D. Cooperman, Viet Ha Nguyen, Igor Maliutov

Gene D. Cooperman

Geant4 is a very large, highly accurate toolkit for Monte Carlo simulation of particle-matter interaction. It has been applied to high-energy physics, cosmic ray modeling, radiation shields, radiation therapy, mine detection, and other areas. Geant4 is being used to help design some high energy physics experiments (notably CMS and Atlas) to be run on the future large hadron collider: the largest particle collider in the world. The parallelization, ParGeant4, represents a challenge due to the unique characteristics of Geant4: (i) complex object-oriented design; (ii) intrinsic use of templates and abstract classes to be instantiated later by the end user; (iii) …

Tree-Based Partition Querying: A Methodology For Computing Medoids In Large Spatial Datasets, Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou

Kyriakos MOURATIDIS

Besides traditional domains (e.g., resource allocation, data mining applications), algorithms for medoid computation and related problems will play an important role in numerous emerging fields, such as location based services and sensor networks. Since the k-medoid problem is NP hard, all existing work deals with approximate solutions on relatively small datasets. This paper aims at efficient methods for very large spatial databases, motivated by: (i) the high and ever increasing availability of spatial data, and (ii) the need for novel query types and improved services. The proposed solutions exploit the intrinsic grouping properties of a data partition index in order …

Anonymous Query Processing In Road Networks, Kyriakos Mouratidis, Man Lung Yiu

Kyriakos MOURATIDIS

The increasing availability of location-aware mobile devices has given rise to a flurry of location-based services (LBSs). Due to the nature of spatial queries, an LBS needs the user position in order to process her requests. On the other hand, revealing exact user locations to a (potentially untrusted) LBS may pinpoint their identities and breach their privacy. To address this issue, spatial anonymity techniques obfuscate user locations, forwarding to the LBS a sufficiently large region instead. Existing methods explicitly target processing in the euclidean space and do not apply when proximity to the users is defined according to network distance …

On-Line Discovery Of Hot Motion Paths, Dimitris Sacharidis, Kostas Patroumpas, Manolis Terrovitis, Verena Kantere, Michalis Potamias, Kyriakos Mouratidis, Timos Sellis

Kyriakos MOURATIDIS

We consider an environment of numerous moving objects, equipped with location-sensing devices and capable of communicating with a central coordinator. In this setting, we investigate the problem of maintaining hot motion paths, i.e., routes frequently followed by multiple objects over the recent past. Motion paths approximate portions of objects' movement within a tolerance margin that depends on the uncertainty inherent in positional measurements. Discovery of hot motion paths is important to applications requiring classification/profiling based on monitored movement patterns, such as targeted advertising, resource allocation, etc. To achieve this goal, we delegate part of the path extraction process to objects, …

Continuous Monitoring Of Spatial Queries In Wireless Broadcast Environments, Kyriakos Mouratidis, Spiridon Bakiras, Dimitris Papadias

Kyriakos MOURATIDIS

Wireless data broadcast is a promising technique for information dissemination that leverages the computational capabilities of the mobile devices in order to enhance the scalability of the system. Under this environment, the data are continuously broadcast by the server, interleaved with some indexing information for query processing. Clients may then tune in the broadcast channel and process their queries locally without contacting the server. Previous work on spatial query processing for wireless broadcast systems has only considered snapshot queries over static data. In this paper, we propose an air indexing framework that 1) outperforms the existing (i.e., snapshot) techniques in …

Optimal Matching Between Spatial Datasets Under Capacity Constraints, Hou U Leong, Kyriakos Mouratidis, Man Lung Yiu, Nikos Mamoulis

Kyriakos MOURATIDIS

Consider a set of customers (e.g., WiFi receivers) and a set of service providers (e.g., wireless access points), where each provider has a capacity and the quality of service offered to its customers is anti-proportional to their distance. The capacity constrained assignment (CCA) is a matching between the two sets such that (i) each customer is assigned to at most one provider, (ii) every provider serves no more customers than its capacity, (iii) the maximum possible number of customers are served, and (iv) the sum of Euclidean distances within the assigned provider-customer pairs is minimized. Although max-flow algorithms are applicable …

Continuous Spatial Assignment Of Moving Users, Leong Hou U, Kyriakos Mouratidis, Nikos Mamoulis

Kyriakos MOURATIDIS

Consider a set of servers and a set of users, where each server has a coverage region (i.e., an area of service) and a capacity (i.e., a maximum number of users it can serve). Our task is to assign every user to one server subject to the coverage and capacity constraints. To offer the highest quality of service, we wish to minimize the average distance between users and their assigned server. This is an instance of a well-studied problem in operations research, termed optimal assignment. Even though there exist several solutions for the static case (where user locations are fixed), …

Shortest Path Computation On Air Indexes, Georgios Kellaris, Kyriakos Mouratidis

Kyriakos MOURATIDIS

Shortest path computation is one of the most common queries in location-based services that involve transportation net- works. Motivated by scalability challenges faced in the mo- bile network industry, we propose adopting the wireless broad- cast model for such location-dependent applications. In this model the data are continuously transmitted on the air, while clients listen to the broadcast and process their queries locally. Although spatial problems have been considered in this environment, there exists no study on shortest path queries in road networks. We develop the rst framework to compute shortest paths on the air, and demonstrate the practicality and …

Preference Queries In Large Multi-Cost Transportation Networks, Kyriakos Mouratidis, Yimin Lin, Man Lung Yiu

Kyriakos MOURATIDIS

Research on spatial network databases has so far considered that there is a single cost value associated with each road segment of the network. In most real-world situations, however, there may exist multiple cost types involved in transportation decision making. For example, the different costs of a road segment could be its Euclidean length, the driving time, the walking time, possible toll fee, etc. The relative significance of these cost types may vary from user to user. In this paper we consider such multi-cost transportation networks (MCN), where each edge (road segment) is associated with multiple cost values. We formulate …

Geant4 Developments And Applications, J. Allison, K. Amako, J. Apostolakis, H. Araujo, P. Arce Dubois, M. Asai, G. Barrand, R. Capra, S. Chauvie, R. Chytracek, G. A. P. Cirrone, Gene D. Cooperman, G. Cosmo, G. Cuttone, G. G. Daquino, M. Donszelmann, M. Dressel, G. Folger, F. Foppiano, J. Generowicz, V. Grichine, S. Guatelli, P. Gumplinger, A. Heikkinen, I. Hrivnacova, A. Howard, S. Incerti, V. Ivanchenko, T. Johnson, F. Jones, T. Koi, R. Kokoulin, M. Kossov, H. Kurashige, V. Lara, S. Larsson, F. Lei, O. Link, F. Longo, M. Maire, A. Mantero, B. Mascialino, I. Mclaren, P. Mendez Lorenzo, K. Minamimoto, K. Murakami, P. Nieminen, L. Pandola, S. Parlati, L. Peralta, J. Perl, A. Pfeiffer, M. G. Pia, A. Ribon, P. Rodrigues, G. Russo, S. Sadilov, G. Santin, T. Sasaki, D. Smith, N. Starkov, S. Tanaka, E. Tcherniaev, B. Tomé, A. Trindade, P. Truscott, L. Urban, M. Verderi, A. Walkden, J. P. Wellisch, D. C. Williams, D. Wright, H. Yoshida

Gene D. Cooperman

Geant4 is a software toolkit for the simulation of the passage of particles through matter. It is used by a large number of experiments and projects in a variety of application domains, including high energy physics, astrophysics and space science, medical physics and radiation protection. Its functionality and modeling capabilities continue to be extended, while its performance is enhanced. An overview of recent developments in diverse areas of the toolkit is presented. These include performance optimization for complex setups; improvements for the propagation in fields; new options for event biasing; and additions and improvements in geometry, physics processes and interactive …

Adaptive Checkpointing For Master-Worker Style Parallelism (Extended Abstract), Gene D. Cooperman, Jason Ansel, Xiaoqin Ma

Gene D. Cooperman

No abstract provided.

Dmtcp: Transparent Checkpointing For Cluster Computations And The Desktop, Jason Ansel, Kapil Arya, Gene D. Cooperman

Gene D. Cooperman

DMTCP (Distributed MultiThreaded CheckPointing) is a transparent user-level checkpointing package for distributed applications. Checkpointing and restart is demonstrated for a wide range of over 20 well known applications, including MATLAB, Python, TightVNC, MPICH2, OpenMPI, and runCMS. RunCMS runs as a 680 MB image in memory that includes 540 dynamic libraries, and is used for the CMS experiment of the Large Hadron Collider at CERN. DMTCP transparently checkpoints general cluster computations consisting of many nodes, processes, and threads; as well as typical desktop applications. On 128 distributed cores (32 nodes), checkpoint and restart times are typically 2 seconds, with negligible run-time …

The Kerf Toolkit For Intrusion Analysis, Javed A. Aslam, Sergey Bratus, David Kotz, Ron Peterson, Brett Tofel, Daniela Rus

Javed A. Aslam

To aid system administrators with post-attack intrusion analysis, the Kerf toolkit provides an integrated front end and powerful correlation and data-representation tools, all in one package.

Towards Software Health Management With Bayesian Networks, Johann Schumann, Ole J. Mengshoel, Ashok Srivastava, Adnan Darwiche

Ole J Mengshoel

More and more systems (e.g., aircraft, machinery, cars) rely heavily on software, which performs safety-critical operations. Assuring software safety though traditional V&V has become a tremendous, if not impossible task, given the growing size and complexity of the software. We propose that iSWHM (Integrated SoftWare Health Management) can increase safety and reliability of high-assurance software systems. iSWHM uses advanced techniques from the area of system health management in order to continuously monitor the behavior of the software during operation, quickly detect anomalies and perform automatic and reliable root-cause analysis, while not replacing traditional V&V. Information provided by the iSWHM system …

Probabilistic Model-Based Diagnosis: An Electrical Power System Case Study, Ole J. Mengshoel, Mark Chavira, Keith Cascio, Adnan Darwiche, Scott Poll, Serdar Uckun

Ole J Mengshoel

We present in this paper a case study of the probabilistic approach to model-based diagnosis. Here, the diagnosed system is a real-world electrical power system (EPS), i.e., the Advanced Diagnstic and Prognostic Testbed (ADAPT) located at the NASA Ames Research Center. Our probabilistic approach is formally well founded and based on Bayesian networks (BNs) and arithmetic circuits (ACs). We pay special attention to meeting two of the main challenges often associated with real-world application of model-based diagnosis technologies: model development and real-time reasoning. To address the challenge of model development, we develop a systematic approach to representing EPSs as BNs, …

Generalized Crowding For Genetic Algorithms, Ole J. Mengshoel, Severino F. Galan

Ole J Mengshoel

Fast Energy Loss Computation And Fuzzy-Based Shunt Capacitor Insertion, Philadelphia University

Philadelphia University, Jordan

No abstract provided.

Understanding The Scalability Of Bayesian Network Inference Using Clique Tree Growth Curves, Ole J. Mengshoel

Ole J Mengshoel

One of the main approaches to performing computation in Bayesian networks (BNs) is clique tree clustering and propagation. The clique tree approach consists of propagation in a clique tree compiled from a BN, and while it was introduced in the 1980s, there is still a lack of understanding of how clique tree computation time depends on variations in BN size and structure. In this article, we improve this understanding by developing an approach to characterizing clique tree growth as a function of parameters that can be computed in polynomial time from BNs, specifically: (i) the ratio of the number of …

Portfolios In Stochastic Local Search: Efficiently Computing Most Probable Explanations In Bayesian Networks, Ole J. Mengshoel, D Roth, D Wilkins

Ole J Mengshoel

Portfolio methods support the combination of different algorithms and heuristics, including stochastic local search (SLS) heuristics, and have been identified as a promising approach to solve computationally hard problems. While successful in experiments, theoretical foundations and analytical results for portfolio-based SLS heuristics are less developed. This article aims to improve the understanding of the role of portfolios of heuristics in SLS. We emphasize the problem of computing most probable explanations (MPEs) in Bayesian networks (BNs). Algorithmically, we discuss a portfolio-based SLS algorithm for MPE computation, Stochastic Greedy Search (SGS). SGS supports the integration of different initialization operators (or initialization heuristics) …

Embedded Systems As Datacenters, Robert Iannucci

Robert A Iannucci

No abstract provided.

Dynamic Pickup And Delivery Problems, Gerardo Berbeglia

Gerardo Berbeglia

No abstract provided.

Joint Feature Selection And Classification For Taxonomic Problems Within Fish Species Complexes, Yixin Chen, Shuqing Huang, Huimin Chen, Henry L. Bart

Huimin Chen

It is estimated that 90% of the world’s species are yet to be discovered and described. The main reason for the slow pace of new species description is that the science of taxonomy can be very laborious. To formally describe a new species, taxonomists have to manually gather and analyze data from large numbers of specimens and identify the smallest subset of external body characters that uniquely diagnose the new species as distinct from all its known relatives. In this paper, we present an automated feature selection and classification scheme using logistic regression with controlled false discovery rate to address …

Diagnosing Intermittent And Persistent Faults Using Static Bayesian Networks, Ole J. Mengshoel, Brian Ricks

Ole J Mengshoel

Both intermittent and persistent faults may occur in a wide range of systems. We present in this paper the introduction of intermittent fault handling techniques into ProDiagnose, an algorithm that previously only handled persistent faults. We discuss novel algorithmic techniques as well as how our static Bayesian networks help diagnose, in an integrated manner, a range of intermittent and persistent faults. Through experiments with data from the ADAPT electrical power system test bed, generated as part of the Second International Diagnostic Competition (DXC-10), we show that this novel variant of ProDiagnose diagnoses intermittent faults accurately and quickly, while maintaining strong …