Benchmarking Grid Applications for Performance and Scalability Predictions

2010 ◽  
pp. 89-121 ◽  
Author(s):  
Radu Prodan ◽  
Farrukh Nadeeem ◽  
Thomas Fahringer
Keyword(s):  
Resource Allocation ◽  
Real Time ◽  
Real World ◽  
Experimental Results ◽  
Problem Size ◽  
Grid Environment ◽  
Computational Costs ◽  
Grid Applications ◽  
Grid Resources ◽  
Grid Site

Application benchmarks can play a key role in analyzing and predicting the performance and scalability of Grid applications, serve as an evaluation of the fitness of a collection of Grid resources for running a specific application or class of applications (Tsouloupas & Dikaiakos, 2007), and help in implementing performance-aware resource allocation policies of real time job schedulers. However, application benchmarks have been largely ignored due to diversified types of applications, multi-constrained executions, dynamic Grid behavior, and heavy computational costs. To remedy these, the authors present an approach taken by the ASKALON Grid environment that computes application benchmarks considering variations in the problem size of the application and machine size of the Grid site. Their system dynamically controls the number of benchmarking experiments for individual applications and manages the execution of these experiments on different Grid sites. They present experimental results of our method for three real-world applications in the Austrian Grid environment.

scholarly journals OFCOD: On the Fly Clustering Based Outlier Detection Framework

Data ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. 1
Author(s):  
Ahmed Elmogy ◽  
Hamada Rizk ◽  
Amany M. Sarhan
Keyword(s):  
Data Mining ◽  
Image Processing ◽  
Intrusion Detection ◽  
Real Time ◽  
Outlier Detection ◽  
Real World ◽  
Medical Data ◽  
Experimental Results ◽  
Real Time Applications ◽  
Real World Datasets

In data mining, outlier detection is a major challenge as it has an important role in many applications such as medical data, image processing, fraud detection, intrusion detection, and so forth. An extensive variety of clustering based approaches have been developed to detect outliers. However they are by nature time consuming which restrict their utilization with real-time applications. Furthermore, outlier detection requests are handled one at a time, which means that each request is initiated individually with a particular set of parameters. In this paper, the first clustering based outlier detection framework, (On the Fly Clustering Based Outlier Detection (OFCOD)) is presented. OFCOD enables analysts to effectively find out outliers on time with request even within huge datasets. The proposed framework has been tested and evaluated using two real world datasets with different features and applications; one with 699 records, and another with five millions records. The experimental results show that the performance of the proposed framework outperforms other existing approaches while considering several evaluation metrics.

scholarly journals A Weight-based Query Forwarding Technique for Super-peer-based Grid Resource Discovery

2017 ◽  
Vol 7 (1) ◽  
pp. 1398-1404
Author(s):  
M. Mollamotalebi ◽  
R. Maghami ◽  
A. S. Ismail
Keyword(s):  
Response Time ◽  
Resource Discovery ◽  
Search Process ◽  
Grid Resource ◽  
Grid Environment ◽  
Grid Applications ◽  
Computing Environments ◽  
Grid Resources ◽  
Grid Resource Discovery ◽  
Super Peer

Grid computing environments include heterogeneous resources shared by a large number of computers to handle data and process intensive applications. The required resources must be accessible for the grid applications on demand, which makes resource discovery a critical service. In recent years, different techniques are provided to index and discover grid resources. Response time and message load during the search process highly affect the efficiency of resource discovery. This paper proposes a technique to forward the queries based on the resource types accessible through each neighbor in super-peer-based grid resource discovery approaches. The proposed technique is simulated in GridSim and the experimental results indicated that it is able to reduce the response time and message load during the search process especially when the grid environment contains a large number of nodes.

Resource Allocation Mechanism with New Models for Grid Environment

2013 ◽  
Vol 5 (2) ◽  
pp. 1-26
Author(s):  
Kuppani Sathish ◽  
A. Rama Mohan Reddy
Keyword(s):  
Resource Allocation ◽  
Waiting Time ◽  
Vital Role ◽  
Allocation Mechanism ◽  
Grid Resource ◽  
Grid Environment ◽  
Grid Resources ◽  
Utilization Cost ◽  
Resource Allocation Mechanism ◽  
Grid Resource Allocation

Resource allocation is playing a vital role in grid environment because of the dynamic and heterogeneous nature of grid resources. Literature offers numerous studies and techniques to solve the grid resource allocation problem. Some of the drawbacks occur during grid resource allocation are low utilization, less economic reliability and increased waiting time of the jobs. These problems were occurred because of the inconsiderable level in the code of allocating right resources to right jobs, poor economic model and lack of provision to minimize the waiting time of jobs to get their resources. So, all these drawbacks need to be solved in any upcoming resource allocation technique. Hence in this paper, the efficiency of the resource allocation mechanism is improved by proposing two allocation models. Both the allocation models have used the Genetic Algorithm to overcome all the aforesaid drawbacks. However, one of the allocation models includes penalty function and the other does not consider the economic reliability. Both the models are implemented and experimented with different number of jobs and resources. The proposed models are compared with the conventional resource allocation models in terms of utilization, cost factor, failure rate and make span.

PROVIDING TIMELY UPDATED SEQUENTIAL PATTERNS IN DECISION MAKING

2010 ◽  
Vol 09 (06) ◽  
pp. 873-888 ◽  
Author(s):  
TZUNG-PEI HONG ◽  
CHING-YAO WANG ◽  
CHUN-WEI LIN
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Real World ◽  
Experimental Results ◽  
Sequential Patterns ◽  
The Past ◽  
Large Databases ◽  
Real World Applications ◽  
Critical Task ◽  
Maintenance Process

Mining knowledge from large databases has become a critical task for organizations. Managers commonly use the obtained sequential patterns to make decisions. In the past, databases were usually assumed to be static. In real-world applications, however, transactions may be updated. In this paper, a maintenance algorithm for rapidly updating sequential patterns for real-time decision making is proposed. The proposed algorithm utilizes previously discovered large sequences in the maintenance process, thus greatly reducing the number of database rescans and improving performance. Experimental results verify the performance of the proposed approach. The proposed algorithm provides real-time knowledge that can be used for decision making.

scholarly journals Distributed and collaborative real-time vehicle detection and classification over the video streams

2017 ◽  
Vol 14 (4) ◽  
pp. 172988141772078 ◽  
Author(s):  
Seda Kul ◽  
Süleyman Eken ◽  
Ahmet Sayar
Keyword(s):  
Information Systems ◽  
Real Time ◽  
Real World ◽  
Traffic Management ◽  
Streaming Media ◽  
Vehicle Detection ◽  
Experimental Results ◽  
Traffic Surveillance ◽  
Video Streams ◽  
Real World Applications

Traffic surveillance cameras are widely used in traffic management and information systems. Processing streaming media in real time is resource and time-consuming processes and even impossible to realize in most real-world applications. To overcome the performance problems in such applications, this article introduces a middleware system based on pub/sub messaging protocol and a dispatcher to preprocess the streams in real time. Experimental results show that proposed middleware may be utilized in different areas such as infrastructure planning, traffic management, and prevention of traffic offenses.

scholarly journals Zone pAth Construction (ZAC) based Approaches for Effective Real-Time Ridesharing

2021 ◽  
Vol 70 ◽  
pp. 119-167
Author(s):  
Meghna Lowalekar ◽  
Pradeep Varakantham ◽  
Patrick Jaillet
Keyword(s):  
Real Time ◽  
Real World ◽  
Ad Hoc ◽  
Experimental Results ◽  
Synthetic Datasets ◽  
The Right ◽  
Online Methods ◽  
Vehicle Capacity

Real-time ridesharing systems such as UberPool, Lyft Line and GrabShare have become hugely popular as they reduce the costs for customers, improve per trip revenue for drivers and reduce traffic on the roads by grouping customers with similar itineraries. The key challenge in these systems is to group the “right” requests to travel together in the “right” available vehicles in real-time, so that the objective (e.g., requests served, revenue or delay) is optimized. This challenge has been addressed in existing work by: (i) generating as many relevant feasible combinations of requests (with respect to the available delay for customers) as possible in real-time; and then (ii) optimizing assignment of the feasible request combinations to vehicles. Since the number of request combinations increases exponentially with the increase in vehicle capacity and number of requests, unfortunately, such approaches have to employ ad hoc heuristics to identify a subset of request combinations for assignment. Our key contribution is in developing approaches that employ zone (abstraction of individual locations) paths instead of request combinations. Zone paths allow for generation of significantly more “relevant” combinations (in comparison to ad hoc heuristics) in real-time than competing approaches due to two reasons: (i) Each zone path can typically represent multiple request combinations; (ii) Zone paths are generated using a combination of offline and online methods. Specifically, we contribute both myopic (ridesharing assignment focussed on current requests only) and non-myopic (ridesharing assignment considers impact on expected future requests) approaches that employ zone paths. In our experimental results, we demonstrate that our myopic approach outperforms the current best myopic approach for ridesharing on both real-world and synthetic datasets (with respect to both objective and runtime). We also show that our non-myopic approach obtains 14.7% improvement over existing myopic approach. Our non-myopic approach gets improvements of up to 12.48% over a recent non-myopic approach, NeurADP. Even when NeurADP is allowed to optimize learning over test settings, results largely remain comparable except in a couple of cases, where NeurADP performs better.

scholarly journals Specification and Runtime Workflow Support in the ASKALON Grid Environment

2007 ◽  
Vol 15 (4) ◽  
pp. 193-211 ◽  
Author(s):  
Radu Prodan
Keyword(s):  
Performance Prediction ◽  
Real World ◽  
Formal Model ◽  
Scientific Workflows ◽  
Experimental Results ◽  
Grid Environment ◽  
Grid Environments ◽  
Real World Applications

We describe techniques to support the runtime execution of scientific workflows in the ASKALON Grid environment. We present a formal model and three middleware services that support in combination the effective execution in heterogeneous and dynamic Grid environments: performance prediction, scheduling, and enactment engine. We validate our techniques with concrete experimental results for two real-world applications executed in the Austrian Grid environment.

A Simple and Practical Method for Incorporating Augmented Reality into the Classroom and Laboratory

2018 ◽  
Author(s):  
Kyle Plunkett
Keyword(s):  
Organic Chemistry ◽  
Augmented Reality ◽  
Real Time ◽  
Real World ◽  
Smart Phone ◽  
Practical Method ◽  
Virtual Expert ◽  
Video Projection

This manuscript provides two demonstrations of how Augmented Reality (AR), which is the projection of virtual information onto a real-world object, can be applied in the classroom and in the laboratory. Using only a smart phone and the free HP Reveal app, content rich AR notecards were prepared. The physical notecards are based on Organic Chemistry I reactions and show only a reagent and substrate. Upon interacting with the HP Reveal app, an AR video projection shows the product of the reaction as well as a real-time, hand-drawn curved-arrow mechanism of how the product is formed. Thirty AR notecards based on common Organic Chemistry I reactions and mechanisms are provided in the Supporting Information and are available for widespread use. In addition, the HP Reveal app was used to create AR video projections onto laboratory instrumentation so that a virtual expert can guide the user during the equipment setup and operation.

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