scholarly journals Fast Dimensional Analysis for Root Cause Investigation in a Large-Scale Service Environment

2020 ◽  
Vol 4 (2) ◽  
pp. 1-23
Author(s):  
Fred Lin ◽  
Keyur Muzumdar ◽  
Nikolay Pavlovich Laptev ◽  
Mihai-Valentin Curelea ◽  
Seunghak Lee ◽  
...  
Keyword(s):  
Dimensional Analysis ◽  
Large Scale ◽  
Service Environment ◽  
Root Cause

scholarly journals Fast Dimensional Analysis for Root Cause Investigation in a Large-Scale Service Environment

2020 ◽  
Vol 48 (1) ◽  
pp. 25-26
Author(s):  
Fred Lin ◽  
Keyur Muzumdar ◽  
Nikolay Pavlovich Laptev ◽  
Mihai-Valentin Curelea ◽  
Seunghak Lee ◽  
...  
Keyword(s):  
Dimensional Analysis ◽  
Large Scale ◽  
Service Environment ◽  
Root Cause

Near-Realtime Server Reboot Monitoring and Root Cause Analysis in a Large-Scale System

2021 ◽  
Author(s):  
Fred Lin ◽  
Bhargav Bolla ◽  
Eric Pinkham ◽  
Neil Kodner ◽  
Daniel Moore ◽  
...  
Keyword(s):  
Large Scale ◽  
Root Cause Analysis ◽  
Cause Analysis ◽  
Large Scale System ◽  
Root Cause

scholarly journals Log Analysis-Based Resource and Execution Time Improvement in HPC: A Case Study

2020 ◽  
Vol 10 (7) ◽  
pp. 2634
Author(s):  
JunWeon Yoon ◽  
TaeYoung Hong ◽  
ChanYeol Park ◽  
Seo-Young Noh ◽  
HeonChang Yu
Keyword(s):  
Execution Time ◽  
High Performance ◽  
Large Scale ◽  
Experimental Result ◽  
Optimization Approach ◽  
Root Cause ◽  
Large Systems ◽  
Job Scheduler ◽  
Performance Computing

High-performance computing (HPC) uses many distributed computing resources to solve large computational science problems through parallel computation. Such an approach can reduce overall job execution time and increase the capacity of solving large-scale and complex problems. In the supercomputer, the job scheduler, the HPC’s flagship tool, is responsible for distributing and managing the resources of large systems. In this paper, we analyze the execution log of the job scheduler for a certain period of time and propose an optimization approach to reduce the idle time of jobs. In our experiment, it has been found that the main root cause of delayed job is highly related to resource waiting. The execution time of the entire job is affected and significantly delayed due to the increase in idle resources that must be ready when submitting the large-scale job. The backfilling algorithm can optimize the inefficiency of these idle resources and help to reduce the execution time of the job. Therefore, we propose the backfilling algorithm, which can be applied to the supercomputer. This experimental result shows that the overall execution time is reduced.

Schedule delays in engineering, procurement, and construction petrochemical projects in Vietnam

2014 ◽  
Vol 8 (1) ◽  
pp. 3-26 ◽  
Author(s):  
Linh Hong Pham ◽  
Harimurti Hadikusumo
Keyword(s):  
Business Process ◽  
Large Scale ◽  
Business Models ◽  
Case Analysis ◽  
Clear Understanding ◽  
Content Type ◽  
Purposive Sampling ◽  
Root Cause ◽  
Schedule Delay ◽  
Cross Case Analysis

Purpose – Petrochemical projects play a very important role in the economic development of Vietnam. For the past ten years, many large-scale petrochemical plants have been developed using the engineering, procurement and construction (EPC) project delivery system for completing the project faster. However, many projects have suffered from schedule delays. In order to solve the delay problem, a clear understanding of the EPC business model and its delays problems are studied in this research. A qualitative research method by using case study on selected EPC projects was adopted. This paper aims to define the current business models used in the Vietnamese petrochemical industry and explores the root cause of delays. Design/methodology/approach – The research methodology used in this study is multiple case studies by purposive sampling on EPC projects. This is chosen due to the limited number of EPC projects in petrochemical in Vietnam and to obtain schedule delay factors from both delayed and on-time projects. In this purposive sampling, the researcher decided on what needs to know and sets out to find the people who can and are willing to share their information. From each project, project manager and project engineer were interviewed to understand the delay factors in their EPC projects. Data from the interview were analyzed by using “pattern coding” described by Miles and Huberman. Then, cross-case analysis was used to identify the common and unique factors occurring in each case. By comparing the three cases, the authors can identify the delay factors in EPC petrochemical in Vietnam. Findings – By interviewing the management level officers in three cases and performing exploratory work on the secondary data, it was observed that the local and foreign contractors of EPC projects in Vietnam have generally similar business process. Then, the codes were grounded based on the EPC business process, and subjected to the cross-case analysis. The root cause of problems in each phase was provided. Originality/value – The paper fulfills an identified root cause of EPC projects in Vietnam.

Prediction of Social Influence for Provenance of Misinformation in Online Social Network Using Big Data Approach

2020 ◽  
Author(s):  
Kumaran P ◽  
Rajeswari Sridhar
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Law Enforcement ◽  
Online Social Networks ◽  
Large Scale ◽  
Online Social Network ◽  
Root Cause ◽  
Minimum Number ◽  
Targeted Marketing ◽  
Implicit And Explicit

Abstract Online social networks (OSNs) is a platform that plays an essential role in identifying misinformation like false rumors, insults, pranks, hoaxes, spear phishing and computational propaganda in a better way. Detection of misinformation finds its applications in areas such as law enforcement to pinpoint culprits who spread rumors to harm the society, targeted marketing in e-commerce to identify the user who originates dissatisfaction messages about products or services that harm an organizations reputation. The process of identifying and detecting misinformation is very crucial in complex social networks. As misinformation in social network is identified by designing and placing the monitors, computing the minimum number of monitors for detecting misinformation is a very trivial work in the complex social network. The proposed approach determines the top suspected sources of misinformation using a tweet polarity-based ranking system in tandem with sarcasm detection (both implicit and explicit sarcasm) with optimization approaches on large-scale incomplete network. The algorithm subsequently uses this determined feature to place the minimum set of monitors in the network for detecting misinformation. The proposed work focuses on the timely detection of misinformation by limiting the distance between the suspected sources and the monitors. The proposed work also determines the root cause of misinformation (provenance) by using a combination of network-based and content-based approaches. The proposed work is compared with the state-of-art work and has observed that the proposed algorithm produces better results than existing methods.

Scaling Effect on Dynamic Impact Response of Structures in Fluid Fields

2013 ◽  
Author(s):  
Zhongheng Guo ◽  
Lingyu Sun ◽  
Taikun Wang ◽  
Junmin Du ◽  
Han Li ◽  
...  
Keyword(s):  
Numerical Simulation ◽  
Dimensional Analysis ◽  
Large Scale ◽  
Scaling Laws ◽  
Scaling Law ◽  
Fluid Pressure ◽  
Structural Safety ◽  
Scale Model ◽  
Small Scale ◽  
Water Tank

At the conceptual design phase of a large-scale underwater structure, a small-scale model in a water tank is often used for the experimental verification of kinematic principles and structural safety. However, a general scaling law for structure-fluid interaction (FSI) problems has not been established. In the present paper, the scaling laws for three typical FSI problems under the water, rigid body moves at a given kinematic equation or is driven by time-dependent fluids with given initial condition, as well as elastic-plastic body moves and then deforms subject to underwater impact loads, are investigated, respectively. First, the power laws for these three types of FSI problems were derived by dimensional analysis method. Then, the laws for the first two types were verified by numerical simulation. In addition, a multipurpose small-scale water sink test device was developed for numerical model updating. For the third type of problem, the dimensional analysis is no longer suitable due to its limitation on identifying the fluid pressure and structural stress, a simulation-based procedure for dynamics evaluation of large-scale structure was provided. The results show that, for some complex FSI problems, if small-scale prototype is tested safely, it doesn’t mean the full-scale product is also safe if both their pressure and stress are the main concerns, it needs further demonstration, at least by numerical simulation.

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