Analysis Framework of Freemodbus

2013 ◽  
Vol 765-767 ◽  
pp. 1610-1613
Author(s):  
Wen Xia Zhang ◽  
Yan Wang ◽  
Shu Hua Li
Keyword(s):  
Product Design ◽  
Data Model ◽  
Network Protocol ◽  
Protocol Stack ◽  
Serial Links ◽  
Analysis Framework ◽  
Network Layer ◽  
Industrial Manufacturing ◽  
Modbus Protocol ◽  
Transmission Models

Modbus is a popular network protocol in the industrial manufacturing environment. A modbus communication stack requires two layers:the modbus application protocol which defines the data model and functions and a Network layer. The FreeMODBUS provides an implementation of the modbus application protocol and supports RTU/ASCII transmission models. The paper introduces the analysis of FreeMODBUSs whole framework and the serial links implementation. According to the analysis, it is easily to realize the modbus protocol stack on the chip which FreeMODBUS hasnt realized and so quickly to finish the product design.

Research on Rapid Detection Algorithm Based on Property Choosing Tree

2012 ◽  
Vol 505 ◽  
pp. 386-392
Author(s):  
Neng Shan Feng ◽  
Zhong Ming Yang
Keyword(s):  
Decision Tree ◽  
Rapid Detection ◽  
Detection Algorithm ◽  
Construction Method ◽  
The State ◽  
Transport Layer ◽  
Network Protocol ◽  
Protocol Stack ◽  
Link Layer ◽  
Network Layer

The construction method used by detection engine Snort-NG based on ID3 decision tree has the problem of excessive memory occupancy. The idea that the test properties are chosen according to the gradation of rule property in network protocol stack was presented in this paper; that is, the property of link layer first determined, and then network layer and transport layer. The atomicity of the value of these properties were preserved and the values of these properties were treated as a whole. The results of experiment showed that the occupancy of memory was much less in the state of non-trivial property being very common with this approach.

CAE Data Management Using Traditional PDM Systems

2004 ◽  
Author(s):  
Alhad A. Joshi
Keyword(s):  
Data Management ◽  
Product Design ◽  
Data Model ◽  
Process Management ◽  
Low Cost ◽  
Data Types ◽  
Physical Test ◽  
Design Alternatives ◽  
Physical Testing ◽  
Warranty Costs

Over the past decade, Computer Aided Engineering (Simulation) has experienced explosive growth being a significant enabler for: 1. Validating product design; 2. Providing low-cost methods for exploring a variety of product design alternatives; 3. Optimizing parts for better service performance; 4. Reducing dependence on physical testing; 5. Reducing warranty costs; 6. Achieving faster time to market. This rapid growth in the number of simulations performed and the amount of data generated in the absence of any significant data and process management initiatives has led to considerable inefficiencies in the CAE domain. Many companies now recognize the need to manage their CAE process and data as well as their desire to leverage their existing PDM systems as the primary repositories of CAE data. Some major issues are: 1. There is a need for a PDM data model to support CAE; 2. The CAE data model can be very complex; 3. There is an immense variety of CAE applications and data types; 4. Many CAE simulations require access to physical test data for input and correlation; 5. Data management discipline is not typically part of the CAE culture today. Despite the unique challenges posed by bringing PDM into the CAE world, the transition could occur faster than it has in the CAD world. This presentation will showcase an approach for managing CAE data in traditional PDM systems. Two working examples of CAE process automation software solutions integrated with CAD and PDM will be discussed. In particular, these applications will show how CAE users can leverage established PDM infrastructure and interact with EDS’ Teamcenter/Enterprise, Teamcenter/Engineering and Dassault Systeme’s SmarTeam through seamless integrations with their CAE systems.

Against Spoofing Attacks in Network Layer

2016 ◽  
pp. 41-56
Author(s):  
Kavisankar L. ◽  
Chellappan C. ◽  
Poovammal E.
Keyword(s):  
Network Security ◽  
Defense Mechanism ◽  
Open Systems ◽  
Denial Of Service ◽  
Internet Protocol ◽  
Network Protocol ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Network Layer ◽  
Open Systems Interconnection

In the context of network security, a spoofing attack is a condition in which one person or a program successfully masquerades as another. This is done by providing counterfeit data with the malicious intention of gaining an illegitimate advantage. Spoofing attack which may be generated in various layer of Open Systems Interconnection model (OSI model) is discussed in this chapter. The chapter ends with discussing about the possible spoofing attacks in network layer and the relevant defense mechanism of the same. The detailed analysis and discussion is made on the spoofing attack over the Network layer because, Denial-of-Service (DoS) and Distributed Denial-of-Service (DDoS) attacks more devastating while using network protocol like Internet Protocol (IP) which have become more of a threat than ever for the past few years.

scholarly journals Implementation of a multi-modal acoustic-optical underwater network protocol stack

2016 ◽  
Author(s):  
Filippo Campagnaro ◽  
Federico Guerra ◽  
Paolo Casari ◽  
Roee Diamant ◽  
Michele Zorzi
Keyword(s):  
Network Protocol ◽  
Protocol Stack

scholarly journals Industrial Cyber-Physical System Evolution Detection and Alert Generation

2019 ◽  
Vol 9 (8) ◽  
pp. 1586 ◽  
Author(s):  
Aitziber Iglesias ◽  
Goiuria Sagardui ◽  
Cristobal Arellano
Keyword(s):  
Monitoring System ◽  
Data Model ◽  
Physical System ◽  
Monitoring Systems ◽  
Cyber Physical System ◽  
Production Lines ◽  
Software Module ◽  
Industrial Manufacturing ◽  
Manufacturing Environments ◽  
Over Time

Industrial Cyber-Physical System (ICPS) monitoring is increasingly being used to make decisions that impact the operation of the industry. Industrial manufacturing environments such as production lines are dynamic and evolve over time due to new requirements (new customer needs, conformance to standards, maintenance, etc.) or due to the anomalies detected. When an evolution happens (e.g., new devices are introduced), monitoring systems must be aware of it in order to inform the user and to provide updated and reliable information. In this article, CALENDAR is presented, a software module for a monitoring system that addresses ICPS evolutions. The solution is based on a data metamodel that captures the structure of an ICPS in different timestamps. By comparing the data model in two subsequent timestamps, CALENDAR is able to detect and effectively classify the evolution of ICPSs at runtime to finally generate alerts about the detected evolution. In order to evaluate CALENDAR with different ICPS topologies (e.g., different ICPS sizes), a scalability test was performed considering the information captured from the production lines domain.

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