Yehia El-khatib, Chris Edwards, Michael Mackay and Gareth Tyson. "Providing Grid Schedulers with Passive Network Measurements". In Proceedings of the 18th International IEEE Conference on Computer Communications and Networks: Workshop on Grid and P2P Systems and Applications (GridPeer 2009), San Francisco, CA, USA, August 2-6 2009.
Cloud network management model a novel approach to manage cloud trafficijccsa
Cloud is in the air. More and More companies and personals are connecting to cloud with so many variety
of offering provided by the companies. The cloud services are based on Internet i.e. TCP/IP. The paper
discusses limitations of one of the main existing network management protocol i.e. Simple Network
Management Protocol (SNMP) with respect to the current network conditions. The network traffic is
growing at a high speed. When we talk about the networked environment of cloud, the monitoring tool
should be capable of handling the traffic tribulations efficiently and represent a correct scenario of the
network condition. The proposed Model ‘Cloud Network Management Model (CNMM)’ provides a
comprehensive solution to manage the growing traffic in cloud and trying to improve communication of
manager and agents as in SNMP (the traditional TCP/IP network management protocol). Firstly CNMM
concentrates on reduction of packet exchange between manager and agent. Secondly it eliminates the
counter problems exist in SNMP by having periodic updates from agent without querying by the manager.
For better management we are including managers using virtualized technology. CNMM is a proposed
model with efficient communication, secure packet delivery and reduced traffic. Though the proposed
model supposed to manage the cloud traffic in a better and efficient way, the model is still a theoretical
study, its implementation and results are yet to discover. The model however is the first step towards
development of supported algorithms and protocol. Our further study will concentrate on development of
supported algorithms.
Yehia El-khatib, Chris Edwards, Michael Mackay and Gareth Tyson. "Providing Grid Schedulers with Passive Network Measurements". In Proceedings of the 18th International IEEE Conference on Computer Communications and Networks: Workshop on Grid and P2P Systems and Applications (GridPeer 2009), San Francisco, CA, USA, August 2-6 2009.
Cloud network management model a novel approach to manage cloud trafficijccsa
Cloud is in the air. More and More companies and personals are connecting to cloud with so many variety
of offering provided by the companies. The cloud services are based on Internet i.e. TCP/IP. The paper
discusses limitations of one of the main existing network management protocol i.e. Simple Network
Management Protocol (SNMP) with respect to the current network conditions. The network traffic is
growing at a high speed. When we talk about the networked environment of cloud, the monitoring tool
should be capable of handling the traffic tribulations efficiently and represent a correct scenario of the
network condition. The proposed Model ‘Cloud Network Management Model (CNMM)’ provides a
comprehensive solution to manage the growing traffic in cloud and trying to improve communication of
manager and agents as in SNMP (the traditional TCP/IP network management protocol). Firstly CNMM
concentrates on reduction of packet exchange between manager and agent. Secondly it eliminates the
counter problems exist in SNMP by having periodic updates from agent without querying by the manager.
For better management we are including managers using virtualized technology. CNMM is a proposed
model with efficient communication, secure packet delivery and reduced traffic. Though the proposed
model supposed to manage the cloud traffic in a better and efficient way, the model is still a theoretical
study, its implementation and results are yet to discover. The model however is the first step towards
development of supported algorithms and protocol. Our further study will concentrate on development of
supported algorithms.
Network Traffic Anomaly Detection Through Bayes NetGyan Prakash
Traffic anomaly detection using high performance measurement systems offers the possibility of improving the speed of
detection and enabling detection of important, short lived anomalies. In this paper we investigate the problem of detecting anomalies
using traffic measurements with fine-grained time stamps. We develop a new detection algorithm (called KS3) that utilizes a Bayes
Net to efficiently consider multiple input signals and to explicitly define what is considered “anomalous”.
The input signals considered KS3 are traffic volumes and correlations between ingress egress packet and bit rates. These
complementary signals enable identification of expanded range of anomalies. Using a set of high precision traffic measurements
collected at our campus border router over a 10 month period and an annotated anomaly log supplied by our network operators, we
show that KS3 is highly accurate, identifying 86% of the anomalies listed in the log. Compared with well known time series-based
and wavelet-based detectors, this represents over a 20% improvement in accuracy. Investigation of events identified by KS3 that did
not appear in the operator log indicate many are, in fact, true positives. Deployment of Ks3 in an operational environment supports
this by showing zero false positives during initial tests.
NON-INTRUSIVE REMOTE MONITORING OF SERVICES IN A DATA CENTREcscpconf
Non-intrusive remote monitoring of data centre services should be such that it does not require
(or minimal) modification of legacy code and standard practices. Also, allowing third party
agent to sit on every server in a data centre is a risk from security perspective. Hence, use of
standard such as SNMPv3 is advocated in this kind of environment. There are many tools (open
source or commercial) available which uses SNMP; but we observe that most of the tools do not
have an essential feature for auto-discovery of network. In this paper we present an algorithm
for remote monitoring of services in a data centre. The algorithm has two stages: 1) auto
discovery of network topology and 2) data collection from remote machine. Further, we
compare SNMP with WBEM and identify some other options for remote monitoring of services
and their advantages and disadvantages.
IEEE 2014 DOTNET PARALLEL DISTRIBUTED PROJECTS A system-for-denial-of-service...IEEEMEMTECHSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
ADRISYA: A FLOW BASED ANOMALY DETECTION SYSTEM FOR SLOW AND FAST SCANIJNSA Journal
Attackers perform port scan to find reachability, liveness and running services in a system or network. Current day scanning tools provide different scanning options and capable of evading various security tools like firewall, IDS and IPS. So in order to detect and prevent attacks in the early stages, an accurate detection of scanning activity in real time is very much essential. In this paper we present a flow based protocol behaviour analysis system to detect TCP based slow and fast scan. This system provides scalable, accurate and generic solution to TCP based scanning by means of automatic behaviour analysis of the network traffic. Detection capability of proposed system is compared with SNORT and result proves the high detection rate of the system over SNORT.
FLOODING ATTACK DETECTION AND MITIGATION IN SDN WITH MODIFIED ADAPTIVE THRESH...IJCNCJournal
Flooding attack is a network attack that sends a large amount of traffic to the victim networks or services to cause denial-of-service. In Software-Defined Networking (SDN) environment, this attack might not only breach the hosts and services but also the SDN controller. Besides, it will also cause a disconnection of links between the controller and the switches. Thus, an effective detection and mitigation technique of flooding attacks is required. Statistical analysis techniques are widely used for the detection and mitigation of flooding attacks. However, the effectiveness of these techniques strongly depends on the defined threshold. Defining the static threshold is a tedious job and most of the time produces a high false positive alarm .In this paper, we proposed the dynamic threshold which is calculated using modified adaptive threshold algorithm (MATA). The original ATA is based on the Exponential Weighted Moving Average (EWMA) formula which produces the high number of false alarms. To reduce the false alarms, the alarm signal will only be generated after a minimum number of consecutive violations of the threshold. This, however, has increased the false negative rate when the network is under attack. In order to reduce this false negative rate, MATA adapted the baseline traffic info of the network infrastructure. The comparative analysis of MATA and ATA are performed through the measurement of false negative rate, and accuracy of detection rate. Our experimental results show that MATA is able to reduce false negative rates up to 17.74% and increase the detection accuracy of 16.11%over the various types of flooding attacks at the transport layer.
Network analysis Using Wireshark Lesson 12 - bandwidth and delay issuesYoram Orzach
Network analysis Using Wireshark Lesson 12
By the end of this lesson, the participant will be able to:
▫ Perform bandwidth and throughput tests
▫ Measure applications throughput
▫ Understand the impact of delay and jitter on network applications
OpenFlow Security Threat Detection and Defense ServicesEswar Publications
The emergence of OpenFlow-capable switches de- couples control plane from the data flow plane so that they support programmable network and allow network administrators to have programmable central control of network traffic via a controller. The controller and its communication with switches and users become a malicious attack target. This paper explores major possible security threats and attacks on the controller of SDN and proposes a new approach to automatically and dynamically detect and monitor malicious behaviors on flow message passing and defend such attacks to ensure the security of SDN. We have built a FlowEye prototype at service level on Mininet API, and simulation tests are done on two feasible attacks on OpenFlow Beacon platform. The paper provides the feasibility study of such attacks and defense protection strategies in SDN security research..
lesson 2- Network analysis Using Wireshark introduction to cellular feb-2017Yoram Orzach
• By the end of this lesson, the you will be able to:
▫ Understand the main menus and commands of Wireshark
▫ Start capturing data with the Wireshark software
▫ Configure basic parameters with Wireshark
Yoram Orzach is Experienced Instructor in the areas of IP technologies, network design, network analysis and optimization and network forensics, providing courses based on strong theoretical background and real-world case studies, based on many years of training and field experience world-wide.
Optimal remote access trojans detection based on network behaviorIJECEIAES
RAT is one of the most infected malware in the hyper-connected world. Data is being leaked or disclosed every day because new remote access Trojans are emerging and they are used to steal confidential data from target hosts. Network behavior-based detection has been used to provide an effective detection model for Remote Access Trojans. However, there is still short comings: to detect as early as possible, some False Negative Rate and accuracy that may vary depending on ratio of normal and malicious RAT sessions. As typical network contains large amount of normal traffic and small amount of malicious traffic, the detection model was built based on the different ratio of normal and malicious sessions in previous works. At that time false negative rate is less than 2%, and it varies depending on different ratio of normal and malicious instances. An unbalanced dataset will bias the prediction model towards the more common class. In this paper, each RAT is run many times in order to capture variant behavior of a Remote Access Trojan in the early stage, and balanced instances of normal applications and Remote Access Trojans are used for detection model. Our approach achieves 99 % accuracy and 0.3% False Negative Rate by Random Forest Algorithm.
Wireless sensor network (WSN) iscomposed of tiny sensors and they are powered by energy-constraint
battery. The continual need to utilize limited bandwidth to absorb most of the packets has led to a great
deal of research in the field of data compression. WSN has been exploited to balance the maintenance of
readable information content with acceptable error and the cost of energy consumed by the collecting
nodes during the compression. In this paper, we compared two compression techniques: JPEGand
watermark authentication. We applied both techniques and used error measurement to indicate system
performance regardless of the number of execution instructions. Wefound that it is not enough to use
errormeasurement onlybut the number of executing instructions must also beconsidered. The digital
watermark approach showed a lower average error compared to JPEGapproach. However, there were
fewer instructions in the JPEG approach compared towatermark approach.
Network Traffic Anomaly Detection Through Bayes NetGyan Prakash
Traffic anomaly detection using high performance measurement systems offers the possibility of improving the speed of
detection and enabling detection of important, short lived anomalies. In this paper we investigate the problem of detecting anomalies
using traffic measurements with fine-grained time stamps. We develop a new detection algorithm (called KS3) that utilizes a Bayes
Net to efficiently consider multiple input signals and to explicitly define what is considered “anomalous”.
The input signals considered KS3 are traffic volumes and correlations between ingress egress packet and bit rates. These
complementary signals enable identification of expanded range of anomalies. Using a set of high precision traffic measurements
collected at our campus border router over a 10 month period and an annotated anomaly log supplied by our network operators, we
show that KS3 is highly accurate, identifying 86% of the anomalies listed in the log. Compared with well known time series-based
and wavelet-based detectors, this represents over a 20% improvement in accuracy. Investigation of events identified by KS3 that did
not appear in the operator log indicate many are, in fact, true positives. Deployment of Ks3 in an operational environment supports
this by showing zero false positives during initial tests.
NON-INTRUSIVE REMOTE MONITORING OF SERVICES IN A DATA CENTREcscpconf
Non-intrusive remote monitoring of data centre services should be such that it does not require
(or minimal) modification of legacy code and standard practices. Also, allowing third party
agent to sit on every server in a data centre is a risk from security perspective. Hence, use of
standard such as SNMPv3 is advocated in this kind of environment. There are many tools (open
source or commercial) available which uses SNMP; but we observe that most of the tools do not
have an essential feature for auto-discovery of network. In this paper we present an algorithm
for remote monitoring of services in a data centre. The algorithm has two stages: 1) auto
discovery of network topology and 2) data collection from remote machine. Further, we
compare SNMP with WBEM and identify some other options for remote monitoring of services
and their advantages and disadvantages.
IEEE 2014 DOTNET PARALLEL DISTRIBUTED PROJECTS A system-for-denial-of-service...IEEEMEMTECHSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
ADRISYA: A FLOW BASED ANOMALY DETECTION SYSTEM FOR SLOW AND FAST SCANIJNSA Journal
Attackers perform port scan to find reachability, liveness and running services in a system or network. Current day scanning tools provide different scanning options and capable of evading various security tools like firewall, IDS and IPS. So in order to detect and prevent attacks in the early stages, an accurate detection of scanning activity in real time is very much essential. In this paper we present a flow based protocol behaviour analysis system to detect TCP based slow and fast scan. This system provides scalable, accurate and generic solution to TCP based scanning by means of automatic behaviour analysis of the network traffic. Detection capability of proposed system is compared with SNORT and result proves the high detection rate of the system over SNORT.
FLOODING ATTACK DETECTION AND MITIGATION IN SDN WITH MODIFIED ADAPTIVE THRESH...IJCNCJournal
Flooding attack is a network attack that sends a large amount of traffic to the victim networks or services to cause denial-of-service. In Software-Defined Networking (SDN) environment, this attack might not only breach the hosts and services but also the SDN controller. Besides, it will also cause a disconnection of links between the controller and the switches. Thus, an effective detection and mitigation technique of flooding attacks is required. Statistical analysis techniques are widely used for the detection and mitigation of flooding attacks. However, the effectiveness of these techniques strongly depends on the defined threshold. Defining the static threshold is a tedious job and most of the time produces a high false positive alarm .In this paper, we proposed the dynamic threshold which is calculated using modified adaptive threshold algorithm (MATA). The original ATA is based on the Exponential Weighted Moving Average (EWMA) formula which produces the high number of false alarms. To reduce the false alarms, the alarm signal will only be generated after a minimum number of consecutive violations of the threshold. This, however, has increased the false negative rate when the network is under attack. In order to reduce this false negative rate, MATA adapted the baseline traffic info of the network infrastructure. The comparative analysis of MATA and ATA are performed through the measurement of false negative rate, and accuracy of detection rate. Our experimental results show that MATA is able to reduce false negative rates up to 17.74% and increase the detection accuracy of 16.11%over the various types of flooding attacks at the transport layer.
Network analysis Using Wireshark Lesson 12 - bandwidth and delay issuesYoram Orzach
Network analysis Using Wireshark Lesson 12
By the end of this lesson, the participant will be able to:
▫ Perform bandwidth and throughput tests
▫ Measure applications throughput
▫ Understand the impact of delay and jitter on network applications
OpenFlow Security Threat Detection and Defense ServicesEswar Publications
The emergence of OpenFlow-capable switches de- couples control plane from the data flow plane so that they support programmable network and allow network administrators to have programmable central control of network traffic via a controller. The controller and its communication with switches and users become a malicious attack target. This paper explores major possible security threats and attacks on the controller of SDN and proposes a new approach to automatically and dynamically detect and monitor malicious behaviors on flow message passing and defend such attacks to ensure the security of SDN. We have built a FlowEye prototype at service level on Mininet API, and simulation tests are done on two feasible attacks on OpenFlow Beacon platform. The paper provides the feasibility study of such attacks and defense protection strategies in SDN security research..
lesson 2- Network analysis Using Wireshark introduction to cellular feb-2017Yoram Orzach
• By the end of this lesson, the you will be able to:
▫ Understand the main menus and commands of Wireshark
▫ Start capturing data with the Wireshark software
▫ Configure basic parameters with Wireshark
Yoram Orzach is Experienced Instructor in the areas of IP technologies, network design, network analysis and optimization and network forensics, providing courses based on strong theoretical background and real-world case studies, based on many years of training and field experience world-wide.
Optimal remote access trojans detection based on network behaviorIJECEIAES
RAT is one of the most infected malware in the hyper-connected world. Data is being leaked or disclosed every day because new remote access Trojans are emerging and they are used to steal confidential data from target hosts. Network behavior-based detection has been used to provide an effective detection model for Remote Access Trojans. However, there is still short comings: to detect as early as possible, some False Negative Rate and accuracy that may vary depending on ratio of normal and malicious RAT sessions. As typical network contains large amount of normal traffic and small amount of malicious traffic, the detection model was built based on the different ratio of normal and malicious sessions in previous works. At that time false negative rate is less than 2%, and it varies depending on different ratio of normal and malicious instances. An unbalanced dataset will bias the prediction model towards the more common class. In this paper, each RAT is run many times in order to capture variant behavior of a Remote Access Trojan in the early stage, and balanced instances of normal applications and Remote Access Trojans are used for detection model. Our approach achieves 99 % accuracy and 0.3% False Negative Rate by Random Forest Algorithm.
Wireless sensor network (WSN) iscomposed of tiny sensors and they are powered by energy-constraint
battery. The continual need to utilize limited bandwidth to absorb most of the packets has led to a great
deal of research in the field of data compression. WSN has been exploited to balance the maintenance of
readable information content with acceptable error and the cost of energy consumed by the collecting
nodes during the compression. In this paper, we compared two compression techniques: JPEGand
watermark authentication. We applied both techniques and used error measurement to indicate system
performance regardless of the number of execution instructions. Wefound that it is not enough to use
errormeasurement onlybut the number of executing instructions must also beconsidered. The digital
watermark approach showed a lower average error compared to JPEGapproach. However, there were
fewer instructions in the JPEG approach compared towatermark approach.
International Journals of Marketing and Technology(IJMT) is a refereed research journal which aims to promote the links between management and IT. The journal focuses on issues related to the development and implementation of new methodologies and technologies, which improve the operational objectives of an organization. These include, among others, product development, human resources management, project management, logistics, production management, e-commerce, quality management, financial planning, risk management, decision support systems, General Management, Banking, Insurance, Economics, IT, Computer Science, Cyber Security and emerging trends in allied subjects. Thus, the journal provides a forum for researchers and practitioners for the publication of innovative scholarly research, which contributes to the adoption of a new holistic managerial approach that ensures a technologically, economically, socially and ecologically acceptable deployment of new technologies in business practice.
The simulation is going to deliver a perfect fashion to the system an there is going to be a generation of the system which is considered to be a significant simulator.
Online stream mining approach for clustering network trafficeSAT Journals
Abstract A large number of research have been proposed on intrusion detection system, which leads to the implementation of agent based intelligent IDS (IIDS), Non – intelligent IDS (NIDS), signature based IDS etc. While building such IDS models, learning algorithms from flow of network traffic plays crucial role in accuracy of IDS systems. The proposed work focuses on implementing the novel method to cluster network traffic which eliminates the limitations in existing online clustering algorithms and prove the robustness and accuracy over large stream of network traffic arriving at extremely high rate. We compare the existing algorithm with novel methods to analyse the accuracy and complexity. Keywords— NIDS, Data Stream Mining, Online Clustering, RAH algorithm, Online Efficient Incremental Clustering algorithm
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Analysis of IT Monitoring Using Open Source Software Techniques: A ReviewIJERD Editor
The Network administrators usually rely on generic and built-in monitoring tools for network
security. Ideally, the network infrastructure is supposed to have carefully designed strategies to scale up
monitoring tools and techniques as the network grows, over time. Without this, there can be network
performance challenges, downtimes due to failures, and most importantly, penetration attacks. These can lead to
monetary losses as well as loss of reputation. Thus, there is a need for best practices to monitor network
infrastructure in an agile manner. Network security monitoring involves collecting network packet data,
segregating it among all the 7 OSI layers, and applying intelligent algorithms to get answers to security-related
questions. The purpose is to know in real-time what is happening on the network at a detailed level, and
strengthen security by hardening the processes, devices, appliances, software policies, etc. The Multi Router
Traffic Grapher, or just simply MRTG, is free software for monitoring and measuring the traffic load
on network links. It allows the user to see traffic load on a network over time in graphical form.
Data Structure- Stack operations may involve initializing the stack, using it and then de-initializing it. Apart from these basic stuffs, a stack is used for the following two primary operations −
PUSH, POP, PEEP
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
UiPath Test Automation using UiPath Test Suite series, part 4
RRD Tool and Network Monitoring
1. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Nirma University
SNMP Based Network Monitoring System
Supporting Real-time Visualization Of Network
SWETA DARGAD(12MCEI37)
CSE-INS,
IT,Nirma University
May 22, 2014
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
2. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Project Profile
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
3. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Outline
1 Topics covered in earlier presentations
2 Related Works
3 3 Level layered Design
4 Implementation
5 SNMS- Working Of Modules
6 Case Study: DOS attack
7 Issues Resolved
8 Conclusion
9 Future Work
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
4. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Topics covered in earlier presentations
1 Topics covered in presentation 1
1 Motivation
2 Problem Definition
3 General Introduction Of NMS And SNMP
4 Literature Survey
5 Related Works
6 Study Of Existing Systems
2 Topics covered in presentation 2
1 General Introduction of RRD
2 Working Of RRD
3 Steps To Network Monitoring
4 Selection Of Tools
3 Topics covered in presentation 3
1 Proposed Approach and Tools Used
2 Design And Implementation
3 Results And Discussions
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
5. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Technical Vocabulary
GPL licence : General Public Licence
NMS: Network Monitoring System
MIB : Management Information Base
MS: Management Station
API : Application Programing Interface
RRD : Round Robin Database
Oid: Object Id
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
6. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Key Points
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
7. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Objective
The objective of this research is to provide a standard framework
to use open source and easily avaialble tools and build a Network
Monitoring System in Linux like environment and easy-to-use
front-end.
It is simple to implement with database in RRD Tool and
storage of other required fields in MySql.
It is flexible
Show Network Map which shows targeted graphs to each
device
Allows a variety of network devices, Interfaces, Operating
sytem to be queried.
Provides Ping, and target to measure bandwidth, cpu, web
statistics, memory, disk, ups etc.
Provides a web-based, menu driven presentations of network
metrices graphically.
Discover SNMP attributes about each target.
Alerts via E-mail or Syslog upon a failure of an added deviceCSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
8. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
SNMP
An SNMP-managed network[7] consists of three components.
A Managed Device[8] is an equipment that is in on network
and is SNMP compliant. A managed device can be Routers,
switches, workstations and printers
The agent is typically software that resides on a managed
device.
A managed device[21] can be any piece of equipment that sits
on your data network and is SNMP compliant. Routers,
switches, hubs, workstations, and printers are all examples of
managed devices
A single SNMP message is referred to as a Protocol Data
Unit.
Data is collected from the devices by the SNMP agents that
uses querying by Net-SNMP.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
9. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Layered Structure of SNMP commands
Figure : SNMP commands in a layered Structure
snmp get, getnext and walk are used to retrieve the value of an
object instance and snmpset is used to write a value to object.
get,getnext,set requests are sent on 161 port and trap on 162 port.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
10. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
RRDTool
RRDtool[14] handles time-series data like network bandwidth,
temperatures, CPU load, etc.
The data is stored in a round-robin database (circular buffer),
thus the system storage footprint remains constant over time.
RRD Tool does not store data as we hand it, rather it
re-samples the data and store the re-sampled version of it.
Data arrive roughly 5 minutes but not exactly. It takes actual
arrival time under curve and create new points in time
between interval and make a curve beneath that real curve.
Thus traffic latency will be same but the numbers shown may
differ.
Reasons of indefinite arrival of data may be Query lost or
Device Down
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
11. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
RRDTool Datastructure
Figure : Above image shows that
data stored in RRD is like in a
circular queue. Figure : rrd curve and RRD’s
mechanism to plot datapoints
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
12. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Life of Data in RRD
Figure : This figure shows that the raw data is sampled at definite
interval of time and consolidation is done which is then stored in the
RRA and later it destroys the oldest sample
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
13. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
3 Level layered Design
Figure : Three Level layered model for Network Monitoring Sytem
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
14. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Layer 3
This layer is very important to control and monitor the
network at their end or from anywhere in the organization
A web-application can be used as a Network Management
Station but which can be accessed from any where in network.
This layer consist of modules like Weathermap, graphing,
statistics, and Alarms.
This layer signifies the need of a Web application at first place.
A network Administrator needs to check his network from any
where in the organization or even out-side
He needs to have a ubiquitous access to the networkThese are
HTML pages which show the network devices linked together
as the user’s network.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
15. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Layer3 : NetworkMap Module
This module is connected to Polling Module, Cron and
RRDTool/Database module in Layer 2.
It uses PHP-Weathermap tool to make beautifully crafted
Network Map.
These are HTML pages which show the network devices linked
together as the user’s network.
We need to create a weathermap.conf file and run it.
Here we can insert icons and labels and links to show the
network layout in a beautifully crafted way.
We need to target the rrd’s which we create in Layer2 using
RRDTool.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
16. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Network Map of IPR network
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
17. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Layer3 : Graphing Module
This module is connected to Polling Module and Cron,
RRDTool/Database module and MySQL database in Layer 2.
It uses PHP script which in turn create a shell script where
rrdcreate is used to create rrd and rrdupdate to update it and
the rrdgraph is used to create a graph of the updated rrd.
These graphs are saved in MySQL database by user which he
could later view.
Also the user will add the shell script to the cron to get
updated graphs.
Also graphs of Memory are made and updated by a script to
map the memory of the system
Realtime CPU Usage and Ram Usage is calculated by ”top”.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
18. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Graphing Module
Figure : Graph of Memory usage last Day
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
19. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Layer3 : Statistics Module
This module is connected to Polling Module.
Which inturn sends SNMPGet request PDU at backend to
gather information from the network devices in Layer 1
SNMP Agent on Layer1 sends the SNMPResponse PDU in
reply which is viewed in statistics Module by user.
Figure : PDU format of SNMP Messages
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
20. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Statistics Module
Figure : Interface statistics of router
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
21. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Layer3 : Alarming Module
This module is connected to PHP-ServerMonitor which stores
info in MySQL database.
It generates alert messages and can send those to user by sms
or email.
It uses POP and SMTP to send mails.
It checks whether the servers listed or the services added are
up and running on the selected ports or not.
The ports and services are monitored at a fixed interval
Also Syslogs are generated and stored to keep a track of
which service went down at which time.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
22. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Alarming Module
Figure : Snapshot of Alarming Module
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
23. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Layer 2
The users request is sent to second layer which consists of
Monitoring Server and is also known as ”Functional layer” .
SNMP request are sent to polling module from time to time
as specified in Cron to the SNMP Agents.
Layer 3 gets all its graphs, Networkmap targets, and satistics
from this layer.
These SNMP Requests are sent to the data collection module
in layer 1.
The data from the SNMP Response are sent to RRD Database
which stores this time series data in form of bit-format files.
The data in the rrds are fed to generate graphs or target in
NetworkMap.
Alerts are sent from PHP-Server Monitor to Alarms module in
Layer 3 which are stored in Database.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
24. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Layer 1
This layer is of Net-SNMP , here data collection is done by
Net-SNMP .
This layer is also known as ”Data layer”.
This layer consist of SNMP Agents who reside on the Network
Devices and network devices.
Data is collected from the devices by the SNMP agents that
use querying of Net-SNMP. The response that is generated by
this Layer is sent to layer 2 in the form of SNMP-Reponse.
The devices always need to listen on port 161 to get requests
and the Monitoring server needs to listen on 162 to get trap
probes.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
25. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Layer2: SNMP Request and Response
Figure : NMS sends SNMP request on UDP(User Datagram Protocol)
and on port 161 to the SNMP agent which is daemon[8].SNMP agent
contacts the subagents on the device on internal port and collect relevent
information of SNMP get request and gives SNMP reponse on UDP port
161 and trap on 162.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
26. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Layer2: RRDtool
RRDtool is responsible of generating graphs in layer 3. There
are three(3) basic steps to setting up RRDtool and graphing
Initialize the database : Create the rrd database and prepare it
to accept data using rrdcreate.
Collect the data sets over time: We update the rrd file after
every specified interval using rrdupdate.
Create the graph : Take the data from the rrd database, do
any calculations we want to do on the data and create that
actual graph using rrdgraph
Add to cron tab: The cron job will run to collect data using a
script to enter that data periodically into the database
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
27. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
RRD create
step is the amount of time in seconds we expect data to be
updated into the database
start It can be ”N” for now or time in epochs
DS:pl:GAUGE:120:0:100 DS stands for DataSet followed by
name of data set followed by type of dataset and the 120 is
heatbeat time in seconds followed by start and end points on
graph.
RRA:MAX:0.5:1:1500 Round Robin Archieve Directive: which
defines how many values the RRD database will archieve
followed by type of value here only MAX, 0.5 is a constant, 1
shows no. of steps and 1500 shows no. of steps to store in
database
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
28. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
User Registration
User Needs to Rgister if he is a new User, On clicking on
”Register”
User enters his User Name and ”Password” and Confirm
”Password”.
A php script runs which connects to database ”nms” and
inserts the UserName and encrypted password into table
”users” .
It also checks if the user is already registered and if so it
throws exception ”UserName is already in Use”.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
29. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Dashboard
Once User completes registration He can Login and see the
Dashboard
Dashboard contains frames showing no. of links ”UP” and
”DOWN” using ”NMAP”
Also User see the realtime graph of the Ping to Internal
Router which if down brings the LAN down.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
30. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
NetworkMap Module
The User can see the NetworkMap of external network and
clicking on the router, he can view the architecture of the
network devices connected to internal network in the iframe
User can click on the links and view the graph of the IN/Out
traffic
User see the link status and average traffic on the first glance
itself
Graphs showing the in and out traffic of the link at one click .
Also status of the link with current traffic on NetworkMap.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
31. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Graphing Module
Also We can view bar graphs of CPU usage and RAM usage
in Real-Time. Bellow figure shows snapshot of the same.
These bar charts are showing the statistics of CPU and RAM
usage in beautiful Bar charts which are easy to understand.
User see Memory usage graphs for which a shell script is run
”rrdtool create” to create a rrd, ” rrdtool update” by
command ”free” and ”rrdtool graph” to graph the data.
User can add new graph to the table ”oldgraphs” of any
HOST which has SNMP enabled on it and view them later.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
32. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Ghraphing Module: Diagram
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
33. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Case Study: Denial of Service Attack
Here we conducted an experiment in which we generated a lot
of traffic on a switch so as to do a DOS attack on it. We will
see how Network Monitoring system can point towards such
attacks also. For this we will see the Traffic graphs of the
switch.
Figure : Graph showing Ping Latency of a Switch
Result : The figure shows the switch was down nearly at 3pm.
The Red bar shows that there was 50-100 packet loss.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
34. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Statistics Module
The user can get statistics in a tabular form which is directly
obtained by quering specific Oid of the devices.
System Uptime
No. of Interfaces
Routing Information
Speed of the links on the Interface
In-traffic and Out-traffic of interface
performance counters
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
35. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Statistics Module: Server Statistcs And Related Oids
Figure : This table shows the Oids, sending snmpget to this oid will give
real-time information of the servers
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
36. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Alarming Module
User can add Servers and Services to the database servermon
and table ”psm-startservers” by just click on ”ADD” button.
We need to specify the label , Domain or IP, Port, type of
service and search pattern to add new Server/Service.
Add email of Users to whom the NMS needs to notify in case
of flaws to table ”psm-startusers”.
View Logs which are stored in ”psm-startlog”.
Change Configuration in ”psm-startconfig”.
Also Logs can be saved which store the information about the
service/server that went down along with the time stamp.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
37. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Data Dictionary for Logs
Figure : The Structure Of The Table For Logging
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
38. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Logs generated By Alarming Module
Figure : Logs Generated
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
39. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Denial of Service Attack
CaseWe study the Denial Of Service attack and detection of the
same using a SNMP based Network Monitoring System.
Objective We will see how our SNMS helps in detection of the
attack and Visualization of the network by just monitoring the
traffic and ping statistics of the switches used to design the
network. Also our objective of Collecting Historic Information For
Base-lining And Trending Purposes can be fulfilled or not. We will
monitor the network and try to get some interesting results. Below
diagram shows the network design of the experiment.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
40. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Network Diagram: Denial of Service Attack
Figure : Network Diagram of Scenerio for DOS Attack
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
41. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Case Study: Denial of Service Attack
We design a network of three switches connected to each
other, say Switch A, Switch B and Switch C.
We connect these switches to an external switch which is
connected to 2 workstation , one of which is a server for our
Network Monitoring System , here it is SNMS (SNMP based
Network Monitoring System).
Now we monitor the switches by generating a graph of In/Out
traffic on the interfaces of those switches.
We generated a lot of traffic by TCP flooding on the switch B
so as to do a DOS attack on it.
We will see how Network Monitoring system can point
towards such attacks also. For this we will see the Traffic
graph of the switch before and after the interval of the attack.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
42. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Results: Denial of Service Attack
Figure : Graph Showing Ping Latency Of SwitchB
Result 1 : The above figure is a graph showing ping statistics of a
switch which was down nearing 3pm. This is understood because
the Red bar shows that there was 50-100 packet loss. The
Monitoring Server was trying to ping but it was unavailable.
Latency was 3.91 to ping the device.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
43. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Case Study: Denial of Service Attack
Figure : Graph Showing In/Out
Traffic Of Switch A At Interafce1
Figure : Graph Showing In/Out
Traffic Of Switch A At Interafce3
Result 2 : We connected SwitchA to the external network at
interface 1 and to Switch B at interface 3. The graph of Switch A
at interface1 has Intraffic 11 Mbps but at the time of attack, the
graph is empty, the SNMS server is unable to send packets at the
interval of time when DOS attack. This shows the SNMP get
Request to graph was unable to get the SNMP reply at the time of
DOS attack.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
44. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Issues Resolved
Figure : Issues Resolved
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
45. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Comparison of Various tools with NMS
Figure : Comparison of Various tool with NMS
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
46. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Conclusion
Considering the features of SNMP like flexibility and simplicity
and less load, A SNMP based Network monitoring system is
designed which supports ubiquitous access.
By querying the network devices from time to time graphs can
be plotted for easy understanding of traffic trend.
Real-time visualization of graphs can be added of disk usage,
memory usage, logged in users and ping latency.
Real-time Bar graphs showing CPU and RAM Usage of the
device on oneclick is possible.
NetworkMap shows underlying Network Design at a glance
with link status and in/out traffic. Also in time of flaws the
NMS can send alerts to users in the form of SMS and E-mail.
In case of loop or any such problem NA can sit on his place
and check the device statistics and also can store Ping
Latency of important devices like Routers.
Status of critical switches along with the number of interfacesCSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
47. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Limitations
The framework which we have designed for SNMS is on a
centralized server. All the querying is done from that server
itself in a LAN network. What if the network is WAN, In such
a network this framework will not be able to monitor. In such
environment there would be a need of Distributed Network
Monitoring System.
Nowadays organizations have started adding wireless devices
to network a lot. These wireless devices create a IEEE 802.11
wireless networks. SNMP is capable of monitoring such a
network. We have not added wireless devices in our objective
to be monitored.
Our project deals with only the network monitoring and not
the Network Management. We have used only SNMP get
commands, But user cannot set the OId which are
READ/WRITE Oids ex: System Information like System
Name, Location.CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
48. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Future Work
SNMP based Distributed Network Monitoring.
SNMP based Network Monitoring of Wireless devices.
Network Management using SNMP.
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
49. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
TimeLine
Figure : Timeline of Project
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
50. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
References
D. Harrington, R. Presuhn, B. Wijnen. ”RFC 3411: An Architecture for Describing Simple Network
Management Protocol (SNMP) Management Frameworks” , IETF, December 2002.
M. Rose, K. McCloghrie. ”RFC 1155: Structure and Identification of Management Information for
TCP/IP-based Internets” , IETF , May 1990
Ranganai Chaparadza,” On designing SNMP based monitoring systems supporting ubiquitous access and
real-time visualization of traffic flow in the network,using low cost tools”, Jounal 13th IEEE International
Conference on Networks,2005
Authors Zeng, Wenxian Wang, Yue ” Design and Implementation of Server Monitoring System Based on
SNMP”, International Joint Conference on Artificial Intelligence, Jounal 2009
Paul Moceri, ”SNMP and Beyond: A Survey of Network Performance Monitoring Tools”
Chakchai Netphakdee, Chinnakorn Wijitsopon, Kasidit ” Web-based Automatic Network Discovery / Map
Systems”,Issue Iccaie ,Year 2011.
Paul Simoneau,” SNMP Network Management” ,1999 .
Douglas R.Mauro and KevinJ.Schmidt, ”Essential SNMP”,Book by OREILLY,2009.
W. Stallings,” SNMP, SNMPv2, and RMON: Practical Network Management, MA Addison-Wesley, 1996.
William Stallings,” SNMP and SNMPv2: The Infrastructure for Network Management”,IEEE
Communications Magazine, March 1998
M. Rose,” The Simple Book: An introduction to Network Management” 3rd ed., Upper Saddle River, NJ:
Prentice Hall, 1996.
Moceri, Paul,”SNMP and Beyond : A Survey of Network Performance Monitoring Tools”, White paper
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network
51. Outline Literarture Survey 3 Level layered Design Implementation SNMS Case Study Conclusion References
Demo
Demo
CSE Department CSE-INS,IT,Nirma University
SNMP Based Network Monitoring System Supporting Real-time Visualization Of Network