In this we discuss about DATA RATE LIMITS
Two theoretical formulas were developed to calculate the data rate:
Nyquist bit rate for a noiseless channel
BitRate = 2 * bandwidth * log 2 L
2: Shannon Capacity for a noisy channel
Capacity = bandwidth * log 2 (1 + SNR)
...............
PERFORMANCE (Network PERFORMANCE) :
Bandwidth: ( Bandwidth in Hertz and Bandwidth in Bits per Seconds) :
Throughput:
These above topics covered in this slide
Thanks You!
Contents:
Data Traffic
Congestion
Congestion Control
Quality of Service
Techniques to improve QOS
How QOS is implemented within the Internet
References..
In this we discuss about DATA RATE LIMITS
Two theoretical formulas were developed to calculate the data rate:
Nyquist bit rate for a noiseless channel
BitRate = 2 * bandwidth * log 2 L
2: Shannon Capacity for a noisy channel
Capacity = bandwidth * log 2 (1 + SNR)
...............
PERFORMANCE (Network PERFORMANCE) :
Bandwidth: ( Bandwidth in Hertz and Bandwidth in Bits per Seconds) :
Throughput:
These above topics covered in this slide
Thanks You!
Contents:
Data Traffic
Congestion
Congestion Control
Quality of Service
Techniques to improve QOS
How QOS is implemented within the Internet
References..
P2P systems started emerging in the early 2000s, started with a variety of very popular systems such as #Napster and #Gnutella.
The first very large-scale distributed systems #Napster and #Gnutella had millions, tens of millions, in some cases hundreds of millions of clients communicate with each other at the same time.
DSM system
Shared memory
On chip memory
Bus based multiprocessor
Working through cache
Write through cache
Write once protocol
Ring based multiprocessor
Protocol used
Similarities and differences b\w ring based and bus based
Wireless Communication Networks and Systems 1st Edition Beard Solutions Manualpuriryrap
Full download : http://alibabadownload.com/product/wireless-communication-networks-and-systems-1st-edition-beard-solutions-manual/
Wireless Communication Networks and Systems 1st Edition Beard Solutions Manual
P2P systems started emerging in the early 2000s, started with a variety of very popular systems such as #Napster and #Gnutella.
The first very large-scale distributed systems #Napster and #Gnutella had millions, tens of millions, in some cases hundreds of millions of clients communicate with each other at the same time.
DSM system
Shared memory
On chip memory
Bus based multiprocessor
Working through cache
Write through cache
Write once protocol
Ring based multiprocessor
Protocol used
Similarities and differences b\w ring based and bus based
Wireless Communication Networks and Systems 1st Edition Beard Solutions Manualpuriryrap
Full download : http://alibabadownload.com/product/wireless-communication-networks-and-systems-1st-edition-beard-solutions-manual/
Wireless Communication Networks and Systems 1st Edition Beard Solutions Manual
These slides cover the fundamentals of data communication & networking. It covers Channel Capacity It is useful for engineering students & also for the candidates who want to master data communication & computer networking.
To be transmitted, data must be transformed to electromagnetic signals
Data can be analog or digital. Analog data are continuous and take continuous values. Digital data have discrete states and take on discrete values.
Signals can be analog or digital. Analog signals can have an infinite number of values in a range; digital signals can have only a limited number of values.
Data and signals are fundamental concepts in the field of communication and information technology. In general, data refers to any information that can be represented in a digital format, while a signal is an analog or digital representation of data that can be transmitted over a communication channel.
There are many ways to present data and signals, and the choice depends on the specific application and requirements of the system. In this answer, we will discuss some common methods used for data and signal presentation.
Analog Signals:
Analog signals are continuous and can take any value within a certain range. Examples of analog signals include sound waves, voltage or current signals in electrical circuits, and temperature measurements. Analog signals can be presented graphically using waveform plots or oscilloscopes. The amplitude of the signal is plotted on the vertical axis, while time is plotted on the horizontal axis.
Digital Signals:
Digital signals, on the other hand, are discrete and take on only a finite set of values. These values are represented by binary digits (bits), which can take on the values of 0 or 1. Digital signals are used in many digital communication systems, such as computers, telecommunication networks, and the internet. Digital signals can be presented in several ways, such as waveform plots, histograms, and eye diagrams.
Textual Data:
Textual data refers to data that is represented by characters, such as letters, numbers, and symbols. Textual data can be presented in many ways, such as plain text, tables, spreadsheets, and databases. Textual data can also be formatted in different ways, such as font size, style, and color.
Graphical Data:
Graphical data refers to data that is presented in a graphical form, such as charts, graphs, and diagrams. Graphical data is commonly used to represent trends, patterns, and relationships between different variables. Common types of graphical data include bar charts, line graphs, scatter plots, and pie charts.
Multimedia Data:
Multimedia data refers to data that includes various types of media, such as images, videos, and audio. Multimedia data can be presented in many different formats, such as JPEG, MPEG, and WAV. Multimedia data can also be compressed and transmitted over networks using various compression techniques, such as JPEG compression and MP3 compression.
In conclusion, data and signals can be presented in many ways, depending on the specific application and requirements of the system. The choice of presentation method will depend on factors such as the type of data or signal being presented, the accuracy and resolution required, and the constraints of the communication system.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
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
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Search and Society: Reimagining Information Access for Radical FuturesBhaskar Mitra
The field of Information retrieval (IR) is currently undergoing a transformative shift, at least partly due to the emerging applications of generative AI to information access. In this talk, we will deliberate on the sociotechnical implications of generative AI for information access. We will argue that there is both a critical necessity and an exciting opportunity for the IR community to re-center our research agendas on societal needs while dismantling the artificial separation between the work on fairness, accountability, transparency, and ethics in IR and the rest of IR research. Instead of adopting a reactionary strategy of trying to mitigate potential social harms from emerging technologies, the community should aim to proactively set the research agenda for the kinds of systems we should build inspired by diverse explicitly stated sociotechnical imaginaries. The sociotechnical imaginaries that underpin the design and development of information access technologies needs to be explicitly articulated, and we need to develop theories of change in context of these diverse perspectives. Our guiding future imaginaries must be informed by other academic fields, such as democratic theory and critical theory, and should be co-developed with social science scholars, legal scholars, civil rights and social justice activists, and artists, among others.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
Knowledge engineering: from people to machines and back
Ch3 4 v1
1. 3.1
3-5 DATA RATE LIMITS3-5 DATA RATE LIMITS
A very important consideration in data communicationsA very important consideration in data communications
is how fast we can send data, in bits per second, over ais how fast we can send data, in bits per second, over a
channel. Data rate depends on three factors:channel. Data rate depends on three factors:
1.1. The bandwidth availableThe bandwidth available
2.2. The level of the signals we useThe level of the signals we use
33. The quality of the channel (the level of noise). The quality of the channel (the level of noise)
Noiseless Channel: Nyquist Bit Rate
Noisy Channel: Shannon Capacity
Using Both Limits
Topics discussed in this section:Topics discussed in this section:
2. 3.2
Increasing the levels of a signal
increases the probability of an error
occurring, in other words it reduces the
reliability of the system. Why??
Note
3. 3.3
Capacity of a System
The bit rate of a system increases with an
increase in the number of signal levels we
use to denote a symbol.
A symbol can consist of a single bit or “n” bits.
The number of signal levels = 2n
.
As the number of levels goes up, the spacing
between level decreases -> increasing the
probability of an error occurring in the
presence of transmission impairments.
4. 3.4
Nyquist Theorem
Nyquist gives the upper bound for the bit rate
of a transmission system by calculating the bit
rate directly from the number of bits in a
symbol (or signal levels) and the bandwidth of
the system (assuming 2 symbols/per cycle
and first harmonic).
Nyquist theorem states that for a noiseless
channel:
C = 2 B log22n
C= capacity in bps
B = bandwidth in Hz
5. 3.5
Does the Nyquist theorem bit rate agree with the
intuitive bit rate described in baseband transmission?
Solution
They match when we have only two levels. We said, in
baseband transmission, the bit rate is 2 times the
bandwidth if we use only the first harmonic in the worst
case. However, the Nyquist formula is more general than
what we derived intuitively; it can be applied to baseband
transmission and modulation. Also, it can be applied
when we have two or more levels of signals.
Example 3.33
6. 3.6
Consider a noiseless channel with a bandwidth of 3000
Hz transmitting a signal with two signal levels. The
maximum bit rate can be calculated as
Example 3.34
7. 3.7
Consider the same noiseless channel transmitting a
signal with four signal levels (for each level, we send 2
bits). The maximum bit rate can be calculated as
Example 3.35
8. 3.8
We need to send 265 kbps over a noiseless channel with
a bandwidth of 20 kHz. How many signal levels do we
need?
Solution
We can use the Nyquist formula as shown:
Example 3.36
Since this result is not a power of 2, we need to either
increase the number of levels or reduce the bit rate. If we
have 128 levels, the bit rate is 280 kbps. If we have 64
levels, the bit rate is 240 kbps.
10. 3.10
Consider an extremely noisy channel in which the value
of the signal-to-noise ratio is almost zero. In other
words, the noise is so strong that the signal is faint. For
this channel the capacity C is calculated as
Example 3.37
This means that the capacity of this channel is zero
regardless of the bandwidth. In other words, we cannot
receive any data through this channel.
11. 3.11
We can calculate the theoretical highest bit rate of a
regular telephone line. A telephone line normally has a
bandwidth of 3000. The signal-to-noise ratio is usually
3162. For this channel the capacity is calculated as
Example 3.38
This means that the highest bit rate for a telephone line
is 34.860 kbps. If we want to send data faster than this,
we can either increase the bandwidth of the line or
improve the signal-to-noise ratio.
12. 3.12
The signal-to-noise ratio is often given in decibels.
Assume that SNRdB = 36 and the channel bandwidth is 2
MHz. The theoretical channel capacity can be calculated
as
Example 3.39
13. 3.13
For practical purposes, when the SNR is very high, we
can assume that SNR + 1 is almost the same as SNR. In
these cases, the theoretical channel capacity can be
simplified to
Example 3.40
For example, we can calculate the theoretical capacity of
the previous example as
14. 3.14
We have a channel with a 1-MHz bandwidth. The SNR
for this channel is 63. What are the appropriate bit rate
and signal level?
Solution
First, we use the Shannon formula to find the upper
limit.
Example 3.41
15. 3.15
The Shannon formula gives us 6 Mbps, the upper limit.
For better performance we choose something lower, 4
Mbps, for example. Then we use the Nyquist formula to
find the number of signal levels.
Example 3.41 (continued)
16. 3.16
The Shannon capacity gives us the
upper limit; the Nyquist formula tells us
how many signal levels we need.
Note