Trending March 2024 # Top 15 Components Of 8085 Architecture # Suggested April 2024 # Top 7 Popular

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Introduction to 8085 Architecture

Eighty-eighty-five is an 8-bit microprocessor created in 1971 by Intel. It requires less circuit and makes the computer system to be simpler and easy to be built. It uses 5-volt power supply and has depletion mode transistors. Hence, 8085 could be compared with 8080 derived CPU. Hence these can be used in the systems with CP/M operating system. It has a DIP package with 40 pins. There is a data bus in the processor to fully utilize the functions of pins. There is built in serial I/O and 5 interrupts so that 8085 has long life similar to the controller used.

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Architecture of 8085:

Components of 8085 Architecture

1. It consists of timing and control unit, accumulator, arithmetic and logic unit, general purpose register, program counter, stack pointer, temporary register, flag register, instruction register and decoder, controls, address buffer and address and data bus.

2. The timing and control unit provides proper signals to the microprocessor to perform functions in the system. We have control signals, status signals, DMA signals and RESET signals. This also controls the internal and external circuits in the system.

3. The accumulator is a register that performs all the arithmetic and logic operations in 8-bit processor. It connects the data bus and ALU unit of the processor.

4. ALU performs all the operations that includes arithmetic and logic operations such as addition, subtraction, multiplication, division, and the logical operations in the system.

5. General purpose registers used in the processor include B, C, D, E, H and L registers. Each register holds the data and also these could be made to work in pairs. Hence these can hold 16-bit data in the processor.

7. Stack pointer works like a stack with a 16-bit register. It performs push or pop operations and is either incremented or decremented by 2 in the register.

8. Temporary data of the operations in ALU is handled in a temporary register which is 8-bit.

9. The 8-bit register with 1-bit flip-flops is called Flag register. There are 5 flip-flops and it holds logic data from the accumulator register. The logic data can be 0 or 1. The five flip-flops are Sign, Zero, Auxiliary Carry, Parity and Carry.

10. Instruction register and decoder is also an 8-bit register where instructions are stored after taking it from the memory. Decoder encrypts the instruction stored in the register.

11. The signal is given to the microprocessor through the timing and control unit to do the operations. There are different time and control signals to perform the operations. They are control signals, status signals, DMA signals, and RESET signals.

13. Serial data communication is controlled using serial input data and serial output data.

14. Stack pointer and program counter load the data into the address buffer and data buffer so that it communicates with the CPU. The chips are connected here and CPU transfers data via these chips to the data buses.

15. Data to be stored is saved in the data bus and it transfers data to different address services.

Features of 8085 Architecture

Any 8-bit data could be processed, accepted, or provided in the microprocessor simultaneously. The power supply is a single 5-volt supply and operates on a 50% duty cycle.

The clock generator in the processor is internal that needs a tuned circuit, either LC or RC or crystal. The frequency is divided by 2 so that the clock signal is generated to synchronize external devices of the system.

3 MHz frequency can be used to operate the processor. The maximum frequency in which 8085 operates is 5 MHz

16 address lines are provided in the processor so that it can access 64 Kbytes of memory in the system. Also, 8 bit I/O addresses are provided to access 256 I/O ports.

The address bus and data bus in the processor is multiplexed so that the number of external pins can be reduced. External hardware is needed to separate the address and data lines in the processor. 74 instructions are supported in the processor with different address modes. The address modes are immediate, register, direct, indirect, and implied modes.

Advantages

The general-purpose electronic processing devices in the system to execute various tasks are called the microprocessors. All the logic and arithmetic operations are performed here and the results are stored in the registers. This helps the CPU to fetch information whenever needed in the system.

Data could be fetched and moved easily to various locations with the help of registers in the microprocessor.

Operands are delivered easily from the microprocessor and this is easy to do than to restore the operands from the memory. Program variables are stored easily in the registers and hence developers prefer to work with processors in the system.

Serial communication is provided with serial control and hardware interrupts are available to deliver urgent requests. It handles the interruptions in a skilled manner so that the process is kept on hold until the urgent requests are fulfilled. Control signals are available so that bus cycles are controlled. This rule out the chance of an external bus controller.

The system bus is shared with Direct Memory Access to transfer huge data from device to memory or vice versa.

Trainer kits are provided in the institutions to learn about microprocessors so that complete documentation is provided to the students regarding the microprocessors. Also, simulators are available for the execution of the codes in the graphical interface. Assembly language programming is added in the microprocessor course so that it helps the students.

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Top 10 Components Of Iot Architecture In 2023

In this article, we aim to examine the concept of IoT architecture, explain the difference between IoT ecosystem and IoT architecture, demonstrate its ten different components, and finally provide a real-life example for contextualization.

What is IoT architecture?

IoT architecture comprises several IoT building blocks connected to ensure that sensor-generated data is collected, transferred, stored, and processed in order for the actuators to perform their designated tasks.

What is the difference between IoT ecosystem and IoT architecture?

IoT ecosystem is the encompassing term attributed to the five general components of devices, communication protocols, the cloud, monitoring, and the end-user in the IoT system.

IoT architecture is the breakdown of the inner workings of these building blocks to make the ecosystem function.

What are the different elements of IoT architecture?

For the sake of brevity, we will only explore the ten most important parts of an IoT architecture.

1- Devices

IoT devices are equipped with sensors that gather the data, which will be transferred over a network. The sensors do not necessarily need to be physically attached to the equipment. In some instances, they are remotely positioned to gather data about the closest environment to the IoT device. Some examples of IoT devices include:

Temperature detectors

Smoke detectors

Cameras and CCTVs

2- Actuators

Actuators are devices that produce motions with the aim of carrying out preprogrammed tasks, for example:

Smart lights turning on or off

Smart locks opening or closing

Thermostat increasing or decreasing the temperature

3- Gateways 4- Cloud gateways 5- Data lake

A data lake is a data storage space that stores all sorts of structured and non-structured data such as images, videos, and audio, generated by IoT devices, which will then be filtered and cleaned to be sent to a data warehouse for further use.

6- Data warehouse

For meaningful insight, data should be extracted from the data lake to the data warehouse, either manually, or by using data warehouse automation tools. A data warehouse contains cleaned, filtered, and mostly structured information, which is all destined for further use.

7- Data analytics

Data analytics is the practice of finding trends and patterns within a data warehouse in order to gain actionable insights and make data-driven decisions about business processes. After having been laid out and visualized, data and IoT analytics tools help identify inefficiencies and work out ways to improve the IoT ecosystem.

8- Control applications

Previously, we mentioned how actuators make “actions” happen. Control applications are a medium which, through them, it’s possible to send out the relevant commands and alerts which will make actuators function. An example of a control application could be soil sensors signaling a dryness in the lawns, and consequently, the actuators turning on the sprinkles to start irrigation.

9- User applications

They are software components (e.g. smartphone apps) of an IoT system that allow users to control the functioning of the IoT network. User applications allow the user to send commands, turn the device on or off, or access other features.

10- Machine learning

Machine learning, if available, gives the opportunity to create more precise and efficient models for control applications. ML models pick up on patterns in order to predict future outcomes, processes, and behavior by making use of historical data that’s accumulated in the data warehouse. Once the applicability and efficiency of the new models are tested and approved by data analysts, new models are adopted.

What is a real-life example IoT architecture?

The sensors take relevant data, such as daylight or people’s movement. The lamps on the other end, are equipped with actuators to switch the light on and off. The data lake stores these raw data coming from the sensors, while a data warehouse houses the inhabitants’ behavior on various days of the week, energy costs, and more. All these data, through field and cloud gateways, are transferred to computing databases (on-premise or cloud).

The users have access to the user application through an app. The app allows them to see which lights are on and off, or it gives them the ability to pass on commands to the control applications. If there is a gap in algorithms, such as when the system mistakenly switches off the lights and the user has to switch it on manually, data analytics can help address these problems at its core.

When daylights get lower than the established threshold, it’s the control applications commanding the actuators to turn the lights on. At other times, if the lights are on power-saving mode and would only be turned on if a user walks past the lawn, it’s the cloud that receives the data of a passerby walking and after identification, alerts the actuators to turn the lights on. This makes sure that false alarms are detected and the power is conserved.

But the control application does not only function with already-established commands. By leveraging machine learning, algorithms would learn more about usage patterns and customize the functionality accordingly. For example, if the inhabitants leave home at 7 am and come back at 5 pm, after some time, the lights would turn off and on in between this interval autonomously. These smart adjustments would, furthermore, reduce the need for human intervention and make for seamless continuity.

For more on the internet of things

To learn more about the technical side of internet of things, read:

Finally, If you believe your business will benefit from an IoT solution, feel free to check our data-driven hub of IoT solutions and tools.

And we can guide you through the process:

He primarily writes about RPA and process automation, MSPs, Ordinal Inscriptions, IoT, and to jazz it up a bit, sometimes FinTech.

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Hbase Architecture: Use Cases, Components & Data Model

HBase Architecture and its Important Components

Below is a detailed architrecutre of HBase with components:

HBase Architecture Diagram

HBase architecture consists mainly of four components

HMaster

HRegionserver

HRegions

Zookeeper

HDFS

In this tutorial- you will learn,

HMaster

The following are important roles performed by HMaster in HBase.

Plays a vital role in terms of performance and maintaining nodes in the cluster.

HMaster provides admin performance and distributes services to different region servers.

HMaster assigns regions to region servers.

HMaster has the features like controlling load balancing and failover to handle the load over nodes present in the cluster.

When a client wants to change any schema and to change any Metadata operations, HMaster takes responsibility for these operations.

Some of the methods exposed by HMaster Interface are primarily Metadata oriented methods.

Table (createTable, removeTable, enable, disable)

ColumnFamily (add Column, modify Column)

Region (move, assign)

The client communicates in a bi-directional way with both HMaster and ZooKeeper. For read and write operations, it directly contacts with HRegion servers. HMaster assigns regions to region servers and in turn, check the health status of region servers.

In entire architecture, we have multiple region servers. Hlog present in region servers which are going to store all the log files.

HBase Region Servers

When HBase Region Server receives writes and read requests from the client, it assigns the request to a specific region, where the actual column family resides. However, the client can directly contact with HRegion servers, there is no need of HMaster mandatory permission to the client regarding communication with HRegion servers. The client requires HMaster help when operations related to metadata and schema changes are required.

HRegionServer is the Region Server implementation. It is responsible for serving and managing regions or data that is present in a distributed cluster. The region servers run on Data Nodes present in the Hadoop cluster.

HMaster can get into contact with multiple HRegion servers and performs the following functions.

Hosting and managing regions

Splitting regions automatically

Handling read and writes requests

Communicating with the client directly

HBase Regions

HRegions are the basic building elements of HBase cluster that consists of the distribution of tables and are comprised of Column families. It contains multiple stores, one for each column family. It consists of mainly two components, which are Memstore and Hfile.

ZooKeeper

HBase Zookeeper is a centralized monitoring server which maintains configuration information and provides distributed synchronization. Distributed synchronization is to access the distributed applications running across the cluster with the responsibility of providing coordination services between nodes. If the client wants to communicate with regions, the server’s client has to approach ZooKeeper first.

It is an open source project, and it provides so many important services.

Services provided by ZooKeeper

Maintains Configuration information

Provides distributed synchronization

Client Communication establishment with region servers

Provides ephemeral nodes for which represent different region servers

Master servers usability of ephemeral nodes for discovering available servers in the cluster

To track server failure and network partitions

Master and HBase slave nodes ( region servers) registered themselves with ZooKeeper. The client needs access to ZK(zookeeper) quorum configuration to connect with master and region servers.

During a failure of nodes that present in HBase cluster, ZKquoram will trigger error messages, and it starts to repair the failed nodes.

HDFS

HDFS is a Hadoop distributed File System, as the name implies it provides a distributed environment for the storage and it is a file system designed in a way to run on commodity hardware. It stores each file in multiple blocks and to maintain fault tolerance, the blocks are replicated across a Hadoop cluster.

HDFS provides a high degree of fault –tolerance and runs on cheap commodity hardware. By adding nodes to the cluster and performing processing & storing by using the cheap commodity hardware, it will give the client better results as compared to the existing one.

In here, the data stored in each block replicates into 3 nodes any in a case when any node goes down there will be no loss of data, it will have a proper backup recovery mechanism.

HDFS get in contact with the HBase components and stores a large amount of data in a distributed manner.

Learn Top 6 Amazing Spark Components

Overview of Spark Components

Hadoop, Data Science, Statistics & others

Top Components of Spark

Currently, we have 6 components in Spark Ecosystem: Spark Core, Spark SQL, Spark Streaming, Spark MLlib, Spark GraphX, and SparkR. Let’s see what each of these components do.

1. Spark Core

As the name suggests, Spark Core is the core unit of a Spark process. It handles task scheduling, fault recovery, memory management, input-output operations, etc. Think of it as something similar to a CPU to a computer. It supports programming languages like Java, Scala, Python, and R and provides APIs for respective languages using which you can build your ETL job or do analytics. All the other Spark components have their APIs built on Spark Core. Spark can handle any workload because of its parallel processing capabilities and in-memory computation.

Spark Core comes with a special kind of data structure called RDD (Resilient Distributed Dataset) which distributes the data across all the nodes within a cluster. RDDs work on a Lazy evaluation paradigm where the computation is memorized and only executed when necessary. This helps in optimizing the process by only computing the necessary objects.

2. Spark SQL

If you have worked with Databases, you understand the importance of SQL. Wouldn’t it be extremely overwhelming if the same SQL code works N times faster, even on a larger dataset? Spark SQL helps you manipulate data on Spark using SQL. It supports JDBC and ODBC connections that connect Java objects and existing databases, data warehouses, and business intelligence tools. Spark incorporates something called Dataframes, which are structured collections of data in the form of columns and rows.

Spark allows you to work on this data with SQL. Dataframes are equivalent to relational tables, and they can be constructed from any external databases, structured files, or existing RDDs. Dataframes have all the features of RDD, such as immutable, resilient, and in-memory, but with the extra feature of being structured and easy to work with. Dataframe API is also available in Scala, Python, R, and Java.

3. Spark Streaming

Streaming is Netflix, Pinterest, and Uber. Apache Kafka can integrate with Spark Streaming, allowing for the decoupling and buffering of input streams. Spark Streaming algorithms process real-time streams using Kafka as the central hub.

4. Spark MLLib

Spark’s major attraction is scaling up the computation massively, and this feature is the most important requirement for any Machine Learning Project. Spark MLLib is Spark’s machine learning component, which contains Machine Learning algorithms such as classification, regression, clustering, and collaborative filtering. It also offers a place for feature extraction, dimensionality reduction, transformation, etc.

You can also save and run your models on larger datasets without worrying about sizing issues. It also contains utilities for linear algebra, statistics, and data handling. Because of Spark’s in-memory processing, fault tolerance, scalability, and ease of programming, with the help of this library, you can run iterative ML algorithms easily.

5. GraphX

It finds the distance between two locations and gives an optimal route suggestion. Another example can be Facebook friends’ suggestions. GraphX works with both graphs and computations. Spark offers a range of graph algorithms like page rank, connected components, label propagation, SVD++, strongly connected components, and triangle count.

6. SparkR

More than 10,000 packages are available for different purposes in R, making it the most widely used statistical language. It uses data frames API, which makes it convenient to work with and provides powerful visualizations for data scientists to analyze their data thoroughly. R does not support parallel processing and limits itself to the memory available in a single machine. This is where SparkR comes into the picture.

Spark developed a package known as SparkR, which solves the scalability issue of R. It is based on distributed data frames and also provides the same syntax as R. Spark’s distributed Processing engine and R’s unparalleled interactivity, packages; visualization combines to give Data Scientists what they want for their analyses.

Conclusion

Since Spark is a general-purpose framework, it finds itself in many applications. Spark is extensively used in most big data applications because of its performance and reliability. The developers update all these components of Spark with new features in every new release, making our lives easier.

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This is a guide to Spark Components. Here we discuss the basic concept and top 6 components of spark with a detailed explanation. You may also look at the following articles to learn more –

Learn The Architecture Of Firewall In Detail

Introduction to Firewall

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The basic concept of a firewall is to protect the internal or organizational environment from any external security attack. Similarly, three major aspects will define the firewall’s configuration, like the network’s objective regarding the organization’s point of view, the development ability, and how we need to implement it. While considering it in terms of the hardware level, then we need to consider the budget also.

Firewall Architecture in Detail

There are different types of architecture available in the firewall.

1 Screened host firewall architecture

We have improved the packet filtering routers firewall architecture in the screened host firewall architecture. In this architecture, we use the packet filtering routers firewall technique with the dedicated or the separate firewall. It is known as the application proxy server. In the packet filtering router’s firewall architecture, we have a very big overhead to filter the network traffic (once the access control list increases). Due to this, we are facing lots of issues. Here, we have tried to overcome it and added a dedicated firewall. This technique will allow the router to access the firewall. Due to this architecture, the routers will pre-screen the network traffic or the packets to minimize the network overhead. It will also help to distribute the load as well.

Work Flow: As per the above architecture, a separate host is available, i.e., the bastion host. It acts like a proxy server to balance the load on the firewall. The firewall holds all the set of rules and access control. The Bastion server will help to filter out the network traffic. If it is a valid packet, it will allow it via proxy access to the internal filter router, moving further in the internal network.

2. Packet filtering routers’ firewall architecture

Many organizations want internet connectivity. If we enable internet connectivity, the organization without a firewall will be exposed to the external world. We need to install and configure the firewall to avoid an external security attack. In the packet filtering routers, we have the router concept. Here, the router interface acts as the internet provider to the organization. The router acts as an intermediate between the organization and the internet provider. On the same level, we are enabling the network packet filtering process.

If any unwanted packets may come, so it will filter them out on the same level. Hence the packages will drop or be rejected. It will not come in the organization-level network. It is a very simple way to implement it. It will also help to lower the risk of external security threats. But it has a few concerns also. If we go with the packet filtering routers, there will be less auditing of the network traffic. Similarly, we are also having the drawback of the strong authentication mechanism. Day by day, the access control list will grow. Hence, it will be a very big overhead to filter the incoming network packets. Due to this, it will decrease the network performance also. In a few cases, we will face a lag.

Work Flow: It is the basic technique to implement the firewall. Here, the ISP will provide an internet connection to the organization. Then, it is attached to the external filter router. First, we need to add the list of ACLs and configurations on the firewall. Then, with the help of the same configuration, the network traffic will filter and pass to the internal filter router. Further, the internal filter router will separate the network traffic into the internal organization-level network.

3. Dual-homed firewall architecture

The architectural complexity is increasing because we need high performance and less network lag. We use the single network interphase card in the previous firewall architecture. But when using such firewall architecture, the bastion host will contain the two different network interphase cards. In this architecture, one network interphase card will connect with the external network, and the other will connect with the internal network. Here, all the network traffic will physically travel from the firewall between internal and external network interphase cards.

Work Flow: In this architecture, there is no separate proxy server. In this firewall architecture, there are two different NIC’s available. In one NIC, the external ISP connection will connect. In the second NIC, the internal network will connect. Once the traffic comes, the firewall will filter the traffic and pass it to the internal network. If the traffic is not valid, the firewall will drop the packet and not flow it further.

Conclusion

We have seen the uncut concept of the “firewall architecture” with the proper explanation. Several firewall architectures are available; we must choose them per our requirements and budget. The firewall will track the traffic on the application level also.

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We hope that this EDUCBA information on “Firewall Architecture” was beneficial to you. You can view EDUCBA’s recommended articles for more information.

Top 15 Programming Languages To Learn In 2024

Coding is an art for those who are passionate about it! In spite of your level of passion, you have to take an effort to learn a particular programming language, for both professional and personal purposes. When you want to develop a web-based app or software for your startup, you might need the help of several programming languages, particularly those popular ones out there. Well, if you are still confused about programming languages that you should learn for the sake of future, we are here to help you!

1. Java

If Java was not there, you would not see many of today’s popular web-based applications. Moreover, Java is used in a number of instances, ranging from dynamic websites — by means of JSP — to Android Development — in which it does play a core role. In between, you can find JavaFx that is used to create desktop applications, J2ME that is used to create apps for Java-powered feature phones and lots more. You can find many links for java download but it’ll be good if you use an authorized link.

2. C Language

If you check history of programming languages, you’ll find that C is one of the oldest languages and most of popular programming languages of today have some sort or other relation with C. C will be damn useful when you want to do system level programming, as in the case of Operating Systems, development of Hardware Drivers and Embedded Systems. Despite being easy to learn, learning C will be quite useful for your coding career.

3. JavaScript 4. C++

During development, you may often need to make use of maximum processing power of a PC, for instance when you develop heavy resource consuming desktop software, games that require hardware acceleration, apps that require a lot of memory to run. In these situations, you can prefer C++ to other tools and you will never regret learning this. It is the most used language when it comes to low level programming.

5. C#

If you are looking forward to develop applications or software for Microsoft-powered devices and platforms, you’ve to give priority to C# in spite the fact that learning C Sharp would not be a tough task if you know C and C++. Indeed, this programming language has a high demand, and you will never have to enjoy boredom if you are quite good at it.

6. SQL

While interacting with computer or letting users interact, there will be a huge amount of data and SQL is a great way to manage the data neatly. SQL is the abbreviated form of Structured Query Language and it is used throughout the globe to manage immense data when it comes to both web and system apps. So, if you have databases to keep, SQL is a must.

7. Visual Basic

If you are developing apps for .NET platforms, your knowledge on Visual Basic would be quite significance, as it’s one of the key languages for the development of .NET. Visual Basic can be quite useful during development of apps that automate business processes, such as office suites. If you have other languages that are useful for .NET development with you, Visual Basic will be a gem.

8. PHP 9. Python

Python is yet another multipurpose programming language that is used in various sectors of technology industry, like web-based apps, data analysis etc. What makes Python even popular is availability of frameworks that will suit lots of requirements of yours. Python can be used to solve problems in case of data analysis as well. So, learning Python will be helpful in one instance or another.

10. Objective C

Objective C is one of the most significance programming languages when it comes to developing for some of popular platforms such as iOS. Although we can sense presence of Swift — Apple’s language for iOS development —, this has to play as the foundation of iOS development, when you have that desire to be in Apple App Store.

11. .NET

.NET is not actually a standalone programming language, but you’ll have to learn this when you want to get into the development of apps for Microsoft cloud. Quite recently, Apple and Google offer support for .NET, which means that your proficiency in .NET will help you build apps that have multi-platform support.

12. Swift

Are you interested in building apps for iOS and Apple OS X? Want to do that with the power of interaction as well as lightning-fast algorithms? Well, then, you should never avoid Swift from your programming language wishlist. Swift was introduced in last WWDC and it has won hearts of almost every developer so far. When compared to Objective C, Swift gives you a far more native experience as the programming language has the touch of Apple.

13. R 14. Perl

Perl is a family of high-level, dynamic programming languages and it includes Perl 5 and Perl 6, which are rumored to be known by a few people only. This powerful programming language is used in confidential sections of tech world including security of cyber world, development of web apps and websites etc. Altogether, the web may pause if there is no Perl to help.

15. Ruby on Rails

Ruby’s a programming language and Ruby on Rails is an application framework that’s written in Ruby. Ruby on Rails had attracted limelight due to increasing popularity of start-ups. When we compare it with Java and .NET, Ruby on Rails has more features to offer for the sake of rapid web development that makes sense. So, you can add Ruby on Rails into your list as well.

SEE ALSO: 20+ Best Front-End Frameworks For Bootstrap Alternative

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