CLOUD COMPUTING CSE-III-II

CLOUD COMPUTING CSE-III-II. A.Senthil Murugan M.E.,M.B.A.,(Ph.D) ASSISTANT PROFESSOR DEPARTMENT OF CSE.

UNIT-I COMPUTING PARADIGMS. High-Performance Computing Parallel Computing Distributed Computing Cluster Computing Grid Computing Cloud Computing Bio computing Mobile Computing Quantum Computing Optical Computing Nano computing.

INTRODUCTION. Cloud Computing is the delivery of computing as a service rather than a product. Cloud Computing means storing and accessing data programs over the internet of your computer’s hard drive. It is the use of remote servers on the internet to store, manage and process data rather than a local server or your personal compute.

Advantages of cloud computing:. 1. Cost: It reduces the huge capital costs of buying hardware and software. 2. Speed: Resources can be accessed in minutes, typically within a few clicks. 3. Scalability: We can increase or decrease the requirement of resources according to the business requirements. 4. Productivity: While using cloud computing, we put less operational effort. We do not need to apply patching, and there is no need to maintain hardware and software. So, in this way, the IT team can be more productive and focus on achieving business goals. 5. Reliability: Backup and recovery of data are less expensive and extremely fast for business continuity. 6. Security: Many cloud vendors offer a broad set of policies, technologies, and controls that strengthen our data security..

High-performance computing. In High-performance computing systems, a pool of processors are connected with other resources like memory, storage, and input and output devices. And the deployed software is enabled to run in the entire system of connected components..

Importance of High performance. It is used for scientific discoveries, game-changing innovations, and to improve quality of life. It is a foundation for scientific and industrial advancements. It is used in technologies like IoT, AI, and 3D imaging evolves & amount of data that is used by organizations is increasing exponentially to increase the ability of a computer, we use High-performance computers. HPC is used to solve complex modeling problems in a spectrum of disciplines. It includes AI, Nuclear Physics, Climate Modelling, etc. HPC is applied to business uses, data warehouses, and transaction processing..

Challenges with HPC. Cost. Scalability. Data Management. Programming. Support for software and tools. Power consumption and cooling..

Applications of HPC. Scientific research Weather forecasting Healthcare: HPC Energy and environmental studies Engineering and Design.

Parallel Computing. parallel computing is also one of the facets of hpc. in parallel computing, since there is simultaneous use of multiple processor machines, the following apply it is run using multiple processors (multiple cpus). a problem is broken down into discrete parts that can be solved concurrently. each part is further broken down into a series of instructions..

Advantages of Parallel Computing. It saves time and money as many resources working together will reduce the time and cut potential costs. It can be impractical to solve larger problems on Serial Computing. It can take advantage of non-local resources when the local resources are finite. Serial Computing ‘wastes’ the potential computing power, thus Parallel Computing makes better work of the hardware..

Types of Parallelism. Bit-level parallelism Instruction-level parallelism Task Parallelism Data-level parallelism (DLP).

Why parallel computing?. The whole real-world runs in dynamic nature i.e. many things happen at a certain time but at different places concurrently. This data is extensively huge to manage. Real-world data needs more dynamic simulation and modeling, and for achieving the same, parallel computing is the key. Parallel computing provides concurrency and saves time and money. Complex, large datasets, and their management can be organized only and only using parallel computing’s approach. Ensures the effective utilization of the resources. The hardware is guaranteed to be used effectively whereas in serial computation only some part of the hardware was used and the rest rendered idle. Also, it is impractical to implement real-time systems using serial computing..

Applications of Parallel Computing. Databases and Data mining. Real-time simulation of systems. Science and Engineering. Advanced graphics, augmented reality, and virtual reality..

Distributed Computing. distributed computing is also a computing system that consists of multiple computers or processor machines connected through a network, which can be homogeneous or heterogeneous, but run as a single system. the cpus in a distributed system can be physically close together and connected by a local network, or they can be geographically distant and connected by a wide area network.

Characteristics. There are several characteristics that define a Distributed Computing System Multiple Devices or Systems: Processing and data storage is distributed across multiple devices or systems. Peer-to-Peer Architecture: Devices or systems in a distributed system can act as both clients and servers, as they can both request and provide services to other devices or systems in the network. Shared Resources: Resources such as computing power, storage, and networking are shared among the devices or systems in the network. Horizontal Scaling: Scaling a distributed computing system typically involves adding more devices or systems to the network to increase processing and storage capacity. This can be done through hardware upgrades or by adding additional devices or systems to the network...

Advantages and Disadvantages. Scalability: Distributed systems are generally more scalable than centralized systems, as they can easily add new devices or systems to the network to increase processing and storage capacity. Reliability: Distributed systems are often more reliable than centralized systems, as they can continue to operate even if one device or system fails. Flexibility: Distributed systems are generally more flexible than centralized systems, as they can be configured and reconfigured more easily to meet changing computing needs. There are a few limitations to Distributed Computing System Complexity: Distributed systems can be more complex than centralized systems, as they involve multiple devices or systems that need to be coordinated and managed. Security: It can be more challenging to secure a distributed system, as security measures must be implemented on each device or system to ensure the security of the entire system. Performance: Distributed systems may not offer the same level of performance as centralized systems, as processing and data storage is distributed across multiple devices or systems..

Applications. Cloud Computing: Cloud Computing systems are a type of distributed computing system that are used to deliver resources such as computing power, storage, and networking over the Internet. Peer-to-Peer Networks: Peer-to-Peer Networks are a type of distributed computing system that is used to share resources such as files and computing power among users. Distributed Architectures: Many modern computing systems, such as microservices architectures, use distributed architectures to distribute processing and data storage across multiple devices or systems..

Cluster Computing. a cluster computing system consists of a set of the same or similar type of processor machines connected using a dedicated network infrastructure. all processor machines share resources such as a common home directory and have a software such as a message passing interface (mpi) implementation installed to allow programs to be run across all nodes simultaneously. this is also a kind of hpc category..

Cont…. [image] INPUT DATA COMPUTER (ROOT NODE) RESULTS COMPUTER (SLAVE NODE 1) COMPUTER (SLAVE NODE 2) COMPUTER (SLAVE NODE n) Ä Simple Cluster Computing Layout.

Types of Cluster computing. 1.High performance (HP) clusters : HP clusters use computer clusters and supercomputers to solve advance computational problems. They are used to performing functions that need nodes to communicate as they perform their jobs. They are designed to take benefit of the parallel processing power of several nodes. 2. Load-balancing clusters : Incoming requests are distributed for resources among several nodes running similar programs or having similar content. This prevents any single node from receiving a disproportionate amount of task. This type of distribution is generally used in a web-hosting environment. 3. High Availability (HA) Clusters : HA clusters are designed to maintain redundant nodes that can act as backup systems in case any failure occurs. Consistent computing services like business activities, complicated databases, customer services like e-websites and network file distribution are provided. They are designed to give uninterrupted data availability to the customers..

Advantages of Cluster Computing. 1. High Performance : The systems offer better and enhanced performance than that of mainframe computer networks. 2. Easy to manage : Cluster Computing is manageable and easy to implement. 3. Scalable : Resources can be added to the clusters accordingly. 4. Expandability : Computer clusters can be expanded easily by adding additional computers to the network. Cluster computing is capable of combining several additional resources or the networks to the existing computer system. 5. Availability : The other nodes will be active when one node gets failed and will function as a proxy for the failed node. This makes sure for enhanced availability. 6. Flexibility : It can be upgraded to the superior specification or additional nodes can be added..

Disadvantages of Cluster Computing. 1. High cost :It is not so much cost-effective due to its high hardware and its design. 2. Problem in finding fault : It is difficult to find which component has a fault. 3. More space is needed : Infrastructure may increase as more servers are needed to manage and monitor..

Applications of Cluster Computing. Various complex computational problems can be solved. It can be used in the applications of aerodynamics, astrophysics and in data mining. Weather forecasting. Image Rendering. Various e-commerce applications. Earthquake Simulation. Petroleum reservoir simulation..

Grid Computing. What is grid computing in cloud computing? Grid computing is a group of networked computers that work together as a virtual supercomputer to perform large tasks, such as analyzing huge sets of data or weather modeling..

Grid Computing Working. Control Node Provider User.

Advantages of Grid Computing. It is not centralized, as there are no servers required, except the control node which is just used for controlling and not for processing. Multiple heterogeneous machines i.e. machines with different Operating Systems can use a single grid computing network. Tasks can be performed parallelly across various physical locations and the users don’t have to pay for them (with money)..

Disadvantages of Grid Computing. The software of the grid is still in the involution stage. A super-fast interconnect between computer resources is the need of the hour. Licensing across many servers may make it prohibitive for some applications. Many groups are reluctant with sharing resources. Trouble in the control node can come to halt in the whole network..

BIO –COMPUTING. uses biological molecules as a medium for data storage and logical operations. DNA, in particular, shows significant potential due to its ability to efficiently self-assemble and naturally store immense amounts of information within its molecular structure..

Why use Bio-computing in Cloud Computing?. The potential applications of bio-computing are endless. Let’s explore a few of them: Healthcare Education Retail Weather and Climate Change.

How does bio-computing work in cloud computing?. Data Collection Data Processing Data Storage Data Analysis.

Advantages of using bio-computing in Cloud Computing.

Limitations of using Bio-computing in Cloud Computing.

MOBILE COMPUTING. Mobile computing is a technology that allows transmission of data, voice and video via a computer or any other wireless enabled device without having to be connected to a fixed physical link..

Communication Methods. Fixed and wired: This configuration describes the typical desktop computer in an office. Neither weight nor power consumption of the devices allow for mobile usage. The devices use fixed networks for performance reasons.  Mobile and wired: Many of today’s laptops fall into this category; users carry the laptop from one hotel to the next, reconnecting to the company’s network via the telephone network and a modem.  Fixed and wireless: This mode is used for installing networks, e.g., in historical buildings to avoid damage by installing wires, or at trade shows to ensure fast network setup.  Mobile and wireless: This is the most interesting case. No cable restricts the user, who can roam between different wireless networks. Most technologies discussed in this book deal with this type of device and the networks supporting them. Today’s most successful example for this category is GSM with more than 800 million users..

APPLICATIONS OF MOBILE COMPUTING. Vehicles Eg.tesla car Emergencies Business Credit Card Verification Replacement of Wired Networks Mobile Payments Marketing.

Limitations of Mobile Computing :.  Resource constraints: Battery  Interference: Radio transmission cannot be protected against interference using shielding and result in higher loss rates for transmitted data or higher bit error rates respectively  Bandwidth: Although they are continuously increasing, transmission rates are still very low for wireless devices compared to desktop systems. Researchers look for more efficient communication protocols with low overhead.  Dynamic changes in communication environment: variations in signal power within a region, thus link delays and connection losses  Network Issues: discovery of the connection-service to destination and connection stability  Interoperability issues: the varying protocol standards.  Security constraints: Not only can portable devices be stolen more easily, but the radio interface is also prone to the dangers of eavesdropping. Wireless access must always include encryption, authentication, and other security mechanisms that must be efficient and simple to use..

characteristics of mobile computing. Ubiquity Location awareness Adaptation Broadcast.

QUANTUM COMPUTING. [image] INTRODUCTION What does "quantum" mean? The word "quantum", in quantum computer, originates from "quantum mechanics," a basic theory in physics. In brief, on the scale of atoms and molecules, matter behaves in a quantum manner. What is a Quantum Com uter? A quantum computer is a machine that performs calculations based on the laws of quantum mechanics, which is the behavior of particles at the sub-atomic level..

What is the quantum computing advantage?. Currently, no quantum computer can perform a useful task faster, cheaper, or more efficiently than a classical computer. Quantum advantage is the threshold where we have built a quantum system that can perform operations that the best possible classical computer cannot simulate in any kind of reasonable time..

What is quantum mechanics?. Quantum mechanics is the area of physics that studies the behavior of particles at a microscopic level. At subatomic levels, the equations that describe how particles behave is different from those that describe the macroscopic world around us. Quantum computers take advantage of these behaviors to perform computations in a completely new way..

What is a qubit?. Quantum bits, or qubits, are represented by quantum particles. The manipulation of qubits by control devices is at the core of a quantum computer's processing power. Qubits in quantum computers are analogous to bits in classical computers. At its core, a classical machine's processor does all its work by manipulating bits. Similarly, the quantum processor does all its work by processing qubits..

How are qubits different from classical bits?. In classical computing, a bit is an electronic signal that is either on or off. The value of the classical bit can thus be one (on) or zero (off). However, because the qubit is based on the laws of quantum mechanics it can be placed in a superposition of states..

What are the principles of quantum computing?. A quantum computer works using quantum principles. Quantum principles require a new dictionary of terms to be fully understood, terms that include superposition entanglement decoherence..

What are the components of a quantum computer?. Quantum computers have hardware and software, similar to a classical computer. Quantum hardware Quantum hardware has three main components. Quantum data plane Control and measurement plane Control processor plane and host processor.

Quantum software. Quantum software implements unique quantum algorithms using quantum circuits. A quantum circuit is a computing routine that defines a series of logical quantum operations on the underlying qubits. Developers can use various software development tools and libraries to code quantum algorithms..

[image] Classical computing vs. quantum computing Classical computing Used by large-scale, multipurpose computers and devices. Information is stored in bits. There is a discrete number of possible states: 0 or 1. Calculations are deterministic, meaning repeating the same input results in the same output. Data processing is carried out by logic and in sequential order. Operations are defined by Boolean algebra. Circuit behavior is defined by classical physics. Quantum computing Used by high-speed, quantum mechanics-based computers. Information is stored in quantum bits. There is an infinite, continuous number of possible states. Calculations are probabilistic, meaning there are multiple possible outputs to the same input. Data processing is carried out by quantum logic at parallel instances. Operations are defined by linear algebra over Hilbert space. Circuit behavior is defined by quantum mechanics..

What are the types of quantum technology?. Gate-based ion trap processors Gate-based superconducting processors Photonic processors Neutral atom processors Rydberg atom processors Quantum annealers.

How do companies use quantum computing?. ML Optimization Simulation.

Pros of Quantum Computing. Speed: Quantum computers are substantially quicker than conventional computers at some sorts of computations, particularly when factoring big numbers and modelling quantum processes. Parallelism: Due to the simultaneous processing of many calculations by quantum computers, certain types of problems can be solved much more quickly. Large-scale optimization: Compared to conventional algorithms, quantum algorithms are faster and more accurate at solving complex optimization issues. Simulating quantum systems: A quantum computer can be used to simulate quantum systems more effectively and precisely than conventional computers since it is based on the ideas of quantum physics. Cryptography: Quantum computers have the ability to crack some of the encryption used by conventional computers, but they also present fresh possibilities for private communication..

Cons of Quantum Computing. Hardware: The size and stability of existing quantum computers are constrained, and developing a large-scale, dependable quantum computer is a big engineering problem. Software: The field of creating quantum algorithms and software is still developing, and qualified professionals are in short supply. Cost: Building and maintaining quantum computers is currently relatively expensive, and this may prevent widespread deployment. Noise and mistakes: Compared to conventional computers, quantum computers are more prone to noise and faults, and fixing these errors is a difficult task. Scalability: At the moment, quantum computers are only partially scalable, and it is yet unclear how to construct a robust, large-scale quantum computer that is capable of solving complex problems. Interoperability: Due to the lack of standards in the realm of quantum computing, it might be challenging to compare and combine various quantum computers..