Notes for BSc CSIT

  BIOLOGY: PROTEIN STRUCTURE PREDICTION (PSP) Cloud computing is a new technology that allows users to access a variety of computer services on demand. It gives users easy access to a pool of higher-level services and other system resources. Cloud computing has become more important in the realms of geology, biology, and other scientific studies. The finest example of a study area that uses cloud technologies for processing and storage is protein structure prediction. A protein is made up of peptide bonds that connect lengthy sequences of amino acids. The varied structures of proteins aid in the development of novel therapeutics, and Protein structure prediction is the prediction of various sequences of proteins based on their three-dimensional structure. Protein primary structures are created first, and secondary, tertiary, and quaternary structures are predicted from the fundamental structure. Protein structural predictions are made in this manner. Protein structure prediction employ

Scientific Applications Scientific applications have been run on both traditional high-performance computing (HPC) systems such as supercomputers and clusters, as well as high throughput computing (HTC) platforms such as Grids, for many years. Many businesses have employed classical HPC to assist tackle a range of problems since they have access to enormous quantities of computer power. Although these systems were often built to solve a specific problem, a growing number of SMEs and even university departments began to use general-purpose HPC systems. Scientists, engineers, system administrators, and developers have been investigating HPC Cloud environments to take advantage of what Cloud Computing has to offer them as new growing technology. Running complex scientific applications has become more accessible to the research community thanks to the popularity of Cloud Computing, which allows researchers to access on-demand compute resources in minutes rather than waiting in queues for t

  Applications that can benefit from cloud computing 1) Scientific Applications Scientific applications have been run on both traditional high-performance computing (HPC) systems such as supercomputers and clusters, as well as high throughput computing (HTC) platforms such as Grids, for many years. Many businesses have employed classical HPC to assist tackle a range of problems since they have access to enormous quantities of computer power. Although these systems were often built to solve a specific problem, a growing number of SMEs and even university departments began to use general-purpose HPC systems. Scientists, engineers, system administrators, and developers have been investigating HPC Cloud environments to take advantage of what Cloud Computing has to offer them as new growing technology. Running complex scientific applications has become more accessible to the research community thanks to the popularity of Cloud Computing, which allows researchers to access on-demand compute

 Cloud The “cloud” in cloud computing can be defined as the set of hardware, networks, storage, services, and interfaces that combine to deliver aspects of computing as a service. Cloud services include the delivery of software, infrastructure, and storage over the Internet. A cloud service is any service made available to users on demand via the Internet from a cloud computing provider's servers as opposed to being provided from a company's own premises servers explained before, the most common cloud service is that one offers data storage disks and virtual servers, i.e. infrastructure. Examples of Infrastructure-as-a-Service (IaaS) companies are Amazon, Rackspace, and Flexi scale. Cloud computing is the use of computing resources (hardware and software) that are delivered as a service over a network (typically the Internet).  Cloud computing is the on-demand availability of computer system resources, especially data storage (cloud storage) and computing power, without direct

 More Uses of Cloud Computing 1. Scalable Usage:  Through different subscription arrangements, cloud computing provides scalable resources. This means you will only be charged for the computer resources you utilize. This allows for the management of demand spikes without the need to invest in computer hardware on a long-term basis. Netflix, for example, takes advantage of cloud computing's capabilities. It experiences substantial spikes in server load during peak periods due to its on-demand streaming service. The shift to the cloud from on-premises data centers allowed the firm to dramatically grow its client base without having to engage in costly infrastructure setup and upkeep. 2. Chatbots:  We can save information about customer preferences thanks to the cloud's increased computational power and capacity. Users' behavior and preferences may be leveraged to give personalized solutions, messages, and goods. The cloud-based natural-language intelligent bots Siri, Alexa, a

 Applications of Cloud Computing 1) Scientific Applications Scientific applications have been run on both traditional high-performance computing (HPC) systems such as supercomputers and clusters, as well as high throughput computing (HTC) platforms such as Grids, for many years. Many businesses have employed classical HPC to assist tackle a range of problems since they have access to enormous quantities of computer power. Although these systems were often built to solve a specific problem, a growing number of SMEs and even university departments began to use general-purpose HPC systems. Scientists, engineers, system administrators, and developers have been investigating HPC Cloud environments to take advantage of what Cloud Computing has to offer them as new growing technology. Running complex scientific applications has become more accessible to the research community thanks to the popularity of Cloud Computing, which allows researchers to access on-demand compute resources in minutes

 The architecture of the Aneka-based computing cloud  The Aneka-based computing cloud is a collection of physical and virtualized resources that are linked via a network, which can be the Internet or a private intranet. Each of these resources contains an instance of the Aneka Container, which represents the runtime environment in which the distributed apps operate. The container offers the fundamental management features of a single node and leverages all other activities on the services that it hosts. The services are divided into three categories: fabric, foundation, and execution. Fabric services provide hardware profiling and dynamic resource provisioning by interacting directly with the node via the Platform Abstraction Layer (PAL). The fundamental system of the Aneka middleware is identified by foundation services, which provide a collection of fundamental capabilities that allow Aneka containers to conduct specialized sets of jobs. Execution services deal directly with the sche