Software-based Computing System
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A Software-based Computing System is a computing system that operates with software components on a hardware-software system (to perform computational tasks).
- Context:
- Input: data input, user commands, system configuration, software instructions
- Output: computation results, system responses, processed data
- Performance Measure: system throughput, response time, resource utilization, error rate
- ...
- It can (typically) manifest a Computer System Behavior, including potential Computer System Disorders.
- It can (typically) be created by a Software Development Process.
- It can (typically) be described in a Software System Reference Document.
- It can (typically) integrate Hardware Elements with hardware components, processors, and memory.
- It can (typically) combine Software Elements with system software and operating systems.
- It can (typically) execute Computational Models through computational resource allocation.
- It can (typically) support Model Simulation via parallel processing and distributed computation.
- It can (often) optimize Model Performance through hardware acceleration and specialized processing.
- It can (often) be composed of Computing System Software Components.
- It can (often) enable System Integration, such as through APIs and service interfaces.
- It can (often) provide System Monitoring, such as through telemetry collection.
- ...
- It can range from being a Software-based Operation to being a Software-based Software Program, depending on its complexity level.
- It can range from being an Interactive Computing System to being a Non-Interactive Computing System, depending on its user interaction model.
- It can range from being a Large-Scale System to being a Small-Scale System, depending on its system scale.
- It can range from being a Single-Server Computing System to being a Cluster-based Computing System, depending on its infrastructure model.
- It can range from being a Domain-Specific Computing System to being a General Computing System, depending on its application scope.
- It can range from being a Front-End Software System to being a Back-End System, depending on its system role.
- It can range from being a Real-Time Computing System to being a Batch Computing System, depending on its processing mode.
- It can range from being a Monolithic Software System to being a Microservices-based System, depending on its architecture pattern.
- It can range from being a Traditional Computing System to being an AI-Enhanced Computing System, depending on its intelligence capability.
- It can range from being a Human-Operated Software-based System to being an Automated Software-based System, depending on its operational control model.
- ...
- It can implement System Security through security protocol
- It can be modeled by a Software System Model (that might align with a software architecture pattern).
- It can rely on Software System-Supporting Systems, such as software tools, software frameworks and software platform.
- It can be impacted by a Computer Hardware-related Invention.
- It can be monitored by an Software System Monitoring System.
- It can be evaluated by a Software System Evaluation Task.
- It can be managed by a Software Engineering Project.
- It can be afflicted by Malware.
- It can contain subsystems such as an Operating System.
- It can interact with users through interfaces and io devices.
- It can handle system faults through fault tolerance mechanism]]s.
- ...
- Examples:
- Enterprise Software-based Systems, such as:
- Traditional Enterprise Software Systems (Pre-2000s), such as:
- Monolithic Business Software Systems, including:
- Early Software-based Information Systems, including:
- Modern Enterprise Software Systems (2000s-Present), such as:
- Distributed Business Software Platforms, including:
- Real-time Business Software Systems, including:
- Document Management Software Systems, including:
- Traditional Enterprise Software Systems (Pre-2000s), such as:
- Software Development and Engineering Systems, such as:
- Traditional Software Development Platforms (Pre-2000s), such as:
- Modern Software Development Platforms (2000s-Present), such as:
- Software DevOps Systems, including:
- Software Analysis Platforms, including:
- Cloud Software Development Platforms, including:
- Software-based Data Management Systems, such as:
- Database Software Systems, such as:
- Information Retrieval Software Systems, such as:
- Stream Processing Software Systems, such as:
- Software-based Intelligent Systems, such as:
- Early Software-based AI Systems (1970s-1990s), such as:
- Rule-based Software Systems, including:
- Knowledge-based Software Systems, including:
- Modern Software-based AI Platforms (2000s-Present), such as:
- Machine Learning Software Systems, including:
- Intelligent Software Services, including:
- Multi-Agent Software Systems, including:
- Early Software-based AI Systems (1970s-1990s), such as:
- Software-based Scientific Computing Systems, such as:
- Traditional Scientific Software Systems (1970s-1990s), such as:
- Modern Scientific Software Platforms (2000s-Present), such as:
- Distributed Computing Software Clusters, including:
- Cloud Research Software Platforms, including:
- Domain-Specific Software-based Systems, such as:
- Healthcare Software Systems, including:
- Geographic Information Software Systems, such as:
- Financial Software Systems, including:
- Software-based Infrastructure and Security Systems, such as:
- System Security Software Platforms, such as:
- Access Control Software Systems, such as:
- System Management Software Platforms, including:
- Emerging Software-based Systems (Current/Future), such as:
- Next-Generation Software Platforms, such as:
- Quantum-Enhanced Software Systems, including:
- Bio-Inspired Software Systems, including:
- Hybrid Software Platforms, such as:
- Edge-Cloud Software Systems, including:
- Mixed Computing Software Systems, including:
- Embedded Software Systems, such as:
- Next-Generation Software Platforms, such as:
- Model-Optimized Computing Systems, such as:
- Domain-Specific Computing Systems, such as:
- ...
- Enterprise Software-based Systems, such as:
- Counter-Examples:
- Hardware-only Systems, which lack software programmability.
- Mechanical Computing Systems, which use mechanical mechanisms rather than software logic.
- Human-based Computing Systems, which lack software components.
- Formal Systems, which are abstract constructs rather than implemented systems.
- See: Computing System, Software System, Information System, Computer Hardware, Programming Language, Software Architecture.
References
2024-11-29
- Perplexity.ai
- Question: What are software-based computing systems, including their core functions, characteristics, and examples? Please explain how these systems integrate hardware and software components to perform computational tasks, manage data processing, and maintain security. Also, describe their scalability from simple software tools to large distributed systems, their support for different architectural patterns like monolithic and microservices, and provide examples of common implementations such as enterprise systems, scientific computing platforms, and machine learning applications. Include information about system resilience, virtualization capabilities, and security protocols.
- Answer: Software-based computing systems are collections of programs, procedures, and data that enable users to interact with computer hardware and perform computational tasks. These systems integrate multiple components to provide essential functionality.
- Core Functions and Characteristics:
- Core Functions:
- Hardware resource management and control.
- Data storage and retrieval.
- Process execution and monitoring.
- User interface and interaction.
- Security and access management.
- Key Characteristics:
- Functionality: Provides specific features and capabilities for intended purposes.
- Reliability: Maintains low failure probability and quick recovery.
- Efficiency: Optimizes resource utilization and performance.
- Maintainability: Allows modifications and improvements.
- Portability: Functions across different environments.
- Core Functions:
- System Architecture Patterns:
- Monolithic Architecture:
- Single unified system with integrated components.
- Performs well for small-scale applications.
- Simple initial development and deployment.
- Resource-intensive scaling requirements.
- Microservices Architecture:
- Distributed independent components.
- Allows selective scaling of specific services.
- Provides better fault isolation.
- Requires more complex management and coordination.
- Monolithic Architecture:
- Enterprise and Scientific Computing Platforms:
- Key Components:
- Data and metadata management systems.
- Web-based interfaces for visualization.
- Computational job scheduling and scaling.
- Workflow management and pipeline support.
- User authentication and access control.
- Key Components:
- Machine Learning and AI Integration:
- Common Features:
- Automated model training and deployment.
- Distributed processing for large datasets.
- Integration with existing infrastructure.
- Support for multiple ML frameworks.
- Model monitoring and management.
- Common Features:
- Core Functions and Characteristics:
- Citations:
[1] https://www.geeksforgeeks.org/software-engineering-software-characteristics/ [2] https://hatchworks.com/blog/software-development/monolithic-vs-microservices/ [3] https://www.geeksforgeeks.org/top-10-machine-learning-tools-in-the-software-industry/ [4] https://www.simplilearn.com/tutorials/programming-tutorial/what-is-system-software [5] https://www.akamai.com/blog/cloud/monolith-versus-microservices-weigh-the-difference [6] https://www.softkraft.co/machine-learning-platforms/ [7] https://squareboat.com/blog/different-types-of-software-with-examples [8] https://frederick.cancer.gov/news/enterprise-data-science-platforms-scientific-computing-and-machine-learning
2024
- (Wikipedia, 2024) ⇒ https://en.wikipedia.org/wiki/Information_system Retrieved:2024-11-26.
- An information system (IS) is a formal, sociotechnical, organizational system designed to collect, process, store, and distribute information. From a sociotechnical perspective, information systems comprise four components: task, people, structure (or roles), and technology.[1] Information systems can be defined as an integration of components for collection, storage and processing of data, comprising digital products that process data to facilitate decision making and the data being used to provide information and contribute to knowledge. A computer information system is a system, which consists of people and computers that process or interpret information. [2] The term is also sometimes used to simply refer to a computer system with software installed. "Information systems" is also an academic field of study about systems with a specific reference to information and the complementary networks of computer hardware and software that people and organizations use to collect, filter, process, create and also distribute data. An emphasis is placed on an information system having a definitive boundary, users, processors, storage, inputs, outputs and the aforementioned communication networks. [3] In many organizations, the department or unit responsible for information systems and data processing is known as "information services". Any specific information system aims to support operations, management and decision-making. An information system is the information and communication technology (ICT) that an organization uses, and also the way in which people interact with this technology in support of business processes. [4] Some authors make a clear distinction between information systems, computer systems, and business processes. Information systems typically include an ICT component but are not purely concerned with ICT, focusing instead on the end-use of information technology. Information systems are also different from business processes. Information systems help to control the performance of business processes. [5] Alter [6] argues that viewing an information system as a special type of work system has its advantages. A work system is a system in which humans or machines perform processes and activities using resources to produce specific products or services for customers. An information system is a work system in which activities are devoted to capturing, transmitting, storing, retrieving, manipulating and displaying information. [7] As such, information systems inter-relate with data systems on the one hand and activity systems on the other. An information system is a form of communication system in which data represent and are processed as a form of social memory. An information system can also be considered a semi-formal language which supports human decision making and action. Information systems are the primary focus of study for organizational informatics. [8]
2010
- http://www.webopedia.com/term/c/computer_system.html
- A complete, working computer. Computer systems will include the computer along with any software and peripheral devices that are necessary to make the computer function. Every computer system, for example, requires an operating system.
2009
- (WordNet, 2009) ⇒ http://wordnetweb.princeton.edu/perl/webwn?o2=&o0=1&o7=&o5=&o1=1&o6=&o4=&o3=&s=computing+system
- S: (n) computer system, computing system, automatic data processing system, ADP system, ADPS (a system of one or more computers and associated software with common storage)
- (Huang, 2009) ⇒ Hao-Chen Huang. (2009). “Designing a Knowledge-based System for Strategic Planning: A Balanced Scorecard Perspective.” In: Expert Systems with Applications. doi:10.1016/j.eswa.2007.09.046
- QUOTE: A properly designed KBS is an interactive software-based system designed to help decision makers compile useful information from raw data, documents, personal knowledge, and/or business models for problem solving and decision-making.
2006
- (Bell et al., 2006) ⇒ Gordon Bell, Jim Gray, and Alex Szalay. (2006). “Petascale Computational Systems: Balanced CyberInfrastructure in a Data-Centric World.” In: Computer, 39(1). doi:10.1109/MC.2006.29
- QUOTE: Computational Science is a new branch of most disciplines. A thousand years ago, science was primarily empirical. Over the last 500 years each discipline has grown a theoretical component. Theoretical models often motivate experiments and generalize our understanding. Today most disciplines have both empirical and theoretical branches. In the last 50 years, most disciplines have grown a third, computational branch (e.g. empirical, theoretical and computational ecology, or physics, or linguistics). Computational Science has meant simulation. It grew out of our inability to find closed form solutions for complex mathematical models. Computers can simulate these complex models.
- ↑ Cite error: Invalid
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- ↑ D'Atri A., De Marco M., Casalino N. (2008). "Interdisciplinary Aspects of Information Systems Studies", Physica-Verlag, Springer, Germany, pp. 1–416,
- ↑ Jessup, Leonard M.; Joseph S. Valacich (2008). Information Systems Today (3rd ed.). Pearson Publishing. Glossary p. 416
- ↑ Kroenke, D M. (2008). Experiencing MIS. Prentice-Hall, Upper Saddle River, NJ
- ↑ O'Brien, J A. (2003). Introduction to information systems: essentials for the e-business enterprise. McGraw-Hill, Boston, MA
- ↑ Alter, S. (2003). "18 Reasons Why IT-Reliant Work Systems Should Replace 'The IT Artifact' as the Core Subject Matter of the IS Field", Communications of the Association for Information Systems, 12(23), Oct., pp. 365–394.
- ↑ Alter, S. (2006) The Work System Method: Connecting People, Processes, and IT for Business Results. Works System Press, CA
- ↑ Beynon-Davies P. (2009). Business Information Systems. Palgrave, Basingstoke