Meta-Heuristic Algorithms for Advanced Distributed Systems

Meta-Heuristic Algorithms for Advanced Distributed Systems

Detalles Bibliográficos
Otros Autores: Anand, Rohit, editor (editor)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Hoboken, New Jersey : John Wiley & Sons, Inc [2024]
Edición:First edition
Materias:
Computer algorithms.
Electronic data processing > Distributed processing.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009828026306719
Tabla de Contenidos:
  • Cover
  • Title Page
  • Copyright Page
  • Contents
  • About the Book
  • About the Editors
  • List of Contributors
  • Preface
  • 1 The Future of Business Management with the Power of Distributed Systems and Computing
  • 1.1 Introduction
  • 1.1.1 Distributed Systems in Business Management
  • 1.2 Understanding Distributed Systems and Computing
  • 1.2.1 Definition of Distributed Systems and Computing
  • 1.2.2 Advantages for Business Management
  • 1.2.3 Characteristics of Distributed Systems and Computing for Business Management
  • 1.3 Applications of Distributed Systems and Computing in Business Management
  • 1.3.1 Inventory Management and Supply Chain Optimization
  • 1.3.2 Customer Relationship Management
  • 1.3.3 Financial Management and Accounting
  • 1.3.4 Data Analytics and Decision-Making
  • 1.3.5 Collaboration and Communication Within and Across Organizations
  • 1.4 Limitations of Distributed Systems in Business Management
  • 1.4.1 Security and Privacy Concerns
  • 1.4.2 Technical Issues and Maintenance
  • 1.4.3 Organizational and Cultural Challenges
  • 1.4.4 Legal and Regulatory Compliance
  • 1.5 Future Developments and Opportunities
  • 1.5.1 Potential Future Developments and their Implications for Business Management
  • 1.5.2 Opportunities for Research and Innovation in the Field
  • 1.6 Conclusion
  • References
  • 2 Applications of Optimized Distributed Systems in Healthcare
  • 2.1 Introduction
  • 2.2 Literature Survey
  • 2.2.1 Need for Optimization of Distributed Systems
  • 2.2.2 Performance Optimization of Distributed Systems
  • 2.2.3 Characteristics of Optimized Distributed Systems in Healthcare
  • 2.2.4 Applications of Optimized Distributed Systems in Healthcare
  • 2.2.5 Technologies Being Used in Healthcare
  • 2.2.5.1 Spark
  • 2.2.5.2 Hadoop
  • 2.3 Real Cases
  • 2.4 Conclusion
  • References.
  • 3 The Impact of Distributed Computing on Data Analytics and Business Insights
  • 3.1 Introduction
  • 3.1.1 Role of Distributed Computing in Data Analytics
  • 3.1.2 Importance of Business Insights in Decision-Making
  • 3.1.3 Overview of Distributed Computing and Data Analytics
  • 3.2 Distributed Computing and Data Analytics
  • 3.2.1 Distributed Computing
  • 3.2.2 Overview of Data Analytics
  • 3.2.3 Distributed Computing in Data Analytics
  • 3.3 Business Insights and Decision-Making
  • 3.3.1 Definition of Business Insights
  • 3.3.2 Importance of Business Insights in Decision-Making
  • 3.3.3 Applications of Business Insights and their Impact
  • 3.4 Challenges and Limitations
  • 3.5 The Impact of Distributed Computing on Data Analytics
  • 3.5.1 Distributed Computing in Improvising Data Analytics
  • 3.6 Conclusion
  • References
  • 4 Machine Learning and Its Application in Educational Area
  • 4.1 Introduction
  • 4.2 Previous Work
  • 4.3 Technique
  • 4.3.1 Machine Learning
  • 4.3.2 Supervised Learning
  • 4.3.3 Unsupervised Learning
  • 4.4 Analysis of Data
  • 4.5 Educational Data Mining
  • 4.6 Hadoop Approach
  • 4.7 Artificial Neural Network (ANN)
  • 4.8 Decision Tree
  • 4.9 Results/Discussion
  • 4.9.1 Personalized Learning Through Adaptive Learning
  • 4.10 Increasing Efficiency Using Learning Analytics
  • 4.11 Predictive Analysis for Better Assessment Evaluation
  • 4.12 Future Scope
  • 4.13 Conclusion
  • References
  • 5 Approaches and Methodologies for Distributed Systems: Threats, Challenges, and Future Directions
  • 5.1 Introduction
  • 5.2 Distributed Systems
  • 5.3 Literature Review
  • 5.4 Threats to Distributed Systems Security
  • 5.4.1 Hacking
  • 5.4.2 Malware
  • 5.4.3 Denial of Service (DoS) Attacks
  • 5.4.4 Man-in-the-Middle (MitM) Attacks
  • 5.4.5 Advanced Persistent Threats (APTs)
  • 5.4.6 Insider Threats
  • 5.4.7 Phishing
  • 5.4.8 Ransomware.
  • 5.5 Security Standards and Protocols
  • 5.5.1 ISO/IEC 27001
  • 5.5.2 NIST SP 800-53
  • 5.5.3 SOC 2
  • 5.5.4 PCI DSS
  • 5.5.5 IEC 62443
  • 5.5.6 OWASP
  • 5.5.7 Control Objectives for Information and Related Technologies (COBIT)
  • 5.6 Network Security
  • 5.7 Access Control
  • 5.7.1 Role-based Access Control (RBAC)
  • 5.7.2 Discretionary Access Control (DAC)
  • 5.7.3 Mandatory Access Control (MAC)
  • 5.8 Authentication and Authorization
  • 5.9 Privacy Concerns
  • 5.10 Case Studies
  • 5.10.1 Equifax Data Breach
  • 5.10.2 Target Data Breach
  • 5.10.3 WannaCry Ransomware Attack
  • 5.11 Conclusion
  • 5.12 Future Scope
  • References
  • 6 Efficient-driven Approaches Related to Meta-Heuristic Algorithms using Machine Learning Techniques
  • 6.1 Introduction
  • 6.2 Stochastic Optimization
  • 6.2.1 Genetic Algorithm
  • 6.2.2 Particle Swarm Optimization
  • 6.3 Heuristic Search
  • 6.3.1 Heuristic Search Techniques
  • 6.4 Meta-Heuristic
  • 6.4.1 Structures of Meta-Heuristic
  • 6.5 Machine Learning
  • 6.5.1 Applications of Meta-Heuristic
  • References
  • 7 Security and Privacy Issues in Distributed Healthcare Systems - A Survey
  • 7.1 Introduction
  • 7.1.1 Traditional Systems
  • 7.1.2 Distributed Systems
  • 7.2 Previous Study
  • 7.2.1 Background and Definitions
  • 7.3 Security and Privacy Needs
  • 7.4 Security and Privacy Goals
  • 7.5 Type of Attacks in Distributed Systems
  • 7.5.1 Malicious Hardware
  • 7.5.2 Malicious Programs
  • 7.6 Recommendations and Future Approaches
  • 7.7 Conclusion
  • References
  • 8 Implementation and Analysis of the Proposed Model in a Distributed e-Healthcare System
  • 8.1 Introduction
  • 8.2 Outmoded Systems
  • 8.3 Distributed Systems
  • 8.3.1 Peer-to-Peer Architecture
  • 8.4 Previous Work
  • 8.5 Service-Oriented Architecture of e-Healthcare
  • 8.6 Implementation of the Proposed Model
  • 8.6.1 Speech Software.
  • 8.7 Evaluation of the Proposed Model Performance
  • 8.8 Conclusion and Future Work
  • References
  • 9 Leveraging Distributed Systems for Improved Educational Planning and Resource Allocation
  • 9.1 Introduction
  • 9.1.1 Overview of the Current State of Educational Planning and Resource Allocation
  • 9.1.2 The Potential Benefits of Leveraging Distributed Systems in Education
  • 9.2 Theoretical Framework
  • 9.2.1 Overview of Distributed Systems and their Key Concepts
  • 9.2.2 Theoretical Basis for the Use of Distributed Systems in Education
  • 9.2.3 Comparison of Different Distributed Systems Architectures
  • 9.3 Distribution System in Education
  • 9.4 Technical Aspects of Distributed Systems in Education
  • 9.4.1 Infrastructure Requirements for Implementing Distributed Systems in Education
  • 9.4.2 Security and Privacy Concerns in Distributed Systems for Education
  • 9.4.3 Data Management and Analysis in Distributed Systems for Education
  • 9.5 Challenges and Limitations
  • 9.5.1 Merits of Distributed Systems for Educational Planning and Resource Allocation
  • 9.5.2 Demerits of Distributed Systems for Educational Planning and Resource Allocation
  • 9.6 Discussion
  • 9.7 Conclusion
  • References
  • 10 Advances in Education Policy Through the Integration of Distributed Computing Approaches
  • 10.1 Introduction
  • 10.1.1 Technology in Education Policy
  • 10.1.2 Advances in Education Policy through Distributed Computing
  • 10.2 Distributed Computing Approaches
  • 10.2.1 Benefits of Education Policy
  • 10.2.2 Types of Distributed Computing Approaches
  • 10.3 Advances in Education Policy Through Distributed Computing Approaches
  • 10.3.1 Significant Impact on Education Policy
  • 10.3.2 Improved Access
  • 10.3.3 Personalized Learning
  • 10.3.4 Data-Driven Decision-Making
  • 10.4 Challenges: Privacy Concerns
  • 10.4.1 Technical Requirements.
  • 10.4.2 Impact of Emerging Technologies and Use of Distributed Computing
  • 10.5 Conclusion
  • References
  • 11 Revolutionizing Data Management and Security with the Power of Blockchain and Distributed System
  • 11.1 Introduction
  • 11.1.1 Importance of Data Management and Security
  • 11.1.2 Current State of Data Management and Security
  • 11.2 Blockchain Technology
  • 11.2.1 Benefits of Using Blockchain for Data Management and Security
  • 11.2.2 Limitations of Using Blockchain for Data Management and Security
  • 11.3 Distributed System
  • 11.3.1 Benefits of Using Distributed Systems for Data Management and Security
  • 11.3.2 Limitations of Using Distributed Systems for Data Management and Security
  • 11.4 Revolutionizing Data Management and Security with Blockchain and Distributed Systems
  • 11.4.1 Blockchain and Distributed Systems Can Revolutionize Data Management and Security
  • 11.4.2 Real-World Examples of Blockchain and Distributed Systems in Data Management and Security
  • 11.5 Challenges of Using Blockchain and Distributed Systems
  • 11.5.1 Limitations of Using Blockchain and Distributed Systems
  • 11.6 Discussion
  • 11.7 Conclusion
  • References
  • 12 Enhancing Business Development, Ethics, and Governance with the Adoption of Distributed Systems
  • 12.1 Introduction
  • 12.1.1 Distributed Systems for Business Development
  • 12.2 Applications of Distributed Systems in Business Development
  • 12.2.1 Characteristics of Distributed Systems
  • 12.2.2 Benefits of Distributed Systems in Business Development
  • 12.2.3 Applications in Business Development
  • 12.3 The Importance of Ethics in Distributed Systems
  • 12.3.1 Ethics in Distributed Systems
  • 12.3.2 Ethics to Business Development and Governance
  • 12.3.3 Distributed Systems in Promoting Ethical Practices
  • 12.4 Governance in Distributed Systems.
  • 12.4.1 Importance of Governance in Distributed Systems.

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