Meta-Heuristic Algorithms for Advanced Distributed Systems / edited by Rohit Anand [and four others].

Format:

Book

Contributor:

Anand, Rohit, editor.

Language:

English

Subjects (All):

Computer algorithms.

Electronic data processing--Distributed processing.

Electronic data processing.

Physical Description:

1 online resource (460 pages)

Edition:

First edition.

Place of Publication:

Hoboken, New Jersey : John Wiley & Sons, Inc., [2024]

Summary:

META-HEURISTIC ALGORITHMS FOR ADVANCED DISTRIBUTED SYSTEMS Discover a collection of meta-heuristic algorithms for distributed systems in different application domains Meta-heuristic techniques are increasingly gaining favor as tools for optimizing distributed systems-generally, to enhance the utility and precision of database searches. Carefully applied, they can increase system effectiveness, streamline operations, and reduce cost. Since many of these techniques are derived from nature, they offer considerable scope for research and development, with the result that this field is growing rapidly. Meta-Heuristic Algorithms for Advanced Distributed Systems offers an overview of these techniques and their applications in various distributed systems. With strategies based on both global and local searching, it covers a wide range of key topics related to meta-heuristic algorithms. Those interested in the latest developments in distributed systems will find this book indispensable. Meta-Heuristic Algorithms for Advanced Distributed Systems readers will also find: * Analysis of security issues, distributed system design, stochastic optimization techniques, and more * Detailed discussion of meta-heuristic techniques such as the genetic algorithm, particle swam optimization, and many others * Applications of optimized distribution systems in healthcare and other key??industries Meta-Heuristic Algorithms for Advanced Distributed Systems is ideal for academics and researchers studying distributed systems, their design, and their applications.

Contents:

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

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

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

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

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

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

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

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

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

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.

Notes:

Description based on publisher supplied metadata and other sources.

Description based on print version record.

Includes bibliographical references and index.

ISBN:

9781394188093

1394188099

9781394188079

1394188072