Anne Benoit – författare

Presenting a complementary perspective to standard books on algorithms, A Guide to Algorithm Design: Paradigms, Methods, and Complexity Analysis provides a roadmap for readers to determine the difficulty of an algorithmic problem by finding an optimal solution or proving complexity results. It gives a practical treatment of algorithmic complexity and guides readers in solving algorithmic problems.

Divided into three parts, the book offers a comprehensive set of problems with solutions as well as in-depth case studies that demonstrate how to assess the complexity of a new problem.

Part I helps readers understand the main design principles and design efficient algorithms. Part II covers polynomial reductions from NP-complete problems and approaches that go beyond NP-completeness. Part III supplies readers with tools and techniques to evaluate problem complexity, including how to determine which instances are polynomial and which are NP-hard.

Drawing on the authors’ classroom-tested material, this text takes readers step by step through the concepts and methods for analyzing algorithmic complexity. Through many problems and detailed examples, readers can investigate polynomial-time algorithms and NP-completeness and beyond.

This book is the first to provide an overview of variable capacity scheduling and how it helps balance the growth of computing with its increasing environmental impact by creating more resilient and efficient systems that adapt to the dynamic nature of resource availability, optimizing utilization and minimizing disruptions. The book covers all aspects of variable capacity scheduling from a technical and a societal perspective. It considers the new age of renewable power generation and how computing services can contribute to sustainability and grid decarbonization. Contributors investigate techniques that can be deployed for schedulers to cope with, or even benefit from, changes in the number of computing resources and the nature of the power sources. They survey emerging computing devices, such as edge servers, as alternatives to classical cloud computing platforms; they identify applications for monitoring energy and regulating power; and they investigate energy minimization and risk-aware scheduling in real-time systems, asking: ‘How can a server with a variable processing speed schedule jobs with hard deadlines while minimizing its energy consumption?’ The authors address the societal impact of computing, exploring how the social sciences play a critical role in solving the computing sustainability challenge and including a holistic analysis of current and future approaches, taking the whole life-cycle and rebound effects into account. Presenting all the corresponding challenges and opportunities of variable capacity scheduling, this is an excellent introduction to the topic for students, researchers, computing scientists, or concerned citizens interested in sustainability.

This book is the first to provide an overview of variable capacity scheduling and how it helps balance the growth of computing with its increasing environmental impact by creating more resilient and efficient systems that adapt to the dynamic nature of resource availability, optimizing utilization and minimizing disruptions. The book covers all aspects of variable capacity scheduling from a technical and a societal perspective. It considers the new age of renewable power generation and how computing services can contribute to sustainability and grid decarbonization. Contributors investigate techniques that can be deployed for schedulers to cope with, or even benefit from, changes in the number of computing resources and the nature of the power sources. They survey emerging computing devices, such as edge servers, as alternatives to classical cloud computing platforms; they identify applications for monitoring energy and regulating power; and they investigate energy minimization and risk-aware scheduling in real-time systems, asking: 'How can a server with a variable processing speed schedule jobs with hard deadlines while minimizing its energy consumption?' The authors address the societal impact of computing, exploring how the social sciences play a critical role in solving the computing sustainability challenge and including a holistic analysis of current and future approaches, taking the whole life-cycle and rebound effects into account. Presenting all the corresponding challenges and opportunities of variable capacity scheduling, this is an excellent introduction to the topic for students, researchers, computing scientists, or concerned citizens interested in sustainability.

This book is the first to provide an overview of variable capacity scheduling and how it helps balance the growth of computing with its increasing environmental impact by creating more resilient and efficient systems that adapt to the dynamic nature of resource availability, optimizing utilization and minimizing disruptions. The book covers all aspects of variable capacity scheduling from a technical and a societal perspective. It considers the new age of renewable power generation and how computing services can contribute to sustainability and grid decarbonization. Contributors investigate techniques that can be deployed for schedulers to cope with, or even benefit from, changes in the number of computing resources and the nature of the power sources. They survey emerging computing devices, such as edge servers, as alternatives to classical cloud computing platforms; they identify applications for monitoring energy and regulating power; and they investigate energy minimization and risk-aware scheduling in real-time systems, asking: 'How can a server with a variable processing speed schedule jobs with hard deadlines while minimizing its energy consumption?' The authors address the societal impact of computing, exploring how the social sciences play a critical role in solving the computing sustainability challenge and including a holistic analysis of current and future approaches, taking the whole life-cycle and rebound effects into account. Presenting all the corresponding challenges and opportunities of variable capacity scheduling, this is an excellent introduction to the topic for students, researchers, computing scientists, or concerned citizens interested in sustainability.

Presenting a complementary perspective to standard books on algorithms, A Guide to Algorithm Design: Paradigms, Methods, and Complexity Analysis provides a roadmap for readers to determine the difficulty of an algorithmic problem by finding an optimal solution or proving complexity results. It gives a practical treatment of algorithmic complexity and guides readers in solving algorithmic problems.Divided into three parts, the book offers a comprehensive set of problems with solutions as well as in-depth case studies that demonstrate how to assess the complexity of a new problem. Part I helps readers understand the main design principles and design efficient algorithms.Part II covers polynomial reductions from NP-complete problems and approaches that go beyond NP-completeness.Part III supplies readers with tools and techniques to evaluate problem complexity, including how to determine which instances are polynomial and which are NP-hard.Drawing on the authors’ classroom-tested material, this text takes readers step by step through the concepts and methods for analyzing algorithmic complexity. Through many problems and detailed examples, readers can investigate polynomial-time algorithms and NP-completeness and beyond.