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Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing
This book presents scientific results of the 23rd ACIS International Summer Virtual Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD2022-Summer) which was held on July 4-6, 2022, at Kyoto City, Japan. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications, and tools) of computer and information science and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the best papers from those papers accepted for presentation at the workshop. The papers were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round of review, 15 of most promising papers are then published in this Springer (SCI) book and not the conference proceedings. We impatiently await the important contributions that we know these authors will bring to the field of computer and information science.
R 6,594.00
Evolutionary Computing and Mobile Sustainable Networks
This book features selected research papers presented at the International Conference on Evolutionary Computing and Mobile Sustainable Networks (ICECMSN 2020), held at the Sir M. Visvesvaraya Institute of Technology on 20–21 February 2020. Discussing advances in evolutionary computing technologies, including swarm intelligence algorithms and other evolutionary algorithm paradigms which are emerging as widely accepted descriptors for mobile sustainable networks virtualization, optimization and automation, this book is a valuable resource for researchers in the field of evolutionary computing and mobile sustainable networks.
R 9,479.01
Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing
This edited book presents scientific results of 15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2014) held on June 30 – July 2, 2014 in Las Vegas Nevada, USA. The aim of this conference was to bring together scientists, engineers, computer users, and students to share their experiences and exchange new ideas, research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the 13 outstanding papers from those papers accepted for presentation at the conference.
R 4,369.32
Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing
This book gathers 14 of the most promising papers presented at the 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2017), which was held on June 26–28, 2017 in Kanazawa, Japan. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. The book presents research findings concerning all aspects (theory, applications and tools) of computer and information science, and discusses the practical challenges encountered along the way, as well as the solutions adopted to solve them.
R 3,768.48
Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing
This book presents the outcomes of the 20th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2019), which was held on July 8–10, 2019, in Toyama, Japan. The aim of the conference was to bring together researchers and scientists, businesspeople and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Further, they presented research results on all aspects (theory, applications and tools) of computer and information science, and discussed the practical challenges encountered in their work and the solutions they adopted to overcome them. The book highlights the best papers from those accepted for presentation at the conference. They were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round, 15 of the conference’s most promising papers were selected for this Springer (SCI) book and not the conference proceedings. We eagerly await the important contributions that we know these authors will make to the field of computer and information science.
R 3,622.61
Information Processing and Network Provisioning
The four-volume set CCIS 2416, 2417, 2418 and 2419 constitutes the refereed post-conference proceedings of the Third International Conference on Information Processing and Network Provisioning, ICIPNP 2024 Spring, held in Beijing, China, during June 14–16, 2024.The 152 revised full papers presented in these proceedings were carefully reviewed and selected from 347 submissions. They focus on topics ranging from 5G/6G evolution and AI in network optimization to quantum communication and green computing.
R 5,442.56
Distributed Average Tracking in Multi-agent Systems
This book presents a systematic study of an emerging field in the development of multi-agent systems. In a wide spectrum of applications, it is now common to see that multiple agents work cooperatively to accomplish a complex task. The book assists the implementation of such applications by promoting the ability of multi-agent systems to track — using local communication only — the mean value of signals of interest, even when these change rapidly with time and when no individual agent has direct access to the average signal across the whole team; for example, when a better estimation/control performance of multi-robot systems has to be guaranteed, it is desirable for each robot to compute or track the averaged changing measurements of all the robots at any time by communicating with only local neighboring robots. The book covers three factors in successful distributed average tracking:algorithm design via nonsmooth and extended PI control;distributed average tracking for double-integrator, general-linear, Euler–Lagrange, and input-saturated dynamics; andapplications in dynamic region-following formation control and distributed convex optimization. The book presents both the theory and applications in a general but self-contained manner, making it easy to follow for newcomers to the topic. The content presented fosters research advances in distributed average tracking and inspires future research directions in the field in academia and industry.
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Network and Traffic Engineering in Emerging Distributed Computing Applications
Network and Traffic Engineering in Emerging Distributed Computing Applications focuses on network management and traffic engineering for Internet and distributed computing technologies, as well as present emerging technology trends and advanced platforms. This premier reference source for academics, students, researchers, readers, and knowledge seekers puts together some of the critical aspects of Internet and distributed systems.
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Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation
In this book, anew method for hybrid intelligent systems is proposed. The proposed method isbased on a granular computing approach applied in two levels. The techniquesused and combined in the proposed method are modular neural networks (MNNs)with a Granular Computing (GrC) approach, thus resulting in a new concept ofMNNs; modular granular neural networks (MGNNs). In addition fuzzy logic (FL)and hierarchical genetic algorithms (HGAs) are techniques used in this researchwork to improve results. These techniques are chosen because in other workshave demonstrated to be a good option, and in the case of MNNs and HGAs, thesetechniques allow to improve the results obtained than with their conventionalversions; respectively artificial neural networks and genetic algorithms.
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Data-Driven Systems and Intelligent Applications
This book comprehensively discusses basic data-driven intelligent systems, the methods for processing the data, and cloud computing with artificial intelligence. It presents fundamental and advanced techniques used for handling large user data, and for the data stored in the cloud. It further covers data-driven decision-making for smart logistics and manufacturing systems, network security, and privacy issues in cloud computing.This book:Discusses intelligent systems and cloud computing with the help of artificial intelligence and machine learning. Showcases the importance of machine learning and deep learning in data-driven and cloud-based applications to improve their capabilities and intelligence. Presents the latest developments in data-driven and cloud applications with respect to their design and architecture. Covers artificial intelligence methods along with their experimental result analysis through data processing tools. Presents the advent of machine learning, deep learning, and reinforcement technique for cloud computing to provide cost-effective and efficient services. The text will be useful for senior undergraduate, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, computer engineering, manufacturing engineering, and production engineering.
R 2,711.00
Learning and Intelligent Optimization
This book constitutes the thoroughly refereed post-conference proceedings of the 8th International Conference on Learning and Optimization, LION 8, which was held in Gainesville, FL, USA, in February 2014. The 33 contributions presented were carefully reviewed and selected for inclusion in this book. A large variety of topics are covered, such as algorithm configuration; multiobjective optimization; metaheuristics; graphs and networks; logistics and transportation; and biomedical applications.
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Exploration of Novel Intelligent Optimization Algorithms
This book constitutes the refereed proceedings of the 12th International Symposium, ISICA 2021, held in Guangzhou, China, during November 19–21, 2021. The 48 full papers included in this book were carefully reviewed and selected from 99 submissions. They were organized in topical sections as follows: new frontier of multi-objective evolutionary algorithms; intelligent multi-media; data modeling and application of artificial intelligence; exploration of novel intelligent optimization algorithm; and intelligent application of industrial production.
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Advanced Engineering Optimization Through Intelligent Techniques
This book comprises select peer-reviewed papers presented at the International Conference on Advanced Engineering Optimization Through Intelligent Techniques (AEOTIT) 2018. The book combines contributions from academics and industry professionals, and covers advanced optimization techniques across all major engineering disciplines like mechanical, manufacturing, civil, automobile, electrical, chemical, computer and electronics engineering. Different optimization techniques and algorithms such as genetic algorithm (GA), differential evolution (DE), simulated annealing (SA), particle swarm optimization (PSO), artificial bee colony (ABC) algorithm, artificial immune algorithm (AIA), teaching-learning-based optimization (TLBO) algorithm and many other latest meta-heuristic techniques and their applications are discussed. This book will serve as a valuable reference for students, researchers and practitioners and help them in solving a wide range of optimization problems.
R 8,959.64
Artificial Intelligence Application in Networks and Systems
The application of artificial intelligence in networks and systems is a rapidly evolving field that has the potential to transform a wide range of industries. The refereed proceedings in this book is from the Artificial Intelligence Application in Networks and Systems session of the Computer Science Online Conference 2023 (CSOC 2023), which was held online in April 2023. The section brings together experts from different fields to present their research and discuss the latest trends and challenges.One of the key themes in this section is the development of intelligent systems that can learn, adapt, and optimize their performance in real time. Researchers are exploring how AI algorithms can be used to create autonomous networks and systems that can make decisions without human intervention.Furthermore, this section highlights the use of AI in improving network performance and efficiency. Researchers are exploring how AI algorithms can be used to optimize network routing, reduce congestion, and improve the quality of service. These efforts can help organizations save costs and improve user experience.
R 9,158.00
Optimization of Stochastic Discrete Systems and Control on Complex Networks
This book presents the latest findings on stochastic dynamic programming models and on solving optimal control problems in networks. It includes the authors’ new findings on determining the optimal solution of discrete optimal control problems in networks and on solving game variants of Markov decision problems in the context of computational networks. First, the book studies the finite state space of Markov processes and reviews the existing methods and algorithms for determining the main characteristics in Markov chains, before proposing new approaches based on dynamic programming and combinatorial methods. Chapter two is dedicated to infinite horizon stochastic discrete optimal control models and Markov decision problems with average and expected total discounted optimization criteria, while Chapter three develops a special game-theoretical approach to Markov decision processes and stochastic discrete optimal control problems. In closing, the book’s final chapter is devoted to finite horizon stochastic control problems and Markov decision processes. The algorithms developed represent a valuable contribution to the important field of computational network theory.
R 3,058.18
Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing 2010
th The purpose of the 11 Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2010) held on June 9 – 11, 2010 in London, United Kingdom was to bring together researchers and scientists, businessmen and entrepreneurs, teachers and students to discuss the numerous fields of computer science, and to share ideas and information in a meaningful way. Our conference officers selected the best 15 papers from those papers accepted for presentation at the conference in order to publish them in this volume. The papers were chosen based on review scores submitted by members of the program committee, and underwent further rounds of rigorous review. In Chapter 1, Cai Luyuan et al. Present a new method of shape decomposition based on a refined morphological shape decomposition process. In Chapter 2, Kazunori Iwata et al. propose a method for reducing the margin of error in effort and error prediction models for embedded software development projects using artificial neural networks (ANNs). In Chapter 3, Viliam Šimko et al. describe a model-driven tool that allows system code to be generated from use-cases in plain English. In Chapter 4, Abir Smiti and Zied Elouedi propose a Case Base Maintenance (CBM) method that uses machine learning techniques to preserve the maximum competence of a system. In Chapter 5, Shagufta Henna and Thomas Erlebach provide a simulation based analysis of some widely used broadcasting schemes within mobile ad hoc networks (MANETs) and propose adaptive extensions to an existing broadcasting algorithm.
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Distributed Intelligent Systems
Distributed Intelligent Systems: A Coordination Perspective comprehensively answers commonly asked questions about coordination in agent-oriented distributed systems. Characterizing the state-of-the-art research in the field of coordination with regard to the development of distributed agent-oriented systems is a particularly complex endeavour; while existing books deal with specific aspects of coordination, the major contribution of this book lies in the attempt to provide an in-depth review covering a wide range of issues regarding multi-agent coordination in Distributed Artificial Intelligence. Key features:Unveils the lack of coherence and order that characterizes the area of research pertaining to coordination of distributed intelligent systemsExamines coordination models, frameworks, strategies and techniques to enable the development of distributed intelligent agent-oriented systemsProvides specific recommendations to realize more widespread deployment of agent-based systems
R 3,019.37
Parallel Combinatorial Optimization
This text provides an excellent balance of theory and application that enables you to deploy powerful algorithms, frameworks, and methodologies to solve complex optimization problems in a diverse range of industries. Each chapter is written by leading experts in the fields of parallel and distributed optimization. Collectively, the contributions serve as a complete reference to the field of combinatorial optimization, including details and findings of recent and ongoing investigations.
R 5,013.00
Robustness Optimization for IoT Topology
The IoT topology defines the way various components communicate with each other within a network. Topologies can vary greatly in terms of security, power consumption, cost, and complexity. Optimizing the IoT topology for different applications and requirements can help to boost the network’s performance and save costs. More importantly, optimizing the topology robustness can ensure security and prevent network failure at the foundation level. In this context, this book examines the optimization schemes for topology robustness in the IoT, helping readers to construct a robustness optimization framework, from self-organizing to intelligent networking.The book provides the relevant theoretical framework and the latest empirical research on robustness optimization of IoT topology. Starting with the self-organization of networks, it gradually moves to genetic evolution. It also discusses the application of neural networks and reinforcement learning to endow the node with self-learning ability to allow intelligent networking.This book is intended for students, practitioners, industry professionals, and researchers who are eager to comprehend the vulnerabilities of IoT topology. It helps them to master the research framework for IoT topology robustness optimization and to build more efficient and reliable IoT topologies in their industry.
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Combustion Optimization Based on Computational Intelligence
This book presents the latest findings on the subject of combustion optimization based on computational intelligence. It covers a broad range of topics, including the modeling of coal combustion characteristics based on artificial neural networks and support vector machines. It also describes the optimization of combustion parameters using genetic algorithms or ant colony algorithms, an online coal optimization system, etc. Accordingly, the book offers a unique guide for researchers in the areas of combustion optimization, NOx emission control, energy and power engineering, and chemical engineering.
R 4,030.00
Developing Networks using Artificial Intelligence
This book mainly discusses the most important issues in artificial intelligence-aided future networks, such as applying different ML approaches to investigate solutions to intelligently monitor, control and optimize networking. The authors focus on four scenarios of successfully applying machine learning in network space. It also discusses the main challenge of network traffic intelligent awareness and introduces several machine learning-based traffic awareness algorithms, such as traffic classification, anomaly traffic identification and traffic prediction. The authors introduce some ML approaches like reinforcement learning to deal with network control problem in this book. Traditional works on the control plane largely rely on a manual process in configuring forwarding, which cannot be employed for today's network conditions. To address this issue, several artificial intelligence approaches for self-learning control strategies are introduced. In addition, resource management problems are ubiquitous in the networking field, such as job scheduling, bitrate adaptation in video streaming and virtual machine placement in cloud computing. Compared with the traditional with-box approach, the authors present some ML methods to solve the complexity network resource allocation problems. Finally, semantic comprehension function is introduced to the network to understand the high-level business intent in this book.With Software-Defined Networking (SDN), Network Function Virtualization (NFV), 5th Generation Wireless Systems (5G) development, the global network is undergoing profound restructuring and transformation. However, with the improvement of the flexibility and scalability of the networks, as well as the ever-increasing complexity of networks, makes effective monitoring, overall control, and optimization of the network extremely difficult. Recently, adding intelligence to the control plane through AI&ML become a trend and a direction of network development This book's expected audience includes professors, researchers, scientists, practitioners, engineers, industry managers, and government research workers, who work in the fields of intelligent network. Advanced-level students studying computer science and electrical engineering will also find this book useful as a secondary textbook.
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Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing 2015
This edited book presents scientific results of the 16th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2015) which was held on June 1 – 3, 2015 in Takamatsu, Japan. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them.
R 3,911.98
Towards User-Centric Intelligent Network Selection in 5G Heterogeneous Wireless Networks
This book presents reinforcement learning (RL) based solutions for user-centric online network selection optimization. The main content can be divided into three parts. The first part (chapter 2 and 3) focuses on how to learning the best network when QoE is revealed beyond QoS under the framework of multi-armed bandit (MAB). The second part (chapter 4 and 5) focuses on how to meet dynamic user demand in complex and uncertain heterogeneous wireless networks under the framework of markov decision process (MDP). The third part (chapter 6 and 7) focuses on how to meet heterogeneous user demand for multiple users inlarge-scale networks under the framework of game theory. Efficient RL algorithms with practical constraints and considerations are proposed to optimize QoE for realizing intelligent online network selection for future mobile networks. This book is intended as a reference resource for researchers and designers in resource management of 5G networks and beyond.
R 3,330.65
Large-Scale Convex Optimization
Starting from where a first course in convex optimization leaves off, this text presents a unified analysis of first-order optimization methods – including parallel-distributed algorithms – through the abstraction of monotone operators. With the increased computational power and availability of big data over the past decade, applied disciplines have demanded that larger and larger optimization problems be solved. This text covers the first-order convex optimization methods that are uniquely effective at solving these large-scale optimization problems. Readers will have the opportunity to construct and analyze many well-known classical and modern algorithms using monotone operators, and walk away with a solid understanding of the diverse optimization algorithms. Graduate students and researchers in mathematical optimization, operations research, electrical engineering, statistics, and computer science will appreciate this concise introduction to the theory of convex optimization algorithms.
R 3,096.13
Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing
This edited book presents scientific results of the 14th ACIS/IEEE International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2013), held in Honolulu, Hawaii, USA on July 1-3, 2013. The aim of this conference was to bring together scientists, engineers, computer users, and students to share their experiences and exchange new ideas, research results about all aspects (theory, applications and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the 17 outstanding papers from those papers accepted for presentation at the conference.
R 4,647.69
Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing
This book presents the outcomes of the 20th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD 2019), which was held on July 8–10, 2019, in Toyama, Japan. The aim of the conference was to bring together researchers and scientists, businesspeople and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way. Further, they presented research results on all aspects (theory, applications and tools) of computer and information science, and discussed the practical challenges encountered in their work and the solutions they adopted to overcome them. The book highlights the best papers from those accepted for presentation at the conference. They were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round, 15 of the conference’s most promising papers were selected for this Springer (SCI) book and not the conference proceedings. We eagerly await the important contributions that we know these authors will make to the field of computer and information science.
R 3,939.30
Distributed Energy Resources in Local Integrated Energy Systems
Distributed Energy Resources in Local Integrated Energy Systems: Optimal Operation and Planning reviews research and policy developments surrounding the optimal operation and planning of DER in the context of local integrated energy systems in the presence of multiple energy carriers, vectors and multi-objective requirements. This assessment is carried out by analyzing impacts and benefits at local levels, and in distribution networks and larger systems. These frameworks represent valid tools to provide support in the decision-making process for DER operation and planning. Uncertainties of RES generation and loads in optimal DER scheduling are addressed, along with energy trading and blockchain technologies. Interactions among various energy carriers in local energy systems are investigated in scalable and flexible optimization models for adaptation to a number of real contexts thanks to the wide variety of generation, conversion and storage technologies considered, the exploitation of demand side flexibility, emerging technologies, and through the general mathematical formulations established.
R 4,414.00
Nature-Inspired Optimization Algorithms for Cyber-Physical Systems
Cyber-physical systems (CPS) integrate computation, communication, control, and physical elements to achieve shared goals with minimal human intervention, encompassing smart technologies such as cities, cloud computing, and smart grids. As CPS components expand, generating vast amounts of data, they face challenges in areas like resource management, security, computation offloading, and automation, demanding advanced techniques beyond traditional algorithms. Nature-inspired optimization algorithms, drawing on natural phenomena, offer scalable and adaptable solutions for these complex issues, making them essential for addressing CPS challenges efficiently and enhancing their role in our daily lives. Nature-Inspired Optimization Algorithms for Cyber-Physical Systems provides relevant theoretical frameworks and the latest empirical research findings in the area. It explores the nature-inspired optimization algorithms intended to boost the performance of CPS. Covering topics such as ant colony optimization, data analysis, and smart cities, this book is an excellent resource for teaching staff, researchers, academicians, graduate and postgraduate students, and more.
R 9,500.98
Intelligent Networks
Substantial new breakthroughs are happening in telecommunications technology. This volume presents a state-of-the-art review of the current research activities in intelligent network technology. It contains the proceedings of a workshop on intelligent networks organized by the International Federation of Information Processsing and held as part of the Third Summer School on Telecommunications in Lappeenranta, Finland, August 1994.
R 6,001.11
Parallel and Distributed Computational Intelligence
Francisco Fern' andez de Vega and Erick Cantu- ' Paz The growing success of biologically inspired algorithms in solving large and complex problems has spawned many interesting areas of research. Over the years, one of the mainstays in bio-inspired research has been the exploi- tion of parallel and distributed environments to speedup computations and to enrich the algorithms. From the early days of research on bio-inspired algorithms, their inherently parallel nature was recognized and di?erent p- allelization approaches have been explored. Parallel algorithms promise - ductions in execution time and open the door to solve increasingly larger problems. But parallel platforms also inspire new bio-inspired parallel al- rithms that, while similar to their sequential counterparts, explore search spaces di?erently and o?er improvements in solution quality. Our objective in editing this book was to assemble a sample of the best work in parallel and distributed biologically inspired algorithms. We invited researchers in di?erent domains to submit their work. We aimed to include diverse topics to appeal to a wide audience.Some of the chapters sum- rize work that has been ongoing for several years, while others describe more recent exploratory work. Collectively, these works o?er a global snapshot of the most recent e?orts of bioinspired algorithms' researchers aiming at pr- iting from parallel and distributed computer architectures-including GPUs, Clusters, Grids, volunteer computing and p2p networks as well as multi-core processors.
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Distributed Computing Innovations for Business, Engineering, and Science
In recent years, distributed systems and computing applications continue to increase its approaches towards business, engineering and science. Distributed Computing Innovations for Business, Engineering, and Science is a collection of widespread research providing relevant theoretical frameworks and research findings on the applications of distributed computing innovations to the business, engineering and science fields. This book aims to provide insights on the management of expertise, knowledge, information and organisational development in distributed computing.
R 7,570.04
4th International Conference on Wireless, Intelligent and Distributed Environment for Communication
This book presents the proceedings of the 4th International Conference on Wireless Intelligent and Distributed Environment for Communication (WIDECOM 2021), which took place at University of KwaZulu-Natal, South Africa, October 13-15, 2021. The book addresses issues related to new dependability paradigms, design, and performance of dependable network computing and mobile systems, as well as issues related to the security of these systems. The main tracks include infrastructure, architecture, algorithms, and protocols. The goal of the conference is to provide a forum for researchers, students, scientists and engineers working in academia and industry to share their experiences, new ideas and research results in the above-mentioned areas.
R 5,947.03
Artificial Intelligence for Communications and Networks
This two-volume set LNICST 286-287 constitutes the post-conference proceedings of the First EAI International Conference on Artificial Intelligence for Communications and Networks, AICON 2019, held in Harbin, China, in May 2019. The 93 full papers were carefully reviewed and selected from 152 submissions. The papers are organized in topical sections on artificial intelligence, mobile network, deep learning, machine learning, wireless communication, cognitive radio, internet of things, big data, communication system, pattern recognition, channel model, beamforming, signal processing, 5G, mobile management, resource management, wireless position.
R 1,603.85
Distributed Computer and Communication Networks
This book constitutes the refereed proceedings of the 19th International Conference on Distributed and Computer and Communication Networks, DCCN 2016, held in Moscow, Russia, in November 2016. The 50 revised full papers and the 6 revised short papers presented were carefully reviewed and selected from 141 submissions. The papers cover the following topics: computer and communication networks architecture optimization; control in computer and communication networks; performance and QoS/QoE evaluation in wireless networks; analytical modeling and simulation of next-generation communications systems; queuing theory and reliability theory applications in computer networks; wireless 4G/5G networks, cm- and mm-wave radio technologies; RFID technology and its application in intellectual transportation networks; internet of things, wearables, and applications of distributed information systems; probabilistic and statistical models in information systems; mathematical modeling of high-tech systems; mathematical modeling and control problems; distributed and cloud computing systems, big data analytics.
R 2,236.49
4th International Conference on Wireless, Intelligent and Distributed Environment for Communication
This book presents the proceedings of the 4th International Conference on Wireless Intelligent and Distributed Environment for Communication (WIDECOM 2021), which took place at University of KwaZulu-Natal, South Africa, October 13-15, 2021. The book addresses issues related to new dependability paradigms, design, and performance of dependable network computing and mobile systems, as well as issues related to the security of these systems. The main tracks include infrastructure, architecture, algorithms, and protocols. The goal of the conference is to provide a forum for researchers, students, scientists and engineers working in academia and industry to share their experiences, new ideas and research results in the above-mentioned areas.
R 5,768.92
Hybrid Optimization
Hybrid Optimization focuses on the application of artificial intelligence and operations research techniques to constraint programming for solving combinatorial optimization problems. This book covers the most relevant topics investigated in the last ten years by leading experts in the field, and speculates about future directions for research.This book includes contributions by experts from different but related areas of research including constraint programming, decision theory, operations research, SAT, artificial intelligence, as well as others. These diverse perspectives are actively combined and contrasted in order to evaluate their relative advantages.This volume presents techniques for hybrid modeling, integrated solving strategies including global constraints, decomposition techniques, use of relaxations, and search strategies including tree search local search and metaheuristics. Various applications of the techniques presented as well as supplementary computational tools are also discussed.
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Distributed Computing and Artificial Intelligence, 21st International Conference
This book serves as a forum to present applications of innovative techniques for studying and solving complex problems in artificial intelligence and computing. This edition brings together experience, current work, and promising future trends related to distributed computing, artificial intelligence, and their applications to provide efficient solutions to real-world problems. The technical program this year is both high in quality and diverse, featuring contributions from well-established and evolving research areas. Specifically, 138 papers were submitted by authors from 43 different countries, representing a truly global network of research activity. The DCAI’24 technical program has selected 36 full papers for the main track, and as in previous editions, there will be special issues in ranked journals. This symposium is organized by the University of Salamanca (Spain). The authors would like to thank all the contributing authors, the program committee members, National Associations (AEPIA, APPIA, LASI), and the sponsors (AIR Institute).
R 7,326.00
Artificial Intelligence for Communications and Networks
This book, AICON 2022, constitutes the post-conference proceedings of the 4th EAI International Conference on Artificial Intelligence for Communications and Networks, AICON 2022, held in Hiroshima, Japan, in November 30- December 1, 2022. The 9 full papers and 4 short papers were carefully reviewed and selected from 36 submissions. The papers detail research in the areas of AI and communication systems related to intelligent systems and computational intelligence for communication and networks. They are organized in topical sections on AI and networks; machine learning; and evolutionary computation.
R 2,725.19
Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing
The 9th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, held in Phuket Thailand on August 6 – 8, 2008 is aimed at bringing together researchers and scientist, businessmen and entrepreneurs, teachers and students to discuss the numerous fields of computer science, and to share ideas and information in a meaningful way. This publication captures 20 of the conference’s most promising papers, and we impatiently await the important contributions that we know these authors will bring to the field.
R 4,380.93
Distributed Computing and Networking
This book constitutes the refereed proceedings of the 11th International Conference on Distributed Computing and Networking, ICDCN 2010, held in Kolkata, India, during January 3-6, 2010. There were 169 submissions, 96 to the networking track and 73 to the distributed computing track. After review the committee selected 23 papers for the networking and 21 for the distributed computing track. The topics addressed are network protocol and applications, fault-tolerance and security, sensor networks, distributed algorithms and optimization, peer-to-peer networks and network tracing, parallel and distributed systems, wireless networks, applications and distributed systems, optical, cellular and mobile ad hoc networks, and theory of distributed systems.
R 4,128.56
Optimization of PID Controllers Using Ant Colony and Genetic Algorithms
Artificial neural networks, genetic algorithms and the ant colony optimization algorithm have become a highly effective tool for solving hard optimization problems. As their popularity has increased, applications of these algorithms have grown in more than equal measure. While many of the books available on these subjects only provide a cursory discussion of theory, the present book gives special emphasis to the theoretical background that is behind these algorithms and their applications. Moreover, this book introduces a novel real time control algorithm, that uses genetic algorithm and ant colony optimization algorithms for optimizing PID controller parameters. In general, the present book represents a solid survey on artificial neural networks, genetic algorithms and the ant colony optimization algorithm and introduces novel practical elements related to the application of these methods to process system control.
R 3,358.43
Conductor: Distributed Adaptation for Heterogeneous Networks
Internet heterogeneity is driving a new challenge in application development: adaptive software. Together with the increased Internet capacity and new access technologies, network congestion and the use of older technologies, wireless access, and peer-to-peer networking are increasing the heterogeneity of the Internet. Applications should provide gracefully degraded levels of service when network conditions are poor, and enhanced services when network conditions exceed expectations. Existing adaptive technologies, which are primarily end-to-end or proxy-based and often focus on a single deficient link, can perform poorly in heterogeneous networks. Instead, heterogeneous networks frequently require multiple, coordinated, and distributed remedial actions. Conductor: Distributed Adaptation for Heterogeneous Networks describes a new approach to graceful degradation in the face of network heterogeneity - distributed adaptation - in which adaptive code is deployed at multiple points within a network. The feasibility of this approach is demonstrated by conductor, a middleware framework that enables distributed adaptation of connection-oriented, application-level protocols. By adapting protocols, conductor provides application-transparent adaptation, supporting both existing applications and applications designed with adaptation in mind. Conductor: Distributed Adaptation for Heterogeneous Networks introduces new techniques that enable distributed adaptation, making it automatic, reliable, and secure. In particular, we introduce the notion of semantic segmentation, which maintains exactly-once delivery of the semantic elements of a data stream while allowing the stream to be arbitrarily adapted in transit. We also introduce a secure architecture for automatic adaptor selection, protecting user data from unauthorized adaptation. These techniques are described both in the context of conductor and in the broader context of distributed systems. Finally, this book presents empirical evidence from several case studies indicating that distributed adaptation can allow applications to degrade gracefully in heterogeneous networks, providing a higher quality of service to users than other adaptive techniques. Further, experimental results indicate that the proposed techniques can be employed without excessive cost. Thus, distributed adaptation is both practical and beneficial. Conductor: Distributed Adaptation for Heterogeneous Networks is designed to meet the needs of a professional audience composed of researchers and practitioners in industry and graduate-level students in computer science.
R 3,030.71
Robustness Optimization for IoT Topology
The IoT topology defines the way various components communicate with each other within a network. Topologies can vary greatly in terms of security, power consumption, cost, and complexity. Optimizing the IoT topology for different applications and requirements can help to boost the network’s performance and save costs. More importantly, optimizing the topology robustness can ensure security and prevent network failure at the foundation level. In this context, this book examines the optimization schemes for topology robustness in the IoT, helping readers to construct a robustness optimization framework, from self-organizing to intelligent networking.The book provides the relevant theoretical framework and the latest empirical research on robustness optimization of IoT topology. Starting with the self-organization of networks, it gradually moves to genetic evolution. It also discusses the application of neural networks and reinforcement learning to endow the node with self-learning ability to allow intelligent networking.This book is intended for students, practitioners, industry professionals, and researchers who are eager to comprehend the vulnerabilities of IoT topology. It helps them to master the research framework for IoT topology robustness optimization and to build more efficient and reliable IoT topologies in their industry.
R 7,299.92
Stochastic Optimization for Distributed Energy Resources in Smart Grids
This brief focuses on stochastic energy optimization for distributed energy resources in smart grids. Along with a review of drivers and recent developments towards distributed energy resources, this brief presents research challenges of integrating millions of distributed energy resources into the grid. The brief then proposes a novel three-level hierarchical architecture for effectively integrating distributed energy resources into smart grids. Under the proposed hierarchical architecture, distributed energy resource management algorithms at the three levels (i.e., smart home, smart neighborhood, and smart microgrid) are developed in this brief based on stochastic optimization that can handle the involved uncertainties in the system.
R 2,015.00
Logistics Management and Optimization through Hybrid Artificial Intelligence Systems
Logistics Management and Optimization through Hybrid Artificial Intelligence Systems offers the latest research within the field of HAIS, surveying the broad topics and collecting case studies, future directions, and cutting edge analyses. Using biologically inspired algorithms such as ant colony optimization and particle swarm optimization, this text includes solutions and heuristics for practitioners and academics alike, offering a vital resource for staying abreast in this ever-burgeoning field.
R 7,613.87
Real-Time Intelligence for Heterogeneous Networks
This book discusses several exciting research topics and applications in the intelligent Heterogenous Networks (Het-Net) and Internet of Things (IoT) era. We are resolving significant issues towards realizing the future vision of the Artificial Intelligence (AI) in IoT-enabled spaces. Such AI-powered IoT solutions will be employed in satisfying critical conditions towards further advances in our daily smart life. This book overviews the associated issues and proposes the most up to date alternatives. The objective is to pave the way for AI-powered IoT-enabled spaces in the next generation Het-Net technologies and open the door for further innovations. The book presents the latest advances and research into heterogeneous networks in critical IoT applications. It discusses the most important problems, challenges, and issues that arise when designing real-time intelligent heterogeneous networks for diverse scenarios.
R 5,312.25
