Networking And Computation
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Crowd Assisted Networking and Computing
Crowd computing, crowdsourcing, crowd-associated network (CrAN), crowd-assisted sensing are some examples of crowd-based concepts that harness the power of people on the web or connected via web-like infrastructure to do tasks that are often difficult for individual users or computers to do alone. This creates many challenging issues like assessing reliability and correctness of crowd generated information, delivery of data and information via crowd, middleware for supporting crowdsourcing and crowd computing tasks, crowd associated networking and its security, Quality of Information (QoI) issues, etc. This book compiles the latest advances in the relevant fields.
Cloud Computing Networking
Cloud computing is the most significant technology transformation since the introduction of the Internet in the early 1990s. This book covers the key networking and system administration concepts as well as the vital hands-on skills you need to master cloud technology. It is designed to help you quickly get started in deploying cloud services for a real-world business. It provides detailed step-by-step instructions for creating a fully functioning cloud-based IT infrastructure using Microsoft Azure. The book enhances your hands-on skills through numerous lab activities.
Computational Network Science
The emerging field of network science represents a new style of research that can unify such traditionally-diverse fields as sociology, economics, physics, biology, and computer science. It is a powerful tool in analyzing both natural and man-made systems, using the relationships between players within these networks and between the networks themselves to gain insight into the nature of each field. Until now, studies in network science have been focused on particular relationships that require varied and sometimes-incompatible datasets, which has kept it from being a truly universal discipline. Computational Network Science seeks to unify the methods used to analyze these diverse fields. This book provides an introduction to the field of Network Science and provides the groundwork for a computational, algorithm-based approach to network and system analysis in a new and important way. This new approach would remove the need for tedious human-based analysis of different datasets and help researchers spend more time on the qualitative aspects of network science research. - Demystifies media hype regarding Network Science and serves as a fast-paced introduction to state-of-the-art concepts and systems related to network science - Comprehensive coverage of Network Science algorithms, methodologies, and common problems - Includes references to formative and updated developments in the field - Coverage spans mathematical sociology, economics, political science, and biological networks