Network infrastructures are growing rapidly to meet the needs of business, but the required repolicing and reconfiguration provide challenges that need to be addressed. The software-defined network (SDN) is the future generation of Internet technology that can help meet these challenges of network management. This book includes quantitative research, case studies, conceptual papers, model papers, review papers, and theoretical backing on SDN. This book investigates areas where SDN can help other emerging technologies deliver more efficient services, such as IoT, industrial IoT, NFV, big data, blockchain, cloud computing, and edge computing. The book demonstrates the many benefits of SDNs, such as reduced costs, ease of deployment and management, better scalability, availability, flexibility and fine-grained control of traffic, and security. The book demonstrates the many benefits of SDN, such as reduced costs, ease of deployment and management, better scalability, availability, flexibility and fine-grained control of traffic, and security. Chapters in the volume address: Design considerations for security issues and detection methods State-of-the-art approaches for mitigating DDos attacks using SDN Big data using Apache Hadoop for processing and analyzing large amounts of data Different tools used for attack simulation Network policies and policy management approaches that are widely used in the context of SDN Dynamic flow tables, or static flow table management A new four-tiered architecture that includes cloud, SDN-controller, and fog computing Architecture for keeping computing resources available near the industrial IoT network through edge computing The impact of SDN as an innovative approach for smart city development More. The book will be a valuable resource for SDN researchers as well as academicians, research scholars, and students in the related areas.

Today's advancements in technology have brought about a new era of speed and simplicity for consumers and businesses. Due to these new benefits, the possibilities of universal connectivity, storage and computation are made tangible, thus leading the way to new Internet-of Things solutions. Resource Management and Efficiency in Cloud Computing Environments is an authoritative reference source for the latest scholarly research on the emerging trends of cloud computing and reveals the benefits cloud paths provide to consumers. Featuring coverage across a range of relevant perspectives and topics, such as big data, cloud security, and utility computing, this publication is an essential source for researchers, students and professionals seeking current research on the organization and productivity of cloud computing environments. Topics Covered: Big Data Cloud Application Services (SaaS) Cloud Security Hybrid Cloud Internet of Things (IoT) Private Cloud Public Cloud Service Oriented Architecture (SOA) Utility Computing Virtualization Technology

SDN-Supported Edge-Cloud Interplay for Next Generation Internet of Things is an invaluable resource coveringa wide range of research directions in the field of edge-cloud computing, SDN, and IoT. The integration of SDN in edge-cloud interplay is a promising framework for enhancing the QoS for complex IoT-driven applications. The interplay between cloud and edge solves some of the major challenges that arise in traditional IoT architecture. This book is a starting point for those involved in this research domain and explores a range of significant issues including network congestion, traffic management, latency, QoS, scalability, security, and controller placement problems. Features: The book covers emerging trends, issues and solutions in the direction of Edge-cloud interplay It highlights the research advances in on SDN, edge, and IoT architecture for smart cities, and software-defined internet of vehicles It includes detailed discussion has made of performance evaluations of SDN controllers, scalable software-defined edge computing, and AI for edge computing Applications areas include machine learning and deep learning in SDN-supported edge-cloud systems Different use cases covered include smart health care, smart city, internet of drones, etc This book is designed for scientific communities including graduate students, academicians, and industry professionals who are interested in exploring technologies related to the internet of things such as cloud, SDN, edge, internet of drones, etc.

Network infrastructures are growing rapidly to meet the needs of business, but the required repolicing and reconfiguration provide challenges that need to be addressed. The software-defined network (SDN) is the future generation of Internet technology that can help meet these challenges of network management. This book includes quantitative research, case studies, conceptual papers, model papers, review papers, and theoretical backing on SDN. This book investigates areas where SDN can help other emerging technologies deliver more efficient services, such as IoT, industrial IoT, NFV, big data, blockchain, cloud computing, and edge computing. The book demonstrates the many benefits of SDNs, such as reduced costs, ease of deployment and management, better scalability, availability, flexibility and fine-grained control of traffic, and security. The book demonstrates the many benefits of SDN, such as reduced costs, ease of deployment and management, better scalability, availability, flexibility and fine-grained control of traffic, and security. Chapters in the volume address: Design considerations for security issues and detection methods State-of-the-art approaches for mitigating DDos attacks using SDN Big data using Apache Hadoop for processing and analyzing large amounts of data Different tools used for attack simulation Network policies and policy management approaches that are widely used in the context of SDN Dynamic flow tables, or static flow table management A new four-tiered architecture that includes cloud, SDN-controller, and fog computing Architecture for keeping computing resources available near the industrial IoT network through edge computing The impact of SDN as an innovative approach for smart city development More. The book will be a valuable resource for SDN researchers as well as academicians, research scholars, and students in the related areas.

Real time distributed systems (RTDS) operate in an environment that un- dergoes unpredictable changes causing certain system performance features to degrade. Such unpredictability can be the result of sudden machine failures, in- creases in system load, or errors caused by inaccurate initial estimation. These systems need robustness to guarantee limited degradation despite uctuations in the behavior of its component parts or environment. The robustness gives an idea of the stability of the solution with regards to another performance metric such as schedule length, load balance of an application, queue waiting time of batch scheduler, etc. Designing robust systems for such environments involves determining resource allocations that can account for uncertainty in estimated system parameters. Robustness of the system can be achieved with proper resource allocation.

Continuous changing scenarios of software development technology make effort estimation more challenging. Some of the difficulties of estimation arise from the complexity and invisibility of software. Software development is intensively human activity and can't be free from error. Ability of ANN(Artificial Neural Network) to model a complex set of relationship between the dependent variable (effort) and the independent variables (cost drivers) makes it as a potential tool for estimation. The application of artificial neural networks in prediction of effort in conventional and Object Oriented Software development approach has been discussed.

Routing and Wavelength Assignment (RWA) is a well known problem in Wavelength Division Multiplexing (WDM) networks. RWA problem is reported in the literature as a single objective ILP problem. In this article, we formulated the RWA problem as a multi objective ILP problem. An attempt is made to obtain a feasible solution using genetic algorithm (GA). The parameters considered for optimization are congestion among the individual lightpath requests, connection set up time, the number of intermediate hops traversed and the number of fibers used to honor the established connection requests. We considered ARPANET and NSFNET for our simulation.

This book gives an excellent overview on secure and energy efficient data collection taking sink as the dynamic and other sensors are static in Wireless Sensor Networks. Mobile sink wireless sensor networks (MSWSN) Sensor nodes are low cost tiny devices with limited storage, computational capability and power except the sink node. Mobile sink has no resource limitation. Here we proposed energy efficient secure data collection techniques with mobile sink wireless sensor networks and secure the data collection process using symmetric key cryptography. we also proved an existing protocol Sensor Protocol for Information via Negation (SPIN) is efficient for critical data transmission to the mobile sink. Then we make it as the secured protocol by using symmetric key cryptography. All the simulation has been carried out with NS 2.34. This work is supported by the literature survey in the area of Mobile Sink Wireless Sensor Networks to make it complete.

Cryptography and Network Security in high speed networks demands for specializedhardware in order to match up with the network speed. These hardwaremodules are being realized using reconfigurable FPGA technology to supportheavy computation. Our work is mainly based on designing an efficient architecturefor a cryptographic module and a network intrusion detection system for ahigh speed network. All the designs are coded using VHDL and are synthesizedusing Xilinx ISE for verifying their functionality. Virtex II pro FPGA is chosenas the target device for realization of the proposed design. The Network IntrusionDetection System (NIDS) module is designed for scanning suspicious patterns indata packets incoming to the network. Scanning a data packet against multiplepatterns in quick time is a highly computational intensive task. The design goal is to increasethe data conversion rate i.e the throughput to a substantial value so thatthe design can be used as a separate hardware module in high speed network applications.