This book provides a timely and comprehensive study of dynamic resource management for network slicing in service-oriented fifth-generation (5G) and beyond core networks. This includes the perspective of developing efficient computation resource provisioning and scheduling solutions to guarantee consistent service performance in terms of end-to-end (E2E) data delivery delay. Network slicing is enabled by the software defined networking (SDN) and network function virtualization (NFV) paradigms. For a network slice with a target traffic load, the E2E service delivery is enabled by virtual network function (VNF) placement and traffic routing with static resource allocations. When data traffic enters the network, the traffic load is dynamic and can deviate from the target value, potentially leading to QoS performance degradation and network congestion. Data traffic has dynamics in different time granularities. For example, the traffic statistics (e.g., mean and variance) can be non-stationary and experience significant changes in a coarse time granularity, which are usually predictable. Within a long time duration with stationary traffic statistics, there are traffic dynamics in small timescales, which are usually highly bursty and unpredictable. To provide continuous QoS performance guarantee and ensure efficient and fair operation of the network slices over time, it is essential to develop dynamic resource management schemes for the embedded services in the presence of traffic dynamics during virtual network operation. Queueing theory is used in system modeling, and different techniques including optimization and machine learning are applied to solving the dynamic resource management problems. Based on a simplified M/M/1 queueing model with Poisson traffic arrivals, an optimization model for flow migration is presented to accommodate the large-timescale changes in the average traffic rates with average E2E delay guarantee, while addressing a trade-off between load balancing and flow migration overhead. To overcome the limitations of Poisson traffic model, the authors present a machine learning approach for dynamic VNF resource scaling and migration. The new solution captures the inherent traffic patterns in a real-world traffic trace with non-stationary traffic statistics in large timescale, predicts resource demands for VNF resource scaling, and triggers adaptive VNF migration decision making, to achieve load balancing, migration cost reduction, and resource overloading penalty suppression in the long run. Both supervised and unsupervised machine learning tools are investigated for dynamic resource management. To accommodate the traffic dynamics in small time granularities, the authors present a dynamic VNF scheduling scheme to coordinate the scheduling among VNFs of multiple services, which achieves network utility maximization with delay guarantee for each service. Researchers and graduate students working in the areas of electrical engineering, computing engineering and computer science will find this book useful as a reference or secondary text. Professionals in industry seeking solutions to dynamic resource management for 5G and beyond networks will also want to purchase this book.

This book constitutes the refereed proceedings of the 5th International Conference on Autonomous Infrastructure, Management and Security, AIMS 2011, held in Nancy, France, in June 2011. The 11 revised full papers presented together 11 papers of the AIMS PhD workshops were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on security management, autonomic network and service management (PhD workshop), policy management, P2P and aggregation schemes, and monitoring and security (PhD workshop).

"This book should be immensely interesting to those trying to decide what MANET research is worth undertaking and why." -J. Christopher Ramming, Program Manager, Defense Advanced Research Projects Agency (DARPA) Strategic Technology Office A thorough, comprehensive treatment of mobile ad hoc network management Mobile ad hoc networking is a hot topic, gaining importance in both commercial and military arenas. Now that the basics in the field have settled and standards are emerging, the time is right for a book on management of these networks. From two experts in the field, Policy-Driven Mobile Ad hoc Network Management provides comprehensive coverage of the management challenges associated with mobile ad hoc networks(MANETs) and includes an in-depth discussion of how policy-based network management can be used for increasing automation in the management of mobile ad hoc networks. This book provides readers with a complete understanding of mobile ad hoc network management and many related topics, including: ?Network management requirements for MANETs, with an emphasis on the differences between the management requirements for MANETs as compared to static, wireline networks ?The use of policies for managing MANETs to increase automation and to tie together management components via policies ?Policy conflict detection and resolution ?Aspects of MANETs that need to be configured and reconfigured at all layers of the protocol stack ?Methodologies for providing survivability in the face of both hard and soft failures in MANETs ?The components of a Quality of Service (QoS) management solution for MANETs based on the widely used Differentiated Services (DiffServ) paradigm ?Important open research issues in the area of MANET management Policy-Driven Mobile Ad hoc Network Management is an ideal resource for professionals, researchers, and advanced graduate students in the field of IP network management who are interested in mobile ad hoc networks.

An authoritative collection of research papers and surveys, Emerging Wireless Networks: Concepts, Techniques, and Applications explores recent developments in next-generation wireless networks (NGWNs) and mobile broadband networks technologies, including 4G (LTE, WiMAX), 3G (UMTS, HSPA), WiFi, mobile ad hoc networks, mesh networks, and wireles

Service platforms have moved into the center of interest in both academic research and the IT industry due to their economic and technical impact. These multitenant platforms provide own or third party software as metered, on-demand services. Corresponding service offers exhibit network effects. The present work introduces a graphical modeling language to support service platform design with focus on the exploitation of these network effects.