Laurence Tianruo Yang – författare

Parallel and distributed computing is one of the foremost technologies for shapingfuture research and development activities in academia and industry. Hyperthreading in Intel processors, hypertransport links in next generation AMD processors, multicore silicon in today’s high-end microprocessors, and emerging cluster and grid computing have moved parallel/distributed computing into the mainstream of computing.

New Horizons of Parallel and Distributed Computing is a collection of self-contained chapters written by pioneering researchers to provide solutions for newly emerging problems in this field. This volume will not only provide novel ideas, work in progress and state-of-the-art techniques in the field, but will also stimulate future research activities in the area of parallel and distributed computing with applications.

New Horizons of Parallel and Distributed Computing is intended for industry researchers and developers, as well as for academic researchers and advanced-level students in computer science and electrical engineering.  A valuable reference work, it is also suitable as a textbook.

Scheduling in Distributed Computing Systems: Analysis, Design and Models intends to inculcate the innovative ideas for the scheduling aspect. Although the models in this book are designed for distributed systems, the same information is applicable for any type of system (i.e., where distributed processing is required).

Scheduling in Distributed Computing Systems: Analysis, Design and Models will dramatically improve the design and management of the processes for industry professionals. This book deals exclusively with the scheduling aspect, which finds little space in other distributed operating system books.

Scheduling in Distributed Computing Systems: Analysis, Design and Models is structured for a professional audience composed of researchers and practitioners in industry. This book is also suitable as a reference for graduate-level students in management sciences, and computer science for distributed computing system classes.

Autonomic Computing and Networking presents introductory and advanced topics on autonomic computing and networking with emphasis on architectures, protocols, services, privacy & security, simulation and implementation testbeds. Autonomic computing and networking are new computing and networking paradigms that allow the creation of self-managing and self-controlling computing and networking environments using techniques such as distributed algorithms and context-awareness to dynamically control networking functions without human interventions. Autonomic networking is characterized by recovery from failures and malfunctions, agility to changing networking environment, self-optimization and self-awareness. The self-control and management features can help to overcome the growing complexity and heterogeneity of exiting communication networks and systems. The realization of fully autonomic heterogeneous networking introduces several research challenges in all aspects of computing and networking and related fields.