Security and Policy Driven Computing

by Lei Liu

Overview

Security and Policy Driven Computing covers recent advances in security, storage, parallelization, and computing as well as applications. The author incorporates a wealth of analysis, including studies on intrusion detection and key management, computer storage policy, and transactional management.

The book first describes multiple variables and index structure derivation for high dimensional data distribution and applies numeric methods to proposed search methods. It also focuses on discovering relations, logic, and knowledge for policy management. To manage performance, the text discusses contention management for transactional structures, buffer tuning, and test environments. It then illustrates search optimization using truncated functions with paralleled techniques. The final chapters present structures, recovery, message conflicts, and test coverage of quantum policies and explain methods of quantum protection for intrusion prevention.

An overview of security and policy applications for systems and computing, this book explores the latest R&D, emerging technology, and state-of-the-art technical studies of security and policy issues. It also looks to future research and technologies that will propel the innovation of next-generation systems.

Product Details

ISBN-13:	9781439825792
Publisher:	Taylor & Francis
Publication date:	12/13/2010
Pages:	290
Product dimensions:	6.20(w) x 9.20(h) x 0.90(d)

About the Author

Lei has hands-on experience with analysis and problem proofs. He has four patents granted and two patents filed in the U.S. patent office. Lei has been writing a book on Next Generation Enterprise System.

Table of Contents

A Parallel Search Optimization Using an Adaptive State-Action Index Structure. A Method of Policy Discovery for Storage and Data Management. Knowledge-Based Policy Discovery for Storage and Data Management. Stabilizing Read-Write Throughput of Transactional Memory for Contention Management. Parallel Search Optimization for Storage Virtualization. Finite Automata for Evaluating Testbed Resource Contention. Adaptive Buffer Tuning for Data Intensive Algebraic Operations. A Quantum Method of Representing Recurring Data Deduplication Policy States. QAM—Quantum Availability Mechanics without Recovery for Storage and Data Management. A Quantum Method with Unknown Future Tasks to Resolve Storage Message Conflicts. A Quantum Automatic Controlled Method for Storage Test Coverage. Protection Mechanics with a Quantum Operator for Anomaly Attacks. Index.