Topics and features:

• Presents a comprehensive analysis of sequential graph algorithms
• Offers a unifying view by examining the same graph problem from each of the three paradigms of sequential, parallel and distributed algorithms
• Describes methods for the conversion between sequential, parallel and distributed graph algorithms
• Surveys methods for the analysis of large graphs and complex network applications
• Includes full implementation details for the problems presented throughout the text
• Surveys advanced graph structures used in artificial intelligence with code examples
• Reviews graph machine-intelligence methods 

This practical guide to the design and analysis of graph algorithms is ideal for advanced and graduate students of computer science, electrical and electronic engineering, and bioinformatics. The material covered will also be of value to any researcher familiar with the basics of discrete mathematics, graph theory and algorithms and machine learning.

Dr. K. Erciyes  is professor of computer engineering at Ya?ar University, Turkey. His other publications include the Springer titles Distributed Graph Algorithms for Computer Networks, Distributed and Sequential Algorithms for Bioinformatics,  and Guide to Distributed Algorithms.