An in-depth introduction to concurrent and distributed computing with Java Combining the two key types of Java programming, Concurrent and Distributed Computing in Java offers both professionals and students a comprehensive guide to fundamental concepts necessary for mastering Java programming. The text is presented in two parts. The first deals with techniques for programming in shared-memory based systems and covers concepts in Java such as: Threads Synchronized methods Waits and notify Multi-threaded programming Algorithms for mutual exclusion, consensus, atomic objects, and wait-free data structures The second half of the text deals with programming in a message-passing system, and covers: Resource allocation problems Logical clocks Global property detection Leader election Message ordering Agreement algorithms Checkpointing Message logging Avoiding excessive mathematical notation while explaining important concepts with both rigor and clarity, this up-to-date text will prove a valuable resource for interested professionals and students alike.

A lucid and up-to-date introduction to the fundamentals of distributed computing systems

As distributed systems become increasingly available, the need for a fundamental discussion of the subject has grown. Designed for first-year graduate students and advanced undergraduates as well as practicing computer engineers seeking a solid grounding in the subject, this well-organized text covers the fundamental concepts in distributed computing systems such as time, state, simultaneity, order, knowledge, failure, and agreement in distributed systems.

Departing from the focus on shared memory and synchronous systems commonly taken by other texts, this is the first useful reference based on an asynchronous model of distributed computing, the most widely used in academia and industry. The emphasis of the book is on developing general mechanisms that can be applied to a variety of problems. Its examples–clocks, locks, cameras, sensors, controllers, slicers, and synchronizers–have been carefully chosen so that they are fundamental and yet useful in practical contexts.

The text’s advantages include:

• Emphasizes general mechanisms that can be applied to a variety of problems
• Uses a simple induction-based technique to prove correctness of all algorithms
• Includes a variety of exercises at the end of each chapter
• Contains material that has been extensively class tested
• Gives instructor flexibility in choosing appropriate balance between practice and theory of distributed computing

A computational perspective on partial order and lattice theory, focusing on algorithms and their applications This book provides a uniform treatment of the theory and applications of lattice theory. The applications covered include tracking dependency in distributed systems, combinatorics, detecting global predicates in distributed systems, set families, and integer partitions. The book presents algorithmic proofs of theorems whenever possible. These proofs are written in the calculational style advocated by Dijkstra, with arguments explicitly spelled out step by step. The author s intent is for readers to learn not only the proofs, but the heuristics that guide said proofs. Introduction to Lattice Theory with Computer Science Applications: * Examines; posets, Dilworth s theorem, merging algorithms, lattices, lattice completion, morphisms, modular and distributive lattices, slicing, interval orders, tractable posets, lattice enumeration algorithms, and dimension theory * Provides end of chapter exercises to help readers retain newfound knowledge on each subject * Includes supplementary material at www.ece.utexas.edu/~garg Introduction to Lattice Theory with Computer Science Applications is written for students of computer science, as well as practicing mathematicians.