Introduction to Distributed Algorithms

Abstract

Distributed algorithms have been the subject of intense development over the last twenty years. The second edition of this successful textbook provides an up-to-date introduction both to the topic, and to the theory behind the algorithms. The clear presentation makes the book suitable for advanced undergraduate or graduate courses, whilst the coverage is sufficiently deep to make it useful for practising engineers and researchers. The author concentrates on algorithms for the point-to-point message passing model, and includes algorithms for the implementation of computer communication networks. Other key areas discussed are algorithms for the control of distributed applications (wave, broadcast, election, termination detection, randomized algorithms for anonymous networks, snapshots, deadlock detection, synchronous systems), and fault-tolerance achievable by distributed algorithms. The two new chapters on sense of direction and failure detectors are state-of-the-art and will provide an entry to research in these still-developing topics.

Fully-Distributed Debugging and Visualization of Distributed Systems in Anonymous Networks

“…Our model is the usual asynchronous message passing model (Tel, 2000;Yamashita and Kameda, 1996). A network is represented by a simple…”

“…Many papers give also specific algorithms to detect some specific predicates that hold in a system such as termination or deadlock (Mattern, 1987;Marzullo and Sabel, 1994;Kshemkalyani and Wu, 2007;Kshemkalyani, 2010). Among well-known global predicates of distributed systems detected with snapshots, one can also consider loss of tokens and garbage collection (see (Tel, 2000;Santoro, 2007;Kshemkalyani and Singhal, 2008)). …”

“…When a process receives for the first time a marker, it does the same thing that an initiator; the incoming channel by which it receives for the first time a marker is set as empty. If we consider an execution of the ChandyLamport algorithm we obtain a consistent snapshot within finite time after its initialization by at least one process (see (Tel, 2000) Theorem 10.7 ). In particular:…”

“…As Tel (Tel, 2000), we define the time complexity by supposing that internal events need zero time units and that the transmission time (i.e. the time between sending and receiving a message) is at most one time unit.…”

Snap-Stabilization in Message-Passing Systems

“…A distributed system can be described using a transition system [32]. A transition system is a 3-uple S = (C, →,I) such that: C is set of configurations, → is a binary transition relation on C, and I ⊆ C is the set of initial configurations.…”