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So far, the distributed computing community has either assumed that all the processes of a distributed system have distinct identifiers or, more rarely, that the processes are anonymous and have no identifiers. These are two extremes of the same general model: namely, n processes use l different identifiers, where 1 l n. We call this model homonymous model. To determine the power of homonymous model as well as the importance of identi ers in distributed computing, this thesis studies algorithms for solving the consensus problem, one of the most famous distributed computing problem."
Dotyczy: gossiping, consensus, distributed algorithms, fault tolerance, adaptive algorithms, processor failures, quantum algorithms.
This book constitutes the refereed proceedings of the 14th International Conference on Distributed Computing and Networking, ICDCN 2013, held in Mumbai, India, during January 3-6, 2013. The 27 revised full papers, 5 short papers presented together with 7 poster papers were carefully reviewed and selected from 149 submissions. The papers cover topics such as distributed algorithms and concurrent data structures; integration of heterogeneous wireless and wired networks; distributed operating systems; internetworking protocols and internet applications; distributed database systems; mobile and pervasive computing, context-aware distributed systems; embedded distributed systems; next generation and converged network architectures; experiments and performance evaluation of distributed systems; overlay and peer-to-peer networks and services; fault-tolerance, reliability, and availability; home networking and services; multiprocessor and multi-core architectures and algorithms; resource management and quality of service; self-organization, self-stabilization, and autonomic computing; network security and privacy; high performance computing, grid computing, and cloud computing; energy-efficient networking and smart grids; security, cryptography, and game theory in distributed systems; sensor, PAN and ad-hoc networks; and traffic engineering, pricing, network management.
This book constitutes the refereed proceedings of the 15th International Conference on Principles of Distributed Systems, OPODIS 2011, held in Toulouse, France, in December 2011. The 26 revised papers presented in this volume were carefully reviewed and selected from 96 submissions. They represent the current state of the art of the research in the field of the design, analysis and development of distributed and real-time systems.
Distributed consensus is fundamental to building fault-tolerant systems. It allows a collection of machines to work as a coherent group that can survive the failures of some of its members. Unfortunately, the most common consensus algorithm, Paxos, is widely regarded as difficult to understand and implement correctly. This dissertation presents a new consensus algorithm called Raft, which was designed for understandability. Raft first elects a server as leader, then concentrates all decision-making onto the leader. These two basic steps are relatively independent and form a better structure than Paxos, whose components are hard to separate. Raft elects a leader using voting and randomized timeouts. The election guarantees that the leader already stores all the information it needs, so data only flows outwards from the leader to other servers. Compared to other leader-based algorithms, this reduces mechanism and simplifies the behavior. Once a leader is elected, it manages a replicated log. Raft leverages a simple invariant on how logs grow to reduce the algorithm's state space and accomplish this task with minimal mechanism. Raft is also more suitable than previous algorithms for real-world implementations. It performs well enough for practical deployments, and it addresses all aspects of building a complete system, including how to manage client interactions, how to change the cluster membership, and how to compact the log when it grows too large. To change the cluster membership, Raft allows adding or removing one server at a time (complex changes can be composed from these basic steps), and the cluster continues servicing requests throughout the change. We believe that Raft is superior to Paxos and other consensus algorithms, both for educational purposes and as a foundation for implementation. Results from a user study demonstrate that Raft is easier for students to learn than Paxos. The algorithm has been formally specified and proven, its leader election algorithm works well in a variety of environments, and its performance is equivalent to Multi-Paxos. Many implementations of Raft are now available, and several companies are deploying Raft.