Distributed computing

Summary

A distributed system is a system whose components are located on different networked computers, which communicate and coordinate their actions by passing messages to one another. Distributed computing is a field of computer science that studies distributed systems. The components of a distributed system interact with one another in order to achieve a common goal. Three significant challenges of distributed systems are: maintaining concurrency of components, overcoming the lack of a global clock, and managing the independent failure of components. When a component of one system fails, the entire system does not fail. Examples of distributed systems vary from SOA-based systems to massively multiplayer online games to peer-to-peer applications. A computer program that runs within a distributed system is called a distributed program, and distributed programming is the process of writing such programs. There are many different types of implementations for the m

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https://en.wikipedia.org/wiki/Distributed_computing

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ClaimChain: Improving the Security and Privacy of In-band Key Distribution for Messaging

Carmela González Troncoso, Bogdan Kulynych, Wouter Lueks

The social demand for email end-to-end encryption is barely supported by mainstream service providers. Autocrypt is a new community -driven open specification for e-mail encryption that attempts to respond to this demand. In Autocrypt the encryption keys are attached directly to messages, and thus the encryption can be implemented by email clients without any collaboration of the providers. The decentralized nature of this in-band key distribution, however, makes it prone to man-in-the-middle attacks and can leak the social graph of users. To address this problem we introduce ClaimChain, a cryptographic construction for privacy-preserving authentication of public keys. Users store claims about their identities and keys, as well as their beliefs about others, in ClaimChains. These chains form authenticated decentralized repositories that enable users to prove the authenticity of both their keys and the keys of their contacts. ClaimChains are encrypted, and therefore protect the stored information, such as keys and contact identities, from prying eyes. At the same time, ClaimChain implements mechanisms to provide strong non-equivocation properties, discouraging malicious actors from distributing conflicting or inauthentic claims. We implemented ClaimChain and we show that it offers reasonable performance, low overhead, and authenticity guarantees.

ACM2018

The contribution of this thesis is twofold. In the first part, we generalize and analyze two classes of error correcting codes: LDPC codes and product codes. We generalize graphical codes by considering checks being arbitrary codes instead of single parities. We analyze the performance of these codes under message passing decoding by using an extended density evolution over erasure channels. Further, we provide an optimal instance of these codes having rates arbitrarily close to the capacity of any binary symmetric channel where a belief propagation algorithm is used for decoding. The relation to other similar constructions is discussed as well. In a similar approach, we introduce irregular product codes, a class of codes where each codeword is represented by a matrix and the entries in each row (column) of the matrix come from a component row (column) code. Unlike product codes, we do not require that all component row and column codes be the same. This relaxation offers additional flexibility and features such as allowing some regions of the codeword to be more error-resilient, providing a more refined spectrum of rates for finite lengths, and improved performance for some of these rates. We study these codes over erasure channels and prove that for many rate distributions on component row codes, there is a matching rate distribution on component column codes such that an irregular product code based on MDS codes with those rate distributions on the component codes has an optimal asymptotic rate. In the second part we consider two novel applications of Raptor codes. Raptor codes are a class of fountain codes which present excellent performance, flexibility, and low decoding complexity over erasure channels. The data synchronization in an IP multicasting scenario involves reflecting changes from a content on a server to multiple clients efficiently. All these clients possess a slightly different copy of the content on the server. Existing methods are a direct extension of the point-to-point setting which is not necessarily optimal in terms of the total bandwidth usage in the multicast setting. We review this problem and its related information theoretic bounds. We propose and analyze an algorithm using Raptor codes which takes advantage of the multicast protocol to address this problem effectively. This method is close to optimal in terms of the amount of required transmitted information and the network usage. In another application, we show how to make satellite Digital Video Broadcasting resilient to signal jamming by distributing programs over multiple satellite links. However, leasing extra bandwidth on satellite links incurs supplementary cost to the broadcasting operator. In our solution we employ Raptor codes to make the bandwidth usage efficient and adaptive according to the link conditions. The proposed solution is fully compatible with the existing standards and infrastructure.

EPFL2013

The correctness of a shared object, which can be accessed by several processes concurrently, is specified through two different kinds of properties - safety and liveness. When implementing a shared object it is important to specify its correctness in a such way that it should be feasible under given assumptions. In this work we study the question of implementability of shared objects that satisfy certain safety and liveness properties under certain assumptions. In particular, we study implementability of liveness properties of transactional memory (TM) shared objects with strict serializability, a strong safety property. TM allows a programmer to encapsulate pieces of sequential code within transactions that run concurrently and it ensures that transactions run in some consistent manner by committing or aborting them. First, we give a formal definition of a liveness property in the TM context. Then, we proceed to show that certain classes of liveness properties of TM can not be implemented with strict serializability in a system in which processes are prone to failures. We also show that, in general, we cannot find a weakest non-implementable (resp. strongest implementable) liveness of TM when we require some common safety property like strict serializability. Moreover, we generalize this result to other shared object types and give a characterization of safety properties for which we can find weakest non-implementable (resp. strongest implementable) liveness. In addition to correctness properties we study the limitations of parallelism which affects performance and scalability of implementations. Specifically, we show that we cannot implement a TM which guarantees disjoint-access parallelism, which say that transactions do not need to synchronize unless they access the same application objects, while guaranteeing very weak safety and the weakest non-blocking liveness.

EPFL2015

EPFL2013