Content-access QoS in peer-to-peer networks using a fast MDS erasure code

This paper describes an enhancement of content access Quality of Service in peer to peer (P2P) networks. The main idea is to use an erasure code to distribute the information over the peers. This distribution increases the users’ choice on disseminated encoded data and therefore statistically enhances the overall throughput of the transfer. A performance evaluation based on an original model using the results of a measurement campaign of sequential and parallel downloads in a real P2P network over Internet is presented. Based on a bandwidth distribution, statistical content-access QoS are guaranteed in function of both the content replication level in the network and the file dissemination strategies. A simple application in the context of media streaming is proposed. Finally, the constraints on the erasure code related to the proposed system are analysed and a new fast MDS erasure code is proposed, implemented and evaluated

A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor

FADI: a fault-tolerant environment for open distributed computing

FADI is a complete programming environment that serves the reliable execution of distributed application programs. FADI encompasses all aspects of modern fault-tolerant distributed computing. The built-in user-transparent error detection mechanism covers processor node crashes and hardware transient failures. The mechanism also integrates user-assisted error checks into the system failure model. The nucleus non-blocking checkpointing mechanism combined with a novel selective message logging technique delivers an efficient, low-overhead backup and recovery mechanism for distributed processes. FADI also provides means for remote automatic process allocation on the distributed system nodes

A Study of Implementation Methodologies for Distributed Real Time Collaboration

Collaboration drives our world and is almost unavoidable in the programming industry. From higher education to the top technological companies, people are working together to drive discovery and innovation. Software engineers must work with their peers to accomplish goals daily in their workplace. When working with others there are a variety of tools to choose from such as Google Docs, Google Colab and Overleaf. Each of the aforementioned collaborative tools utilizes the Operational Transform (OT) technique in order to implement their real time collaboration functionality. Operational transform is the technique seen amongst most if not all major collaborative tools in our industry today. However, there is another way of implementing real time collaboration through a data structure called Conflict-free Replicated Data Type (CRDT) which has made claims of superiority over OT. Previous studies have taken place with the focus on comparing the theory behind OT and CRDT\u27s, but as far as we know, there have not been studies which compare real time collaboration performance using an OT implementation versus a CRDT implementation in a popularly used product such as Google Docs or Overleaf. Our work will focus on comparing OT and CRDT\u27s real time collaborative performance in Overleaf, an academic authorship tool, which allows for easy collaboration on academic and professional papers. Overleaf\u27s current published version implements real time collaboration using operational transform. This thesis will contribute an analysis of the current real time collaboration performance of operational transform in Overleaf, an implementation of CRDT\u27s for real time collaboration in Overleaf and an analysis of the performance of real time collaboration through the CRDT implementation in Overleaf. This thesis describes the main advantages and disadvantages of OT vs CRDTs, as well as, to our knowledge, the first results of a non-theoretical attempt at implementing CRDTs for handling document edits in a collaborative environment which was originally operating using an OT implementation

FMKe: A realistic benchmark for key-value stores

Standard benchmarks are essential tools to evaluate and compare database management systems in terms of relevant semantic properties and performance. They provide the means to evaluate a system with workloads that mimic real applications. Although a number of realistic benchmarks already exist for relational database systems, the same cannot be said for NoSQL databases. This latter class of data storage systems has become increasingly relevant for geo-distributed systems, and this has led developers and researchers to either rely on benchmarks that do not model realistic workloads or to adapt the aforementioned benchmarks for relational databases to work for NoSQL databases, in a somewhat ad-hoc fashion. Since these benchmarks assume an isolation and transactional model in the database, they are inherently inadequate to evaluate NoSQL databases. In this thesis, we propose a new benchmark that addresses the lack of realistic evaluation tools for distributed key-value stores. We consider a workload that is based on information we have acquired about a real world deployment of a large-scale application that operates over a distributed key-value store, that is responsible for managing patient prescriptions at a nation-wide level in Denmark. We design our benchmark to be extensible to a wide range of distributed key-value storage systems and some relational database systems with minimal effort for programmers, which only need to design and implement specific data storage drivers to benchmark different alternatives. We further present a study on the performance of multiple database management systems in different deployment scenarios