Protocolo Híbrido de Ordem Total Uniforme com entrega Optimista

Broadcast algorithms with total uniform order simplify the development of applications that use replication as a fault-tolerance technique. This paper presents and compares three alternatives to implement an optimistic delivery service in total order uniform broadcast protocols for large-scale systems

An Indulgent Uniform Total Order Algorithm with Optimistic Delivery

A total order algorithm is a fundamental building block in the construction of distributed fault-tolerant applications. Unfortunately, the implementation of such a primitive can be expensive both in terms of communication steps and of number of messages exchanged. This problem is exacerbated in large-scale systems, where the performance of the algorithm may be limited by the presence of high-latency links. Typically, the most efficient total order algorithms do not provide uniform delivery and assume the availability of a perfect failure detector. Such algorithms may provide inconsistent results if the system assumptions do not hold. On the other hand, algorithms that assume an unreliable failure detector always provide consistent results but exhibit higher costs. This paper presents a new algorithm that combines the advantages of both approaches. On good periods, when the system is stable and processes are not suspected, the algorithm operates as if a perfect failure detector is assumed. Yet, the algorithm is indulgent, since it never violates consistency, even in runs where processes are suspecte

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

Towards JMS-Compliant Group Communication

Group communication provides communication primitives with various semantics and their use greatly simplifies the development of highly available services. However, despite tremendous advances in research and numerous prototypes, group communication stays confined to small niches and academic prototypes. In contrast, message-oriented middleware such as the Java Messaging Service (JMS) is widely used, and has become a de-facto standard. We believe that the lack of standard interfaces is the reason that hinders the deployment of group communication systems. Since JMS is well-established, an interesting solution is to map group communication primitives onto the JMS API. This requires to adapt the traditional specifications of group communication in order to take into account the features of JMS. The resulting group communication API, together with corresponding specifications, defines group communication primitives compatible with the JMS syntax and semantics

Privacy Intelligence: A Survey on Image Sharing on Online Social Networks

Image sharing on online social networks (OSNs) has become an indispensable part of daily social activities, but it has also led to an increased risk of privacy invasion. The recent image leaks from popular OSN services and the abuse of personal photos using advanced algorithms (e.g. DeepFake) have prompted the public to rethink individual privacy needs when sharing images on OSNs. However, OSN image sharing itself is relatively complicated, and systems currently in place to manage privacy in practice are labor-intensive yet fail to provide personalized, accurate and flexible privacy protection. As a result, an more intelligent environment for privacy-friendly OSN image sharing is in demand. To fill the gap, we contribute a systematic survey of 'privacy intelligence' solutions that target modern privacy issues related to OSN image sharing. Specifically, we present a high-level analysis framework based on the entire lifecycle of OSN image sharing to address the various privacy issues and solutions facing this interdisciplinary field. The framework is divided into three main stages: local management, online management and social experience. At each stage, we identify typical sharing-related user behaviors, the privacy issues generated by those behaviors, and review representative intelligent solutions. The resulting analysis describes an intelligent privacy-enhancing chain for closed-loop privacy management. We also discuss the challenges and future directions existing at each stage, as well as in publicly available datasets.Comment: 32 pages, 9 figures. Under revie

Department of Computer Science Activity 1998-2004

This report summarizes much of the research and teaching activity of the Department of Computer Science at Dartmouth College between late 1998 and late 2004. The material for this report was collected as part of the final report for NSF Institutional Infrastructure award EIA-9802068, which funded equipment and technical staff during that six-year period. This equipment and staff supported essentially all of the department\u27s research activity during that period