2,424 research outputs found

    Non-uniform replication for replicated objects

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    A large number of web applications/services are supported by applications running in cloud computing infrastructures. Many of these application store their data in georeplicated key-value stores, that maintain replicas of the data in several data centers located across the globe. Data management in these settings is challenging, with solutions needing to balance availability and consistency. Solutions that provide high-availability, by allowing operations to execute locally in a single data center, have to cope with a weaker consistency model. In such cases, replicas may be updated concurrently and a mechanism to reconcile divergent replicas is needed. Using the semantics of data types (and operations) helps in providing a solution that meets the requirements of applications, as shown by conflict-free replicated data types. As information grows it becomes difficult or even impossible to store all information at every replica. A common approach to deal with this problem is to rely on partial replication, where each replica maintains only part of the total system information. As a consequence, each partial replica can only reply to a subset of the possible queries. In this thesis, we introduce the concept of non-uniform replication where each replica stores only part of the information, but where all replicas store enough information to answer every query. We apply this concept to eventual consistency and conflict-free replicated data types and propose a set of useful data type designs where replicas synchronize by exchanging operations. Furthermore, we implement support for non-uniform replication in AntidoteDB, a geo-distributed key-value store, and evaluate the space efficiency, bandwidth overhead, and scalability of the solution

    Archiving scientific data

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    We present an archiving technique for hierarchical data with key structure. Our approach is based on the notion of timestamps whereby an element appearing in multiple versions of the database is stored only once along with a compact description of versions in which it appears. The basic idea of timestamping was discovered by Driscoll et. al. in the context of persistent data structures where one wishes to track the sequences of changes made to a data structure. We extend this idea to develop an archiving tool for XML data that is capable of providing meaningful change descriptions and can also efficiently support a variety of basic functions concerning the evolution of data such as retrieval of any specific version from the archive and querying the temporal history of any element. This is in contrast to diff-based approaches where such operations may require undoing a large number of changes or significant reasoning with the deltas. Surprisingly, our archiving technique does not incur any significant space overhead when contrasted with other approaches. Our experimental results support this and also show that the compacted archive file interacts well with other compression techniques. Finally, another useful property of our approach is that the resulting archive is also in XML and hence can directly leverage existing XML tools

    Distributed data service for data management in internet of things middleware

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    The development of the Internet of Things (IoT) is closely related to a considerable increase in the number and variety of devices connected to the Internet. Sensors have become a regular component of our environment, as well as smart phones and other devices that continuously collect data about our lives even without our intervention. With such connected devices, a broad range of applications has been developed and deployed, including those dealing with massive volumes of data. In this paper, we introduce a Distributed Data Service (DDS) to collect and process data for IoT environments. One central goal of this DDS is to enable multiple and distinct IoT middleware systems to share common data services from a loosely-coupled provider. In this context, we propose a new specification of functionalities for a DDS and the conception of the corresponding techniques for collecting, filtering and storing data conveniently and efficiently in this environment. Another contribution is a data aggregation component that is proposed to support efficient real-time data querying. To validate its data collecting and querying functionalities and performance, the proposed DDS is evaluated in two case studies regarding a simulated smart home system, the first case devoted to evaluating data collection and aggregation when the DDS is interacting with the UIoT middleware, and the second aimed at comparing the DDS data collection with this same functionality implemented within the Kaa middleware

    Synovial joint lubrication – does nature teach more effective engineering lubrication strategies?

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    Nature shows numerous examples of systems which show energy efficiency, elegance in their design and optimum use of materials. Biomimetics is an emerging field of research in engineering and successes have been documented in the diverse fields of robotics, mechanics, materials engineering and many more. To date little biomimetics research has been directed towards tribology in terms of transferring technologies from biological systems into engineering applications. The potential for biomimicry has been recognised in terms of replicating natural lubricants but this system reviews the potential for mimicking the synovial joint as an efficient and durable tribological system for potential engineering systems. The use of materials and the integration of materials technology and fluid/surface interactions are central to the discussion

    Micro/Nano Manufacturing

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    Micro- and nano-scale manufacturing has been the subject of ever more research and industrial focus over the past 10 years. Traditional lithography-based technology forms the basis of micro-electro-mechanical systems (MEMS) manufacturing, but also precision manufacturing technologies have been developed to cover micro-scale dimensions and accuracies. Furthermore, these fundamentally different technology platforms are currently combined in order to exploit the strengths of both platforms. One example is the use of lithography-based technologies to establish nanostructures that are subsequently transferred to 3D geometries via injection molding. Manufacturing processes at the micro-scale are the key-enabling technologies to bridge the gap between the nano- and the macro-worlds to increase the accuracy of micro/nano-precision production technologies, and to integrate different dimensional scales in mass-manufacturing processes. Accordingly, this Special Issue seeks to showcase research papers, short communications, and review articles that focus on novel methodological developments in micro- and nano-scale manufacturing, i.e., on novel process chains including process optimization, quality assurance approaches and metrology

    Backup and Recovery Mechanisms of Cassandra Database: A Review

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    Cassandra is a NoSQL database having a peer-to-peer, ring-type architecture. Cassandra offers fault-tolerance, data replication for higher availability as well as ensures no single point of failure. Given that Cassandra is a NoSQL database, it is evident that it lacks the amount of research that has gone into comparatively older and more widely and broadly used SQL databases. Cassandra’s growing popularity in recent times gives rise to the need of addressing any security-related or recovery-related concerns associated with its usage. This review paper discusses the existing deletion mechanism in Cassandra and presents some identified issues related to backup and recovery in the Cassandra database. Further, failure detection as well as handling of failures such as node failure or data center failure has been explored in the paper. In addition, several possible solutions to address backup and recovery including recovery in case of disasters have been reviewed

    An overview of virtual machine live migration techniques

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    In a cloud computing the live migration of virtual machines shows a process of moving a running virtual machine from source physical machine to the destination, considering the CPU, memory, network, and storage states. Various performance metrics are tackled such as, downtime, total migration time, performance degradation, and amount of migrated data, which are affected when a virtual machine is migrated. This paper presents an overview and understanding of virtual machine live migration techniques, of the different works in literature that consider this issue, which might impact the work of professionals and researchers to further explore the challenges and provide optimal solutions
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