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Introducing the new paradigm of Social Dispersed Computing: Applications, Technologies and Challenges

机译:介绍社会分散计算的新范式:应用,技术和挑战

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If last decade viewed computational services as a utility then surely this decade has transformed computation into a commodity. Computation is now progressively integrated into the physical networks in a seamless way that enables cyber-physical systems (CPS) and the Internet of Things (IoT) meet their latency requirements. Similar to the concept of "platform as a service" or "software as a service", both cloudlets and fog computing have found their own use cases. Edge devices (that we call end or user devices for disambiguation) play the role of personal computers, dedicated to a user and to a set of correlated applications. In this new scenario, the boundaries between the network node, the sensor, and the actuator are blurring, driven primarily by the computation power of IoT nodes like single board computers and the smartphones. The bigger data generated in this type of networks needs clever, scalable, and possibly decentralized computing solutions that can scale independently as required. Any node can be seen as part of a graph, with the capacity to serve as a computing or network router node, or both. Complex applications can possibly be distributed over this graph or network of nodes to improve the overall performance like the amount of data processed over time. In this paper, we identify this new computing paradigm that we call Social Dispersed Computing, analyzing key themes in it that includes a new outlook on its relation to agent based applications. We architect this new paradigm by providing supportive application examples that include next generation electrical energy distribution networks, next generation mobility services for transportation, and applications for distributed analysis and identification of non-recurring traffic congestion in cities. The paper analyzes the existing computing paradigms (e.g., cloud, fog, edge, mobile edge, social, etc.), solving the ambiguity of their definitions; and analyzes and discusses the relevant foundational softwa
机译:如果上十年被视为计算服务作为实用程序,那么这十年就已经将计算转化为商品。现在以无缝方式逐步集成到物理网络中,这使得网络物理系统(CPS)和物联网(物联网)满足其延迟要求。与“平台作为服务”或“软件作为服务”的概念类似,两次Cloudlet和Fog Computing都发现了自己的用例。边缘设备(我们呼叫结束或用户设备用于消歧)播放个人计算机的角色,专用于用户和一组相关应用程序。在这种新场景中,网络节点,传感器和致动器之间的边界主要是模糊的,主要由单板计算机和智能手机等IOT节点的计算能力驱动。这种类型的网络中产生的更大数据需要巧妙,可扩展,并且可能的分散计算解决方案,可以根据需要独立缩放。任何节点都可以被视为图的一部分,其容量用作计算或网络路由器节点,或两者。可以在该图形或节点网络上分布复杂的应用程序,以提高整体性能,如随时间处理的数据量。在本文中,我们确定了我们称呼社交分散计算的新计算范例,分析了它的关键主题,其中包括与基于代理应用程序的关系的新展望。我们通过提供包括下一代电能分配网络的支持性应用示例,用于运输的下一代移动性服务以及用于在城市中非重复交通拥堵的分布式分析和识别的应用程序的支持性应用示例构建了这种新的范例。本文分析了现有的计算范例(例如,云,雾,边缘,移动边缘,社交等),解决了定义的歧义;并分析并讨论相关的基础软件

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