33,661 research outputs found
Publishing LO(D)D: Linked Open (Dynamic) Data for Smart Sensing and Measuring Environments
The paper proposes a distributed framework that provides a systematic way to publish environment data which is being updated continuously; such updates might be issued at specific time intervals or bound to some environment- specific event. The framework targets smart environments having networks of devices and sensors which are interacting with each other and with their respective environments to gather and generate data and willing to publish this data. This paper addresses the issues of supporting the data publishers to maintain up-to-date and machine understandable representations, separation of views (static or dynamic data) and delivering up-to-date information to data consumers in real time, helping data consumers to keep track of changes triggered from diverse environments and keeping track of evolution of the smart environment. The paper also describes a prototype implementation of the proposed architecture. A preliminary use case implementation over a real energy metering infrastructure is also provided in the paper to prove the feasibility of the architectur
Agile Data Offloading over Novel Fog Computing Infrastructure for CAVs
Future Connected and Automated Vehicles (CAVs) will be supervised by
cloud-based systems overseeing the overall security and orchestrating traffic
flows. Such systems rely on data collected from CAVs across the whole city
operational area. This paper develops a Fog Computing-based infrastructure for
future Intelligent Transportation Systems (ITSs) enabling an agile and reliable
off-load of CAV data. Since CAVs are expected to generate large quantities of
data, it is not feasible to assume data off-loading to be completed while a CAV
is in the proximity of a single Road-Side Unit (RSU). CAVs are expected to be
in the range of an RSU only for a limited amount of time, necessitating data
reconciliation across different RSUs, if traditional approaches to data
off-load were to be used. To this end, this paper proposes an agile Fog
Computing infrastructure, which interconnects all the RSUs so that the data
reconciliation is solved efficiently as a by-product of deploying the Random
Linear Network Coding (RLNC) technique. Our numerical results confirm the
feasibility of our solution and show its effectiveness when operated in a
large-scale urban testbed.Comment: To appear in IEEE VTC-Spring 201
An Efficient Transport Protocol for delivery of Multimedia An Efficient Transport Protocol for delivery of Multimedia Content in Wireless Grids
A grid computing system is designed for solving complicated scientific and
commercial problems effectively,whereas mobile computing is a traditional
distributed system having computing capability with mobility and adopting
wireless communications. Media and Entertainment fields can take advantage from
both paradigms by applying its usage in gaming applications and multimedia data
management. Multimedia data has to be stored and retrieved in an efficient and
effective manner to put it in use. In this paper, we proposed an application
layer protocol for delivery of multimedia data in wireless girds i.e.
multimedia grid protocol (MMGP). To make streaming efficient a new video
compression algorithm called dWave is designed and embedded in the proposed
protocol. This protocol will provide faster, reliable access and render an
imperceptible QoS in delivering multimedia in wireless grid environment and
tackles the challenging issues such as i) intermittent connectivity, ii) device
heterogeneity, iii) weak security and iv) device mobility.Comment: 20 pages, 15 figures, Peer Reviewed Journa
Synergizing Roadway Infrastructure Investment with Digital Infrastructure for Infrastructure-Based Connected Vehicle Applications: Review of Current Status and Future Directions
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The safety, mobility, environmental and economic benefits of Connected and Autonomous Vehicles (CAVs) are potentially dramatic. However, realization of these benefits largely hinges on the timely upgrading of the existing transportation system. CAVs must be enabled to send and receive data to and from other vehicles and drivers (V2V communication) and to and from infrastructure (V2I communication). Further, infrastructure and the transportation agencies that manage it must be able to collect, process, distribute and archive these data quickly, reliably, and securely. This paper focuses on current digital roadway infrastructure initiatives and highlights the importance of including digital infrastructure investment alongside more traditional infrastructure investment to keep up with the auto industry's push towards this real time communication and data processing capability. Agencies responsible for transportation infrastructure construction and management must collaborate, establishing national and international platforms to guide the planning, deployment and management of digital infrastructure in their jurisdictions. This will help create standardized interoperable national and international systems so that CAV technology is not deployed in a haphazard and uncoordinated manner
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
Real Time Global Tests of the ALICE High Level Trigger Data Transport Framework
The High Level Trigger (HLT) system of the ALICE experiment is an online
event filter and trigger system designed for input bandwidths of up to 25 GB/s
at event rates of up to 1 kHz. The system is designed as a scalable PC cluster,
implementing several hundred nodes. The transport of data in the system is
handled by an object-oriented data flow framework operating on the basis of the
publisher-subscriber principle, being designed fully pipelined with lowest
processing overhead and communication latency in the cluster. In this paper, we
report the latest measurements where this framework has been operated on five
different sites over a global north-south link extending more than 10,000 km,
processing a ``real-time'' data flow.Comment: 8 pages 4 figure
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