25,933 research outputs found
Matching model of flow table for networked big data
Networking for big data has to be intelligent because it will adjust data
transmission requirements adaptively during data splitting and merging.
Software-defined networking (SDN) provides a workable and practical paradigm
for designing more efficient and flexible networks. Matching strategy in the
flow table of SDN switches is most crucial. In this paper, we use a
classification approach to analyze the structure of packets based on the
tuple-space lookup mechanism, and propose a matching model of the flow table in
SDN switches by classifying packets based on a set of fields, which is called
an F-OpenFlow. The experiment results show that the proposed F-OpenFlow
effectively improves the utilization rate and matching efficiency of the flow
table in SDN switches for networked big data.Comment: 14 pages, 6 figures, 2 table
When Things Matter: A Data-Centric View of the Internet of Things
With the recent advances in radio-frequency identification (RFID), low-cost
wireless sensor devices, and Web technologies, the Internet of Things (IoT)
approach has gained momentum in connecting everyday objects to the Internet and
facilitating machine-to-human and machine-to-machine communication with the
physical world. While IoT offers the capability to connect and integrate both
digital and physical entities, enabling a whole new class of applications and
services, several significant challenges need to be addressed before these
applications and services can be fully realized. A fundamental challenge
centers around managing IoT data, typically produced in dynamic and volatile
environments, which is not only extremely large in scale and volume, but also
noisy, and continuous. This article surveys the main techniques and
state-of-the-art research efforts in IoT from data-centric perspectives,
including data stream processing, data storage models, complex event
processing, and searching in IoT. Open research issues for IoT data management
are also discussed
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