24,099 research outputs found
Mobility Study for Named Data Networking in Wireless Access Networks
Information centric networking (ICN) proposes to redesign the Internet by
replacing its host-centric design with information-centric design.
Communication among entities is established at the naming level, with the
receiver side (referred to as the Consumer) acting as the driving force behind
content delivery, by interacting with the network through Interest message
transmissions. One of the proposed advantages for ICN is its support for
mobility, by de-coupling applications from transport semantics. However, so
far, little research has been conducted to understand the interaction between
ICN and mobility of consuming and producing applications, in protocols purely
based on information-centric principles, particularly in the case of NDN. In
this paper, we present our findings on the mobility-based performance of Named
Data Networking (NDN) in wireless access networks. Through simulations, we show
that the current NDN architecture is not efficient in handling mobility and
architectural enhancements needs to be done to fully support mobility of
Consumers and Producers.Comment: to appear in IEEE ICC 201
CASPR: Judiciously Using the Cloud for Wide-Area Packet Recovery
We revisit a classic networking problem -- how to recover from lost packets
in the best-effort Internet. We propose CASPR, a system that judiciously
leverages the cloud to recover from lost or delayed packets. CASPR supplements
and protects best-effort connections by sending a small number of coded packets
along the highly reliable but expensive cloud paths. When receivers detect
packet loss, they recover packets with the help of the nearby data center, not
the sender, thus providing quick and reliable packet recovery for
latency-sensitive applications. Using a prototype implementation and its
deployment on the public cloud and the PlanetLab testbed, we quantify the
benefits of CASPR in providing fast, cost effective packet recovery. Using
controlled experiments, we also explore how these benefits translate into
improvements up and down the network stack
CloudJet4BigData: Streamlining Big Data via an Accelerated Socket Interface
Big data needs to feed users with fresh processing results and cloud platforms can be used to speed up big data applications. This paper describes a new data communication protocol (CloudJet) for long distance and large volume big data accessing operations to alleviate the large latencies encountered in sharing big data resources in the clouds. It encapsulates a dynamic multi-stream/multi-path engine at the socket level, which conforms to Portable Operating System Interface (POSIX) and thereby can accelerate any POSIX-compatible applications across IP based networks. It was demonstrated that CloudJet accelerates typical big data applications such as very large database (VLDB), data mining, media streaming and office applications by up to tenfold in real-world tests
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