5,077 research outputs found
A Marketplace for Efficient and Secure Caching for IoT Applications in 5G Networks
As the communication industry is progressing towards
fifth generation (5G) of cellular networks, the traffic it
carries is also shifting from high data rate traffic from cellular
users to a mixture of high data rate and low data rate traffic
from Internet of Things (IoT) applications. Moreover, the need
to efficiently access Internet data is also increasing across 5G
networks. Caching contents at the network edge is considered
as a promising approach to reduce the delivery time. In this
paper, we propose a marketplace for providing a number of
caching options for a broad range of applications. In addition,
we propose a security scheme to secure the caching contents
with a simultaneous potential of reducing the duplicate contents
from the caching server by dividing a file into smaller chunks.
We model different caching scenarios in NS-3 and present the
performance evaluation of our proposal in terms of latency and
throughput gains for various chunk sizes
Improving Mobile Video Streaming with Mobility Prediction and Prefetching in Integrated Cellular-WiFi Networks
We present and evaluate a procedure that utilizes mobility and throughput
prediction to prefetch video streaming data in integrated cellular and WiFi
networks. The effective integration of such heterogeneous wireless technologies
will be significant for supporting high performance and energy efficient video
streaming in ubiquitous networking environments. Our evaluation is based on
trace-driven simulation considering empirical measurements and shows how
various system parameters influence the performance, in terms of the number of
paused video frames and the energy consumption; these parameters include the
number of video streams, the mobile, WiFi, and ADSL backhaul throughput, and
the number of WiFi hotspots. Also, we assess the procedure's robustness to time
and throughput variability. Finally, we present our initial prototype that
implements the proposed approach.Comment: 7 pages, 15 figure
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
On Content-centric Wireless Delivery Networks
The flux of social media and the convenience of mobile connectivity has
created a mobile data phenomenon that is expected to overwhelm the mobile
cellular networks in the foreseeable future. Despite the advent of 4G/LTE, the
growth rate of wireless data has far exceeded the capacity increase of the
mobile networks. A fundamentally new design paradigm is required to tackle the
ever-growing wireless data challenge.
In this article, we investigate the problem of massive content delivery over
wireless networks and present a systematic view on content-centric network
design and its underlying challenges. Towards this end, we first review some of
the recent advancements in Information Centric Networking (ICN) which provides
the basis on how media contents can be labeled, distributed, and placed across
the networks. We then formulate the content delivery task into a content rate
maximization problem over a share wireless channel, which, contrasting the
conventional wisdom that attempts to increase the bit-rate of a unicast system,
maximizes the content delivery capability with a fixed amount of wireless
resources. This conceptually simple change enables us to exploit the "content
diversity" and the "network diversity" by leveraging the abundant computation
sources (through application-layer encoding, pushing and caching, etc.) within
the existing wireless networks. A network architecture that enables wireless
network crowdsourcing for content delivery is then described, followed by an
exemplary campus wireless network that encompasses the above concepts.Comment: 20 pages, 7 figures,accepted by IEEE Wireless
Communications,Sept.201
Random Linear Network Coding for 5G Mobile Video Delivery
An exponential increase in mobile video delivery will continue with the
demand for higher resolution, multi-view and large-scale multicast video
services. Novel fifth generation (5G) 3GPP New Radio (NR) standard will bring a
number of new opportunities for optimizing video delivery across both 5G core
and radio access networks. One of the promising approaches for video quality
adaptation, throughput enhancement and erasure protection is the use of
packet-level random linear network coding (RLNC). In this review paper, we
discuss the integration of RLNC into the 5G NR standard, building upon the
ideas and opportunities identified in 4G LTE. We explicitly identify and
discuss in detail novel 5G NR features that provide support for RLNC-based
video delivery in 5G, thus pointing out to the promising avenues for future
research.Comment: Invited paper for Special Issue "Network and Rateless Coding for
Video Streaming" - MDPI Informatio
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