2,662 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
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
Data sharing in secure multimedia wireless sensor networks
© 2016 IEEE. The use of Multimedia Wireless Sensor Networks (MWSNs) is becoming common nowadays with a rapid growth in communication facilities. Similar to any other WSNs, these networks face various challenges while providing security, trust and privacy for user data. Provisioning of the aforementioned services become an uphill task especially while dealing with real-time streaming data. These networks operates with resource-constrained sensor nodes for days, months and even years depending on the nature of an application. The resource-constrained nature of these networks makes it difficult for the nodes to tackle real-time data in mission-critical applications such as military surveillance, forest fire monitoring, health-care and industrial automation. For a secured MWSN, the transmission and processing of streaming data needs to be explored deeply. The conventional data authentication schemes are not suitable for MWSNs due to the limitations imposed on sensor nodes in terms of battery power, computation, available bandwidth and storage. In this paper, we propose a novel quality-driven clustering-based technique for authenticating streaming data in MWSNs. Nodes with maximum energy are selected as Cluster Heads (CHs). The CHs collect data from member nodes and forward it to the Base Station (BS), thus preventing member nodes with low energy from dying soon and increasing life span of the underlying network. The proposed approach not only authenticates the streaming data but also maintains the quality of transmitted data. The proposed data authentication scheme coupled with an Error Concealment technique provides an energy-efficient and distortion-free real-time data streaming. The proposed scheme is compared with an unsupervised resources scenario. The simulation results demonstrate better network lifetime along with 21.34 dB gain in Peak Signal-to-Noise Ratio (PSNR) of received video data streams
Effective Caching for the Secure Content Distribution in Information-Centric Networking
The secure distribution of protected content requires consumer authentication
and involves the conventional method of end-to-end encryption. However, in
information-centric networking (ICN) the end-to-end encryption makes the
content caching ineffective since encrypted content stored in a cache is
useless for any consumer except those who know the encryption key. For
effective caching of encrypted content in ICN, we propose a novel scheme,
called the Secure Distribution of Protected Content (SDPC). SDPC ensures that
only authenticated consumers can access the content. The SDPC is a lightweight
authentication and key distribution protocol; it allows consumer nodes to
verify the originality of the published article by using a symmetric key
encryption. The security of the SDPC was proved with BAN logic and Scyther tool
verification.Comment: 7 pages, 9 figures, 2018 IEEE 87th Vehicular Technology Conference
(VTC Spring
Why (and How) Networks Should Run Themselves
The proliferation of networked devices, systems, and applications that we
depend on every day makes managing networks more important than ever. The
increasing security, availability, and performance demands of these
applications suggest that these increasingly difficult network management
problems be solved in real time, across a complex web of interacting protocols
and systems. Alas, just as the importance of network management has increased,
the network has grown so complex that it is seemingly unmanageable. In this new
era, network management requires a fundamentally new approach. Instead of
optimizations based on closed-form analysis of individual protocols, network
operators need data-driven, machine-learning-based models of end-to-end and
application performance based on high-level policy goals and a holistic view of
the underlying components. Instead of anomaly detection algorithms that operate
on offline analysis of network traces, operators need classification and
detection algorithms that can make real-time, closed-loop decisions. Networks
should learn to drive themselves. This paper explores this concept, discussing
how we might attain this ambitious goal by more closely coupling measurement
with real-time control and by relying on learning for inference and prediction
about a networked application or system, as opposed to closed-form analysis of
individual protocols
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