2,442 research outputs found
Covert Quantum Internet
We apply covert quantum communication based on entanglement generated from
the Minkowski vacuum to the setting of quantum computation and quantum
networks. Our approach hides the generation and distribution of entanglement in
quantum networks by taking advantage of relativistic quantum effects. We devise
a suite of covert quantum teleportation protocols that utilize the shared
entanglement, local operations, and covert classical communication to transfer
or process quantum information in stealth. As an application of our covert
suite, we construct two prominent examples of measurement-based quantum
computation, namely the teleportation-based quantum computer and the one-way
quantum computer. In the latter case we explore the covert generation of graph
states, and subsequently outline a protocol for the covert implementation of
universal blind quantum computation.Comment: 9 pages, 2 figure
GraphX: Unifying Data-Parallel and Graph-Parallel Analytics
From social networks to language modeling, the growing scale and importance
of graph data has driven the development of numerous new graph-parallel systems
(e.g., Pregel, GraphLab). By restricting the computation that can be expressed
and introducing new techniques to partition and distribute the graph, these
systems can efficiently execute iterative graph algorithms orders of magnitude
faster than more general data-parallel systems. However, the same restrictions
that enable the performance gains also make it difficult to express many of the
important stages in a typical graph-analytics pipeline: constructing the graph,
modifying its structure, or expressing computation that spans multiple graphs.
As a consequence, existing graph analytics pipelines compose graph-parallel and
data-parallel systems using external storage systems, leading to extensive data
movement and complicated programming model.
To address these challenges we introduce GraphX, a distributed graph
computation framework that unifies graph-parallel and data-parallel
computation. GraphX provides a small, core set of graph-parallel operators
expressive enough to implement the Pregel and PowerGraph abstractions, yet
simple enough to be cast in relational algebra. GraphX uses a collection of
query optimization techniques such as automatic join rewrites to efficiently
implement these graph-parallel operators. We evaluate GraphX on real-world
graphs and workloads and demonstrate that GraphX achieves comparable
performance as specialized graph computation systems, while outperforming them
in end-to-end graph pipelines. Moreover, GraphX achieves a balance between
expressiveness, performance, and ease of use
Architectures for the Future Networks and the Next Generation Internet: A Survey
Networking research funding agencies in the USA, Europe, Japan, and other countries are encouraging research on revolutionary networking architectures that may or may not be bound by the restrictions of the current TCP/IP based Internet. We present a comprehensive survey of such research projects and activities. The topics covered include various testbeds for experimentations for new architectures, new security mechanisms, content delivery mechanisms, management and control frameworks, service architectures, and routing mechanisms. Delay/Disruption tolerant networks, which allow communications even when complete end-to-end path is not available, are also discussed
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