16,826 research outputs found
Cloud for Gaming
Cloud for Gaming refers to the use of cloud computing technologies to build
large-scale gaming infrastructures, with the goal of improving scalability and
responsiveness, improve the user's experience and enable new business models.Comment: Encyclopedia of Computer Graphics and Games. Newton Lee (Editor).
Springer International Publishing, 2015, ISBN 978-3-319-08234-
Impact of Processing-Resource Sharing on the Placement of Chained Virtual Network Functions
Network Function Virtualization (NFV) provides higher flexibility for network
operators and reduces the complexity in network service deployment. Using NFV,
Virtual Network Functions (VNF) can be located in various network nodes and
chained together in a Service Function Chain (SFC) to provide a specific
service. Consolidating multiple VNFs in a smaller number of locations would
allow decreasing capital expenditures. However, excessive consolidation of VNFs
might cause additional latency penalties due to processing-resource sharing,
and this is undesirable, as SFCs are bounded by service-specific latency
requirements. In this paper, we identify two different types of penalties
(referred as "costs") related to the processingresource sharing among multiple
VNFs: the context switching costs and the upscaling costs. Context switching
costs arise when multiple CPU processes (e.g., supporting different VNFs) share
the same CPU and thus repeated loading/saving of their context is required.
Upscaling costs are incurred by VNFs requiring multi-core implementations,
since they suffer a penalty due to the load-balancing needs among CPU cores.
These costs affect how the chained VNFs are placed in the network to meet the
performance requirement of the SFCs. We evaluate their impact while considering
SFCs with different bandwidth and latency requirements in a scenario of VNF
consolidation.Comment: Accepted for publication in IEEE Transactions on Cloud Computin
Wearable Communications in 5G: Challenges and Enabling Technologies
As wearable devices become more ingrained in our daily lives, traditional
communication networks primarily designed for human being-oriented applications
are facing tremendous challenges. The upcoming 5G wireless system aims to
support unprecedented high capacity, low latency, and massive connectivity. In
this article, we evaluate key challenges in wearable communications. A
cloud/edge communication architecture that integrates the cloud radio access
network, software defined network, device to device communications, and
cloud/edge technologies is presented. Computation offloading enabled by this
multi-layer communications architecture can offload computation-excessive and
latency-stringent applications to nearby devices through device to device
communications or to nearby edge nodes through cellular or other wireless
technologies. Critical issues faced by wearable communications such as short
battery life, limited computing capability, and stringent latency can be
greatly alleviated by this cloud/edge architecture. Together with the presented
architecture, current transmission and networking technologies, including
non-orthogonal multiple access, mobile edge computing, and energy harvesting,
can greatly enhance the performance of wearable communication in terms of
spectral efficiency, energy efficiency, latency, and connectivity.Comment: This work has been accepted by IEEE Vehicular Technology Magazin
Wireless Communications in the Era of Big Data
The rapidly growing wave of wireless data service is pushing against the
boundary of our communication network's processing power. The pervasive and
exponentially increasing data traffic present imminent challenges to all the
aspects of the wireless system design, such as spectrum efficiency, computing
capabilities and fronthaul/backhaul link capacity. In this article, we discuss
the challenges and opportunities in the design of scalable wireless systems to
embrace such a "bigdata" era. On one hand, we review the state-of-the-art
networking architectures and signal processing techniques adaptable for
managing the bigdata traffic in wireless networks. On the other hand, instead
of viewing mobile bigdata as a unwanted burden, we introduce methods to
capitalize from the vast data traffic, for building a bigdata-aware wireless
network with better wireless service quality and new mobile applications. We
highlight several promising future research directions for wireless
communications in the mobile bigdata era.Comment: This article is accepted and to appear in IEEE Communications
Magazin
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