597 research outputs found
Speeding up Future Video Distribution via Channel-Aware Caching-Aided Coded Multicast
Future Internet usage will be dominated by the consumption of a rich variety
of online multimedia services accessed from an exponentially growing number of
multimedia capable mobile devices. As such, future Internet designs will be
challenged to provide solutions that can deliver bandwidth-intensive,
delay-sensitive, on-demand video-based services over increasingly crowded,
bandwidth-limited wireless access networks. One of the main reasons for the
bandwidth stress facing wireless network operators is the difficulty to exploit
the multicast nature of the wireless medium when wireless users or access
points rarely experience the same channel conditions or access the same content
at the same time. In this paper, we present and analyze a novel wireless video
delivery paradigm based on the combined use of channel-aware caching and coded
multicasting that allows simultaneously serving multiple cache-enabled
receivers that may be requesting different content and experiencing different
channel conditions. To this end, we reformulate the caching-aided coded
multicast problem as a joint source-channel coding problem and design an
achievable scheme that preserves the cache-enabled multiplicative throughput
gains of the error-free scenario,by guaranteeing per-receiver rates unaffected
by the presence of receivers with worse channel conditions.Comment: 11 pages,6 figures,to appear in IEEE JSAC Special Issue on Video
Distribution over Future Interne
Separation Framework: An Enabler for Cooperative and D2D Communication for Future 5G Networks
Soaring capacity and coverage demands dictate that future cellular networks
need to soon migrate towards ultra-dense networks. However, network
densification comes with a host of challenges that include compromised energy
efficiency, complex interference management, cumbersome mobility management,
burdensome signaling overheads and higher backhaul costs. Interestingly, most
of the problems, that beleaguer network densification, stem from legacy
networks' one common feature i.e., tight coupling between the control and data
planes regardless of their degree of heterogeneity and cell density.
Consequently, in wake of 5G, control and data planes separation architecture
(SARC) has recently been conceived as a promising paradigm that has potential
to address most of aforementioned challenges. In this article, we review
various proposals that have been presented in literature so far to enable SARC.
More specifically, we analyze how and to what degree various SARC proposals
address the four main challenges in network densification namely: energy
efficiency, system level capacity maximization, interference management and
mobility management. We then focus on two salient features of future cellular
networks that have not yet been adapted in legacy networks at wide scale and
thus remain a hallmark of 5G, i.e., coordinated multipoint (CoMP), and
device-to-device (D2D) communications. After providing necessary background on
CoMP and D2D, we analyze how SARC can particularly act as a major enabler for
CoMP and D2D in context of 5G. This article thus serves as both a tutorial as
well as an up to date survey on SARC, CoMP and D2D. Most importantly, the
article provides an extensive outlook of challenges and opportunities that lie
at the crossroads of these three mutually entangled emerging technologies.Comment: 28 pages, 11 figures, IEEE Communications Surveys & Tutorials 201
A Taxonomy of Self-configuring Service Discovery Systems
We analyze the fundamental concepts and issues in service
discovery. This analysis places service discovery in the context of distributed
systems by describing service discovery as a third generation
naming system. We also describe the essential architectures and the
functionalities in service discovery. We then proceed to show how service
discovery fits into a system, by characterizing operational aspects.
Subsequently, we describe how existing state of the art performs service
discovery, in relation to the operational aspects and functionalities, and
identify areas for improvement
Middleware-based Database Replication: The Gaps between Theory and Practice
The need for high availability and performance in data management systems has
been fueling a long running interest in database replication from both academia
and industry. However, academic groups often attack replication problems in
isolation, overlooking the need for completeness in their solutions, while
commercial teams take a holistic approach that often misses opportunities for
fundamental innovation. This has created over time a gap between academic
research and industrial practice.
This paper aims to characterize the gap along three axes: performance,
availability, and administration. We build on our own experience developing and
deploying replication systems in commercial and academic settings, as well as
on a large body of prior related work. We sift through representative examples
from the last decade of open-source, academic, and commercial database
replication systems and combine this material with case studies from real
systems deployed at Fortune 500 customers. We propose two agendas, one for
academic research and one for industrial R&D, which we believe can bridge the
gap within 5-10 years. This way, we hope to both motivate and help researchers
in making the theory and practice of middleware-based database replication more
relevant to each other.Comment: 14 pages. Appears in Proc. ACM SIGMOD International Conference on
Management of Data, Vancouver, Canada, June 200
When Virtual Reality Meets Rate Splitting Multiple Access: A Joint Communication and Computation Approach
Rate Splitting Multiple Access (RSMA) has emerged as an effective
interference management scheme for applications that require high data rates.
Although RSMA has shown advantages in rate enhancement and spectral efficiency,
it has yet not to be ready for latency-sensitive applications such as virtual
reality streaming, which is an essential building block of future 6G networks.
Unlike conventional High-Definition streaming applications, streaming virtual
reality applications requires not only stringent latency requirements but also
the computation capability of the transmitter to quickly respond to dynamic
users' demands. Thus, conventional RSMA approaches usually fail to address the
challenges caused by computational demands at the transmitter, let alone the
dynamic nature of the virtual reality streaming applications. To overcome the
aforementioned challenges, we first formulate the virtual reality streaming
problem assisted by RSMA as a joint communication and computation optimization
problem. A novel multicast approach is then proposed to cluster users into
different groups based on a Field-of-View metric and transmit multicast streams
in a hierarchical manner. After that, we propose a deep reinforcement learning
approach to obtain the solution for the optimization problem. Extensive
simulations show that our framework can achieve the millisecond-latency
requirement, which is much lower than other baseline schemes
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