59,963 research outputs found
The Price of Fog: a Data-Driven Study on Caching Architectures in Vehicular Networks
Vehicular users are expected to consume large amounts of data, for both
entertainment and navigation purposes. This will put a strain on cellular
networks, which will be able to cope with such a load only if proper caching is
in place, this in turn begs the question of which caching architecture is the
best-suited to deal with vehicular content consumption. In this paper, we
leverage a large-scale, crowd-collected trace to (i) characterize the vehicular
traffic demand, in terms of overall magnitude and content breakup, (ii) assess
how different caching approaches perform against such a real-world load, (iii)
study the effect of recommendation systems and local contents. We define a
price-of-fog metric, expressing the additional caching capacity to deploy when
moving from traditional, centralized caching architectures to a "fog computing"
approach, where caches are closer to the network edge. We find that for
location-specific contents, such as the ones that vehicular users are most
likely to request, such a price almost disappears. Vehicular networks thus make
a strong case for the adoption of mobile-edge caching, as we are able to reap
the benefit thereof -- including a reduction in the distance traveled by data,
within the core network -- with little or no of the associated disadvantages.Comment: ACM IoV-VoI 2016 MobiHoc Workshop, The 17th ACM International
Symposium on Mobile Ad Hoc Networking and Computing: MobiHoc 2016-IoV-VoI
Workshop, Paderborn, German
Orchestrating Service Migration for Low Power MEC-Enabled IoT Devices
Multi-Access Edge Computing (MEC) is a key enabling technology for Fifth
Generation (5G) mobile networks. MEC facilitates distributed cloud computing
capabilities and information technology service environment for applications
and services at the edges of mobile networks. This architectural modification
serves to reduce congestion, latency, and improve the performance of such edge
colocated applications and devices. In this paper, we demonstrate how reactive
service migration can be orchestrated for low-power MEC-enabled Internet of
Things (IoT) devices. Here, we use open-source Kubernetes as container
orchestration system. Our demo is based on traditional client-server system
from user equipment (UE) over Long Term Evolution (LTE) to the MEC server. As
the use case scenario, we post-process live video received over web real-time
communication (WebRTC). Next, we integrate orchestration by Kubernetes with S1
handovers, demonstrating MEC-based software defined network (SDN). Now, edge
applications may reactively follow the UE within the radio access network
(RAN), expediting low-latency. The collected data is used to analyze the
benefits of the low-power MEC-enabled IoT device scheme, in which end-to-end
(E2E) latency and power requirements of the UE are improved. We further discuss
the challenges of implementing such schemes and future research directions
therein
Cost-Effective Cache Deployment in Mobile Heterogeneous Networks
This paper investigates one of the fundamental issues in cache-enabled
heterogeneous networks (HetNets): how many cache instances should be deployed
at different base stations, in order to provide guaranteed service in a
cost-effective manner. Specifically, we consider two-tier HetNets with
hierarchical caching, where the most popular files are cached at small cell
base stations (SBSs) while the less popular ones are cached at macro base
stations (MBSs). For a given network cache deployment budget, the cache sizes
for MBSs and SBSs are optimized to maximize network capacity while satisfying
the file transmission rate requirements. As cache sizes of MBSs and SBSs affect
the traffic load distribution, inter-tier traffic steering is also employed for
load balancing. Based on stochastic geometry analysis, the optimal cache sizes
for MBSs and SBSs are obtained, which are threshold-based with respect to cache
budget in the networks constrained by SBS backhauls. Simulation results are
provided to evaluate the proposed schemes and demonstrate the applications in
cost-effective network deployment
Big Data Meets Telcos: A Proactive Caching Perspective
Mobile cellular networks are becoming increasingly complex to manage while
classical deployment/optimization techniques and current solutions (i.e., cell
densification, acquiring more spectrum, etc.) are cost-ineffective and thus
seen as stopgaps. This calls for development of novel approaches that leverage
recent advances in storage/memory, context-awareness, edge/cloud computing, and
falls into framework of big data. However, the big data by itself is yet
another complex phenomena to handle and comes with its notorious 4V: velocity,
voracity, volume and variety. In this work, we address these issues in
optimization of 5G wireless networks via the notion of proactive caching at the
base stations. In particular, we investigate the gains of proactive caching in
terms of backhaul offloadings and request satisfactions, while tackling the
large-amount of available data for content popularity estimation. In order to
estimate the content popularity, we first collect users' mobile traffic data
from a Turkish telecom operator from several base stations in hours of time
interval. Then, an analysis is carried out locally on a big data platform and
the gains of proactive caching at the base stations are investigated via
numerical simulations. It turns out that several gains are possible depending
on the level of available information and storage size. For instance, with 10%
of content ratings and 15.4 Gbyte of storage size (87% of total catalog size),
proactive caching achieves 100% of request satisfaction and offloads 98% of the
backhaul when considering 16 base stations.Comment: 8 pages, 5 figure
EVEREST IST - 2002 - 00185 : D23 : final report
Deliverable pĂşblic del projecte europeu EVERESTThis deliverable constitutes the final report of the project IST-2002-001858 EVEREST. After its successful completion, the project presents this document that firstly summarizes the context, goal and the approach objective of the project. Then it presents a concise summary of the major goals and results, as well as highlights the most valuable lessons derived form the project work. A list of deliverables and publications is included in the annex.Postprint (published version
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