4,885 research outputs found
Many-to-Many Matching Games for Proactive Social-Caching in Wireless Small Cell Networks
In this paper, we address the caching problem in small cell networks from a
game theoretic point of view. In particular, we formulate the caching problem
as a many-to-many matching game between small base stations and service
providers' servers. The servers store a set of videos and aim to cache these
videos at the small base stations in order to reduce the experienced delay by
the end-users. On the other hand, small base stations cache the videos
according to their local popularity, so as to reduce the load on the backhaul
links. We propose a new matching algorithm for the many-to-many problem and
prove that it reaches a pairwise stable outcome. Simulation results show that
the number of satisfied requests by the small base stations in the proposed
caching algorithm can reach up to three times the satisfaction of a random
caching policy. Moreover, the expected download time of all the videos can be
reduced significantly
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
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