Topics: Optimization techniques; Anticipatory networking
Authors: Valentino Pacifici, Slavana Joilo and György Dan (KTH Royal Institute of Technology, Sweden)
Presenter bio:
Valentino Pacifici is a postdoctoral researcher at the Laboratory
for Communication Networks in KTH Royal Institute of Technology,
Stockholm, Sweden. He studied computer engineering at Politecnico di
Milano in Milan, Italy. In October 2010, he completed a joint M.Sc.
degree in computer engineering, between Politecnico di Milano and KTH
Royal Institute of Technology. He received the Ph.D. in
Telecommunications from KTH in 2016. His research interests include game
theoretical and stochastic modeling, design and analysis of content
management systems.
Abstract:
The growing popularity of mobile multimedia
content and the increase of wireless access bitrates are straining
backhaul capacity in mobile networks. A cost-effective solution to
reduce the strain, enabled by emerging all-IP 4G and 5G mobile backhaul
architectures, could be in-network caching of popular content during
times of peak demand. In this paper we formulate the problem of content
caching in a mobile backhaul as a binary integer programming problem,
and we propose a 2-approximation algorithm for the problem. The
2-approximation requires full information about the network topology and
the link costs, as well as about the content demands at the different
caches, we thus propose two distributed algorithms that are based on
local information on the content demands. We show that the distributed
algorithms terminate in a finite number of steps, and we provide
analytical results on their approximation ratios. We use simulations to
evaluate the proposed algorithms in terms of the achieved approximation
ratio and computational complexity on realistic mobile backhaul
topologies.
