A Lightweight Distributed Solution to Content Replication in Mobile Networks

Performance and reliability of content access in mobile networks is conditioned by the number and location of content replicas deployed at the network nodes. Facility location theory has been the traditional, centralized approach to study content replication: computing the number and placement of replicas in a network can be cast as an uncapacitated facility location problem. The endeavour of this work is to design a distributed, lightweight solution to the above joint optimization problem, while taking into account the network dynamics. In particular, we devise a mechanism that lets nodes share the burden of storing and providing content, so as to achieve load balancing, and decide whether to replicate or drop the information so as to adapt to a dynamic content demand and time-varying topology. We evaluate our mechanism through simulation, by exploring a wide range of settings and studying realistic content access mechanisms that go beyond the traditional assumptionmatching demand points to their closest content replica. Results show that our mechanism, which uses local measurements only, is: (i) extremely precise in approximating an optimal solution to content placement and replication; (ii) robust against network mobility; (iii) flexible in accommodating various content access patterns, including variation in time and space of the content demand.Comment: 12 page

Jointly Optimal Routing and Caching for Arbitrary Network Topologies

We study a problem of fundamental importance to ICNs, namely, minimizing routing costs by jointly optimizing caching and routing decisions over an arbitrary network topology. We consider both source routing and hop-by-hop routing settings. The respective offline problems are NP-hard. Nevertheless, we show that there exist polynomial time approximation algorithms producing solutions within a constant approximation from the optimal. We also produce distributed, adaptive algorithms with the same approximation guarantees. We simulate our adaptive algorithms over a broad array of different topologies. Our algorithms reduce routing costs by several orders of magnitude compared to prior art, including algorithms optimizing caching under fixed routing.Comment: This is the extended version of the paper "Jointly Optimal Routing and Caching for Arbitrary Network Topologies", appearing in the 4th ACM Conference on Information-Centric Networking (ICN 2017), Berlin, Sep. 26-28, 201

Content Replication in Mobile Networks

Performance and reliability of content access in mobile networks is conditioned by the number and location of content replicas deployed at the network nodes. In this work, we design a practical, distributed solution to content replication that is suitable for dynamic environments and achieves load balancing. Simulation results show that our mechanism, which uses local measurements only, approximates well an optimal solution while being robust against network and demand dynamics. Also, our scheme outperforms alternative approaches in terms of both content access delay and access congestio

Content-aware resource allocation model for IPTV delivery networks

Nowadays, with the evolution of digital video broadcasting, as well as, the advent of high speed broadband networks, a new era of TV services has emerged known as IPTV. IPTV is a system that employs the high speed broadband networks to deliver TV services to the subscribers. From the service provider viewpoint, the challenge in IPTV systems is how to build delivery networks that exploits the resources efficiently and reduces the service cost, as well. However, designing such delivery networks affected by many factors including choosing the suitable network architecture, load balancing, resources waste, and cost reduction. Furthermore, IPTV contents characteristics, particularly; size, popularity, and interactivity play an important role in balancing the load and avoiding the resources waste for delivery networks. In this paper, we investigate the problem of resource allocation for IPTV delivery networks over the recent architecture, peer-service area architecture. The Genetic Algorithm as an optimization tool has been used to find the optimal provisioning parameters including storage, bandwidth, and CPU consumption. The experiments have been conducted on two data sets with different popularity distributions. The experiments have been conducted on two popularity distributions. The experimental results showed the impact of content status on the resource allocation process