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

Asymptotic Laws for Joint Content Replication and Delivery in Wireless Networks

We investigate on the scalability of multihop wireless communications, a major concern in networking, for the case that users access content replicated across the nodes. In contrast to the standard paradigm of randomly selected communicating pairs, content replication is efficient for certain regimes of file popularity, cache and network size. Our study begins with the detailed joint content replication and delivery problem on a 2D square grid, a hard combinatorial optimization. This is reduced to a simpler problem based on replication density, whose performance is of the same order as the original. Assuming a Zipf popularity law, and letting the size of content and network both go to infinity, we identify the scaling laws and regimes of the required link capacity, ranging from O(\sqrt{N}) down to O(1)

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

Optimal Content Replication and Request Matching in Large Caching Systems

We consider models of content delivery networks in which the servers are constrained by two main resources: memory and bandwidth. In such systems, the throughput crucially depends on how contents are replicated across servers and how the requests of specific contents are matched to servers storing those contents. In this paper, we first formulate the problem of computing the optimal replication policy which if combined with the optimal matching policy maximizes the throughput of the caching system in the stationary regime. It is shown that computing the optimal replication policy for a given system is an NP-hard problem. A greedy replication scheme is proposed and it is shown that the scheme provides a constant factor approximation guarantee. We then propose a simple randomized matching scheme which avoids the problem of interruption in service of the ongoing requests due to re-assignment or repacking of the existing requests in the optimal matching policy. The dynamics of the caching system is analyzed under the combination of proposed replication and matching schemes. We study a limiting regime, where the number of servers and the arrival rates of the contents are scaled proportionally, and show that the proposed policies achieve asymptotic optimality. Extensive simulation results are presented to evaluate the performance of different policies and study the behavior of the caching system under different service time distributions of the requests.Comment: INFOCOM 201