The Road Ahead for Networking: A Survey on ICN-IP Coexistence Solutions

In recent years, the current Internet has experienced an unexpected paradigm shift in the usage model, which has pushed researchers towards the design of the Information-Centric Networking (ICN) paradigm as a possible replacement of the existing architecture. Even though both Academia and Industry have investigated the feasibility and effectiveness of ICN, achieving the complete replacement of the Internet Protocol (IP) is a challenging task. Some research groups have already addressed the coexistence by designing their own architectures, but none of those is the final solution to move towards the future Internet considering the unaltered state of the networking. To design such architecture, the research community needs now a comprehensive overview of the existing solutions that have so far addressed the coexistence. The purpose of this paper is to reach this goal by providing the first comprehensive survey and classification of the coexistence architectures according to their features (i.e., deployment approach, deployment scenarios, addressed coexistence requirements and architecture or technology used) and evaluation parameters (i.e., challenges emerging during the deployment and the runtime behaviour of an architecture). We believe that this paper will finally fill the gap required for moving towards the design of the final coexistence architecture.Comment: 23 pages, 16 figures, 3 table

Understanding complementary multi-layer collaborative heuristics for adaptive caching in heterogeneous mobile opportunistic networks

Current research aims to deal with emerging challenges of the opportunistic discovery of content stored in remote mobile publishers and the delivery to the subscribers in heterogeneous mobile opportunistic networks. Innovative network and service architectures leverage in-network caching to improve transmission efficiency, reduce delay and handle disconnections. In this paper, we investigate the influences of multi-dimensional heuristics utilised by our adaptive collaborative caching framework CafRepCache on the performance of content dissemination and query in heterogeneous mobile opportunistic environments. We consider the complementary multi-layer heuristics that combine social driven, resources driven, ego network driven and content popularity driven analytics. We extensively evaluate the performance of each complementary heuristic and discuss the impact of each one on every layer of our caching framework across heterogeneous real-world mobility, connectivity traces and use YouTube dataset for different workload and content popularity patterns. We show that the multilayer heuristics enable CafRepCache to be responsive to dynamically changing network topology, congestion avoidance and varying patterns of content publishers/subscribers which balances the trade-off that achieves higher cache hit ratio, delivery success ratios while keeping lower delays and packet loss

Network Coding Enabled Named Data Networking Architectures

The volume of data traffic in the Internet has increased drastically in the last years, mostly due to data intensive applications like video streaming, file sharing, etc.. This motivates the development of new communication methods that can deal with the growing volume of data traffic. To this aim, Named Data Networking (NDN) has been proposed as a future Internet architecture that changes how the Internet works, from the exchange of content between particular nodes of the network, to retrieval of particular content in the network. The NDN architecture enables ubiquitous in-network caching and naturally supports dynamic selection of content sources, characteristics that fit well with the communication needs of data intensive applications. However, the performance of data intensive applications is degraded by the limited throughput seen by applications, which can be caused by (i) limited bandwidth, (ii) network bottlenecks and (iii) packet losses. In this thesis, we argue that introducing network coding into the NDN architecture improves the performance of NDN-based data intensive applications by alleviating the three issues presented above. In particular, network coding (i) enables efficient multipath data retrieval in NDN, which allows nodes to aggregate all the bandwidth available through their multiple interfaces; (ii) allows information from multiple sources to be combined at the intermediate routers, which alleviates the impact of network bottlenecks; and (iii) enables clients to efficiently handle packet losses. This thesis first provides an architecture that enables network coding in NDN for data intensive applications. Then, a study demonstrates and quantifies the benefits that network coding brings to video streaming over NDN, a particular data intensive application. To study the benefits that network coding brings in a more realistic NDN scenario, this thesis finally provides a caching strategy that is used when the in-network caches have limited capacity. Overall, the evaluation results show that the use of network coding permits to exploit more efficiently available network resources, which leads to reduced data traffic load on the sources, increased cache-hit rate at the in-network caches and faster content retrieval at the clients. In particular, for video streaming applications, network coding enables clients to watch higher quality videos compared to using traditional NDN, while it also reduces the video servers' load. Moreover, the proposed caching strategy for network coding enabled NDN maintains the benefits that network coding brings to NDN even when the caches have limited storage space

Adaptive real-time predictive collaborative content discovery and retrieval in mobile disconnection prone networks

Emerging mobile environments motivate the need for the development of new distributed technologies which are able to support dynamic peer to peer content sharing, decrease high operating costs, and handle intermittent disconnections. In this paper, we investigate complex challenges related to the mobile disconnection tolerant discovery of content that may be stored in mobile devices and its delivery to the requesting nodes in mobile resource-constrained heterogeneous environments. We propose a new adaptive real-time predictive multi-layer caching and forwarding approach, CafRepCache, which is collaborative, resource, latency, and content aware. CafRepCache comprises multiple multi-layer complementary real-time distributed predictive heuristics which allow it to respond and adapt to time-varying network topology, dynamically changing resources, and workloads while managing complex dynamic tradeoffs between them in real time. We extensively evaluate our work against three competitive protocols across a range of metrics over three heterogeneous real-world mobility traces in the face of vastly different workloads and content popularity patterns. We show that CafRepCache consistently maintains higher cache availability, efficiency and success ratios while keeping lower delays, packet loss rates, and caching footprint compared to the three competing protocols across three traces when dynamically varying content popularity and dynamic mobility of content publishers and subscribers. We also show that the computational cost and network overheads of CafRepCache are only marginally increased compared with the other competing protocols

Quality of experience-centric management of adaptive video streaming services : status and challenges

Video streaming applications currently dominate Internet traffic. Particularly, HTTP Adaptive Streaming ( HAS) has emerged as the dominant standard for streaming videos over the best-effort Internet, thanks to its capability of matching the video quality to the available network resources. In HAS, the video client is equipped with a heuristic that dynamically decides the most suitable quality to stream the content, based on information such as the perceived network bandwidth or the video player buffer status. The goal of this heuristic is to optimize the quality as perceived by the user, the so-called Quality of Experience (QoE). Despite the many advantages brought by the adaptive streaming principle, optimizing users' QoE is far from trivial. Current heuristics are still suboptimal when sudden bandwidth drops occur, especially in wireless environments, thus leading to freezes in the video playout, the main factor influencing users' QoE. This issue is aggravated in case of live events, where the player buffer has to be kept as small as possible in order to reduce the playout delay between the user and the live signal. In light of the above, in recent years, several works have been proposed with the aim of extending the classical purely client-based structure of adaptive video streaming, in order to fully optimize users' QoE. In this article, a survey is presented of research works on this topic together with a classification based on where the optimization takes place. This classification goes beyond client-based heuristics to investigate the usage of server-and network-assisted architectures and of new application and transport layer protocols. In addition, we outline the major challenges currently arising in the field of multimedia delivery, which are going to be of extreme relevance in future years