Optimal Content Placement in ICN Vehicular Networks

Information Centric Networking (ICN) is a networking framework for content distribution. The communication is based on a request/response model where the attention is centered on the content. The user sends interest messages naming the content it desires and the network chooses the best node from which delivers the content. This way for retrieving contents naturally fits a context where users continuously change their location. One of the main problems of user mobility is the intermittent connectivity that causes loss of packets. This work shows how in a Vehicle-to-Infrastructure scenario, the network can exploit the ICN architecture with content pre-distribution to maximize the probability that the user retrieves the desired content. We give an ILP formulation of the problem of optimally distributing the contents in the network nodes and discuss how the system assumptions impact the success probability. Moreover, we validate our model by means of simulations with ndnSIM

Optimal Content Prefetching in NDN Vehicle-to-Infrastructure Scenario

Data replication and in-network storage are two basic principles of the Information Centric Networking (ICN) framework in which caches spread out in the network can be used to store the most popular contents. This work shows how one of the ICN architectures, the Named Data Networking (NDN), with content pre-fetching can maximize the probability that a user retrieves the desired content in a Vehicle-to-Infrastructure scenario. We give an ILP formulation of the problem of optimally distributing content in the network nodes while accounting for the available storage capacity and the available link capacity. The optimization framework is then leveraged to evaluate the impact on content retrievability of topology- and network-related parameters as the number and mobility models of moving users, the size of the content catalog and the location of the available caches. Moreover, we show how the proposed model can be modified to find the minimum storage occupancy to achieve a given content retrievability level. The results obtained from the optimization model are finally validated against a Name Data Networking architecture through simulations in ndnSIM

Efficient Proactive Caching for Supporting Seamless Mobility

We present a distributed proactive caching approach that exploits user mobility information to decide where to proactively cache data to support seamless mobility, while efficiently utilizing cache storage using a congestion pricing scheme. The proposed approach is applicable to the case where objects have different sizes and to a two-level cache hierarchy, for both of which the proactive caching problem is hard. Additionally, our modeling framework considers the case where the delay is independent of the requested data object size and the case where the delay is a function of the object size. Our evaluation results show how various system parameters influence the delay gains of the proposed approach, which achieves robust and good performance relative to an oracle and an optimal scheme for a flat cache structure.Comment: 10 pages, 9 figure

A Content-based Centrality Metric for Collaborative Caching in Information-Centric Fogs

Information-Centric Fog Computing enables a multitude of nodes near the end-users to provide storage, communication, and computing, rather than in the cloud. In a fog network, nodes connect with each other directly to get content locally whenever possible. As the topology of the network directly influences the nodes' connectivity, there has been some work to compute the graph centrality of each node within that network topology. The centrality is then used to distinguish nodes in the fog network, or to prioritize some nodes over others to participate in the caching fog. We argue that, for an Information-Centric Fog Computing approach, graph centrality is not an appropriate metric. Indeed, a node with low connectivity that caches a lot of content may provide a very valuable role in the network. To capture this, we introduce acontent-based centrality (CBC) metric which takes into account how well a node is connected to the content the network is delivering, rather than to the other nodes in the network. To illustrate the validity of considering content-based centrality, we use this new metric for a collaborative caching algorithm. We compare the performance of the proposed collaborative caching with typical centrality based, non-centrality based, and non-collaborative caching mechanisms. Our simulation implements CBC on three instances of large scale realistic network topology comprising 2,896 nodes with three content replication levels. Results shows that CBC outperforms benchmark caching schemes and yields a roughly 3x improvement for the average cache hit rate

A review on green caching strategies for next generation communication networks

© 2020 IEEE. In recent years, the ever-increasing demand for networking resources and energy, fueled by the unprecedented upsurge in Internet traffic, has been a cause for concern for many service providers. Content caching, which serves user requests locally, is deemed to be an enabling technology in addressing the challenges offered by the phenomenal growth in Internet traffic. Conventionally, content caching is considered as a viable solution to alleviate the backhaul pressure. However, recently, many studies have reported energy cost reductions contributed by content caching in cache-equipped networks. The hypothesis is that caching shortens content delivery distance and eventually achieves significant reduction in transmission energy consumption. This has motivated us to conduct this study and in this article, a comprehensive survey of the state-of-the-art green caching techniques is provided. This review paper extensively discusses contributions of the existing studies on green caching. In addition, the study explores different cache-equipped network types, solution methods, and application scenarios. We categorically present that the optimal selection of the caching nodes, smart resource management, popular content selection, and renewable energy integration can substantially improve energy efficiency of the cache-equipped systems. In addition, based on the comprehensive analysis, we also highlight some potential research ideas relevant to green content caching

Coexistence of ICN and IP networks: an NFV as a service approach

International audienceIn contrast to the current host-centric architecture, Information-Centric Networking (ICN) adopts content naming instead of host address and in-network caching to enhance the content delivery, improve the data distribution, and satisfy users' requirements. As ICN is being incrementally deployed in different real-world scenarios, it will exist with IP-based services in a hybrid network setting. Full deployment of ICN and total replacement of IP protocol is not feasible at the current stage since IP is dominating the Internet. On the other hand, redesigning TCP/IP applications from ICN perspective is a time-consuming task and requires a careful investigation from both business and technical point of view. Thus, the coexistence of ICN and IP is one of the suitable solutions. Towards this end, we propose a simple yet efficient coexistence solution based on Network Function Virtualization (NFV) technology. We define a set of communication regions and control virtual functions. A gateway node is used as an intermediate entity to fetch and deliver content over regions. The simulation results show that the proposed approach is valid and allow content fetching and delivering from different ICN and/to IP regions in an efficient manner