Enhancing multi-source content delivery in content-centric networks with fountain coding

Fountain coding has been considered as especially suitable for lossy environments, such as wireless networks, as it provides redundancy while reducing coordination overheads between sender(s) and receiver(s). As such it presents beneficial properties for multi-source and/or multicast communication. In this paper we investigate enhancing/increasing multi-source content delivery efficiency in the context of Content-Centric Networking (CCN) with the usage of fountain codes. In particular, we examine whether the combination of fountain coding with the in-network caching capabilities of CCN can further improve performance. We also present an enhancement of CCN's Interest forwarding mechanism that aims at minimizing duplicate transmissions that may occur in a multi-source transmission scenario, where all available content providers and caches with matching (cached) content transmit data packets simultaneously. Our simulations indicate that the use of fountain coding in CCN is a valid approach that further increases network performance compared to traditional schemes

Exploiting Caching and Multicast for 5G Wireless Networks

The landscape toward 5G wireless communication is currently unclear, and, despite the efforts of academia and industry in evolving traditional cellular networks, the enabling technology for 5G is still obscure. This paper puts forward a network paradigm toward next-generation cellular networks, targeting to satisfy the explosive demand for mobile data while minimizing energy expenditures. The paradigm builds on two principles; namely caching and multicast. On one hand, caching policies disperse popular content files at the wireless edge, e.g., pico-cells and femto-cells, hence shortening the distance between content and requester. On other hand, due to the broadcast nature of wireless medium, requests for identical files occurring at nearby times are aggregated and served through a common multicast stream. To better exploit the available cache space, caching policies are optimized based on multicast transmissions. We show that the multicast-aware caching problem is NP-hard and develop solutions with performance guarantees using randomized-rounding techniques. Trace-driven numerical results show that in the presence of massive demand for delay tolerant content, combining caching and multicast can indeed reduce energy costs. The gains over existing caching schemes are 19% when users tolerate delay of three minutes, increasing further with the steepness of content access pattern

Tube streaming: Modelling collaborative media streaming in urban railway networks

We propose a quality assessment framework for crowdsourced media streaming in urban railway networks. We assume that commuters either tune in to some TV/radio channel, or submit requests for content they desire to watch or listen to, which eventually forms a playlist of videos/podcasts/tunes. Given that connectivity is challenged by the movement of trains and the disconnection that this movement causes, users collabo-ratively download (through cellular and WiFi connections) and share content, in order to maintain undisrupted playback. We model collaborative media streaming for the case of the London Underground train network. The proposed quality assessment framework comprises a utility function which characterises the Quality of Experience (QoE) that users (subjectively) perceive and takes into account all the necessary parameters that affect smooth playback. The framework can be used to assess the media streaming quality in any railway network, after adjusting the related parameters. To the best of our knowledge, this is the first study to quantify the perceptual quality of collaborative media streaming in (underground) railway networks from a modelling perspective, as opposed to a systems perspective. Based on real commuter traces from the London Underground network, we evaluate whether audio and video can be streamed to commuters with acceptable QoE. Our results show that even with very high-speed Internet connection, users still experience disruptions, but a carefully designed collaborative mechanism can result in high levels of perceived QoE even in such disruptive scenarios

Efficient Hash-routing and Domain Clustering Techniques for Information-Centric Networks

Hash-routing is a well-known technique used in server-cluster environments to direct content requests to the responsible servers hosting the requested content. In this work, we look at hash-routing from a different angle and apply the technique to Information-Centric Networking (ICN) environments, where in-network content caches serve as temporary storage for content. In particular, edge-domain routers re-direct requests to in-network caches, more often than not off the shortest path, according to the hash-assignment function. Although the benefits of this off-path in-network caching scheme are significant (e.g., high cache hit rate with minimal co-ordination overhead), the basic scheme comes with disadvantages. That is, in case of very large domains the off-path detour of requests might increase latency to prohibitive levels. In order to deal with extensive detour delays, we investigate nodal/domain clustering techniques, according to which large domains are split in clusters, which in turn apply hash-routing in the subset of nodes of each cluster. We model and evaluate the behaviour of nodal clustering and report significant improvement in delivery latency, which comes at the cost of a slight decrease in cache hit rates (i.e., up to 50% improvement in delivery latency for less than 10% decrease in cache hit rate compared to the original hash-routing scheme applied in the whole domain)

Opportunistic off-path content discovery in information-centric networks

Recent research in Information-Centric Networks has considered various approaches for discovering content in the cache-enabled nodes of the network. Such approaches include scoped flooding and deploying a control plane protocol to disseminate the cache contents in the network, to name a few. In this work, we consider an opportunistic approach that uses trails left behind by data packets from the content origin to the sources in order to discover off-path cached content. We evaluate our approach using an ISP topology for various system parameters. We propose two new forwarding strategies built on top of our approach. Our results indicate that the opportunistic discovery mechanism can significantly increase cache hit rate compared to NDN's default forwarding strategy, while limiting the overhead at acceptable levels

A native content discovery mechanism for the information-centric networks

Recent research has considered various approaches for discovering content in the cache-enabled nodes of an Autonomous System (AS) to reduce the costly inter-AS traffic. Such approaches include i) searching content opportunistically (on-path) along the default intra-AS path towards the content origin for limited gain, and ii) actively coordinate nodes when caching content for significantly higher gains, but also higher overhead. In this paper, we try to combine the merits of both worlds by using traditional opportunistic caching mechanisms enhanced with a lightweight content discovery approach. Particularly, a content retrieved through an inter-AS link is cached only once along the intra-AS delivery path to maximize network storage utilization, and ephemeral forwarding state to locate temporarily stored content is established opportunistically at each node along that path during the processing of Data packets. The ephemeral forwarding state either points to the arriving or the destination face of the Data packet depending on whether the content has already been cached along the path or not. The challenge in such an approach is to appropriately use and maintain the ephemeral forwarding state to minimize inter-AS content retrieval, while keeping retrieval latency and overhead at acceptable levels. We propose several forwarding strategies to use and manage ephemeral state and evaluate our mechanism using an ISP topology for various system parameters. Our results indicate that our opportunistic content discovery mechanism can achieve near-optimal performance and significantly reduce inter-AS traffic

Phase Transitions in Disordered Systems: The Example of the Random-Field Ising Model in Four Dimensions

By performing a high-statistics simulation of the D=4 random-field Ising model at zero temperature for different shapes of the random-field distribution, we show that the model is ruled by a single universality class. We compute to a high accuracy the complete set of critical exponents for this class, including the correction-to-scaling exponent. Our results indicate that in four dimensions (i) dimensional reduction as predicted by the perturbative renormalization group does not hold and (ii) three independent critical exponents are needed to describe the transition

Information-Centric Connectivity

Mobile devices are often presented with multiple connectivity options usually making a selection either randomly or based on load/wireless conditions metrics, as is the case of current offloading schemes. In this paper we claim that link-layer connectivity can be associated with information-availability and in this respect connectivity decisions should be information-aware. This constitutes a next step for the Information-Centric Networking paradigm, realizing the concept of Information-Centric Connectivity (ICCON). We elaborate on different types of information availability and connectivity decisions in the context of ICCON, present specific use cases and discuss emerging opportunities, challenges and technical approaches. We illustrate the potential benefits of ICCON through preliminary simulation and numerical results in an example use case

Information-aware access network selection

Mobile devices are increasingly presented with multiple connectivity options, including WiFi hotspots, micro-/macro-cells or even other devices in device-to-device (D2D) communications. By and large, connectivity management for mobile devices has primarily focused on contention, congestion and wireless medium conditions. In this paper, we assess the role of information-centrism in mobile device connectivity management. Motivated by the increasing availability of content and services in in-network caches and micro-data centres, we design an access network selection scheme that takes into account information availability within each connectivity option. Our simulations show that information-awareness results in a significant increase of cache hit ratios by up to 115% in certain scenarios

Resource Provisioning and Allocation in Function-as-a-Service Edge-Clouds

Edge computing has emerged as a new paradigm to bring cloud applications closer to users for increased performance. Unlike back-end cloud systems which consolidate their resources in a centralized data center location with virtually unlimited capacity, edge-clouds comprise distributed resources at various computation spots, each with very limited capacity. In this paper, we consider Function-as-a-Service (FaaS) edge-clouds where application providers deploy their latency-critical functions that process user requests with strict response time deadlines. In this setting, we investigate the problem of resource provisioning and allocation. After formulating the optimal solution, we propose resource allocation and provisioning algorithms across the spectrum of fully-centralized to fully-decentralized. We evaluate the performance of these algorithms in terms of their ability to utilize CPU resources and meet request deadlines under various system parameters. Our results indicate that practical decentralized strategies, which require no coordination among computation spots, achieve performance that is close to the optimal fully-centralized strategy with coordination overheads