Cache "less for more" in information-centric networks (extended version)

Ubiquitous in-network caching is one of the key aspects of information-centric networking (ICN) which has received widespread research interest in recent years. In one of the key relevant proposals known as Content-Centric Networking (CCN), the premise is that leveraging in-network caching to store content in every node along the delivery path can enhance content delivery. We question such an indiscriminate universal caching strategy and investigate whether caching less can actually achieve more. More specifically, we study the problem of en route caching and investigate if caching in only a subset of nodes along the delivery path can achieve better performance in terms of cache and server hit rates. We first study the behavior of CCN's ubiquitous caching and observe that even naïve random caching at a single intermediate node along the delivery path can achieve similar and, under certain conditions, even better caching gain. Motivated by this, we propose a centrality-based caching algorithm by exploiting the concept of (ego network) betweenness centrality to improve the caching gain and eliminate the uncertainty in the performance of the simplistic random caching strategy. Our results suggest that our solution can consistently achieve better gain across both synthetic and real network topologies that have different structural properties. We further find that the effectiveness of our solution is correlated to the precise structure of the network topology whereby the scheme is effective in topologies that exhibit power law betweenness distribution (as in Internet AS and WWW networks)

Cache replacement positions in information-centric network

Information dissemination as the sole functionality driving the current Internet trend has been of keen interest for its manageability. Information Centric Network (ICN) proposed as a new paradigm shift to mitigate the predicted traffic of the current Internet.However, caching as an advantageous building block of ICN is faced with the challenges of content placement, content replacement and eviction.The current practice of ICN caching has given birth to the problems of content redundancy, path redundancy and excessive wastage of bandwidth.This study analyzes the intelligence in cache content management to palliate the gross expenses incurred in the ICN practice.The use of the current factors in previous studies in recency and frequency in content usage play delicate roles in our study. Replacement strategies are agreed to influence the entire cache-hit, stretch and Network diversity

Proxcache: A new cache deployment strategy in information-centric network for mitigating path and content redundancy

One of the promising paradigms for resource sharing with maintaining the basic Internet semantics is the Information-Centric Networking (ICN). ICN distinction with the current Internet is its ability to refer contents by names with partly dissociating the host-to-host practice of Internet Protocol addresses. Moreover, content caching in ICN is the major action of achieving content networking to reduce the amount of server access. The current caching practice in ICN using the Leave Copy Everywhere (LCE) progenerate problems of over deposition of contents known as content redundancy, path redundancy, lesser cache-hit rates in heterogeneous networks and lower content diversity. This study proposes a new cache deployment strategy referred to as ProXcache to acquire node relationships using hyperedge concept of hypergraph for cache positioning. The study formulates the relationships through the path and distance approximation to mitigate content and path redundancy. The study adopted the Design Research Methodology approach to achieve the slated research objectives. ProXcache was investigated using simulation on the Abilene, GEANT and the DTelekom network topologies for LCE and ProbCache caching strategies with the Zipf distribution to differ content categorization. The results show the overall content and path redundancy are minimized with lesser caching operation of six depositions per request as compared to nine and nineteen for ProbCache and LCE respectively. ProXcache yields better content diversity ratio of 80% against 20% and 49% for LCE and ProbCache respectively as the cache sizes varied. ProXcache also improves the cache-hit ratio through proxy positions. These thus, have significant influence in the development of the ICN for better management of contents towards subscribing to the Future Internet

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

GA for Popularity Based Cache Management in ICN

One paragraph only. Information Centric Networks (ICNs) is a new architecture for the Future Internet to deliver content at large-scale. It relies on named data and caching features, which consists of storing content across the delivery path to serve forthcoming requests. In this paper, we study the problem of finding the optimal assignment of popular contents in the available caches storage in ICN. We formulate this problem as a combinatorial optimization problem. Metaheuristic methods are considered as effective methods for solving this problem. We will adapt cache management system based on GA for solving the considered problem in order to minimize overall network overhead

Cost-aware caching: optimizing cache provisioning and object placement in ICN

Caching is frequently used by Internet Service Providers as a viable technique to reduce the latency perceived by end users, while jointly offloading network traffic. While the cache hit-ratio is generally considered in the literature as the dominant performance metric for such type of systems, in this paper we argue that a critical missing piece has so far been neglected. Adopting a radically different perspective, in this paper we explicitly account for the cost of content retrieval, i.e. the cost associated to the external bandwidth needed by an ISP to retrieve the contents requested by its customers. Interestingly, we discover that classical cache provisioning techniques that maximize cache efficiency (i.e., the hit-ratio), lead to suboptimal solutions with higher overall cost. To show this mismatch, we propose two optimization models that either minimize the overall costs or maximize the hit-ratio, jointly providing cache sizing, object placement and path selection. We formulate a polynomial-time greedy algorithm to solve the two problems and analytically prove its optimality. We provide numerical results and show that significant cost savings are attainable via a cost-aware design