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

On-Demand Routing for Scalable Name-Based Forwarding

Information-centric Networking (ICN) is a future Internet architecture design, where application-level names are directly used to route interests to fetch a copy of the desired content/data from any location. Following the conventions of the Internet Protocol to store the pre-computed routing/forwarding state for all prefixes at the network nodes raises scalability concerns in ICN (where content name prefixes need to be stored), especially at the inter-domain level. Instead, we consider the other extreme; that is, On-Demand Routing (ODR) computation for content name prefixes as interests arrive. ODR makes use of domain-level, per-prefix routing instructions usable by all the forwarders in a domain, named Routing Information Objects (RIO). Forwarders discover and retrieve RIOs in a similar way as content and can be cached in a new data structure called Route Information Store (RIS). RIOs are handed to a routing strategy module to perform a routing decision before relaying the packets. We demonstrate through extensive simulations that ODR scales the storage of routing/forwarding information through caching and information discovery-two mechanisms inherent to the ICN design. We propose our design as an extension of the Named Data Networking (NDN) architecture and discuss all the proposed enhancements in detail

Compound popular content caching strategy to enhance the cache management performance in named data networking

Named Data Networking (NDN) is a leading research paradigm for the future Internet architecture. The NDN offers in-network cache which is the most beneficial feature to reduce the difficulties of the location-based Internet paradigm. The objective of cache is to achieve a scalable, effective, and consistent distribution of information. However, the main issue which NDN facing is the selection of appropriate router during the content’s transmission that can disrupt the overall network performance. The reason is that how each router takes a decision to the cache which content needs to cache at what location that can enhance the complete caching performance. Therefore, several cache management strategies have been developed. Still, it is not clear which caching strategy is the most ideal for each situation. This study proposes a new cache management strategy named as Compound Popular Content Caching Strategy (CPCCS) to minimize cache redundancy with enhanced diversity ratio and improving the accessibility of cached content by providing short stretch paths. The CPCCS was developed by combining two mechanisms named as Compound Popular Content Selection (CPCS) and Compound Popular Content Caching (CPCC) to differentiate the contents regarding their Interest frequencies using dynamic threshold and to find the best possible caching positions respectively. CPCCS is compared with other NDN-based caching strategies, such as Max-Gain In-network Caching, WAVE popularity-based caching strategy, Hop-based Probabilistic Caching, Leaf Popular Down, Most Popular Cache, and Cache Capacity Aware Caching in a simulation environment. The results show that the CPCCS performs better in which the diversity and cache hit ratio are increased by 34% and 14% respectively. In addition, the redundancy and path stretch are decreased by 44% and 46% respectively. The outcomes showed that the CPCCS have achieved enhanced caching performance with respect to different cache size (1GB to 10GB) and simulation parameters than other caching strategies. Thus, CPCCS can be applicable in future for the NDN-based emerging technologies such as Internet of Things, fog and edge computing