Value-Based Dynamic Caching Over Information-Centric Networks (ICNs)
Information-Centric Network (ICN) , Caching , Value-based Caching , Economic Caching , Dynamic Caching and Pricing
Information-Centric Network (ICN) is a promising developing communication paradigm focusing on efficient content distribution and retrieval regardless of the content storage location to scale with the projected traffic demand and usage patterns of the Internet. In-network caching in ICN is pivotal in providing fast, reliable, and scalable content dissemination and retrieval. In this thesis, we aim to maximize the caching utilities based on the valuations of cache contents and cache nodes in ICNs. Most existing ICN caching schemes consider a consumer-centric perspective only for cache valuation. We embed the producer-centric caching perspective along with the consumer-centric perspective for optimal utilization of the inherent caching capability of ICN. This thesis also introduces a value-based economic caching perspective in ICN. Our research on value-based caching puts forth the following contributions. First, we present a comprehensive taxonomy, and second, we perform qualitative and quantitative performance analyses of some well-known ICN caching schemes. We identify the design factors of our research of value-based caching grounded upon the proposed taxonomy and the performance analyses. Third, we propose a novel content utility value-based dynamic caching scheme for maximizing the aggregated content utility value of an ICN cache service provider. The proposed caching scheme ensures caching diversity and availability of good quality content and demonstrates an acceptable cache hit ratio while maximizing the aggregated content value. Fourth, we propose a novel caching model in which content producers valuate and select cache nodes to cache their contents based on the topological and dynamic attributes of nodes. Our proposed model enables the content producers to maximize the caching utility while reducing delay and increasing cache hit ratio. Fifth, we address the dynamic cache allocation and pricing problem involving multiple content producers and competing ICN cache service providers. We present frameworks, building on producer-driven caching and pricing decisions, leveraging reverse auction-based and utility value-based schemes. Extensive simulations demonstrate the effectiveness of all our proposed value-based caching schemes in terms of several research-objective-related and standard caching performance metrics. Simulation results suggest that value-based caching can leverage the in-network caching capability of ICN to achieve efficient content dissemination and retrieval.