Information-Centric Networking (ICN) has the characteristics of in-network caching, which can reduce the transmission of duplicate traffic, reduce the load on the servers and improve the user experience. From a technical point of view, it is a very promising network architecture. A reasonable pricing mechanism can encourage internet service providers, content providers and users to participate in the operation and use of ICN, and convert ICN technical advantages into economic benefits, thereby promote the large-scale deployment of ICN. The current research focuses on ICN pricing to analyze the pricing mechanism on the internet service provider (ISP) side and the corresponding market equilibrium results. But the model of content providers (CPs) is usually relatively simple in this research. The model assumes the existence of one single CP operator, which will be very different from future deployment scenarios. Multiple CPs will introduce competition and stimulate end users to use ICN networks and ISPs to deploy ICN networks. Moreover, the relationship between CPs is not only competitive but also cooperative. This paper focuses on the complex relationship of competition and cooperation among multiple CPs, solves the non-cooperative game model based on game theory, and studies the interaction between cache and pricing strategies of ICN entities. The optimal cache share of ISPs and the optimal pricing of ISPs and CPs are obtained by establishing the optimal utility function of each entity. Finally, numerical analysis is performed to derive the utility function of ICN entities as the critical pricing and caching parameters change, while verifying the consistency with the equilibrium solution. 

Cache Pricing Mechanism for ICN in the Scenario of Multiple Content Providers

This paper addresses a wireless sensor network technology that supports the deployment of sustainable IoT applications essential to future zero-carbon smart cities. We propose a novel data collection and retrieval scheme to adopt an information-centric network into wireless sensor networks for energy efficiency. The results of laboratory-based experiments using a testbed and prototype network demonstrate the feasibility and applicability of the proposed scheme in terms of network throughput, latency, jitter, and energy consumption.

A preliminary analysis of data collection and retrieval scheme for green information-centric wireless sensor networks

Ubiquitous caching is a feature shared by all proposed information-centric network (ICN) architectures. Prioritising storage resources to popular content in the network is a proven way to guarantee hit rates, reduce the number of hops forwarded, and reduce user request latency. An ideal ICN caching mechanism should make the best use of relevant information such as content information, network state, and user requirements to achieve optimal selection and have the ability to adaptively adjust the decision cache content for dynamic scenarios. Since router nodes have limited cache space, it is then useless to accurately predict the popularity of the content with very low popularity, as this content has no chance of being cached. A more effective approach is to focus on content with high popularity that influences caching decisions. As for different nodes, they have different sets of popular content, and using this property, this paper designs a caching method based on the popularity hierarchy with topological weights. The method considers managing the cached content in nodes with a hierarchy of popularity and improving their distribution in terms of the importance of the nodes’ position in the network. Finally, the scheme is simulated by changing the parameter settings under different actual topologies on the simulation platform to confirm the feasibility of the scheme.

https://downloads.hindawi.com/journals/wcmc/2022/4979057.pdf

An Information-Centric Network Caching Method Based on Popularity Rating and Topology Weighting

To address the problems in end-to-end networks, researchers have proposed an information-centric network(ICN). In-network caching is one of the important features of ICN, which can greatly improve the efficiency of content distribution. However, the Internet Service Providers(ISP) only deploy Innetwork caching if there is some financial incentives. The existing ICN pricing mechanisms only study paid content but ignore free content in the network. In addition, the existing ICN economic models do not take into account ISP cooperating with Content Provider(CP) to deploy in-network caches. Therefore, the pricing mechanisms already in place cannot be applied in practice. In this paper, different from the existing models which based on the paid content, a new ICN pricing model with free content based on non-cooperative game theory was proposed for the first time and advertisers were effectively added to the ICN pricing model. After analyzing the behavioral relationships between entities within the network, the authors establish the utility function for each entity. The authors analyze the impact of caching and pricing on the revenues of all entities and solve the equilibrium point to develop win-win pricing strategies. Considering the case where paid content coexists with free content in real networks, the authors proposes a more realistic and integrated model. In this paper, many experimental analyses have been conducted in addition to the theoretical analysis, and the experimental results show that the new model is closer to reality than the existing models and can provide better theoretical guidance for network pricing.

An ICN Cache Pricing Mechanism Based on Non-cooperative Game Model of Users and Advertisers

The key feature of NDN is in-network caching that every router has its cache to store data for future use, thus improve the usage of the network bandwidth and reduce the network latency. However, in-network caching increases the security risks - cache pollution attacks (CPA), which includes locality disruption (ruining the cache locality by sending random requests for unpopular contents to make them popular) and False Locality (introducing unpopular contents in the router’s cache by sending requests for a set of unpopular contents). In this paper, we propose a machine learning method, named Triangle Area Based Multivariate Correlation Analysis (TAB-MCA) that detects the cache pollution attacks in NDN. This detection system has two parts, the triangle-area-based MCA technique, and the threshold-based anomaly detection technique. The TAB-MCA technique is used to extract hidden geometrical correlations between two distinct features for all possible permutations and the threshold-based anomaly detection technique. This technique helps our model to be able to distinguish attacks from legitimate traffic records without requiring prior knowledge. Our technique detects locality disruption, false locality, and combination of the two with high accuracy. Implementation of XC-topology, the proposed method shows high efficiency in mitigating these attacks. In comparison to other ML-methods, our proposed method has a low overhead cost in mitigating CPA as it doesn’t require attackers’ prior knowledge. Additionally, our method can also detect non-uniform attack distributions.

Triangle Area Based Multivariate Correlation Analysis for Detecting and Mitigating Cache Pollution Attacks in Named Data Networking

Most research on NDMANET cache strategy does not take the priority of content into consideration, which will affect the usability of important content in the mobile environment. Aiming at solving this problem, this paper proposes a cache replacement strategy based on content priority. First, the content is prioritized according to the different needs for the availability of different content. Then, the priority of the content is used as a reference factor for cache replacement to make a cache replacement decision, and the goal is to improve the hit rate and availability of important content. At the same time, the simulation results of ndnSIM show that the strategy can significantly increase the number of cached important content without affecting the global hit rate and response delay, thereby improving the availability of important content.

Liu Yuan

Papers

An ICN Cache Pricing Mechanism Based on Non-cooperative Game Model of Users and Advertisers

Triangle Area Based Multivariate Correlation Analysis for Detecting and Mitigating Cache Pollution Attacks in Named Data Networking

Research on Content Priority-Based Caching Strategy in NDMANET