Biblio
Filters: Keyword is information-centric networking architectures [Clear All Filters]
A Stackelberg-Based Optimal Profit Split Scheme in Information-Centric Wireless Networks. 2019 IEEE International Conference on Communications Workshops (ICC Workshops). :1–6.
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2019. The explosive growth of mobile traffic in the Internet makes content delivery a challenging issue to cope with. To promote efficiency of content distribution and reduce network cost, Internet Service Providers (ISPs) and content providers (CPs) are motivated to cooperatively work. As a clean-slate solution, nowadays Information-Centric Networking architectures have been proposed and widely researched, where the thought of in-network caching, especially edge caching, can be applied to mobile wireless networks to fundamentally address this problem. Considered the profit split issue between ISPs and CPs and the influence of content popularity is largely ignored, in this paper, we propose a Stackelberg-based optimal network profit split scheme for content delivery in information-centric wireless networks. Simulation results show that the performance of our proposed model is comparable to its centralized solution and obviously superior to current ISP-CP cooperative schemes without considering cache deployment in the network.
A Novel Congestion-Aware Interest Flooding Attacks Detection Mechanism in Named Data Networking. 2019 28th International Conference on Computer Communication and Networks (ICCCN). :1–6.
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2019. Named Data Networking (NDN) is a promising candidate for future internet architecture. It is one of the implementations of the Information-Centric Networking (ICN) architectures where the focus is on the data rather than the owner of the data. While the data security is assured by definition, these networks are susceptible of various Denial of Service (DoS) attacks, mainly Interest Flooding Attacks (IFA). IFAs overwhelm an NDN router with a huge amount of interests (Data requests). Various solutions have been proposed in the literature to mitigate IFAs; however; these solutions do not make a difference between intentional and unintentional misbehavior due to the network congestion. In this paper, we propose a novel congestion-aware IFA detection and mitigation solution. We performed extensive simulations and the results clearly depict the efficiency of our proposal in detecting truly occurring IFA attacks.