- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
In-network caching is an important solution for content offloading from content service providers. However despite a rather high maturation in the definition of caching techniques, minor attention has been given to the strategic interaction among the multiple content providers. Situations involving multiple content providers (CPs) and one Internet Service Provider (ISP) having to give them access to its caches are prone to high cache contention, in particular at the appealing topology cross-points. While available cache contention situations from the literature were solved by considering each storage as one autonomous and self managed cache, we propose in this paper to address this contention situation by segmenting the storage on a per-content provider basis (e.g., each CP receives a portion of the storage space depending on its storage demand). We propose a resource allocation and pricing framework to support the network cache provider in the cache allocation to multiple CPs, for situations where CPs have heterogeneous sets of files and untruthful demands need to be avoided. As cache imputations to CPs need to be fair and robust against overclaiming, we evaluate common proportional and max–min fairness (PF, MMF) allocation rules, as well as two coalitional game rules, the Nucleolus and the Shapley value. When comparing our cache allocation algorithm for the different allocation rules with the naive least-recently-used-based cache allocation approach, we find that the latter provides proportional fairness. Moreover, the game-theoretic rules outperform in terms of content access latency the naive cache allocation approach as well as PF and MMF approaches, while sitting in between PF and MMF in terms of fairness. Furthermore, we show that our pricing scheme encourages the CPs to declare their truthful demands by maximizing their utilities for real declarations.
Novel technologies are difficult to adopt as it has to be proven that they are incentive compatible for all the involved stakeholders. In this paper, we address a multi-stakeholder situation (i.e., involving more than one provider) that appears as a win–win setting toward ICN deployment, i.e., the case of an Internet Network Service Provider deploying ICN for external content providers, offering a neutral interface and pricing to multiple content providers. The network cache provider hence allocates to external content providers spaces in its ICN router caches for content delivery. In this context, we argue that the proper way the network cache provider shall design the cache allocation framework and model the behavior of external content providers is game theory, so as to qualify and counter-balance their natural tendency to form oligopolies and to ally to have a stronger position in getting the available caching resources. We investigate the application of wellknown concepts from cooperative game-theory showing desirable properties, the Nucleolus and the Shapley value, as well as other principles commonly adopted in networking research, the proportional fairness (PF) and the max–min fairness (MMF). We propose a cache allocation algorithm, applied in the context of ICN, that can be performed upon significant changes of content providers’ demands. This algorithm is able to incorporate these different allocation rules applying them to clusters of routers ordered with respect to centrality metrics suggested in the literature. Moreover, we propose a pricing framework that, taking advantages of the monotonicity of the presented cache allocation rules, correctly nullifies the threat of malicious behaviors in formulating content caching demands.