Information-centric networking (ICN) is a novel paradigm that aims at improving the performance of today's Internet by supporting caching and multicast content delivery on every network device. The main contribution of this paper is to propose a centralized strategy to stimulate third parties to jointly lease the unused bandwidth and storage available on wireless access points (APs) in an ICN. We formulate this problem as a combinatorial reverse auction run by a content provider (CP) willing to increase the number of users reached by its service. We show that the optimal allocation with partial coverage problem is NP-hard, provide greedy heuristics that guarantee the individual rationality and truthfulness properties, and compare their performance numerically. We evaluate the benefits of our proposed mechanisms in terms of the cost savings for the CP obtained by offloading its infrastructure through the caches and the reduced computational time to execute the allocation algorithms. We compare the results obtained in this centralized setting with those that can be observed when the mobile clients autonomously choose which AP they prefer to use, among those activated by the auction mechanism. We model this second scenario as a congestion game, showing that it exhibits the desired properties (i.e., existence and uniqueness of a Nash equilibrium) and by comparing its social welfare with the centralized case.
Bandwidth and Cache Leasing in Wireless Information-Centric Networks: A Game-Theoretic Study
CAPONE, ANTONIO
2017-01-01
Abstract
Information-centric networking (ICN) is a novel paradigm that aims at improving the performance of today's Internet by supporting caching and multicast content delivery on every network device. The main contribution of this paper is to propose a centralized strategy to stimulate third parties to jointly lease the unused bandwidth and storage available on wireless access points (APs) in an ICN. We formulate this problem as a combinatorial reverse auction run by a content provider (CP) willing to increase the number of users reached by its service. We show that the optimal allocation with partial coverage problem is NP-hard, provide greedy heuristics that guarantee the individual rationality and truthfulness properties, and compare their performance numerically. We evaluate the benefits of our proposed mechanisms in terms of the cost savings for the CP obtained by offloading its infrastructure through the caches and the reduced computational time to execute the allocation algorithms. We compare the results obtained in this centralized setting with those that can be observed when the mobile clients autonomously choose which AP they prefer to use, among those activated by the auction mechanism. We model this second scenario as a congestion game, showing that it exhibits the desired properties (i.e., existence and uniqueness of a Nash equilibrium) and by comparing its social welfare with the centralized case.File | Dimensione | Formato | |
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