In internet market, content providers (CPs) continue to play a primordial role in the process of accessing different types of data. Competition in this area is fierce; customers are looking for providers that offer them good content (credibility of content and quality of service) with a reasonable price. In this work, the authors analyze this competition between CPs and the economic influence of their strategies on the market. The authors formulate their problem as a non-cooperative game among multiple CPs for the same market. Through a detailed analysis, the researchers prove uniqueness of a pure Nash Equilibrium (NE). Furthermore, a fully distributed algorithm to converge on the NE point is presented. In order to quantify how efficient the NE point is, a detailed analysis of the Price of Anarchy (PoA) is adopted to ensure the performance of the system at equilibrium. Finally, an extensive numerical study is provided to describe the interactions between CPs and to point out the importance of quality of service (QoS) and credibility of content in the market.
To select or change a service provider, customers use the best compromise between price and quality of service (QoS). In this work, the authors formulate a game theoretic framework for the dynamical behaviors of Service Providers (SPs). They share the same market and are competing to attract more customers to gain more profit. Due to the divergence of SPs interests, it is believed that this situation is a non-cooperative game of price and QoS. The game converges to an equilibrium position known Nash Equilibrium. Using Genetic Algorithms (GAs), the authors find strategies that produce the most favorable profile for players. GAs are from optimization methods that have shown their great power in the learning area. Using these meta-heuristics, the authors find the price and QoS that maximize the profit for each SP and illustrate the corresponding strategy in Nash Equilibrium (NE). They also show the influence of some parameters of the problem on this equilibrium.
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