Abstract

With the deregulation of telecommunication industry and the fast development of broadband wireless technologies, i.e., Wireless Mesh Network (WMN), WiFi (802.11g) and WiMAX (802.16), it can be imagined that in the future users can access Internet or other wireless services, e.g., telephony, through diverse wireless service providers (WSPs) and technologies. In this complex networking landscape, moving decision-making from access points to users is a path to achieving system scalability (Zemlianov & de Veciana, 2005). Thus, for users, it is increasingly the case that they have more freedom to choose among several WSPs who provide wireless services instead of being contractually tied to a single WSP. For example, a user wishing to access the Internet via a WiFi hotspot or access point (AP) may find him in a zone covered by several wireless access providers, or he may choose among different transmission platforms: WiFi, WiMAX, 3G, and so on. In such a market, in which multiple WSPs compete for users who are priceand congestion-sensitive, it is important to investigate the economic issues that arise due to the presence of multiple competing service providers. In such a competitive environment, all players are self-interested in a sense that their actions or reactions in response to others’ actions only focus on maximizing their own payoffs. From a WSP’s point of view, it has to compete for users with other WSPs while maximizing its profit. From a user’s point of view, he aims to maximize his compensated utility by choosing a WSP offering the best trade-off between quality of service (QoS) and price. Our primary goal is to understand how each WSP sets its price in the presence of price-sensitive and congestion-sensitive users and other competing WSPs to maximize its own profit. Note that we focus on the price setting problem among multiple WSPs instead of price discrimination among users. Thus we simply assume that the users are homogeneous in utility functions and willingness to pay. According to the current design of WMN architectures, a user’s requests will be routed to one AP or base station (BS) (in the IEEE802.16 standards APs of the IEEE 802.11 are called base stations) automatically so that the data flows generated by the user’s requests can take the most appropriate route in terms minimum hop count or other QoS metrics (i.e., bandwidth, end-to-end delay, and so on). However, from the user’s point of view, besides QoS, the price is also an important consideration when the user selects an AP or BS for wireless service delivery. It is generally accepted that the current wireless data network models are flawed in the sense that they fail to capture (Das et al., 2004): 12

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