Team dionysos

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Section: New Results

Network Economics

Participants : Hai Tran Hoang, Bruno Tuffin.

While pricing telecommunication networks was one of our main activities for the past few years, we are now dealing with the more general topic of network economics. We have tackled it from different sides: i) investigating how QoS or QoE can be related to users' willingness to pay, ii) pricing for telecommunication access, iii) investigating the consequences and equilibrium due competition among providers in different contexts, iv) studying the economic aspect of interdomain relationships, v) looking at the economics of applications, for example adword auctions for search engines, vi) investigating the economics of security in telecommunications.

On the first item, in [48] , [26] , we have studied how utility functions can be related to QoE recent research. Indeed, a logarithmic version of utility usually serves as the standard example due to its simplicity and mathematical tractability. We argue that there are much more (and better) reasons to consider logarithmic utilities as really paradigmatic, at least when it comes to characterizing user experience with specific telecommunication services. We justify this claim and demonstrate that, especially for Voice-over-IP and mobile broadband scenarios, there is increasing evidence that user experience and satisfaction follows logarithmic laws. Finally, we go even one step further and put these results into the broader context of the Weber-Fechner Law, a key principle in psychophysics describing the general relationship between the magnitude of a physical stimulus and its perceived intensity within the human sensory system.

We have continued to design efficient pricing for network access, based on congestion. As a general pricing principle, since there is usually no strict guarantee of QoS, we have designed in [30] a technique where a reimbursement is realized in case a QoS threshold is not met. We have compared it with the case without reimbursement and illustrated that it could drive to a higher revenue for a provider (because more users are likely to apply).

Our main activity has nevertheless been around competition among telecommunication providers [69] . Our main models have been reviewed in [64] , [65] . While most of the previous research was focusing on price optimization for a provider in a monopoly, we believe that the same results would not be valid in the current telecommunication world, with several providers in competition for customers. This additional component is therefore a key part of our work. For example, in [20] , we have studied the case of a WiFi operator against a WiMAX one, WiFi being operated in the smaller area. Using a simple model, we discuss how, for fixed prices, (elastic) demand is split among providers, and then characterize the Nash equilibria for the price war. We derive the conditions on provider capacities and coverage areas under which providers share demand on the common area. Similarly, we have studied in [43] , [21] another level of game on top of the price war: providers have indeed the possibility to choose which technologies to implement, depending on the infrastructure and licence (if any) costs, anticipating what would be the resulting price war outcome and revenue for given profiles of sets of technologies. This type of study may help a regulator to decide a licence cost (for instance the last 3G licence cost) in order to drive the resulting Nash equilibrium to a better point in terms of social or user welfare.

Another important activity is around interdomain issues, a network like the Internet being made of thousands of autonomous systems. Intermediate domains need some (economic in our case) incentives for forwarding the traffic of other domains. In [29] , we have described the problem, provided a state of the art and highlighted the difficulties that must be solved. In [53] , we have designed a decentralized algorithm based on double-sided auctions to allocate (and charge) the resource usage.

We are also starting to look at the application side. In order to make money many service providers base their revenue on advertisement. We focus in [42] on search engine providers for which specific slots in response to keywords are assigned to advertisers depending on the amount each advertiser agrees to pay if a user clicks on its link. While auctions with a deterministic allocation rule form the pricing mechanism applied by sponsored search engine and the one getting all the attention, we illustrate that an alternative pricing scheme, selecting randomly but with a prespecified distribution the advertisers to be displayed, can bring a larger revenue.

Finally, we have looked in [73] at the competition aspects linked to security. We have reviewed the interactions and strategies of attackers and defenders, and started to investigate the economics of security service providers, an issue on which we have worked this year.


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