SDP research papers can be roughly categorized by the different types of pricing that they investigate. We consider 15 such topics here. If you know of a paper we missed, let us know.
Pricing of heterogeneous networks (12)
While most pricing plans for mobile data focus on pricing only data in cellular networks, some service providers also offer other supplementary networks, e.g., WiFi hotspots or femtocells. Service providers can relieve congestion on cellular networks by offering bundled access plans for cellular and supplementary networks and offloading traffic onto these networks. Some papers study the joint problem of pricing two network types, while others consider only the WiFi or femotcell pricing problem, supposing that the WiFi provider is a different entity from the cellular service provider. Still other papers allow users to act as mobile hotspots for other users, creating a “crowdsourced” mobile network.
Tuan LeAnh, Nguyen H. Tran, S. M. Ahsan Kazmi, Thant Zin Oo, and Choong Seon Hong Proceedings of ICOIN, 2015
In this paper, we study cooperation among mobile users for uplink in two-tiers heterogeneous wireless networks. In our cooperative model, a macrocell user equipment can relay its data via a femtocell user equipment when it cannot connect to its macro base station or any femtocell base stations directly. In this scenario, the macrocell user equipment tries to find the best relay user in a set of candidate relay femtocell user equipments to maximize its utility function. Additionally, the candidate relay femtocell user equipments give a pricing-based strategy per each power unit to the macrocell user equipment along with power level at relay femtocell user equipments which would be used for relaying data in order to maximize both the relay femto and macrocell user equipment's utility function. In static network environment, this problem is formulated as a Stackelberg game. Moreover, in stochastic network environment we find stochastic optimization in a long-term for both the utility functions by modeling the problem as a restless bandit problem. Simulation results illustrate the efficiency of our proposal.
N. Shetty, S. Parekh and J. Walrand Proceedings of IEEE GLOBECOM, 2009
Femtocells or home base stations are a proposed solution to the problem of degraded indoor service from the macrocell base station in future 4G data networks. In this paper, we study user incentives for the adoption of femtocells and their resulting impact on network operator revenues. We model a monopolist network operator who offers the option of macrocell access or macro+femtocell access to a population of users who possess linear valuations for the data throughput. We compare the revenues from two possible spectrum schemes for femtocell deployment; the split spectrum scheme, where femtocells and macrocells operate on different frequencies and do not interfere, and, the common spectrum scheme, where they operate on the same frequencies (partially or fully) and interfere. Our results suggest that the optimal pricing scheme always charges a higher price for the femtocell service, i.e., the operator does not offer any subsidies for adoption. Yet, at the optimal prices, almost full adoption of femtocells is achieved even for many common spectrum schemes that degrade macrocell capacity. Femtocell deployments provide huge revenue gains when macrocell capacities are low. However, in this range, even common spectrum schemes that heavily degrade the macrocell capacity perform comparably to the split spectrum scheme. Some common spectrum schemes with moderate macrocell degradation yield revenues comparable or higher than the split spectrum scheme at all levels of macrocell congestion.
S. Sen, Y. Jin, R. Guérin and K. Hosanagar IEEE/ACM Transactions on Networking, 18(6): 1793—1805, 2010
New network technologies constantly seek to displace incumbents. Their success depends on technological superiority, the size of the incumbent's installed base, users' adoption behaviors, and various other factors. The goal of this paper is to develop an understanding of competition between network technologies and identify the extent to which different factors, in particular converters (a.k.a. gateways), affect the outcome. Converters can help entrants overcome the influence of the incumbent's installed base by enabling cross-technology interoperability. However, they have development, deployment, and operations costs and can introduce performance degradations and functionality limitations, so that if, when, why, and how they help is often unclear. To this end, the paper proposes and solves a model for adoption of competing network technologies by individual users. The model incorporates a simple utility function that captures key aspects of users' adoption decisions. Its solution reveals a number of interesting and at times unexpected behaviors, including the possibility for converters to reduce overall market penetration of the technologies and to prevent convergence to a stable state, something that never arises in their absence. The findings were tested for robustness, e.g., different utility functions and adoption models, and found to remain valid across a broad range of scenarios.
C. Joe-Wong, S. Sen and S. Ha Proceedings of IEEE INFOCOM, 2013
To alleviate the congestion caused by rapid growth in demand for mobile data, wireless service providers (WSPs) have begun encouraging users to offload some of their traffic onto supplementary network technologies, e.g., offloading from 3G or 4G to WiFi or femtocells. With the growing popularity of such offerings, a deeper understanding of the underlying economic principles and their impact on technology adoption is necessary. To this end, we develop a model for user adoption of a base technology (e.g., 3G) and a bundle of the base plus a supplementary technology (e.g., 3G + WiFi). Users individually make their adoption decisions based on several factors, including the technologies’ intrinsic qualities, negative congestion externalities from other subscribers, and the flat access rates that a WSP charges. We then show how these user-level decisions translate into aggregate adoption dynamics and prove that these converge to a unique equilibrium for a given set of exogenously determined system parameters. We fully characterize these equilibria and study adoption behaviors of interest to a WSP. We then derive analytical expressions for the revenue-maximizing prices and optimal coverage factor for the supplementary technology and examine some resulting non-intuitive user adoption behaviors. Finally, we develop a mobile app to collect empirical 3G/WiFi usage data and numerically investigate the profit-maximizing adoption levels when a WSP accounts for its cost of deploying the supplemental technology and savings from offloading traffic onto this technology.
S. Ren, J. Park and M. van der Schaar IEEE/ACM Transactions on Networking, 21(1): 218—232, 2013
Focusing on a femtocell communications market, we study the entrant network service provider's (NSP's) long-term decision: whether to enter the market and which spectrum sharing technology to select to maximize its profit. This long-term decision is closely related to the entrant's pricing strategy and the users' aggregate demand, which we model as medium-term and short-term decisions, respectively. We consider two markets, one with no incumbent and the other with one incumbent. For both markets, we show the existence and uniqueness of an equilibrium point in the user subscription dynamics, and provide a sufficient condition for the convergence of the dynamics. For the market with no incumbent, we derive upper and lower bounds on the optimal price and market share that maximize the entrant's revenue, based on which the entrant selects an available technology to maximize its long-term profit. For the market with one incumbent, we model competition between the two NSPs as a non-cooperative game, in which the incumbent and the entrant choose their market shares independently, and provide a sufficient condition that guarantees the existence of at least one pure Nash equilibrium. Finally, we formalize the problem of entry and spectrum sharing scheme selection for the entrant and provide numerical results to complement our analysis.
J. Musacchio and J. Walrand IEEE/ACM Transactions on Networking, 14(2): 289-301, 2006
We study the economic interests of a wireless access point owner and his paying client, and model their interaction as a dynamic game. The key feature of this game is that the players have asymmetric information-the client knows more than the access provider. We find that if a client has a "web browser" utility function (a temporal utility function that grows linearly), it is a Nash equilibrium for the provider to charge the client a constant price per unit time. On the other hand, if the client has a "file transferor" utility function (a utility function that is a step function), the client would be unwilling to pay until the final time slot of the file transfer. We also study an expanded game where an access point sells to a reseller, which in turn sells to a mobile client and show that if the client has a web browser utility function, that constant price is a Nash equilibrium of the three player game. Finally, we study a two player game in which the access point does not know whether he faces a web browser or file transferor type client, and show conditions for which it is not a Nash equilibrium for the access point to maintain a constant price.
K. R. Lam, D. M. Chiu and J. C. S. Lui IEEE Transactions on Computing, 56(11): 140-146, 2007
Distributed wireless mesh network technology is ready for public deployment in the near future. However, without an incentive system, one should not assume that private self-interested wireless nodes would participate in such a public network and cooperate in the packet forwarding service. This paper studies the use of pricing as an incentive mechanism for stimulating participation and collaboration in public wireless mesh networks. Our focus is on the "economic behavior" of the network nodes-the pricing and purchasing strategies of the access point, wireless relaying nodes, and clients. We use a "game-theoretic approach" to analyze their interactions from one-hop to multihop networks and when the network has an unlimited or limited channel capacity. The important results that we show are that the access point and relaying wireless nodes will adopt a simple yet optimal fixed-rate pricing strategy in a multihop network with an unlimited capacity. However, the access price grows quickly with the hop distance between a client and the access point, which may limit the "scalability" of the wireless mesh network. In case where the network has limited capacity, the optimal strategy for the access point is to vary the access charge and even interrupt service to connecting clients. To this end, we focus on the access point adopting a non-self-enforcing but more practical "fixed-rate noninterrupted service" model and propose an algorithm based on the Markovian decision theory to devise the optimal pricing strategy. Results show that the scalability of a network with limited capacity is upper bounded by one with an unlimited capacity. We believe that this work will shed light on the deployment and pricing issues of distributed public wireless mesh networks.
L. Duan, J. Huang and B. Shou Proceedings of IEEE INFOCOM, 2013
This paper analyzes two pricing schemes commonly used in WiFi markets: flat-rate pricing and usage-based pricing. The flat-free pricing encourages users to achieve the maximum WiFi usage and targets at users with high valuations in mobile Internet access, whereas the usage-based pricing is flexible to attract more users - even those with low valuations. First, we show that for a local provider, the flat-rate pricing provides more revenue than the usage-based pricing, which is consistent with the common practice in today's local markets. Second, we study how Skype may work with many local WiFi providers to provide a global WiFi service. We formulate the interactions between Skype, local providers, and users as a two-stage dynamic game. In Stage I, Skype bargains with each local provider to determine the global Skype WiFi service price and revenue sharing agreement; in Stage II, local users and travelers decide whether and how to use local or Skype WiFi service. Our analysis discovers two key insights behind Skype's current choice of usage-based pricing for its global WiFi service: to avoid severe competition with local providers and attract travelers to the service. We further show that at the equilibrium, Skype needs to share the majority of his revenue with a local provider to compensate the local provider's revenue loss due to competition. When there are more travelers or fewer local users, the competition between Skype and a local provider becomes less severe, and Skype can give away less revenue and reduce its usage-based price to attract more users.
L. Gao, G. Iosifidis, J. Huang and L. Tassiulas Proceedings of the 2nd IEEE International Workshop on Smart Data Pricing (SDP), 2013
Mobile data offloading is a promising approach to alleviate network congestion and enhance quality of service (QoS) in mobile cellular networks. In this paper, we investigate the economics of mobile data offloading through third-party WiFi or femtocell access points (APs). Specifically, we consider a market-based data offloading solution, where macrocellular base stations (BSs) pay APs for offloading traffic. The key questions arising in such a marketplace are following: (i) how much traffic should each AP offload for each BS? and (ii) what is the corresponding payment of each BS to each AP? We answer these questions by using the non-cooperative game theory. In particular, we define a multi-leader multi-follower data offloading game (DOFF), where BSs (leaders) propose market prices, and accordingly APs (followers) determine the traffic volumes they are willing to offload. We characterize the subgame perfect equilibrium (SPE) of this game, and further compare the SPE with two other classic market outcomes: (i) the market balance (MB) in a perfect competition market (i.e., without price participation), and (ii) the monopoly outcome (MO) in a monopoly market (i.e., without price competition). Our results analytically show that (i) the price participation (of BSs) will drive market prices down, compared to those under the MB outcome, and (ii) the price competition (among BSs) will drive market prices up, compared to those under the MO outcome.
J. Lee, Y. Yi, S. Chong and Y. Jin IEEE Transactions on Wireless Communications, 13(3): 1540—1554, 2014
Cellular networks are facing severe traffic overloads due to the proliferation of smart handheld devices and traffic-hungry applications. A cost-effective and practical solution is to offload cellular data through WiFi. Recent theoretical and experimental studies show that a scheme, referred to as delayed WiFi offloading, can significantly save the cellular capacity by delaying users' data and exploiting mobility and thus increasing chance of meeting WiFi APs (Access Points). Despite a huge potential of WiFi offloading in alleviating mobile data explosion, its success largely depends on the economic incentives provided to users and operators to deploy and use delayed offloading. In this paper, we study how much economic benefits can be generated due to delayed WiFi offloading, by modeling a market based on a two-stage sequential game between a monopoly provider and users. We also provide extensive numerical results computed using a set of parameters from the real traces and Cisco's projection of traffic statistics in year 2015. In both analytical and numerical results, we model a variety of practical scenarios and control knobs in terms of traffic demand and willingness to pay of users, spatio-temporal dependence of pricing and traffic, and diverse pricing and delay tolerance. We demonstrate that delayed WiFi offloading has considerable economic benefits, where the increase ranges from 21% to 152% in the provider's revenue, and from 73% to 319% in the users' surplus, compared to on-the-spot WiFi offloading.
L. Gao, G. Iosifidis, J. Huang and L. Tassiulas Proceedings of IEEE INFOCOM, 2014
User-provided connectivity (UPC) is a promising paradigm to achieve a low-cost ubiquitous connectivity. In this paper, we study a network-assisted UPC service model, where a mobile virtual network operator (MVNO) enables its subscribers to operate as mobile WiFi hotspots (hosts) and provide Internet connectivity for others. A unique aspect of this service model is that the MVNO offers some free data quota to hosts as reimbursements (incentives) for connectivity sharing. This reimbursing scheme, together with a usage-based pricing, constitute a revolutionary hybrid data pricing-reimbursing scheme, which has not been considered before. We analyze the different impacts of data price and reimbursement on the host's connectivity sharing decision systematically. Based on this analysis, we further derive the optimal hybrid pricing-reimbursing policy that maximizes the MVNO's revenue. Our numerical result indicates that by using the proposed hybrid pricing policy, the MVNO can increase its revenue by 20% to 135% under an elastic client demand, and by 20% to 550% under an inelastic client demand, comparing to those achieved under a pricing-only policy.
M. H. Afrasiabi and R. Guérin Proceedings of IEEE INFOCOM, 2012
User-provided connectivity (UPC) services offer a possible alternative, or complement, to existing infrastructure-based connectivity. A user allows other users to occasionally connect through its “home base” in exchange for reciprocation, or possibly compensation. This service model exhibits strong positive and negative externalities. A large user base makes the service more attractive, as it offers more connectivity options to roaming users, but it also implies a greater volume of (roaming) traffic passing through a user's home base, which can increase congestion. These interactions make it difficult to predict the eventual success of such a service offering, and in particular how to effectively price it. This paper investigates a two-price policy where the first price is an introductory price that expires once service adoption reaches a certain level. The paper uses a simplified analytical model to investigate pricing strategies under this policy, and their sensitivity to changes in system parameters. The insight and practical guidelines this yields are validated numerically under more realistic conditions.
Two-sided pricing (15)
QoS-aware pricing (14)