Optimization flow control—I: basic algorithm and convergence
IEEE/ACM Transactions on Networking (TON)
Congestion-dependent pricing of network services
IEEE/ACM Transactions on Networking (TON)
IEEE/ACM Transactions on Networking (TON)
Pricing WiFi at Starbucks: issues in online mechanism design
Proceedings of the 4th ACM conference on Electronic commerce
Commissioned Paper: An Overview of Pricing Models for Revenue Management
Manufacturing & Service Operations Management
Dynamic power allocation and routing for satellite and wireless networks with time varying channels
Dynamic power allocation and routing for satellite and wireless networks with time varying channels
Simplification of network dynamics in large systems
IEEE/ACM Transactions on Networking (TON)
Resource allocation and cross-layer control in wireless networks
Foundations and Trends® in Networking
WiFi access point pricing as a dynamic game
IEEE/ACM Transactions on Networking (TON)
Economics of network pricing with multiple ISPs
IEEE/ACM Transactions on Networking (TON)
On the Access Pricing and Network Scaling Issues of Wireless Mesh Networks
IEEE Transactions on Computers
Pricing Communication Services with Delay Guarantee
INFORMS Journal on Computing
Energy optimal control for time-varying wireless networks
IEEE Transactions on Information Theory
Dynamic power allocation and routing for time-varying wireless networks
IEEE Journal on Selected Areas in Communications
Pricing congestible network resources
IEEE Journal on Selected Areas in Communications
Utility optimal scheduling in processing networks
Performance Evaluation
CrowdMAC: a crowdsourcing system for mobile access
Proceedings of the 13th International Middleware Conference
LIFO-backpressure achieves near-optimal utility-delay tradeoff
IEEE/ACM Transactions on Networking (TON)
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This paper considers the problem of pricing and transmission scheduling for an access point (AP) in a wireless network, where the AP provides service to a set of mobile users. The goal of the AP is to maximize its own time-average profit. We first obtain the optimum time-average profit of the AP and prove the "Optimality of Two Prices" theorem. We then develop an online scheme that jointly solves the pricing and transmission scheduling problem in a dynamic environment. The scheme uses an admission price and a business decision as tools to regulate the incoming traffic and to maximize revenue. We show the scheme can achieve any average profit that is arbitrarily close to the optimum, with a tradeoff in average delay. This holds for general Markovian dynamics for channel and user state variation, and does not require a priori knowledge of the Markov model. The model and methodology developed in this paper are general and apply to other stochastic settings where a single party tries to maximize its time-average profit.