###### Abstract  
Rapidly increasing mobile data traffic have placed a significant burden on mobile Internet networks. Due to limited network capacity, a mobile network is congested when it handles too much data traffic simultaneously. In turn, some customers leave the network, which induces a revenue loss for the mobile service provider. To manage demand and maximize revenue, we propose a dynamic plan control method for the mobile service providers under connection-speed-restriction pricing. This method allows the mobile service provider to dynamically set the data plans' availability for potential customers' new subscriptions. With dynamic plan control, the service provider can adjust data network utilization and achieve high customer satisfaction and a low churn rate, which reflect high service supply chain performance. To find the optimal control policy, we transform the high-dimensional dynamic programming problem into an equivalent mixed integer linear programming problem. We find that dynamic plan control is an effective tool for managing demand and increasing revenue in the long term. Numerical evaluation with a large European mobile service provider further supports our conclusion. Furthermore, when network capacity or potential customers' willingness to join the network changes, the dynamic plan control method generates robust revenue for the service provider. demand management; dynamic plan control; mobile Internet network congestion; connection-speed-restriction pricing +
Footnote †: journal:  
network capacity is threatened by immense data traffic. Specifically, when a mobile network handles too much data traffic simultaneously, network congestion occurs [3,4]. Network congestion leads to customer dissatisfaction in this wireless service supply chain. For example, Internet web pages cannot be displayed quickly, and videos cannot be played smoothly. In turn, customer dissatisfaction drives a number of customers to leave the wireless network and then influences the service provider's revenue and the wireless service supply chain's performance. Therefore, mobile service providers should take the potential network congestion into consideration while maximizing revenue [5]. To this end, several demand management methods considering congestion have been proposed and studied, such as time-of-day pricing [6] and Wi-Fi offloading [7]. A detailed discussion of these demand management methods is included in the literature review. It is worth noting that the pricing scheme, where demand management methods apply, has evolved with the progression of wireless telecommunications technology. In the 1980s, the first-generation of wireless telecommunications technology (1G) was launched. Its connection speed was only 2.4 Kb/s (1 Gb = 1024 Mb; 1 Mb = 1024 Kb), and users could only make voice calls. At this time, flat-rate pricing dominated, which charges each user a fixed fee per session independently of the user's data usage. As wireless telecommunications technology upgraded to the second-generation (2G) and third-generation (3G), the connection speed could reach up to 10 Mb/s. Multimedia services emerged, such as the global positioning system (GPS) and video conferencing [8]. In the era of 2G and 3G, people used mobile Internet for different purposes, which made data usage vary greatly from one user to another. In 2011, the top 1% of mobile Internet users generated approximately 35% of the traffic over the world [9]. To better match a customer's cost with her/his data usage, many service providers moved away from the simple flat-rate pricing to metered pricing, which charges a user in proportion to her/his data usage. In contrast to flat-rate pricing, metered pricing is concerned about not only whether a customer uses the data service, but also how much data she/he consumes. Since the fourth-generation of wireless telecommunications technology (4G) was launched around 2009, connection speed has been greatly improved to 100 Mb/s.