In this paper, a new bandwidth allocation scheme is proposed based on the Mechanism Design (MD); MD is a branch of game theory that stimulates rational users to behave cooperatively for a global goal. The proposed scheme consists of bandwidth adaptation, call admission control and pricing computation algorithms to improve network performance. These algorithms are designed based on the adaptive online approach and work together to maximize bandwidth efficiency economically. A simulation shows that the proposed scheme can satisfy contradictory requirements and so provide well-balanced network performance.

The past decade has seen a surge of research activities in the fields of mobile computing and wireless communication. In particular, recent technological advances have made portable devices, such as PDA, laptops, and wireless modems to be very compact and affordable. To effectively operate portable devices, energy efficiency and Quality of Service (QoS) provisioning are two primary concerns. Dynamic Voltage Scaling (DVS) is a common method for energy conservation for portable devices. However, due to the amount of data that needs to be dynamically handled in varying time periods, it is difficult to apply conventional DVS techniques to QoS sensitive multimedia applications. In this paper, a new adaptive DVS algorithm is proposed for QoS assurance and energy efficiency. Based on the repeated learning model, the proposed algorithm dynamically schedules multimedia service requests to strike the appropriate performance balance between contradictory requirements. Experimental results clearly indicate the performance of the proposed algorithm over that of existing schemes.

In this paper, a new adaptive online price control scheme is formalized based on the Stackelberg game model. To provide the most desirable network performance, the proposed scheme consists of two different control mechanisms; user-based and operator-based mechanisms. By using the hierarchical interaction strategy, control decisions in each mechanism act cooperatively and collaborate with each other to satisfy conflicting performance criteria. With a simulation study, the proposed scheme can adaptively adjust the network price to approximate an optimized solution under widely diverse network situations.