Sungwook Kim

An integrated adaptive bandwidth-management framework for QoS-sensitive multimedia cellular networks

Bandwidth is an extremely valuable and scarce resource in a wireless network. Therefore, efficient bandwidth management is necessary in order to provide high-quality service to users in a multimedia wireless/mobile network. In this paper, we propose new online bandwidth-management algorithms for bandwidth reservation, call admission, bandwidth migration, and call-preemption strategies. These techniques are combined in an integrated framework that is able to balance the traffic load among cells accommodating heterogeneous multimedia services while ensuring efficient bandwidth utilization. In addition, our online framework to adaptively control bandwidth is a cell-oriented approach that has low complexity, which makes it practical for real cellular networks. Simulation results indicate the superior performance of our bandwidth-management framework to strike the appropriate performance balance between contradictory quality-of-service requirements.

Adaptive load balancing with preemption for multimedia cellular networks

Efficient bandwidth management is necessary in order to provide high quality service to users in a multimedia wireless/mobile network. In this paper, we propose an on-line load balancing algorithm with preemption. This technique is able to balance the traffic load among cells accommodating heterogeneous multimedia services while ensuring efficient bandwidth utilization. The most important features of our algorithm are its adaptability, flexibility and responsiveness to current network conditions. In addition, our online scheme to control bandwidth adaptively is a cell-oriented approach. This approach has low complexity making it practical for real cellular networks. Simulation results indicate the superior performance of our algorithm.

Adaptive online power control scheme based on the evolutionary game theory

In view of the remarkable growth in the number of users and the limited network resource, an efficient network management is very important and has been an active area of research over the years. Especially, during wireless network operations, adaptive power control is an effective way to enhance the network performance. In this study, a new online power control scheme is proposed based on the evolutionary game theory. To converge a desirable network equilibrium, the proposed scheme adaptively adjusts a transmit power level in a distributed online manner. For the efficient network management, the online approach is dynamic and flexible that can adaptively respond to current network conditions. With a simulation study, the author demonstrates that the proposed scheme improves the network performance under widely diverse network environments.

Cellular network bandwidth management scheme by using Nash bargaining solution

Bandwidth is an extremely valuable and scarce resource in wireless networks. Therefore efficient bandwidth management plays an important role in determining network performance. Adaptive bandwidth reservation and borrowing algorithms are proposed for multimedia cellular networks here. Based on the well known game-theoretic concept of bargaining, wireless bandwidth is controlled as efficiently as possible while ensuring quality-of-service (QoS) guarantees for higher-priority traffic services. Under dynamic network condition changes, control decisions in the proposed algorithms are made adaptively to strike a well-balanced network performance. This dynamic online approach can provide adaptability, feasibility and efficiency for real-world network operations. With a simulation study, the proposed scheme approximates an optimised solution under widely diverse traffic load intensities.

An Ant-based Multipath Routing Algorithm for QoS Aware Mobile Ad-hoc Networks

In the wireless ad-hoc network management, Quality of Service (QoS) is an important issue. Along with the QoS ensuring, another desirable property is the network reliability. In data communications, multi-path routing strategy can cope with the problem of traffic overloads while balancing the network resource consumption. In this paper, we propose a new multipath routing algorithm for QoS-sensitive multimedia services. Based on the ant colony optimization technique, the proposed algorithm can establish effective multi-paths to enhance the network reliability. According to the load balancing strategy, data packets are adaptively distributed through the established paths while maintaining an acceptable level of QoS requirement. The most important feature of the proposed approach is its adaptability to current traffic conditions. Simulation results indicate the superior performance of the proposed algorithm, while other schemes cannot offer such an attractive performance balance.

Multi-leader multi-follower Stackelberg model for cognitive radio spectrum sharing scheme

Radio spectrum is one of the most scarce and variable resources for wireless communications. Therefore, the proliferation of devices and rapid growth of wireless services continue to strain the limited radio spectrum resource. Cognitive Radio (CR) paradigm is a promising technology to solve the problem of spectrum scarcity. In this paper, a new fair-efficient spectrum sharing scheme is proposed for cognitive radio networks. Based on the multiple-leader multiple-follower Stackelberg game model, the proposed scheme increases opportunistic use of the licensed radio spectrum. To adaptively use the spectrum resource, control decisions are coupled with one another; the result of the each users decisions is the input back to the other users decision process. Under widely diverse network environments, this adaptive feedback process approach can provide an effective way of finding a suitable solution. The simulation results demonstrate that the proposed scheme has excellent network performance, while other schemes cannot offer such an attractive performance balance.

Cognitive Radio Bandwidth Sharing Scheme Based on the Two-way Matching Game

Bandwidth is an extremely valuable and scarce resource, and may become congested to accommodate diverse services in wireless communications. To enhance the efficiency of bandwidth usage, the concept of cognitive radio has emerged as a new design paradigm. In this paper, a new bandwidth sharing algorithm is developed for cognitive radio networks. Under dynamically changing network environments, we formulate the bandwidth sharing problem as a two-way matching game model. In addition, modified game theory is adopted to reach a near Pareto optimal solution while avoiding bandwidth inefficiency. This approach can make the system more responsive to the current network situation. With a simulation study, it is demonstrated that the proposed scheme approximates an optimized solution under widely diverse traffic load intensities.

A repeated Bayesian auction game for cognitive radio spectrum sharing scheme

Due to the remarkable growth in the number of users and the limited spectrum resource, an efficient spectrum sharing scheme is very important and has been an active area of research over the years. Auction model is a rich mathematical tool and widely used to solve the spectrum allocation problem in cognitive radio networks. In this paper, a new spectrum sharing scheme is proposed based on the repeated auction model. In the proposed scheme, users adaptively decide their prices by using the Bayesian game approach and share spectrum bands based on the double auction protocol. According to a distributed control manner, the proposed scheme is dynamic and flexible that can adaptively respond to current system conditions. With a simulation study, it is confirmed that the effective solution of spectrum sharing is achieved under widely diverse system environments.

Biform game based cognitive radio scheme for smart grid communications

Smart grid is widely considered to be a next generation power grid, which will be integrated with information feedback communications. However, smart grid communication technologies are subject to inefficient spectrum allocation problems. Cognitive radio networks can solve the problem of spectrum scarcity by opening the under-utilized licensed bands to secondary users. In this paper, adaptive cognitive radio spectrum sensing and sharing algorithms are developed for smart grid environments. Simulation results are presented to demonstrate the effectiveness of the proposed scheme in comparison with other existing schemes.

Femtocell network power control scheme based on the weighted voting game

Future wireless networks are designed to cope with drastically increasing user demands. However, network resources reach the limits of their capacity to user requirements. Recently, femtocell networks have attracted much attention to enhance the efficiency of wireless resource usage. In this article, a new adaptive power control scheme is developed for the femtocell network system. By using the concept of the weighted voting game, the proposed scheme adaptively adjusts a transmit power level while ensuring relevant tradeoff between system efficiency and fairness. This power control paradigm can provide the ability to practically respond to current communication conditions and suitable for real network operations. Simulation results are presented to verify the effectiveness of the proposed voting game-based scheme in comparison with the existing schemes.