Biologically inspired self-adaptive multi-path routing in overlay networks
Communications of the ACM - Self managed systems
Cognitive Radio Technology (Communications Engineering)
Cognitive Radio Technology (Communications Engineering)
An overview of vertical handover decision strategies in heterogeneous wireless networks
Computer Communications
Threshold-Based Media Streaming Optimization for Heterogeneous Wireless Networks
IEEE Transactions on Mobile Computing
Cognitive radio: brain-empowered wireless communications
IEEE Journal on Selected Areas in Communications
Automated network selection in a heterogeneous wireless network environment
IEEE Network: The Magazine of Global Internetworking
Foreword: Special Issue on Multidisciplinary Emerging Networks and Systems
Journal of Computer and System Sciences
Journal of Systems Architecture: the EUROMICRO Journal
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In the forthcoming future, various means of wireless communication, such as cellular, Wi-Fi, WiMAX, and DSRC, will be available to mobile users and applications. With the development of wireless communication and mobile devices, more and more users and applications will be accommodated in mobile environment. Since mobile users and applications compete for the limited wireless resources whose communication quality dynamically change, we need an adaptive mechanism for mobile users and applications to share the available network resources while satisfying each application@?s QoS requirements. In this paper, we propose an adaptive resource allocation mechanism where each node autonomously determines wireless network resources to assign to each of networked applications running on it. For this purpose, we adopt an attractor composition model, which is based on an autonomous and adaptive behavior of biological systems. Through numerical analysis, we confirmed that our mechanism could adaptively and stably allocate wireless network resources to applications, while considering their QoS requirements and fairly sharing network resources with other nodes. It also is shown that our mechanism superiors to a mechanism where a node determines resource allocation by solving an optimization problem.