Wireless network, network design, safety-critical applications, quality of service
Recent advances in wireless communication technology have enabled large and small wireless nodes to communicate with each other even when they are not physically connected and have mobility. To take advantage of these advantages, wireless communication technologies applied in various fields, including safety-critical networks. In safety-critical environments, catastrophic consequences can be occurred including equipment damage and life-threatening, such as death or injury, when the system fails to operate normally. From the network perspective, problems can arise if they fail to meet the special requirements of safety-critical applications, thus the problems can be solved or prevented by guaranteeing quality of service (QoS). However, it is hard to meet the requirements with commercial networks, thus a suitable network design is need that can reflect the environment of the safety-critical network. This dissertation proposes a network design to guarantee service quality in three areas of safety-critical environment: 1) medical network, 2) vehicle network, and 3) tactical network. The problems of each environment and the proposed solution can be summarized as follows. In medical environments, various medical and non-medical data are transmitted through wireless channels, and the quality of service requirements and the importance of each traffic are different. Since important medical data are directly related to the patient's life, transmission opportunity should be differentially provided based on their priorities. Therefore, we propose an algorithm that adjusts channel access probability of low priority traffic to guarantee medical-grade quality of service and improve overall network performance. In addition, we performed admission control by deriving a model that can calculate real-time traffic capacity to avoid network saturation. For driving safety, all vehicles in the vehicle network periodically broadcast their state information such as location, speed, acceleration, brakes, etc., with beacon signals. However, in a real-time changing vehicle network environment, channel congestion can be occurred without proper action on the periodically broadcast beacons and it makes hard to receive beacons, which result in a potential threat to drivers such as traffic accidents. To provide safety in vehicle network environment with beacon reception guarantee, we propose a congestion control algorithm based on beacon inter-reception time. Simulation results obtained through OMNeT ++ show that the performance of the proposed algorithm outperforms the conventional schemes. As a representative safety-critical network, sensor information, command and control (C2) information, and situational awareness information transmitted through the tactical network can adversely affect to soldier survivability and military operational success rate if not delivered in time or lost. In addition, a tactical network have a poor environment due to lack of infrastructure, frequent node mobility, and crowded environment and require a reliable network system that can fulfill the requirements of tactical traffic. As a solution of such a tactical network, we propose a situational backoff reset algorithm based on channel preemption to prioritize tactical traffic in consideration of importance and urgency according to the mission and satisfy the requirements.
Table Of Contents
Abstract List of contents List of tables List of algorithm List of figures Ⅰ. INTRODUCTION 1.1 Background 1.1.1 IEEE 802.11 WLAN 1.1.2 IEEE 802.11e for QoS 1.1.1 IEEE 802.11p for V2X 1.2 Research problems and solution approaches 1.2.1 Healthcare applications 1.2.2 Vehicle-to-vehicle safety beacon in VANET 1.2.3 Tactical network traffic 1.3 Dissertation organization Ⅱ. ROBUST NETWORK DESIGN FOR HEALTHCARE 2.1 Introduction 2.2 Motivation 2.2.1 Background of IEEE 802.11e 2.2.2 Problem statement via preliminary simulation 2.3 Related work 2.4 Proposed algorithm 2.4.1 Adaptive AIFS scheme 2.4.2 Admission control with network capacity analysis 2.5 Performance evaluation 2.5.1 Simulation configuration and performance indices 2.5.2 Performance comparison 2.5.3 Effect of admission control 2.6 Conclusion Ⅲ. ROBUST NETWORK DESIGN FOR V2V COMMUNICATIONS 3.1 Introduction 3.2 Conventional Congestion Control Algorithms 3.3 Beacon Inter-Reception Time Ensured Adaptive Transmission (BEAT) 3.4 Performance of BEAT 3.4 Conclusions Ⅳ. ROBUST NETWORK DESIGN FOR TACTICAL APPLICATIONS 4.1 Introduction 4.2 Related work 4.3 Proposed algorithm 4.3.1 Situational backoff reset algorithm 4.3.2 Branch node based routing algorithm 4.4 Performance evaluation 4.5 Conclusion Ⅴ. CONCLUSION AND FUTURE WORK REFERENCES SUMMARY (Korean)