It is known that to pursuit end-to-end QoS of a class-based traffic flow is inefficient in Differentiated Service Networks. Therefore in this thesis, we propose an effective throughput-recovery mechanism to allow high-priority traffic flow to receive suitable resource allocation, and hence the end-to-end QoS is guaranteed. The proposed throughput-recovery mechanism assures a predefined minimum departure rate of low-latency EF dataflow. It consists of two parts. The first part is referred to as the feedback self-adaptive mechanism, where the egress node measures and monitors throughput of EF dataflow to decide whether to send the control messages to ingress node. When ingress node receives the control messages, it will reallocate the resources to improve EF throughput. The second part is referred to as the dynamic weight adjustment mechanism, which can prevent EF packets from dropping when congestion occurs in the core routers. For the purpose of demonstration, we build a mathematical model and use NS-2 simulator. We have proved our throughput-recovery mechanism is effective in improving the throughput of EF traffic flow. Finally, we modify the traditional WRR such that it can adjust weight based on the delay requirements.

Traditional TCP when applied in wireless networks may encounter two limitations. The first limitation is the higher bit error rate (BER) due to noise, fading, and multipath interference. Because traditional TCP is designed for wired and reliable networks, packet loss is mainly caused by network congestions. As a result, TCP may decrease congestion window inappropriately upon detecting a packet loss. The second limitation is about the packet scheduling, which mostly does not consider wireless characteristics. In this Thesis, we propose a local retransmission mechanism to improve TCP throughput for wireless networks with higher BER. In addition, we measure the packet loss ratio (PLR) to adjust the queue weight such that the available bandwidth for each queue can be changed accordingly. In our mechanism, the queue length is used to determine whether there is a congestion in wireless networks. When the queue length exceeds a threshold, it indicates that the wireless networks may have congestion very likely. We not only propose the dynamic weight-adjustment mechanism, but also solve the packet out-of-sequence problem, which results form when a TCP flow changes to a new queue. For the purpose of demonstration, we implement the proposed weight-adjustment mechanisms on the Linux platform. Through the measurements and discussions, we have shown that the proposed mechanisms can effectively improve the TCP throughput in wireless networks.

Sampling weights are recommended to be incorporated in surveys to compensate for the disproportionality of the sample with respect to the target population of interest. This report presents how to develop sampling weights for a population-based study where a sample was randomly selected and demonstrates the process of developing such sampling weights. We exemplify the development of sampling weights with a real research project entitled School Physical Activity and Nutrition (SPAN) project. In this report, we first introduce the probability-based survey and related key concepts, such as sampling design, sampling frame and sampling weights. Then we discuss the sampling design and the construction of the sampling frame for the SPAN project. We next demonstrate the method and the process of developing the sampling weights for the SPAN project. Lastly, we present the results with an example. / text