Yantai Shu

Multipath source routing in wireless ad hoc networks

We propose a new multipath routing protocol for ad hoc wireless networks-multipath source routing (MSR), which is based on DSR (dynamic source routing). MSR extends DSRs route discovery and route maintenance mechanism to deal with multipath routing. Based on the measurement of RTT, we propose a scheme to distribute load between multiple paths. The simulation results show that our approach improves the throughput of TCP and UDP and the packet delivery ratio, and reduces the end-to-end delay and the queue size, while adding little overhead. As a result, MSR decreases the network congestion quite well.

Adaptive multipath source routing in ad hoc networks

In this paper, we propose a new multipath routing protocol for ad hoc wireless networks-multipath source routing (MSR), which is an extension of DSR (dynamic source routing). Based on the measurement of RTT, we propose a scheme to distribute load among multiple paths. The simulation results show that our approach improves the packet delivery ratio and the throughput of TCP and UDP, and reduces the end-to-end delay and the average queue size, while adding little overhead. As a result, MSR decreases the network congestion and increases the path fault tolerance quite well.

Traffic prediction using FARIMA models

Previous traffic measurements have found the coexistence of both long-range and short-range dependence in network traffic. Therefore, models are required to predict traffic that has both long-range and short-range dependence. This paper provides a procedure to model and predict traffic using FARIMA (p,d,q) models. Our experiments illustrate that the FARIMA model is a good model and is capable of capturing the property of actual traffic. We provide guidelines to simplify the FARIMA model fitting procedure and thus to reduce the time of traffic modeling and prediction.

Study on network traffic prediction techniques

We briefly describe a number of traffic predictors (such as ARIMA, FARIMA, ANN and wavelet-based predictors) and analyze their computational complexity. We compare their performance with MSE, NMSE and computational complexity by simulating the predictors on four wireless network traffic traces and decide the most suitable network traffic predictor based on acceptable performance and accuracy.

Wireless Traffic Modeling and Prediction Using Seasonal ARIMA Models

Seasonal ARIMA model is a good traffic model capable of capturing the behavior of a network traffic stream. In this paper, we give a general expression of seasonal ARIMA models with two periodicities and provide procedures to model and to predict traffic using seasonal ARIMA models. The experiments conducted in our feasibility study showed that seasonal ARIMA models can be used to model and predict actual wireless traffic such as GSM traffic in China.

Traffic modeling based on FARIMA models

We provide a procedure to fit a FARIMA(p,d,q) (fractional autoregressive integrated moving average) model to the actual traffic trace, as well as a method to generate a FARIMA process with given parameters. We show how to model the traffic by fitting FARIMA models to four measured traces. Our experiments illustrate that the FARIMA model is a good traffic model and is capable of capturing the property of real traffic with long-range and short-range dependent behavior. Unlike previous work on FARIMA models, we deduce some guidelines to reduce the complexity of fitting the FARIMA model which would allow us to reduce the computational time of fitting.

TCP Unfairness in ad hoc wireless networks and a neighborhood RED solution

Significant TCP unfairness in ad hoc wireless networks has been reported during the past several years. This unfairness results from the nature of the shared wireless medium and location dependency. If we view a node and its interfering nodes to form a “neighborhood”, the aggregate of local queues at these nodes represents the distributed queue for this neighborhood. However, this queue is not a FIFO queue. Flows sharing the queue have different, dynamically changing priorities determined by the topology and traffic patterns. Thus, they get different feedback in terms of packet loss rate and packet delay when congestion occurs. In wired networks, the Randomly Early Detection (RED) scheme was found to improve TCP fairness. In this paper, we show that the RED scheme does not work when running on individual queues in wireless nodes. We then propose a Neighborhood RED (NRED) scheme, which extends the RED concept to the distributed neighborhood queue. Simulation studies confirm that the NRED scheme can improve TCP unfairness substantially in ad hoc networks. Moreover, the NRED scheme acts at the network level, without MAC protocol modifications. This considerably simplifies its deployment.

Improving source routing reliability in mobile ad hoc networks

In this paper, we propose a novel on-demand routing protocol called backup source routing (BSR) to establish and maintain backup routes that can be utilized after the primary path breaks. The key advantage of BSR is the reduction of the frequency of route discovery flooding, which is recognized as a major overhead in on-demand protocols. We define a new routing metric, called the route reliability, and use it to provide the basis for the backup path selection. We use a heuristic cost function to develop an analytical model and an approximation method to measure this metric. Various algorithms for our BSR protocol in the route discovery phase and route maintenance phase have been designed based on this cost function. Extensive simulations demonstrated that our routing strategy has two interesting features: 1) in less stressful situations of lower mobility, BSR has similar performance to DSR, 2) in more challenging situations of high mobility, BSR can improve the performance significantly.

Delay analysis of the IEEE 802.11 DCF

With the rising popularity of delay-sensitive real-time multimedia applications (video, voice, data) in wireless local area networks (WLANs), it is becoming important to study the delay performance of WLANs. When the medium access control (MAC) protocol is taken into consideration, the access contention delay is a key problem. In this paper, based on a Markov model, we analyze delay performance of the IEEE 802.11 distributed coordination function (DCF). In addition, through extensive simulations, we calculate the delay performance of both basic access and RTS/CTS access mechanism of the 802.11 protocol.

SVM-Based Models for Predicting WLAN Traffic

A novel type of learning machine called support vector machine (SVM) has been receiving increasing interests in the areas ranging from its original application in pattern recognition to other applications such as regression estimation due to its remarkable generalization performance. In this paper, we employ the SVM to forecast traffic in WLANs. We study the issues of one-step-ahead prediction and multi-step-ahead prediction without any assumption on the statistical property of actual WLAN traffic. We also evaluate the performance of different prediction models using four real WLAN traffic traces. The simulation results will show that among these methods, SVM outperforms other prediction models in WLAN traffic forecasting for both one-step-ahead and multi-step-ahead prediction.