Yikun Wang

Bio: Yikun Wang is an academic researcher from University of Ottawa. The author has contributed to research in topics: Handover & IEEE 802.11r-2008. The author has an hindex of 2, co-authored 2 publications receiving 37 citations.

Design of a Fast Location-Based Handoff Scheme for IEEE 802.11 Vehicular Networks

Abstract: IEEE 802.11 is an economical and efficient standard that has been applied to vehicular networks. However, the long handoff latency of the standard handoff scheme for IEEE 802.11 has become an important issue for seamless roaming in vehicular environments, because more handoffs may be triggered due to the higher mobility of vehicles. This paper presents a new and fast location-based handoff scheme particularly designed for vehicular environments. With the position and movement direction of a vehicle and the location information of the surrounding access points (APs), our protocol is able to accurately predict several APs that the vehicle may possibly visit in the future and to assign these APs different priority levels. APs on higher priority levels will be scanned first. A blacklist scheme is also used to exclude those APs that showed no response to the scanning during previous handoffs. Thus, time spent on scanning APs is supposed to be significantly reduced. The simulation results show that the proposed scheme attains not only a lower prediction error rate but also lower link layer handoff latency and that it has a smaller influence on jitter and throughput. Moreover, these results show that the proposed scheme has a smaller total number of handoffs than other handoff schemes.

A fast location-based handoff scheme for vehicular networks

Abstract: IEEE 802.11 is an economical and efficient standard that has been applied to vehicular networks. The long handoff latency of the traditional handoff scheme for IEEE 802.11, however, becomes an important issue for seamless connections in vehicular environments, as more handoffs may be triggered due to higher mobility of vehicles. This paper presents a new fast location-based handoff scheme particularly designed for vehicular networks. With the position and direction of a vehicle and locations of its surrounding access points (APs), our algorithm can accurately predict the next AP that the vehicle may visit. Time spent on scanning APs in handoff procedures is therefore significantly saved. The AP selection scheme can also reduce the total number of handoffs by selecting APs on the vehicle's advancing path. Finally, simulation results demonstrate that the proposed scheme attains low prediction error rates, low layer-2 handoff latency and the reduced number of unnecessary handoffs.

Emergency medical service planning considering dynamic and stochastic demands of infected and non-infected patients during epidemics

Abstract: During a large-scale epidemic, a local healthcare system can be overwhelmed by a large number of infected and non-infected patients. To serve the infected and non-infected patients well with limited medical resources, effective emergency medical service planning should be conducted before the epidemic. In this study, we propose a two-stage stochastic programming model, which integrally deploys various types of emergency healthcare facilities before an epidemic and serves infected and non-infected patients dynamically at the deployed healthcare facilities during the epidemic. With the service equity of infected patients and various practical requirements of emergency medical services being explicitly considered, our model minimizes a weighted sum of the expected operation cost and the equity cost. We develop two comparison models and conduct a case study on Chengdu, a Chinese city influenced by the COVID-19 epidemic, to show the effectiveness and benefits of our proposed model. Sensitivity analyses are conducted to generate managerial insights and suggestions. Our study not only extends the existing emergency supply planning models but also can facilitate better practices of emergency medical service planning for large-scale epidemics.

A Novel Predictive Handover Protocol for Mobile IP in Vehicular Networks

Abstract: Vehicular networking is an emerging technology that offers the potential of providing a variety of new services. However, extending vehicular networks to include internet protocol (IP) connections is still problematic, due in part to the incompatibility of mobile IP handovers with the increased mobility of vehicles. The handover process, consisting of discovery, registration, and packet forwarding, has a large overhead and disrupts connectivity. With increased handover frequency and smaller access-point (AP) dwell times in vehicular networks, the handover causes a large degradation in performance. This paper proposes a predictive handover protocol, using a combination of a Kalman filter (KF) and an online hidden Markov model (HMM), to minimize the effects of prediction errors and to capitalize on advanced handover registration. Extensive simulated experiments were carried out in the network simulator ns-2 to study the performance of the proposed protocol within a variety of traffic and network topology scenarios. Results show a significant improvement to both prediction accuracy and network performance when compared with recent proposed approaches.

Design of a Fast Location-Based Handoff Scheme for IEEE 802.11 Vehicular Networks

Abstract: IEEE 802.11 is an economical and efficient standard that has been applied to vehicular networks. However, the long handoff latency of the standard handoff scheme for IEEE 802.11 has become an important issue for seamless roaming in vehicular environments, because more handoffs may be triggered due to the higher mobility of vehicles. This paper presents a new and fast location-based handoff scheme particularly designed for vehicular environments. With the position and movement direction of a vehicle and the location information of the surrounding access points (APs), our protocol is able to accurately predict several APs that the vehicle may possibly visit in the future and to assign these APs different priority levels. APs on higher priority levels will be scanned first. A blacklist scheme is also used to exclude those APs that showed no response to the scanning during previous handoffs. Thus, time spent on scanning APs is supposed to be significantly reduced. The simulation results show that the proposed scheme attains not only a lower prediction error rate but also lower link layer handoff latency and that it has a smaller influence on jitter and throughput. Moreover, these results show that the proposed scheme has a smaller total number of handoffs than other handoff schemes.

Reliable Emergency Message Dissemination Scheme for Urban Vehicular Networks

Abstract: Vehicular safety applications based on DSRC/802.11p have strict reliability requirement (greater than 0.99). However, it is difficult to achieve high reliability in wireless medium as the transmission is vulnerable to various wave propagation issues. To the best of our knowledge, none of the existing emergency message dissemination schemes in the literature, achieves a predefined reliability in lossy channel. In this paper, we propose a novel scheme, called reliable emergency message dissemination scheme (REMD), which achieves a predefined reliability for message dissemination while satisfying delay requirements, for various channel conditions. We aim to guarantee very high reliability (e.g., 99%) in each hop, with low control overhead while keeping low end-to-end latency for time-critical applications. We employ zero-correlated unipolar orthogonal codes to combat hidden terminal problem. We exploit periodic beacons, to accurately estimate reception quality of 802.11p wireless link in each cell; then, we use this information to determine the optimal number of broadcast repetitions in each hop. In addition, to ensure reliability in multi-hop, we utilize cooperative communication. The simulation results show that REMD outperforms the existing well-known schemes in the literature. Furthermore, REMD satisfies latency requirements for time-critical vehicular applications and has less network overhead than the existing schemes.

Smart Handoff Technique for Internet of Vehicles Communication using Dynamic Edge-Backup Node

Abstract: A vehicular adhoc network (VANET) recently emerged in the the Internet of Vehicles (IoV); it involves the computational processing of moving vehicles. Nowadays, IoV has turned into an interesting field of research as vehicles can be equipped with processors, sensors, and communication devices. IoV gives rise to handoff, which involves changing the connection points during the online communication session. This presents a major challenge for which many standardized solutions are recommended. Although there are various proposed techniques and methods to support seamless handover procedure in IoV, there are still some open research issues, such as unavoidable packet loss rate and latency. On the other hand, the emerged concept of edge mobile computing has gained crucial attention by researchers that could help in reducing computational complexities and decreasing communication delay. Hence, this paper specifically studies the handoff challenges in cluster based handoff using new concept of dynamic edge-backup node. The outcomes are evaluated and contrasted with the network mobility method, our proposed technique, and other cluster-based technologies. The results show that coherence in communication during the handoff method can be upgraded, enhanced, and improved utilizing the proposed technique.

Traffic big data analysis supporting vehicular network access recommendation

Abstract: With the explosive growth of Internet of Vehicles (IoV), it is undoubted that vehicular demands for real-time Internet access would get a surge in the near future. Therefore, it is foreseeable that the cars within the IoV will generate enormous data. On the one hand, the huge volume of data mean we could get much information (e.g., vehicle's condition and real-time traffic distribution) through the big data analysis. On the other hand, the huge volume of data will overload the cellular network since the cellular infrastructure still represents the dominant access methods for ubiquitous connections. The vehicular ad hoc network (VANET) offloading is a promising solution to alleviate the conflict between the limited capacity of cellular network and big data collection. In a vehicular heterogeneous network formed by cellular network and VANET, an efficient network selection is crucial to ensure vehicles' quality of service. To address this issue, we develop an intelligent network recommendation system supported by traffic big data analysis. Firstly, the traffic model for network recommendation is built through big data analysis. Secondly, vehicles are recommended to access an appropriate network by employing the analytic framework which takes traffic status, user preferences, service applications and network conditions into account. Furthermore an Android application is developed, which enables individual vehicle to access network automatically based on the access recommender. Finally, extensive simulation results show that our proposal can effectively select the optimum network for vehicles, and network resource is fully utilized at the same time.