Chiapin Wang

A neural-network-based context-aware handoff algorithm for multimedia computing

The access of multimedia computing in wireless networks is concerned with the efficiency of handoff because of the irretrievable property of real-time data delivery. To lessen throughput degradation leading to media computing disruption perceived by users, this paper presents a link quality based handoff algorithm. Neural networks are used to learn the correlation between link quality estimator and the corresponding context metric indictors. Based on a pre-processed learning of link quality profile, neural networks make efficient handoff decisions with an evaluation of link quality instead of a comparison between relative signal strength. The experimental and simulation results show that the number of lost packets is minimized using the proposed algorithm without incurring unnecessary handoffs.

A Cross-Layer Adaptation Scheme for Improving IEEE 802.11e QoS by Learning

In this letter, we propose a cross-layer adaptation scheme which improves IEEE 802.11e quality of service (QoS) by online adapting multidimensional medium access control (MAC)-layer parameters depending on the application-layer QoS requirements and physical layer (PHY) channel conditions. Our solution is based on an optimization approach which utilizes neural networks (NNs) to learn the cross-layer function. Simulations results demonstrate the effectiveness of our adaptation scheme

Attack-Resistant Wireless Localization Using an Inclusive Disjunction Model

Wireless positioning is vulnerable to malicious attacks due to the nature of its open medium. This study proposes an attack-resistant fingerprinting localization algorithm based on a probabilistic inclusive disjunction model. This model allows an attacked observation to play a less significant role during the localization process, thus achieving more robust location estimations under security threats. This study included experiments conducted in an actual Wi-Fi network. Experimental results demonstrated that this approach apparently achieves more robust estimation than cluster-based, median-based, and sensor-selection methods under various attacks on RSS.

Delay-scheduler coupled throughput-fairness resource allocation algorithm in the long-term evolution wireless networks

This study proposes a delay-scheduler coupled throughput-fairness resource allocation algorithm for users of mixed traffic in a long-term evolution (LTE) wireless network. The design objective is to maintain quality of services (QoSs) for real-time (RT) traffic as well as to provide throughput fairness for non-RT (NRT) applications. Instead of classifying packets as RT and NRT types like other methods do, the authors’ scheme classifies packets as ‘urgent’ and ‘non-urgent’ for channel scheduling to optimise the tradeoff between RT, QoS and NRT throughput. The proposed scheme consists of two stages. In the first stage, the scheme determines the scheduling priorities of the ‘urgent’ packets to guarantee QoS for RT services. In the second stage, the authors’ approach aims at providing fairness of channel utilisation for the ‘non-urgent’ traffic flows including NRT flows and the RT flows which are below the delay bonds. From the simulation results, it is shown that the proposed algorithm can effectively improve the QoS for RT users and achieve throughput fairness for NRT users by comparison with other approaches in the downlink transmission of LTE wireless networks.

Performance analysis of a cross-layer handoff ordering scheme in wireless networks

In this paper we propose a cross-layer handoff ordering scheme. The frame success rate (FSR) is adopted as the basis of prioritization. Different quality of service (QoS) requirements of various applications would result in different FSR requirements. In order to indicate how critical a handoff request is, both the FSR requirement from the application layer and the FSR measurement from the medium access control layer are taken into consideration in the proposed scheme. The prioritization of handoff requests follows the most-critical-first policy. Performance analysis shows that the proposed scheme effectively reduces the forced termination probabilities. Under the same forced termination probability requirements, it could provide 1.95% to 11.13% more arrival calls compared to previous works.

A Neural Network Based Adaptive Algorithm for Multimedia Quality Fairness in WLAN Environments

This paper investigates multimedia quality fairness in wireless LAN environments where channel are error-prone due to mobility and fading. The experimental results show that using fixed MAC arguments for nodes in heterogeneous channel conditions leads to unequal throughput performance and that may incur the degradation of multimedia QoS. To overcome the unfairness problem for provisioning QoS, we propose a cross-layer adaptation scheme by on-line adapting the multidimensional MAC-layer backoff parameters depending on the application-layer QoS requirements and PHY-layer channel conditions. Our solution is based on an optimization approach which utilizes neural networks to learn the cross-layer function. Simulation results demonstrate that our adaptive scheme can tackle a variety of channel condition to provide fair throughput for nodes in heterogeneous channel conditions

Fairness analysis of throughput and delay in WLAN environments with channel diversities

The article investigates fairness in terms of throughput and packet delays among users with diverse channel conditions due to the mobility and fading effects in IEEE 802.11 WLAN (wireless local area networks) environments. From our analytical results, it is shown that 802.11 CSMA/CA can present fairness among hosts with identical link qualities regardless of equal or different data rates applied. Our analytical results further demonstrate that the presence of diverse channel conditions can pose significant unfairness on both throughput and packet delays even with a link adaptation mechanism since the MCSs (modulation and coding schemes) available are limited. The simulation results validate the accuracy of our analytical model.

On Throughput Performance of Channel Inequality in IEEE 802.11 WLANs

In this paper we investigate the throughput performance of IEEE 802.11 distributed coordination function (DCF) in the presence of physical-layer (PHY) inequality, i.e. varied channel conditions and/or unequal data rates determined by the Link Adaptation (LA) scheme. We present a theoretical model for DCF protocol with the LA scheme of auto rate fallback (ARF). The analysis results show that the system throughput of DCF-based WLANs is determined by the lowest data rate used with stations; throughput sharing among stations depends on the variation of link qualities rather than the difference of data rates. The simulation results validate the accuracy of our analytical model.

Utility-based admission control for mobile WiMAX networks

This paper presents a novel utility-based connection admission control (CAC) scheme for IEEE 802.16e broadband wireless access networks. We develop specific utility functions for real-time and non-real-time services coupled with a handover process. Given these utility functions we characterize the network utility with respect to the allocated bandwidth, and further propose a CAC algorithm which admits a connection that conducts to the greatest utility so as to maximize the total resource utilization. The simulation results demonstrate the effectiveness of the proposed CAC algorithm in terms of network utility.

Dynamic admission control and bandwidth reservation for IEEE 802.16e mobile WiMAX networks

The article presents a dynamic connection admission control (CAC) and bandwidth reservation (BR) scheme for IEEE 802.16e Broadband Wireless Access networks to simultaneously improve the utilization efficiency of network resources and guarantee QoS for admitted connections. The proposed CAC algorithm dynamically determines the admission criteria according to network loads and adopts an adaptive QoS strategy to improve the utilization efficiency of network resources. After new or handoff connections enter the networks based on current admission criteria, the proposed adaptive BR scheme adjusts the amount of reserved bandwidth for handoffs according to the arrival distributions of new and handoff connections in order to increase the admission opportunities of new connections and provide handoff QoS as well. We conduct simulations to compare the performance of our proposed CAC algorithm and BR scheme with that of other approaches. The results illustrate that our approach can effectively improve the network efficiency in terms of granting more connections by as large as about 22% in comparison with other schemes, and can also guarantee adaptive QoS for admitted new and handoff connections.