Wan-Liang Wang

A fast CU depth decision mechanism for HEVC

HEVC requires a high computational complexity.The RD cost calculations outside the adaptive CU depth range are skipped.The RD cost calculations at the current CU depth are further skipped.The computational complexity of HEVC is reduced by about 16% on average.The proposed mechanism still maintains high video quality. In order to reduce the computational complexity of High Efficiency Video Coding (HEVC), a fast Coding Unit (CU) depth decision mechanism is proposed by utilizing the spacial correlations in the sequence frame. The proposed mechanism includes an adaptive CU depth range determination and a CU depth comparison algorithm. CU depth range is determined according to the distribution of CU depths in the same sequence. Thus, the Rate Distortion (RD) cost calculations at the CU depths outside of the range can be skipped. Furthermore, by comparing the depths of neighbor CUs with the current CU depth, the RD cost calculations at the current CU depth may be further skipped. Experimental results show that the proposed mechanism achieves a significant reduction of the computational complexity by comparing with the original HEVC, while still maintaining high video quality.

Ipb-frame adaptive mapping mechanism for video transmission over IEEE 802.11e WLANs

This paper proposed an IPB-frame Adaptive Mapping Mechanism (AMM) to improve the video transmission quality over IEEE 802.11e Wireless Local Area Networks (WLANs). Based on the frame structure of hierarchical coding technology, the probability of each frame allocated to the most appropriate Access Category (AC) was dynamically updated according to its importance and traffic load of each AC. Simulation results showed the superior performance of the proposed AMM by comparing with three other existing mechanisms in terms of three objective metrics.

Bio-inspired self-adaptive rate control for multi-priority data transmission over WLANs

In Wireless Local Area Networks (WLANs), the unpredictable injection of traffic load and the limitations of DCF based bandwidth allocation may result in network congestion. Also the Quality of Service (QoS) of data flows with different priorities may not be strictly guaranteed. In order to support service differentiation and guarantee QoS of data transmission over WLANs, based on the extended Lotka-Volterra (LV) biological competitive model, a bio-inspired self-adaptive rate control approach for multi-priority data transmission is proposed in this paper. This approach guides data flows to compete for network bandwidth in the way of a native ecosystem. As a result, both service differentiation and QoS can be guaranteed, simultaneously. In particular, it also achieves higher bandwidth utilization. Then the proposed approach is applied to four categories of data flows defined in the EDCA protocol, the allocated bandwidth of each category is optimized through model parameters (i.e. competition coefficients among categories) optimization. Extensive simulation studies have been conducted to show the superior performance of the proposed approach. Under the recommended model parameter values, the total bandwidth utilization is maximized up to 93% compared with 60-70% achieved by the EDCA protocol, whilst maintaining the service differentiation of multi-priority flows.

Video streaming transmission: performance modelling over wireless local area networks under saturation condition

Transmitting delay-sensitive video streaming over IEEE 802.11e wireless local area networks (WLANs) is becoming increasingly popular. However, the transmission of real-time video streaming is very challenging because of the time-varying wireless channels and video content characteristics. The authors propose an accurate model to assess the perceived quality of video streaming over WLANs with enhanced distributed coordination function (EDCF) mechanism. The analytical model considers not only the packet loss caused by wireless interference and channel fading, but also the effects of loss from channel access competition. Based on the Markov chain, the authors then present the discrete probability distribution of medium access control (MAC) layer packet service time by using the signal transfer function of the generalised state transition diagram. Moreover, the coding relation of lost video frames is also explored in the performance analysis of the proposed model. Simulations based on Network Simulator 2 (NS-2) are conducted to verify the performance of the analytical model. The results show that the proposed model provides superior accuracy for the perceived quality of MPEG-4 video streaming over IEEE 802.11e EDCF-based WLANs.

Scheme for preventing low-level denial-of-service attacks on wireless sensor network-based home automation systems

Remote access to home automation systems (HASs) through the Internet creates the potential for malicious users from across the Internet to attack the HASs. One such threat is that of a denial-of-service (DoS) attack that may disrupt communications or block remote access to the HASs. Existing approaches for DoS defence are generic and are not capable of filtering out all attack traffic, so a small amount of attack traffic reaches an HAS. This small level of attack traffic poses a significant threat to the HAS that are increasingly comprised of resource-limited wireless sensor networks (WSNs). This study proposes implements and evaluates a novel defence strategy designed to work alongside existing approaches for DoS defence to overcome the aforementioned shortcomings. The proposed defence strategy consists of three entities, the virtual home, remote home server and DoS defence server. The experimental results show that the proposed strategy can filter low-level attack traffic and thereby protect low-resource networks, such as WSN-based HASs.

Joint Parameter Optimization for Perpetual Nanonetworks and Maximum Network Capacity

One of the major bottlenecks in nanonetworks is the very limited energy that can be accessed by nanodevices. To achieve perpetual data transmission, it is required to investigate in-depth the relationship between energy harvesting and consumption, and the underlying constraints in nanonetworks. In this paper, the tradeoff between energy harvesting and consumption is analyzed by considering the peculiarities of THz communication. First, based on the TS-OOK scheme and constrained energy in nanodevices, the upper bound of the transmitted pulse amplitude is presented. Second, given the proposed mathematical expression of the signal-to-interference-noise ratio (SINR) in multi-user nanonetworks, the lower bound of pulse amplitude is presented to satisfy the required SINR threshold. Third, the minimum spreading factor is derived to guarantee the perpetual nanonetworks by considering the energy harvesting-consumption tradeoff. Finally, the maximization of network capacity is investigated by jointly optimizing the parameters of spreading factor, transmission distance, amplitude of the transmitted pulse, pulse probability, and node density for perpetual nanonetworks. The simulation results demonstrate short transmission distance and small spreading factor are recommended to improve the network capacity. Moreover, pulse probability, pulse amplitude, spreading factor, and node density are required to be comprehensively manipulated to achieve the maximum network capacity and perpetual communication.

A Novel Hybrid Slot Allocation Mechanism for 802.11e EDCA Protocol

This letter proposes a novel Hybrid Slot Allocation Mechanism (HSAM) to solve the high collision problem among four Access Categories (ACs) introduced by IEEE 802.11e EDCA protocol. In the HSAM, three time slots are assembled into a super-slot, each slot in the super slot is allocated to a particular AC according to its priority. The main idea of HSAM is to stagger the transmission slots of different ACs to reduce collisions, while maintaining the service differentiation. Extensive results from simulations have demonstrated good performance of HSAM comparing with EDCA protocol in terms of throughput, packet loss and MAC delay.

Incremental min-max projection analysis for classification

For data classification, the standard implementation of projection algorithms do not scale well with large dataset size. It makes the computation of large samples infeasible. In this paper, we utilize a block optimization strategy to propose a new locally discriminant projection algorithm termed min-max projection analysis (MMPA). The algorithm takes into account both intra-class and interclass geometries and also possesses the orthogonality property. Furthermore, an incremental MMPA is proposed to learn the local discriminant subspace with newly inserted data by employing the idea of singular value decomposition updating algorithm. Moreover, we extend MMPA to the semi-supervised case and nonlinear case, namely, semi-supervised MMPA and kernel MMPA. The experimental results on image database, hand written digit database, and face database demonstrate the effectiveness of those proposed algorithms.

PABM-EDCF: parameter adaptive bi-directional mapping mechanism for video transmission over WSNs

To support and keep high quality of video transmission over wireless sensor networks, this paper proposes a parameter adaptive bi-directional cross-layer mapping algorithm on the basis of the operation mechanism of IEEE 802.11e Enhanced Distributed Coordination Function (EDCF) supporting video service differentiation, named PABM-EDCF. Instead of classifying video data to a specific access category in 802.11e network, our proposed adaptive cross-layer scheme makes use of the hierarchy characteristic of video stream, dynamically maps video data to the appropriate access categories according to both the significance of the different video frames and the network traffic load. The significance passes from the application layer to the media access layer through a cross-layer architecture. In order to prevent the network congestion and keep the high transmission quality, the proposed algorithm adopts bi-directional floating mapping algorithm and congestion awareness mechanism based on the queue length and frame types. The mapping parameters are updated according to the network condition in time. Our simulation results indicate: the proposed method (a) improves the video transmission quality; (b) optimizes the management and utilization of queue resources; and (c) yields superior performance (under different loads) over 802.11e, static mapping and adaptive mapping schemes.

Pulse Position Coding for Information Capacity Promotion in Electromagnetic Nanonetworks

With the development of nanotechnology, Wireless Nano Sensor Networks (WNSN) have been envisioned for many unique applications. In order to optimize the data transmission in nanonetworks, the information rate of individual nanonode should be manipulated to maximize the network capacity. In this paper, information capacity is formulated as a function of the parameters of transmission distance and spreading factor in data transmission. The information interference is also presented and regulated by proposing a novel Pulse Position Coding (PPC) for nanonetworks. According to the experimental results, the achievable information capacity is improved significantly with the proposed coding mechanism, and the most appropriate values of spreading factor and transmission distance for nanonetworks are recommended. Moreover, low interference power is also achieved with PPC mechanism.