Der-Jiunn Deng

Contention window optimization for ieee 802.11 DCF access control

According to the latest version of the IEEE 802.11 standard, the backoff parameters of its collision avoidance mechanism are far from optimal, especially in a heavy load or error-prone WLAN environment. This strategy has a high collision probability and channel utilization is degraded in bursty arrivals or congested scenarios. Besides, the standard backoff mechanism may treat noise corruption as packet collisions. In this paper, we identify the relationship between backoff parameters, contention level, and channel BER in order to propose a simple, but yet well-performing distributed algorithm that allows a station to dynamically adjust its contention window size based on turn-around-time measurement of channel status. In addition to theoretical analysis, simulations are conducted to evaluate its performance. The proposed scheme works very well in providing a substantial performance improvement in heavy loaded and error-prone WLAN environments.

IEEE 802.11ax: Next generation wireless local area networks

Recently, IEEE 802 started a task group to investigate and deliver next generation WLAN technologies for the scenarios of dense networks with a large number of stations and access point. The proposal is specified as the IEEE 802.11ax amendment. Due to the significant network capacity increase achieved by 802.11ax, the term high-efficiency WLAN (HEW) is also used in reference to this new amendment. This paper summarizes the IEEE 802.11ax standardization activities in progress and presents an overview of the most important features proposed in the 802.11ax amendment. Expected features and challenges for 802.11ax in the design of physical layer (PHY) and media access control sub-layer (MAC), toward a new era of wireless LANs, are also discussed.

Sub-packet forward error correction mechanism for video streaming over wireless networks

Traditional Forward Error Correction (FEC) mechanisms can be divided into Packet level FEC (PFEC) mechanisms and Byte level FEC (BFEC) mechanisms. The PFEC mechanism of recovering from errors in a source packet requires an entire FEC redundant packet even though the error involves a few bit errors. The recovery capability of the BFEC mechanism is only half of the FEC redundancy. Accordingly, an adaptive Sub-Packet FEC (SPFEC) mechanism is proposed in this paper to improve the quality of video streaming data over wireless networks, simultaneously enhancing the recovery performance and reducing the end-to-end delay jitter. The SPFEC mechanism divides a packet into n sub-packets by means of the concept of a virtual packet. The SPFEC mechanism uses a checksum in each sub-packet to identify the position of the error sub-packet. Simulation experiments show the adaptive SPFEC mechanism achieves high recovery performance and low end-to-end delay jitter. The SPFEC mechanism outperforms traditional FEC mechanism in terms of packet loss rate and video Peak Signal-to-Noise Ratio (PSNR). SPFEC offers an alternative for improved efficiency video streaming that will be of interest to the designers of the next generation environments.

Quality-aware bandwidth allocation for scalable on-demand streaming in wireless networks

In this paper, we propose a scalable transport scheme for delivering on-demand video streams over broadband wireless networks in next-generation network/IP multimedia subsystem (NGN/IMS) architecture. The proposed transport scheme makes use of fine-granular-scalability (FGS) encoded videos to accommodate high bandwidth variation of wireless networks. We formulate the bandwidth allocation to FGS-encoded streams as a resource allocation problem and develop a quality-aware bandwidth allocation scheme, called QABA. With QABA, the proposed transport scheme can dynamically adjust the bit rate allocated to different streams to maximize the overall perceptual quality when available network bandwidth varies with time. QABA is theoretically proven to be able to find the optimal bandwidth allocation for all on-demand streams. To validate the effectiveness of QABA, extensive trace-based simulations are performed.

A Collision Alleviation Scheme for IEEE 802.11p VANETs

IEEE 802.11p protocol, also known as Wireless Access for the Vehicular Environment provides dedicated short range communication for future Vehicular Ad Hoc Networks (VANETs). According to the IEEE 802.11p standard, the highest priority traffic transmission often suffers from the consecutive collisions in bursty arrival or congested scenarios because of the naive pre-assumption of a low level of congestion in the system, and thus results in emergent messages delayed. In this paper, we propose a simple, but yet well performing collision alleviation scheme to alleviate intensive collisions between highest priority access categories which usually used to schedule emergency message since safety is the most critical and promising issue in VANET. In addition to theoretical analysis, simulations are conducted to evaluate its performance. The simulation results show that the proposed scheme can not only increase the achievable channel throughput of the legacy protocol at most 15%, but also reduce the average packet access delay of the legacy protocol at least 5% and the packet collision probability at most 60% in congested VANET environments.

Live Data Mining Concerning Social Networking Forensics Based on a Facebook Session Through Aggregation of Social Data

Social Networking Service (SNS) emerges to be one of the most promising directions of web applications regarding the next generation of Internet technology evolutions. Substantively, innumerable global on-line community members share common interests with each other via the User Generated Content (UGC) platforms. Facebook is one of them and it facilitates the social networking participants to deliver the digital contents to authorized consumers or specific groups. As cybercrimes mushroom in recent years, more and more digital crime investigations have strong relations to Facebook. Unarguably, Facebook has been exploited via global perpetrators. Consequently, we spotlight on live data acquisition within the RAM of the desktop PC with emphasis on some distinct strings that could be found in order to reconstruct the previous Facebook session, which plays an extremely precious role for the associate digital forensics investigators to incubate additional thoughtful decisions concerning the discovery of breadcrumb digital evidences in this unparalleled cybercrime incidents era.

A novel parallel algorithm for frequent pattern mining with privacy preserved in cloud computing environments

Parallel and distributed computing techniques have attracted extensive attentions on the ability to manage and compute the significant amount of data in the past decades. The difficulty of mining large database launched the research of designing parallel and distributed algorithms to solve the problem. In this paper, we propose a novel data mining algorithm, named Cloud-based Association Rule Mining (CARM), abbreviated as CARM, which is able to efficiently utilise the nodes to discover frequent patterns in cloud computing environments with data privacy preserved. Through empirical evaluations on various simulation conditions, the proposed CARM delivers excellent performance in terms of scalability and execution time.

On Connected Target Coverage for Wireless Heterogeneous Sensor Networks with Multiple Sensing Units

The paper considers the connected target coverage (CTC) problem in wireless heterogeneous sensor networks (WHSNs) with multiple sensing units, termed MU-CTC problem. MU-CTC problem can be reduced to a connected set cover problem and further formulated as an integer linear programming (ILP) problem. However, the ILP problem is an NP-complete problem. Therefore, two distributed heuristic schemes, REFS (remaining energy first scheme) and EEFS (energy efficiency first scheme), are proposed. In REFS, each sensor considers its remaining energy and its neighbors’ decisions to enable its sensing units and communication unit such that all targets can be covered for the required attributes and the sensed data can be delivered to the sink. The advantages of REFS are its simplicity and reduced communication overhead. However, to utilize sensors’ energy efficiently, EEFS is proposed. A sensor in EEFS considers its contribution to the coverage and the connectivity to make a better decision. To our best knowledge, this paper is the first to consider target coverage and connectivity jointly for WHSNs with multiple sensing units. Simulation results show that REFS and EEFS can both prolong the network lifetime effectively. EEFS outperforms REFS in network lifetime, but REFS is simpler.

A Cloud-Based Smart-Parking System Based on Internet-of-Things Technologies

This paper introduces a novel algorithm that increases the efficiency of the current cloud-based smart-parking system and develops a network architecture based on the Internet-of-Things technology. This paper proposed a system that helps users automatically find a free parking space at the least cost based on new performance metrics to calculate the user parking cost by considering the distance and the total number of free places in each car park. This cost will be used to offer a solution of finding an available parking space upon a request by the user and a solution of suggesting a new car park if the current car park is full. The simulation results show that the algorithm helps improve the probability of successful parking and minimizes the user waiting time. We also successfully implemented the proposed system in the real world.

Forward-Looking Forward Error Correction Mechanism for Video Streaming Over Wireless Networks

Video streaming over wireless network poses a great challenge because the high packet error rate usually decreases the quality of video streaming. Forward error correction (FEC) mechanism is generally used to protect the video quality. However, the recovery performance of the FEC mechanism decreases when burst packet loss is larger than the added FEC redundant packets. In this paper, the forward-looking forward error correction (FL-FEC) mechanism is proposed to recover lost packets for video streaming over wireless networks. The FL-FEC mechanism recovers not only the lost packet from its FEC block but also the previous FEC block from the recovered packet, repeating the recovery procedure until recovering the first FEC block. If the play-out buffer at the receiver is large, the FL-FEC mechanism can execute a chain of recovery procedures to ultimately recover all lost packets without any negative impact on application performance. The FL-FEC mechanism selects non-continuous source packets in previous FEC blocks to generate FEC redundancy with the FEC block. Hence, the FL-FEC mechanism can significantly disperse burst packet loss into different FEC blocks. The FL-FEC mechanism uses an analytical model to decide the number of FEC redundant packets in order to obtain the minimum recovery overhead. The FL-FEC mechanism is tested to show the benefits of high recovery performance and low recovery overhead in improving the peak signal-to-noise ratio and the decodable frame rate of video streaming over wireless networks.