Qingqi Pei

A connectivity-aware intersection-based routing in VANETs

Vehicular ad hoc networks (VANETs) are going to be an important communication infrastructure in our moving life. The design of routing protocols in VANETs is a significant and necessary issue for supporting VANET-based applications. However, due to high mobility, frequent link disconnection, and uneven distribution of vehicles, it becomes quite challenging to establish a robust route for delivering packets. This paper presents a connectivity-aware intersection-based routing (CAIR) protocol to address these problems by selecting an optimal route with higher probability of connectivity and lower experienced delay; then, geographical forwarding based on position prediction is used to transfer packets between any two intersections along the route. Simulation results show that the proposed protocol outperforms existing routing protocols in terms of data delivery ratio and average transmission delay in typical urban scenarios.

Connectivity Analysis for Free-Flow Traffic in VANETs: A Statistical Approach

Intervehicle communication gives vehicles opportunities to exchange packets within the limited radio range and self-organized in Ad Hoc manner into VANETs (Vehicular Ad Hoc Networks). However, due to issues such as the high mobility, insufficient market penetration ratio, and lacking of roadside units, connectivity is actually a big problem in VANETs. In addition, relying only on the direct connectivity in most of the previous works, say broadcasting which provides one-hop connections between nodes is far from the continuously growing application demands in VANETs, such as inter-vehicle entertainments, cooperative collision avoidances, and inter-vehicle emergency notifications. Therefore, the indirect connectivity from multihop forwarding is also a necessary complement especially for the case where direct connection is hardly achieved. In this paper, we define a new metric, that is, available connectivity, to consider both direct and indirect connectivity. After analyzing the statistical properties of direct and indirect connectivity in vehicular environment, the available connectivity is proposed and quantified for practical usage. Numerical results show that our available connectivity could provide correct and useful references for protocols design and performance improvements of different applications.

A Trust Value-Based Spectrum Allocation Algorithm in CWSNs

With the increase of congestible frequency spectrums and the rapid development of wireless sensor networks (WSNs) applications, the new technology—combing cogitative radio technology with WSNs—called CWSNs will bring broad prospects to the field of radio and sensor networks. CWSN devotes itself to the solution of spectrum sharing in forms of networks, such as IEEE 802.11 and Bluetooth. A new algorithm is proposed for allocating the idle spectrum to secondary users (SUs). This algorithm uses “the last diminisher” algorithm, which appears in fair division models. It can help solve complicated problems in a simple fashion. This article combines the trust value and the method of spectrum allocation. The concept of trust value in reputation management is introduced. All the factors are applied to solve the realistic problems of spectrum allocation. With the growing number of sensor nodes, the stable throughput is of vital importance.

Reputation-based coalitional games for spectrum allocation in distributed Cognitive Radio networks

Cognitive Radio (CR) technique is proved to be an efficient approach for mitigating the spectrum scarcity problem in wireless communications and spectrum allocation methods construct the foundation of such a technique. However, it will degrade the performance of CR when paying no attention to the behavior of second users (SUs) and their demands for spectrum attribute. In this paper, the spectrum allocation problem is first modeled as a coalition formation game, taking SUs reputation and requirements of spectrums into consideration. The rule named Assigning spectrum by probability among coalitions and by demand within coalitions is used to optimize the spectrum utilization and fairness when allocating spectrum among SUs. For each SU is equipped with an agent, a central authority is not needed and therefore the scheme can be more applicable in dynamic cognitive radio networks. Simulation results show that the proposed approach can efficiently improve the fairness and efficiency of spectrum allocation in CR context.

Spoofing attacks and countermeasures in fm indoor localization system

FM-based indoor localization identifies the location of an user by looking at the received signal strength (RSS) at the user’s location. In this paper, we discover a spoofing attack which is able to cause the FM-based indoor localization system to malfunction. The newly discovered, easy launched spoofing attack which enables the adversary to deceive a victim user to obtain a fake indoor location through remotely manipulating the RSS at the user’s location simultaneously. By analyzing the features of the received and FM signals in the frequency domain, we propose a defense method to deal with this attack. The proposed method contains two levels of detections. Specifically, the first level of detection distinguishes between the normal signal and the attack/noise signal, and the second level of detection finally detects the existence of the attack signal. We perform real-world experiments on Universal Software Radio Peripherals (USRPs) to spoof a target location to four different locations 6 - 32 meters away from the target location. The experiment results show a promising performance of the proposed defense method with a false negative rate and a false alarm rate of 3.9% and 6.4%, respectively.

Cognitive networking for next-G wireless communications

With the development and the promising future of nextgeneration wireless communications, cognitive networking has emerged as a promising technology to address spectrum scarcity and achieve higher data rate. Despite of its benefit, the employment of cognitive techniques at different layers brings nontrivial design challenges to many networking functionalities. In such context, this special issue is aimed at investigating and seeking potential solutions to various challenges in cognitive networking for next-generation (Next-G) wireless communications, such as cognitive communication architecture and topology control, spectrum sensing, sharing, andmanagementmechanisms, cognitive techniques and networking for Next-G wireless communications, and security and privacy in Next-G wireless communications. Specifically, the special issue is composed of the following papers. Here we present a high-level overview of them.

A Novel Power-Saving Scheduling Scheme in Large Scale Smart-Grid Networks

The IEEE 802.11ah Task Group is going to specify a global WLAN standard. However, .ah drafts still employs the carrier sense multiple access with collision avoidance (CSMA/CA) medium access protocol, which is an energy-consuming protocol and not suitable for networks where STAs are generally battery supplied. Besides, since .ah could support up to 6000 stations at most to be scheduled within one BSS, the introduced overhead and corresponding processing delay are non-trivial. In this paper, a power saving scheduling scheme is proposed which could greatly reduce the introduced overhead while successfully scheduling the uplink/downlink traffic of meters. Our model could also save the station’s battery with best efforts thus making our protocol specifically suitable for Smart-Grid networks where battery changing for stations is difficult. Numerical results show that our scheme outperforms the PSM (Power Saving Mechanism) and PSMP (Power Save Multi-Poll) protocols in terms of overheads, throughput and energy consumptions.

Reversible Image Watermarking Using Hybrid Prediction

In this paper, a hybrid prediction algorithm is designed to improve the histogram shifting based reversible watermarking method. This algorithm not only uses the local information near a pixel, but also utilizes the global information of the whole image. As a result, it produces a sharper histogram for watermark embedding. In addition, we enable the use of sorting idea by introducing an estimation function of the hybrid prediction. Experimental results illustrate that the proposed watermarking method outperforms many recently proposed methods.