Zhaolong Ning

Vehicular Social Networks: Enabling Smart Mobility

Vehicular transportation is an essential part of modern cities. However, the ever increasing number of road accidents, traffic congestion, and other such issues become obstacles for the realization of smart cities. As the integration of the Internet of Vehicles and social networks, vehicular social networks (VSNs) are promising to solve the above-mentioned problems by enabling smart mobility in modern cities, which are likely to pave the way for sustainable development by promoting transportation efficiency. In this article, the definition of and a brief introduction to VSNs are presented first. Existing supporting communication technologies are then summarized. Furthermore, we introduce an application scenario on trajectory data-analysis-based traffic anomaly detection for VSNs. Finally, several research challenges and open issues are highlighted and discussed.

Joint scheduling and routing algorithm with load balancing in wireless mesh network

Wireless mesh network (WMN) is a promising solution for last mile broadband internet access. Mesh nodes or mesh routers are connected via wireless links to form a multi-hop backbone infrastructure and improving throughput is the primary goal. While previous works mainly focused on either link level protocol design or complex mathematical model, in this paper, we investigate the performance gains from jointly optimizing scheduling and routing in a multi-radio, multi-channel and multi-hop wireless mesh network. Then, two optimization objectives are addressed by considering wireless media contention and spatial multiplexing. The first objective is to maximize throughput by exploiting spatial reuse while the second one is to ensure fairness among different links. We design a cross-layer algorithm by considering both MAC layer and network layer. Simulation results show that our joint optimization algorithm can significantly increase throughput as well as fairness.

Social-Oriented Adaptive Transmission in Opportunistic Internet of Smartphones

Stable and reliable wireless communication is one of the critical demands for smart cities to connect people and devices. Although intelligent terminals can be leveraged to deliver and exchange data through Internet, poor network coverage and expensive network access challenge the deployment of network infrastructure. In this paper, we propose a social-oriented smartphone-based adaptive transmission mechanism to improve the network connectivity and throughput in Internet of Things (IoTs) for smart cities. First, a social-oriented double-auction-based relay selection scheme is investigated to stimulate the relay smartphones to forward packets for others so that the network connectivity can be strengthened. Furthermore, for the sake of achieving high throughput in smartphone-based IoTs, the relay method selection is determined by integrating various kinds of transmission schemes in an optimal fashion to make full use of wireless spectrum resource. Due to its high computational complexity, a firefly-algorithm-based scheme is investigated, by which the formulated NP-complete problem can be solved effectively. Simulation results demonstrate the superiority of our proposed method.

Link stability estimation based on link connectivity changes in mobile ad-hoc networks

Link stability issue is significant in many aspects, especially for the route selection process in mobile ad-hoc networks (MANETs). Most previous works focus on the link stability in static environments, with fixed sampling windows which are only suitable for certain network topologies. In this paper, we propose a scheme to estimate the link stability based on link connectivity changes, which can be performed on the network layer, without the need of peripheral devices or low layer data. We adopt a variable sized sampling window and propose a method to estimate the link transition rates. The estimation scheme is not restricted to specific network topologies or mobility models. After that, we propose a routing method which adjusts its operating mode based on the estimated link stability. Simulation results show that the proposed scheme can provide correct estimation in both stationary and non-stationary scenarios, and the presented routing protocol outperforms conventional routing schemes without link stability estimation.

Integration of scheduling and network coding in multi-rate wireless mesh networks

In order to fully utilize spectrum resource in wireless mesh networks (WMNs), we propose a combination of some popular communication techniques, including link scheduling, spatial reuse, power and rate adaptation and network coding (NC), to activate as many transmission links as possible during one scheduling period, so that the total scheduling length can be minimized and network throughput can be maximized. Different from previous studies, we consider the interplay among these techniques and present an optimal NC-aware link scheduling mechanism in multi-rate WMNs, which relies on the enumeration of all possible schedules. Due to the high computational complexity of our proposed model, we utilize a column generation (CG)-based method to resolve the optimization problem and decompose it into a master problem (MP) and a pricing problem (PP). Furthermore, we present a distributed power control algorithm for PP, by which the computational complexity of the CG-based scheme can be largely reduced. Simulation results demonstrate the superiority of our method under various network situations.

Bibliographic Analysis of Nature Based on Twitter and Facebook Altmetrics Data

This paper presents a bibliographic analysis of Nature articles based on altmetrics. We assess the concern degree of social users on the Nature articles through the coverage analysis of Twitter and Facebook by publication year and discipline. The social media impact of a Nature article is examined by evaluating the mention rates on Twitter and on Facebook. Moreover, the correlation between tweets and citations is analyzed by publication year, discipline and Twitter user type to explore factors affecting the correlation. The results show that Twitter users have a higher concern degree on Nature articles than Facebook users, and Nature articles have higher and faster-growing impact on Twitter than on Facebook. The results also show that tweets and citations are somewhat related, and they mostly measure different types of impact. In addition, the correlation between tweets and citations highly depends on publication year, discipline and Twitter user type.

A Social-Aware Group Formation Framework for Information Diffusion in Narrowband Internet of Things

Due to the heterogeneous and resource-constrained characters of Internet of Things (IoT), how to guarantee ubiquitous network connectivity is challenging. Although LTE cellular technology is the most promising solution to provide network connectivity in IoTs, information diffusion by cellular network not only occupies its saturating bandwidth, but also costs additional fees. Recently, NarrowBand-IoT (NB-IoT), introduced by 3GPP, is designed for low-power massive devices, which intends to refarm wireless spectrum and increase network coverage. For the sake of providing high link connectivity and capacity, we stimulate effective cooperations among user equipments (UEs), and propose a social-aware group formation framework to allocate resource blocks (RBs) effectively following an in-band NB-IoT solution. Specifically, we first introduce a social-aware multihop device-to-device (D2D) communication scheme to upload information toward the eNodeB within an LTE, so that a logical cooperative D2D topology can be established. Then, we formulate the D2D group formation as a scheduling optimization problem for RB allocation, which selects the feasible partition for the UEs by jointly considering relay method selection and spectrum reuse for NB-IoTs. Since the formulated optimization problem has a high computational complexity, we design a novel heuristic with a comprehensive consideration of power control and relay selection. Performance evaluations based on synthetic and real trace simulations manifest that the presented method can significantly increase link connectivity, link capacity, network throughput, and energy efficiency comparing with the existing solutions.

Markov-based vertical handoff decision algorithms in heterogeneous wireless networks

Our work has considered the QoS factors and constructed a reward function to model the QoS properties.Our work has considered MTs velocity, network access cost and switching cost for vertical handoff decision.We have applied G1 and entropy methods to calculate the weight of each QoS factor in the reward function.By taking the MTs velocity into consideration, our work can avoid unnecessary handoffs. In this paper, we propose a received signal strength (RSS)-based single-attribute handoff decision algorithm at first, and investigate handoff decision model based on connection lifetime, which can keep mobile terminals (MTs) staying long enough in the preferred network. Since the preferred quality of service (QoS) parameters may be distinct among different MTs, we then formulate the vertical handoff decision problem as a Markov decision process, with the objectives of maximizing the expected total reward and minimizing average number of handoffs. A reward function is constructed to assess the QoS during each connection, and the G1 and entropy methods are applied in an iterative way, by which we can work out a stationary deterministic handoff decision policy. Numerical results demonstrate the superiority of our proposed schemes compared with other existing algorithms.

A channel estimation based opportunistic scheduling scheme in wireless bidirectional networks

Generally speaking, there are two assumptions in the previous bidirectional networks. The first one is assuming that no direct transmission paths exist between the source and destination nodes due to high shadow fading or large separation. The second one is assuming that either channel parameters are pre-established or perfect global channel state information (CSI) can be obtained by the relay nodes. In this paper, we get rid of these limitations and estimate channel gains for both analog network coding (ANC) and time division broadcasting (TDBC) schemes based on outage probability. As the channel gain of each link varies from time to time in wireless networks, we first estimate the channel gain according to outage probability, then propose an opportunistic scheduling scheme to optimize the sum rate values by maximizing the minimum link transmission rate. Simulation results are presented to demonstrate the effectiveness of our channel estimation scheme, and the performance of our proposed opportunistic scheduling scheme is compared with the round robin scheduling (RRS) scheme for both ANC and TDBC schemes.

Novel Framework of Risk-Aware Virtual Network Embedding in Optical Data Center Networks

The traffic between geographically distributed data centers (DCs) becomes bandwidth hungry. Since the optical interconnection has a high capacity, the optical data center network (ODCN)—where DCs are located at the edge of the optical backbone—emerges. By virtualization, the virtual networks—representing service requirements—are embedded onto the same part of the substrate ODCN. Each virtual network has virtual machine (VM) nodes interconnected by virtual links (VLs). Therefore, a virtual network embedding (VNE) operation includes two components: 1) the VM mapping for putting a VM into the server of an appropriate DC and 2) the VL mapping for establishing one substrate path to support inter-VM communications. In this paper, we focus on a risk-aware VNE framework because a blind VNE operation would result in severe information leakage among coresident VMs in the server. By evaluating VM threat and vulnerability, risky VMs are identified according to experimental results. To perform physical isolation between risky and security VMs, a risk-aware VNE heuristic algorithm is proposed. The simulation results show that our heuristic algorithm performs better than the benchmark in terms of maintaining ODCN security and earning rental revenue. There is also a good match between our algorithm solution and the problem bound.