Jiacheng Chen

When vehicles meet TV white space: A QoS guaranteed dynamic spectrum access approach for VANET

Vehicular ad hoc network(VANET) is an emerging wireless communication scenario and has caught the attentions of both academia and industry. However, some challenges still exist, one of which is the spectrum scarcity problem, especially for the throughput-demanding downlink infotainment services. In this paper, we present a solution to the problem by introducing the state-of-the-art cognitive radio technology, namely the exploitation of TV white space(TVWS). First, we give an overview of the compositions of this new networking paradigm. Then, taking into account the characteristics of both VANET and TVWS, we develop a novel TVWS resource model tailored for the system. After that, we focus on the dynamic spectrum access problem and formulate it as a matching between vehicles/requests and available channels. Both the throughput of the network and the guarantee of QoS are considered during the calculation of preference lists. Furthermore, an algorithm is also brought forth to implement the matching process. It is proved that after the execution of the algorithm, the matching is stable and vehicle-optimal. Numerical results demonstrate the feasibility and efficiency of our system.

Providing Vehicular Infotainment Service Using VHF/UHF TV Bands via Spatial Spectrum Reuse

In this paper, we identify the potential of the television bands to be used for providing vehicular infotainment service. Specifically, content delivery from the roadside unit to vehicular users is conducted by exploiting the spectrum holes, which is also referred to as spatial spectrum reuse. In this manner, the spectrum utilization efficiency is improved and the digital television service is not interfered. We first give a thorough description on such vehicular content delivery network and indicate the major design issues. After that, we respectively develop user and resource models tailored for our scenario by considering their characteristics and formulate the resource allocation as a system throughput maximization problem based on these models. For practical implementation, we devise a vehicular content delivery protocol incorporating a dynamic spectrum access algorithm and a maximal frame size design method, both of which aim at throughput and spectrum efficiency enhancement. Extensive simulations are conducted and the numerical results show the system performance is improved with our approaches.

Service-Oriented Dynamic Connection Management for Software-Defined Internet of Vehicles

Internet of vehicles (IoV) is an emerging paradigm for accommodating the requirements of future intelligent transportation systems (ITSs) with the overwhelming trend of equipping vehicles with versatile sensors and communications modules, and facilitating drivers and passengers with a variety of innovative ITS applications. However, the implementation of IoV still faces many challenges, such as flexible and efficient connections, quality of service guarantee, and multiple concurrent support requests. To this end, in this paper we introduce the software-defined IoV (SD-IoV), which is able to tackle the above-mentioned issues by adopting the software-defined networking framework. We first present the architecture of SD-IoV and develop a centralized vehicular connection management approach. Then, we aim to allocate dedicated communications resources and underlying vehicular nodes to satisfy each service. We formulate the dynamic vehicular connection as an overlay vehicular network creation (OVNC) problem. A comprehensive utility function is also designed to serve as the optimization objective of OVNC. Finally, we solve the OVNC problem by developing a graph-based genetic algorithm and a heuristic algorithm, respectively. Extensive simulation results are provided to demonstrate the effectiveness of our proposed solution of dynamic vehicular connection management.

Database-assisted dynamic spectrum access with QoS guarantees: A double-phase auction approach

Since FCCs opening for white space (WS) utilization, database-assisted dynamic spectrum access (DSA) has become the de facto solution for the realization of dynamic spectrum sharing (DSS), due to its simplicity and compatibility with commercial off-the-shelf (COTS) devices. It is envisioned that such technology will strongly support the prosperous wireless multimedia networking (WMN) applications with satisfying QoS guarantees in the future. However, how to counter the time-frequency variant property when exploiting the WS spectrum for the provision of these services to secondary users (SUs) still remains a great challenge. In such context, a dynamic secondary access scheme for database-assisted spectrum sharing networks is proposed in this paper. In the beginning, the spectrum requirements of SUs for diverse services are modeled by considering the minimum required service data-rate and spectrum access duration. Afterwards, the spectrum demand evaluation and bidding policy are formulated based on the service classes of SUs. Furthermore, a double-phase (DP) spectrum allocation scheme, which consists of the initial resource allocation phase and resource allocation adjustment phase, is carefully designed for DSA. Finally, extensive simulations are conducted and the results demonstrate that our scheme can increase the spectrum trading revenue and adapt to varying service requirements.

QoS-Driven Efficient Client Association in High-Density Software-Defined WLAN

A software-defined wireless local area network (SDWLAN) has gained significant interest recently from both the academic and industrial communities and initiated a paradigmatic reconsideration on the stereotyped management and control of current WLAN due to its flexibility and programmability. However, with the proliferation of mobile devices, efficient client association with quality of service (QoS) guarantees in the high-density SDWLAN is a very challenging issue. In this paper, we study the client association problem in the SDWLAN with new features, including centralized association, global network state awareness, seamless handoff, and flow-level association. We formulate the client association in a high-density scenario as an optimization problem aiming to minimize the interpacket delay of individual flows, based on an unsaturated and heterogeneous Markovian analytical model. Furthermore, we interpret the optimization problem as an NP-hard supermodular set function minimization problem, which is solved by two low-complexity heuristic methods, namely the greedy algorithm and the bounded local search algorithm. Through simulations, we demonstrate the effectiveness of our proposed client association solution.

Mobile cloudlet assisted computation offloading in heterogeneous mobile cloud

Recently, with the advent of Internet of things, mobile devices are expected to carry on more and more computation-intensive applications, and mobile cloud computing also comes in to help mitigate the burden of mobile devices. However, due to the rapidly growing density of mobile devices, the current single cloud environment will still encounter resource depletion, which will lead to application offloading failure and user dissatisfaction. In order to enhance the scalability and reliability of application offloading service in mobile cloud computing, we study the heterogeneous mobile cloud, which integrates mobile cloudlet with infrastructure-based cloudlet. In such a scenario, when the infrastructure-based cloudlet becomes unavailable due to insufficient resource, mobile cloudlet can help to provide computation offloading service. We develop a centralized task scheduling algorithm to select reliable worker nodes in mobile cloudlet for the offloaded tasks. Simulation results show that heterogeneity of cloud resource can enhance scalability of offloading service efficiently. Also, the proposed scheduling algorithm can extend the network lifetime and keep balance of energy consumption in the mobile cloudlet.

A group-based M2M multiple access scheme in massive MIMO MU-SCMA cellular networks

Machine-to-machine (M2M) communications is regarded as the keystone of Internet of things (IoT) since it enables ubiquitous data exchange among devices without any artificial intervention. Cellular system is expected to play a significant role in successfully implementing the M2M communications for its ready-to-use infrastructure. However, there still exist many challenges, such as co-channel interferences to existing mobile users, congestions and limited battery capacity of M2M devices. In this paper, in order to realize M2M communication over cellular system, we propose a power- and spectrum-efficient massive-code-space-multiplex (massive-CSM) access scheme, in which quasi-orthogonal massive MIMO channels are utilized as resource blocks in the framework of SCMA. In the proposed scheme, group headers gather data from M2M devices by D2D links and communicate with eNB. Additionally, D2D-link power consumption optimization and transmit layers allocation algorithm are provided to minimize power consumption of codewords distribution among group headers. By applying random matrix theory, we also drive an uplink asymptotic equivalent (AE) of signal to interference plus noise ratio (SINR) of the system as the number of eNB antennas approach infinity. Simulation results show that the proposed multiplex access scheme improves the uplink capacity several times than traditional scheme and our algorithm achieves better results with less time complexity.

Cournot equilibrium in the mobile virtual network operator oriented oligopoly offloading market

Cellular networks are now facing severe traffic overload problems due to the explosive growth of mobile data traffic. One of the promising solutions is to offload part of the traffic through WiFi. In this paper, we investigate an oligopoly offloading market, where several Mobile Virtual Network Operators (MVNOs) compete to serve end users using the network infrastructure leased from the host Mobile Network Operator (MNO) at the wholesale market. First, we study the competitive interactions among the MVNOs considering the overload problems of the offloading market. Specially, we formulate the interactions as a non-cooperative inventory competition game, where each MVNO determines the amount of cellular traffic it can provide to end users (named as the traffic inventory of each MVNO in this paper) simultaneously. We analyze and derive the existence of the Cournot equilibrium using game theory. Furthermore, we study the impact of the MNOs wholesale price strategy on the market equilibrium. Based on these analysis, we find the optimal initial inventory strategy for these competitors according to the Cournot equilibrium. Finally, our simulations present the process of achieving the market equilibrium and illustrate the impact of the host MNO to the MVNOs.

Caching algorithms for broadcasting and multicasting in disruption tolerant networks

In delay and disruption tolerant networks, the contacts among nodes are intermittent. Because of the importance of data access, providing efficient data access is the ultimate aim of analyzing and exploiting disruption tolerant networks. Caching is widely proved to be able to improve data access performance. In this paper, we consider caching schemes for broadcasting and multicasting to improve the performance of data access. First, we propose a caching algorithm for broadcasting, which selects the community central nodes as relays from both network structure perspective and social network perspective. Then, we accommodate the caching algorithm for multicasting by considering the data query pattern. Extensive trace-driven simulations are conducted to investigate the essential difference between the caching algorithms for broadcasting and multicasting and evaluate the performance of these algorithms. Copyright