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An increasing number of cloud providers now offer mobile edge computing (MEC) services for their customers to support task offloading. This is undertaken to reduce latency associated with forwarding data from IoT devices owned by customers to cloud platforms. However, two challenges remain in existing MEC scenarios: (i) the coverage of MEC services is limited; (ii) there is limited ability to develop an audit trail about which MEC service providers have processed a user's data. A new architecture for automatically offloading user tasks in MEC scenarios is proposed that addresses the two challenges above. The architecture makes use of drones to dynamically cache data generated from IoT devices and forward this data to MEC servers that participate in a private blockchain network. Our simulated experiments demonstrate the flexibility of the task offloading process through the proposed architecture, which can provide greater visibility of MEC service providers involved in processing users' data.

In most metropolises, commuters spend a considerable amount of time on public transport, and many of them entertain themselves with the content (like music or videos) on their mobile devices to alleviate boredom. Currently, the content, usually shared in co-located wireless networks to avoid huge monetary cost of using cellular data, is delivered from single host (resource owner) to single request user, which brings low transmission quality, due to the uncertainty of mobile edge networks in public transport environments. In this paper, we present an intelligent incentive framework called GoSharing which encourages multiple hosts to share content collaboratively to improve delivery quality, by taking advantage of users’ association and consideration of network Quality of Service(QoS) requirements. The highlight of GoSharing is the novel Association-based Intelligent incentive mechanism that consists of three key components. First, a Fast Candidate Generation algorithm discovers users’ association according to their stored content and QoS requirements and filters the candidate groups from large host groups. Second, a Host Selection algorithm finds a near-optimal solution among candidate groups within an approximate factor of F ( d ) , where d denotes the maximum size of completed tasks when any candidate group is selected. Last but not least, a Payment Determination algorithm determines the payment of resource contributors while guaranteeing the truthfulness of their bids based on the procurement auction. Both theoretical analysis and extensive simulations demonstrate that GoSharing not only effectively motivates hosts’ collaborative sharing, but also achieves the properties of truthfulness, individual rationality, high computational efficiency, low overpayment ratio, and high download ratio.

Dementia affects millions of elderly worldwide causing remarkable costs to society, but effective treatment is still lacking. Acupuncture is one of the complementary therapies that has been applied to cognitive deficits such as Alzheimer’s disease (AD) and vascular cognitive impairment (VCI), while the underlying mechanisms of its therapeutic efficiency remain elusive. Neuroplasticity is defined as the ability of the nervous system to adapt to internal and external environmental changes, which may support some data to clarify mechanisms how acupuncture improves cognitive impairments. This review summarizes the up-to-date and comprehensive information on the effectiveness of acupuncture treatment on neurogenesis and gliogenesis, synaptic plasticity, related regulatory factors, and signaling pathways, as well as brain network connectivity, to lay ground for fully elucidating the potential mechanism of acupuncture on the regulation of neuroplasticity and promoting its clinical application as a complementary therapy for AD and VCI.

According to the IEEE 802.15.6 standard, interference within each wireless body area network (WBAN) can be well addressed by the time division multiple access (TDMA)-based media access control (MAC) protocol. However, the inter-WBAN interference will be caused after multiple WBANs are gathered together. This paper proposes a priority-aware price-based power control (PPPC) scheme for mitigating the inter-WBAN interference. Specifically, to maximize the transmission data rate of sensors and control the aggregate interference suffered by coordinators, a Stackelberg game is established, in which the coordinators issue interference prices and the active sensors adjust their transmission power accordingly. On the other hand, since the information about the identities of the active sensors in a specific time slot is kept private, a Bayesian game is designed to model the interaction among sensors. Moreover, the timeliness and reliability of data transmission are guaranteed by designing the sensors&rsquo, priority factors and setting a priority-related active probability for each sensor. At last, a power control algorithm is designed to obtain optimal strategies of game players. Simulation results show that compared with other existing schemes, the proposed scheme achieves better fairness with a comparable network sum data rate and is more energy efficient.

In this paper, we tackle the problem of stimulating users to join mobile crowdsourcing applications with personal devices such as smartphones and tablets. Wireless personal networks facilitate to exploit the communication opportunity and makes diverse spare-resource of personal devices utilized. However, it is a challenge to motivate sufficient users to provide their resource of personal devices for achieving good quality of service. To address this problem, we propose an incentive framework based on Stackelberg game to model the interaction between the server and users. Traditional incentive mechanisms are applied for either single task or multiple dependent tasks, which fails to consider the interrelation among various tasks. In this paper, we focus on the common realistic scenario with multiple collaborative tasks, where each task requires a group of users to perform collaboratively. Specifically, participants would consider task priority and the server would design suitable reward functions to allocate the total payment. Considering the information of users' costs and the types of tasks, four incentive mechanisms are presented for various cases to the above problem, which are proved to have the Nash equilibrium solutions in all cases for maximizing the utility of the server. Moreover, online incentive mechanisms are further proposed for real time tasks. Through both rigid theoretical analysis and extensive simulations, we demonstrate that the proposed mechanisms have good performance and high computational efficiency in real world applications.

We present a Bayesian sparse representation (BSR) model for synthetic aperture radar (SAR) image classification. It involves the design of the sub-categorization scheme for the samples, the formulation of the BSR model, and the implementation of the classification decision. First, the training samples of each target category are sub-categorized into multiple subclasses. The discriminative features are then extracted from each sample within one subclass. These same features from all samples are gathered to construct a sub-dictionary. After collecting all sub-dictionaries from all features, the sparse reconstructions are performed for all features. A BSR framework is employed for such purposes. Finally, a fusion strategy is applied to the residuals to predict the class label of the test sample. By sub-categorizing the samples into multi-clusters, the proposed model decreases the intra-class variations between the samples and thus improve the representation ability of the features to different targets. The test results using real field data demonstrate that the proposed method has superiority to some state-of-the-art methods.

In the practical crowd sourcing systems, there exist many cooperative tasks, each of which requires a group of users to perform together, such as finding the shortest multi-hop path or obtaining the media resources from a set of hosts. In this paper, we tackle the problem of how to truthfully and fairly schedule or allocate sufficient users who join mobile crowd sourcingapplications with their smartphones. Moreover, the cooperation among users is taken into account. Thus, we present a novel Cooperative Crowd sourcing (C2) auction mechanism for crowd sourcing multiple cooperative tasks. C2 contains two parts: user selection and payment computation. In the first part,we first prove that users selection with the minimum social cost is NP hard problem and design a greedy algorithm to achieve near-optimal solution in polynomial time. The other part is that the server determines the payments of selected users to avoid the bidder’s cheating behavior through a pricing algorithm that if and only if users honestly bid their cost, they can obtain the maximum utility. Both theoretical analysis and extensive simulations demonstrate that C2 auction achieves not only truthfulness, individual rationality and high computational efficiency, but also low over payment ratio.

Multihop data delivery between vehicles is an important technique to support the implementation of vehicular ad hoc networks (VANETs). However, many inherent characteristics of VANETs (e.g., dynamic network topology) bring great challenges to the data delivery. In particular, dynamic topology and intermittent connectivity make it difficult to design an efficient and stable geographic routing protocol for different applications of VANETs. To solve this problem, the paper proposes an adaptive routing protocol based on QoS and vehicular density (ARP-QD) in urban VANETs environments. The basic idea is to find the best path for end-to-end data delivery, which can satisfy diverse QoS requirements by considering hop count and link duration simultaneously. To reduce the network overhead furthermore, ARP-QD adopts an adaptive neighbor discovery algorithm to obtain neighbors’ information based on local vehicular density. In addition, a recovery strategy with carry-and-forward is utilized when the routing path is disrupted. Numerical simulations show that the proposed ARP-QD has higher delivery ratio than two prominent routing protocols in VANETs, without giving large compromise on delivery delay. The adaptivity of ARP-QD is also analyzed.

In low-duty-cycle wireless sensor networks, wireless nodes usually have two states: active state and dormant state. The necessary condition for a successful wireless transmission is that both the sender and the receiver are awake. In this paper, we study the problem: How fast can raw data be collected from all source nodes to a sink in low-duty-cycle WSNs with general topology? Both the lower and upper tight bounds are given for this problem. We use TDMA scheduling on the same frequency channel and present centralized and distributed fast data collection algorithms to find an optimal solution in polynomial time when no interfering links happen. If interfering links happen, multichannel scheduling is introduced to eliminate them. We next propose a novel Receiver-based Channel and Time Scheduling (RCTS) algorithm to obtain the optimal solution. Based on real trace, extensive simulations are conducted and the results show that the proposed RCTS algorithm is significantly more efficient than the link schedule on one channel and achieves the lower bound. We also evaluate the proposed data collection algorithms and find that RCTS is time-efficient and suffices to eliminate most of the interference in both indoor and outdoor environment for moderate size networks.

Electro-optic (EO) polymer modulators are very promising in the realization of cost-effective and high-performance optical transmissions. In this article, general strategies and specific designs of the traveling wave electrodes in EO polymer modulators were presented to reduce the modulator drive power while maintaining a broadband response. The optimum device parameters and corresponding conditions were estimated using finite element method based on electrode design. In calculating the results, the comprehensive characteristics of polymer modulator with 1.21 V half-wave voltage and 91 GHz bandwidth was demonstrated with electro-optic interaction length is 20 mm, electro-optic coefficient is 55 pm/V, and operation wavelength is 1.319 μm. These results agree with the 0.8 V half-wave voltage and 30 mm electro-optic interaction length reported in Science. In the five designs presented, a hybrid electrode structure combining CPW and microstrip lines were advanced. The characteristics of this structure are lik...

Hybrid electrode combined coplanar waveguide (CPW) and microstrip lines in ultra-broadband electro-optic modulators. The characteristics of the modulators with hybrid electrode is like that of the modulator with the microstrip lines, in which the microstrip electrode is loaded above only one arm of Mach-Zehnder (M-Z) optical waveguide, besides the problem of microstrip line to coaxial transition and corona polarization in polymer modulators have been best solved at the same time. By using finite element method (FEM), the characteristic parameters such as half-wave voltage, modulation bandwidth characteristic impedance, effective microwave refractive index of polymer modulators with microstrip line and hybrid electrode are analysed and compared in this paper. The results present that velocity match, impendence match and lower microwave propagating loss is easily realized in modulators with hybrid electrode.

In low-duty-cycle wireless sensor networks, wireless nodes usually have two states: active state and dormant state. The necessary condition for a successful wireless transmission is that both the sender and the receiver are awake. In this paper, we study the problem: How fast can raw data be collected from all source nodes to a sink in low-duty-cycle WSNs? To address this, we define the Minimum Data Collection Delay (MDCD) problem, and give both the lower and upper tight bounds on the minimum delay for data collection when interfering links are eliminated. Furthermore, a novel concept, Virtual Grid Network (VGN) is introduced to successfully convert the MDCD problem into max-flow problem, and present a MDCD algorithm enlightened by the Ford-fulkerson max-flow method, which is able to find an optimal solution in polynomial time and achieves the lower bound. Extensive simulations are conducted and the results show that the proposed MDCD algorithm significantly outperforms the Shortest Path Routing algorithm (up to 32%) and achieves the lower bound.

Wireless sensor networks have special characteristic of spatial correlation, which results in the statistical redundancy of data. In addition, the finite batteries of the nodes demand energy-balanced network control. In this article, we propose an energy-balanced representative node selecting (EBRNS) algorithm inspired by vector quantization (VQ) method, which solves the problem of energy consumption among nodes unbalanced. Furthermore, the proposed algorithm is shown to prolong the network lifetime compared with that of classical method (INS) by numerical simulations.

The characteristics of the polymer modulator are determined by many interrelated physical phenomena. The key issue of this paper is to find out the optimum device parameters and corresponding conditions by taking into account all the related factors. The optical field in ridge waveguides is calculated using the FEM software with MATLAB and then fit to a Gauss function. The parameters such as half-wave voltage, bandwidth are calculated using the FEM software with FORTRAN language. In the calculating results, the comprehensive characterization of the polymer modulator with 1.21v half-wave voltage, 91GHz bandwidth is presented, electro-optic interaction length is 20mm, electro-optic coefficient is 55pm/V, and wavelength is 1.319μm. These results fit the 0.8v half-wave voltage, electro-optic interaction length is 30mm reported on Science perfectly. More important, five structures of polymer modulators are presented all together and are compared of the merits and shortcomings. One of them is a combination of CPW and microstrip lines. The characterization of this structure is like that of the microstrip lines with single arm electrode on one arm of the waveguide, but it solves the problem of microstrip-coaxial transition and corona polarization.

The characterization of Z-cut LiNbO 3 optical modulators with novel complex electrode are discussed by using the finite-element method (FEM) and studied experimentally in this paper. The calculation results show that the configuration of the electrode can realize microwave-optical velocity match easily and reduce microwave electrode losses drastically, so the modulators with such electrode are candidate devices for future ultra-high-speed optical fiber transmission systems. The traveling wave electrode consists of upper and lower parts. Because the thickness of the hot electrode can be thicker, the microwave attenuation coefficient of the traveling-wave electrode (alpha) 0 is able to be less than 0.35 dB/(cm GHz 1/2 ). The configurations of the electrode are optimized by criteria of the ratio of 3dB optical bandwidth to drive power. The results of optimization show that the properties of the modulators can be improved by increasing the electrode gaps. An electro-optic modulator with bandwidth 100 GHz, half wave voltage 6V is designed. The modulator is being fabricated in our laboratory. Some experimental results of the traveling- wave electrode are obtained. The characteristic of low microwave transmission loss of the electrode is demonstrated. The attenuation coefficient (alpha) 0 measured by microwave network analyzer is as low as 0.35 dB/(cm GHz 1/2 ).