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An angle measurement method based on the rotating spot images and machine vision technology is proposed. This method abandons the traditional coding disk but uses image sensor to capture the images of a spot rotating synchronously with the measured shaft. Assuming the center of the rotation shaft is fixed, the mathematic model of the trajectory of the spot images is an ellipse. ${N}$ spot images are used to fit the ellipse equation, where the eccentric angle of the ellipse is the measured rotation angle. The basic algorithms and a compact lensless transmission angle measurement structure are also proposed. The simulation and experiment results are verified the feasibility of the measurement method, where the 5.4” accuracy can be obtained and a random collection of ${N}\ge 36$ spot images is recommended. Since the shape of the ellipse trajectory does not affect the measurement accuracy, this method allows the spot disk to be non-concentric with the rotating shaft, and allows the spot disk to be non-parallel to the image sensor. Therefore, the proposed method can achieve precision measurement under non-precision installation.

Planning ideal transit routes in the complex urban environment can improve the performance and efficiency of public transportation systems effectively. However, finding such routes is computationally difficult due to the huge solution space constituted by billions of possible routes. Considering the limited scalability of exact search methods, heuristic search methods were proposed to boost the efficiency and incorporate flexible constraints. Nevertheless, the existing methods conceal multiple criteria in an objective, and thus evaluating the performance of the generated route becomes challenging due to the lack of comparable alternatives. Inspired by the prior study, we formulate the definition of pareto-optimal transit routes based on multiple criteria. However, extracting these routes remains challenging because: A) the sheer volume of possible transit routes; and B) the sparsity of pareto-optimal routes. We address these challenges by developing an efficient search framework: for challenge A, a random search method is developed based on Monte Carlo tree search where the unproductive solution subspaces are pruned progressively to reduce the search cost; and for challenge B, an estimation method is derived to guide the search process by assessing the value for each solution subspace. The superior effectiveness of our approach in approximating the pareto-optimal transit routes was demonstrated by the comprehensive evaluation based on the real-world data.

Detection of live microalgae is critical to ballast water treatment. A novel handheld high-throughput ballast water rapid detection device based on microfluidic chip and fluorometry for counting single living microalgae cell is demonstrated in this article. The viability of individual microalgae cells can be evaluated and the number of the living microalgae cells in an aqueous solution sample can be obtained at a rate of one milliliter per minute in a fully automatic and real-time manner. It is experimentally confirmed that the detection results of this device are not influenced by free chlorophyll from the lysed microalgae, nor by the salinity and turbidity of the sample within the variation range of ballast water. Furthermore, this device has been used in a port to test the actual ballast water samples processed by ballast water treatment systems based on different principles or loaded at different locations, and the conclusion of this device on the qualification of the ship is consistent with the conclusion of the laboratory standard test. To the best of our knowledge, this is the first ballast water rapid detection device using a microfluidic chip as the detection platform, which can be used on board of ships for on-site counting the numbers of the living microalgae cells in ballast water.

Emerging energy harvesting technology can harvest and convert ambient energy into electrical power. It is a quite effective way to extend the lifetime of Wireless Multihop Networks (WMNs), and has been widely applied in WMNs. Meanwhile, the interference-free link scheduling is an indispensable operation in WMNs to reduce energy waste caused by link collision. In the energy harvesting WMNs with link scheduling, a few works take into account the impact of non-ideal battery on energy efficiency and network lifetime. This article studies the harvested energy-saving link scheduling problem in the energy harvesting WMNs under the imperfect storage efficiency. We establish the energy model to index the link weight with the harvested energy consumed on it. Furthermore, we propose a Centralized Scheduling (CS) algorithm, a Centralized Scheduling with Minimum interference weights (CSM) algorithm and a distributed one to activate the links with the maximum weights so as to maximize the utilization of the harvested energy and to minimize the energy stored in the battery. Finally, this article conducts the simulation experiment to verify the effectiveness of our algorithms and the correctness of our theoretical analysis.

In data centers, a lot of cluster computing applications follow the coflow working pattern. That is, a collection of flows between two groups of machines is semantically related. On the other hand, network function virtualization sufficiently improves the performance of data center networks. It however complicates the network environment by introducing many multi-function middleboxes each with multiple resources. Coflows encounter extremely different processing delays under diverse network functions. Prior coflow scheduling schemes are insufficient to guarantee the coflow completion time in the multi-resource environment. In this paper, we propose, model, and analyze the coflow scheduling problem in the multi-resource environment. We present a dedicated method, data rate guarantee for coflow (DRGC), to guarantee the data rate requirements of coflows in this situation. DRGC prioritizes the coflow scheduling sequence, assigns precise data rates for coflows, and deploys a packet scheduling algorithm at middleboxes to guarantee their transmissions. In our experiments, DRGC efficiently guarantees the completion times of coflows and supports 15% more workload, compared with other scheduling schemes.

The emerging deployment of large-scale cloud applications incurs significant inter-datacenter traffic, which makes the scarce wide-area bandwidth across data centers become the performance bottleneck. To achieve the desirable network performance, bandwidth guarantee should be provided for the resulting inter-datacenter traffic. However, the existing bandwidth allocation methods mainly focus on intra-datacenter traffic, and cannot achieve the cost-minimizing bandwidth guarantee for inter-datacenter traffic. In this paper, we focus on the bandwidth guarantee problem for inter-datacenter traffic and present a novel bandwidth allocation model. Our model can ensure the bandwidth guarantee, minimize the resulting network cost, and efficiently avoid the potential traffic overload on low cost links. To solve the large-scale optimization problem in our model, we are motivated to develop a distributed algorithm by blending the advantages of alternating direction method of multipliers (ADMM) and the auxiliary variable method. Specifically, we efficiently decompose the optimization problem into many small sub-problems, which are allowed to be processed in a large-scale computing environment, where each server solves a few small sub-problems. We further present a theoretically proved globally, asymptotically stable algorithm to solve these sub-problems. Extensive evaluation results demonstrate that our bandwidth allocation method can effectively realize the bandwidth guarantee for inter-datacenter traffic with reduced network cost and outperforms the prior method PS-L. In particular, the total network cost is reduced by 59.57 percent on average.

The accurate prediction of the highway traffic speed plays an important role in improving the production efficiency and the convenience of lives, and it is also one of the important issues in vehicle social big data analyses. Aiming at the problem of highway traffic speed data preprocessing, this paper proposes the algorithm of Redundant Data Reducing (RDR) that can greatly reduce the amount of data in model training of long short-term memory (LSTM) and improve the training speed under the condition that the influence on prediction accuracy is small and controllable. Aiming at the problem of low prediction accuracy for holiday traffic speeds due to small data volume, this paper proposes the Segment Prediction Algorithm (SPA) based on the speed features, which can effectively improve the prediction accuracy. The experimental results show that RDR can reduce the training data by up to 60% without notably affecting the prediction accuracy, while it improves the training speed by 60%. Compared with the current LSTM algorithm, the prediction accuracy of SPA improves significantly.

Software Defined Networking (SDN) provides flexible network management by decoupling control plane and data plane. However, such separation introduces the issues regarding the reliability of the control plane and controller load imbalance in the distributed SDN network, which will cause the low network stability and the poor controller performance. This paper proposes Reliable and Load balance-aware Multi-controller Deployment (RLMD) strategy to address the above problems. Firstly, we establish a multiple-controller network model and define the relevant parameters for RLMD. Then, we design the corresponding algorithms to implement this strategy. By weighing node efficiency and path quality, Controller Placement Selection (CPS) algorithm is introduced to explore the reliable deployments of the controllers. On this basis, we design Multiple Domain Partition (MDP) algorithm to allocate switches for controllers according to node attractability and controller load balancing rate, which could realize the reasonable domain planning. Finally, the simulations show that, compared with the typical strategies, RLMD has the better performance in improving the reliability of the control plane and balancing the distribution of the controller loads.

Software Defined Networking (SDN) provides flexible network management by decoupling control plane from data plane. And multiple controllers are deployed to improve the scalability and reliability of the control plane, which could divide the network into several subdomains with separate controllers. However, such deployment introduces a new problem of controller load imbalance due to the dynamic traffic and the static configuration between switches and controllers. To address this issue, this paper proposes a Distribution Decision Mechanism (DDM) based on switch migration in the multiple subdomains SDN network. Firstly, through collecting network information, it constructs distributed migration decision fields based on the controller load condition. Then we choose the migrating switches according to the selection probability, and the target controllers are determined by integrating three network costs, including data collection, switch migration and controller state synchronization. Finally, we set the migrating countdown to achieve the ordered switch migration. Through verifying several evaluation indexes, results show that the proposed mechanism can achieve controller load balancing with better performance.

Software defined networking (SDN) realizes the full decoupling between control plane and data plane, and it could effectively simplify network management and promote network innovation. In the large SDN network, there are the single point of failure and the lack of control resources for one centralized SDN controller, so several researchers have presented deploying multi-controller to improve the reliability and scalability of the network. However, unreasonable deployment of multiple controllers may cause the unbalanced distribution of controller loads, and it is harmful to the network stability. In order to address the above problems, this paper proposes bidirectional matching strategy (BMS) and designs its corresponding algorithm to implement multi-controller deployment. First, through collecting the information of hops, delay, and traffic in the network, we build the matching lists of switches and controllers, respectively. Then, according to the specific sequencing of elements in the matching lists, we design a mutual selection strategy that the switch and controller will select the optimal elements from its list to implement matching in turns until realizing the construction of the distributed network. Meanwhile, we implement the strict mathematical derivation to demonstrate the feasibility of BMS. Finally, simulation shows that BMS can achieve the better multi-controller deployment when compared with the existing algorithms.

Energy-harvested wireless sensor networks may operate perpetually with extra energy supply from natural energy such as solar energy. Nevertheless, harvested energy is often too limited to support perpetual network operation with full duty cycle. To achieve perpetual network operation and process the data with high importance, measured by value of information (VoI), sensor nodes have to operate under partial duty cycle and to improve the efficiency of harvested energy. A challenging problem is how to deal with the stochastic feature of natural energy and variable data VoI. We consider the energy consumption during the energy storage and the diversity of the data process including sampling, transmitting, and receiving, which consume different power levels. The problem is then mapped as a budget-dynamic multiarm bandit problem by treating harvested energy as budget and the data process as arm pulling. This paper proposes an opportunistic duty cycling (ODC) scheme to improve the energy efficiency while satisfying perpetual network operation. ODC chooses some proper opportunities to store harvested energy or to spend it on the data process based on historical information of energy harvesting and VoI of the processed data. With this scheme, each sensor node only needs to estimate ambient natural energy in short term so as to reduce computation cost and storage capacity for the historical information. It then can adjust its own duty cycle distributively with its local historical information. This paper conducts extensive theoretical analysis for the performance of our scheme ODC on the regret, which is the difference between the optimal scheme and ours. Our experimental results also manifest the promising performance of ODC.

Towards line speed and accurateness on-line content popularity monitoring on Content Centric Networking (CCN) routers, we propose a three-stage scheme based on Bloom filters and hash tables for differentiated traffic. At the first stage, we decide whether to deliver the content to the next stage depending on traffic types. The second stage consisting of Standard Bloom filters (SBF) and Counting Bloom filters (CBF) identifies the popular content. Meanwhile, a scalable sliding time window based monitoring scheme for different traffic types is proposed to implement frequent and real-time updates by the change of popularities. Hash tables according with sliding window are used to record the popularity at the third stage. Simulation results reveal that this method reaches a 40Gbps processing speed at lower error probability with less memory, and it is more sensitive to the change of popularity. Additionally, the architecture which can be implemented in CCN router is flexible and scalable.

Existing work on flooding in wireless sensor networks (WSNs) mainly focuses on single-packet problem, while the work on sequential multipacket problem is surprisingly little. This paper proposes OppCode , a new opportunistic network-coding-based flooding architecture for multipacket dissemination in WSNs, where both unreliable and correlated links commonly exist. Instead of flooding a single packet each time, each node encodes multiple native packets chosen from a specific fixed-size page to an encoded packet and then rebroadcasts it further. The key idea consists of two parts. One is opportunistically coding decision , in which each node grasps every possible coding opportunity greedily to maximize its aggregate coding gain of all neighbors based on the probabilistic estimation of packets each neighbor already has. The other is paged collective acknowledgements (ACKs), in which one rebroadcast acts as not only an implicit ACK of successful disseminations of all packets in the entire page for the sender, but also probabilistic ACK to update page-scale per-packet coverage estimations for its neighbors in a batch. Experiments based on extensive simulations and 21-node testbed show that OppCode significantly increases performance of multipacket flooding in terms of reliability, transmission overhead, delay, and load balance.

Large-scale data centers are the key infrastructures for hosting and running a variety of applications. Besides traditional L2/L3 devices, middleboxes are widely deployed in data centers and perform many important functions, e.g., the intrusion detection and firewall. Middleboxes are equipped with multiple kinds of resources, such as CPU and memory. Data flows undergoing different functions have heterogeneous processing time requirements on diverse resources. Researchers are in a dilemma as to how to provide fair service for flows and efficiently utilize those scarce resources. To address this problem, we propose a novel packet scheduling method, active time fairness queuing (ATFQ), for multi-resource environments. Prior packet scheduling methods usually focus on pursuing the fairness among flows, resulting in enormous waste of those scarce resources. ATFQ overcomes this essentially by redefining the fairness and can maximize the resource utilization with the guarantee of fairness. We conduct extensive simulations to evaluate the performance of ATFQ. The evaluation results demonstrate that flows get better service in many aspects under ATFQ. Meanwhile, the resource utilization rises up by about 10% than the traditional DRFQ, which is one of the mainstream involved methods.

Data centers have emerged as infrastructures for deploying various applications and services. To improve the security and performance, middleboxes are vastly deployed inside data centers to perform a large range of functionalities. Each of such middleboxes is equipped with diverse resources. Compared with traditional switches, middleboxes analyze the content of packets. This leads to the long processing time for flows passing through a middlebox. Additionally, executing different functionalities incurs diverse consumption on resources. Consequently, data flows undergoing different function components need different processing time on diverse resources. How to complete the transmission of such flows before their deadlines when passing through a middlebox comes out to be an essential issue, which lacks effective solutions. In this paper, we propose multi-resource & deadline-driven flow scheduling (MDFS) to satisfy the deadline requirements of flows in multi-resource environments. Besides guaranteeing the deadline, MDFS treats flows fairly and provides reliable service for them. To the best of our knowledge, this is the first paper trying to solve the deadline-driven flow scheduling problem in a multi-resource environment. With respect to the performance evaluation, up to $90$ percent flows meet their deadlines in normal conditions by using MDFS, which greatly outperforms the performance of other scheduling schemes.

Based on the concept of the new drought index called Vegetation Drought Response Index (VegDRI) using data-mining technology, an Integrated Surface Drought Index (ISDI) was established in this study. ISDI improved the original model, adding remote sensed temperature information into the input factors. This index attempt to describe drought from a more comprehensive perspective, the integrated information including: traditional meteorological data, satellite-derived earth surface water and heat environments, vegetation conditions, and inherent properties of the earth's surface. The Cross-validation results indicated that ISDI construction models for three phases of growth season have very high regression accuracy. The practical application of ISDI in mid-eastern China during the reported dry year 2009 also demonstrated that it can provide accurate and detailed drought condition both at regional and local scale. This investigation showed that ISDI has good application potential for drought monitoring across China.

Lithium-ion-based battery energy storage system has started to become the most popular form of energy storage system for its high charge and discharge efficiency and high energy density. This paper proposes a high-efficiency grid-tie lithium-ion-battery-based energy storage system, which consists of a LiFePO4-battery-based energy storage and a high-efficiency bidirectional ac-dc converter. The battery management system estimates the state of charge and state of health of each battery cell and applies active charge equalization to balance the charge of all the cells in the pack. The bidirectional ac-dc converter works as the interface between the battery pack and the ac grid. A highly efficient opposed-current half-bridge-type inverter along with an admittance-compensated quasi-proportional resonant controller is adopted to ensure high power quality and precision power flow control. A 1-kW prototype has been designed and implemented to validate the proposed architecture and system performance.

This paper reports on newly developed high-performance 4H-SiC bipolar junction transistors (BJT) with improved current gain and power handling capabilities based on an intentionally designed continuously grown 4H-SiC BJT wafer. The measured dc common-emitter current gain is as high as 70, the specific ON-state resistance (RSP-ON) is as low as 3.0 mOmegamiddotcm2, and the open-base breakdown voltage (VCEO) reaches 1750 V. Large-area 4H-SiC BJTs with a footprint of 4.1 times 4.1 mm have been successfully packaged into a high-gain (beta = 50.8) high-power (80 A times 700 V) all-SiC copack and evaluated at high temperature up to 250degC. Small 4H-SiC BJTs have been stress tested under a continuous collector current density of 100 A/cm2 for 24 h and, for the first time, have shown no obvious forward voltage drift and no current gain degradation. Numerical simulations and experimental results have confirmed that simultaneous high current gain and high open-base breakdown voltage could be achieved in 4H-SiC BJTs.

This paper reports the demonstration of a hybrid Darlington bipolar junction transistor (BJT) with a high current gain and a power handling capability substantially higher than the power level of previously reported SiC Darlington BJTs. The Darlington transistor has been tested up to a collector current of 23.5 A and BV/sub ceo/ of 500 V, showing a large-signal dc common emitter current gain (/spl beta/) of 430 and an ac common emitter current gain of 650. Also reported for the first time are the Darlington characteristics up to an ambient temperature of 150/spl deg/C as well as inductively loaded half-bridge inverter switching characteristics. Comparison between a single SiC BJT and a Darlington BJT is made based on the dc and switching results at both room temperature and 150/spl deg/C, and the results are reported.

This paper describes a dual-mode digitally controlled buck converter IC for cellular phone applications. An architecture employing internal power management is introduced to ensure voltage compatibility between a single-cell lithium-ion battery voltage and a low-voltage integrated circuit technology. Special purpose analog and digital interface elements are developed. These include a ring-oscillator-based A/D converter (ring-ADC), which is nearly entirely synthesizable, is robust against switching noise, and has flexible resolution control, and a very low power ring-oscillator-multiplexer-based digital pulse-width modulation (PWM) generation module (ring-MUX DPWM). The chip, which includes an output power stage rated for 400 mA, occupies an active area 2 mm/sup 2/ in 0.25-/spl mu/m CMOS. Very high efficiencies are achieved over a load range of 0.1-400 mA. Measured quiescent current in PFM mode is 4 /spl mu/A.

This letter reports the first 4H-SiC power bipolar junction transistor (BJT) with double base epilayers which is completely free of ion implantation and hence of implantation-induced crystal damages and high-temperature activation annealing-induced surface roughness. Based on this novel design and implantation-free process, a 4H-SiC BJT was fabricated to reach an open base collector-to-emitter blocking voltage of over 1300 V, with a common-emitter current gain up to 31. Improvements on reliability have also been observed, including less forward voltage drift (< 2%) and no significant degradation on current gain in the active region.

This letter reports the experimental demonstration of the first 4H-SiC normally off high-voltage lateral junction field-effect transistor. The design and fabrication of such a device have been investigated. The fabricated device has a vertical channel length of 1.8 mum created by tilted aluminum implantation on the sidewalls of deep trenches and a lateral drift-region length of 5 mum. Normally off operation (VGS=0V) with a blocking voltage Vbr of 430 V has been achieved with a specific on-resistance Ron-sp of 12.4 mOmegamiddotcm2, which is the lowest specific on-resistance for 4H-SiC lateral power switches reported to date, resulting in a Vbr 2/Ron-sp value of 15 MW/cm2. This is among the best Vbr 2/R on-sp figure-of-merit reported to date for 4H-SiC lateral high-voltage devices

This letter reports a newly achieved best result on the specific ON-resistance (R/sub SP/spl I.bar/ON/) of power 4H-SiC bipolar junction transistors (BJTs). A 4H-SiC BJT based on a 12-/spl mu/m drift layer shows a record-low specific-ON resistance of only 2.9 m/spl Omega//spl middot/cm/sup 2/, with an open-base collector-to-emitter blocking voltage (V/sub ceo/) of 757 V, and a current gain of 18.8. The active area of this 4H-SiC BJT is 0.61 mm/sup 2/, and it has a fully interdigitated design. This high-performance 4H-SiC BJT conducts up to 5.24 A at a forward voltage drop of V/sub CE/=2.5 V, corresponding to a low R/sub SP-ON/ of 2.9 m/spl Omega//spl middot/cm/sup 2/ up to J/sub c/=859 A/cm/sup 2/. This is the lowest specific ON-resistance ever reported for high-power 4H-SiC BJTs.

This letter reports the development of a high-performance power 4H-SiC bipolar junction transistor (BJT) with, simultaneously, a high blocking voltage and a low specific on-resistance (R/spl I.bar//sub ON/). A single BJT cell with an active area of 0.61 mm/sup 2/ achieves an open base collector-to-emitter blocking voltage (V/sub ceo/) of 1677 V and conducts up to 3.2 A at a forward voltage drop of V/sub CE/=3.0 V, corresponding to a low R/spl I.bar//sub ON/ of 5.7 m/spl Omega//spl middot/cm/sup 2/ up to Jc=525 A/cm/sup 2/ and a record high value of V/sub B//sup 2//R/sub SP/spl I.bar/ON/ of 493 MW/cm/sup 2/.

This letter reports the design and fabrication of 4H-SiC bipolar junction transistors with both high voltage (>1kV) and high dc current gain (/spl beta/=32) at a collector current level of I/sub c/=3.83A (J/sub c/=319 A/cm/sup 2/). An Al-free base ohmic contact has been used which, when compared with BJTs fabricated with Al-based base contact, shows clearly improved blocking voltage. A specific on-resistance of 17 m/spl Omega//spl middot/cm/sup 2/ has been achieved for collector current densities up to 289 A/cm/sup 2/.

This work reports the development of high power 4H-SiC bipolar junction transistors (BJTs) by using reduced implantation dose for p+ base contact region and annealing in nitric oxide of base-to-emitter junction passivation oxide for 2 hours at 1150/spl deg/C. The transistor blocks larger than 480 V and conducts 2.1 A (J/sub c/=239 A/cm/sup 2/) at V/sub ce/=3.4 V, corresponding to a specific on-resistance (R/sub sp on/) of 14 m/spl Omega/cm/sup 2/, based on a drift layer design of 12 /spl mu/m doped to 6/spl times/10/sup 15/cm/sup -3/. Current gain /spl beta//spl ges/35 has been achieved for collector current densities ranging from J/sub c/=40 A/cm/sup 2/ to 239 A/cm/sup 2/ (I/sub c/=2.1 A) with a peak current gain of 38 at J/sub c/=114 A/cm/sup 2/.