Toward Energy-Efficient and Trustworthy eHealth Monitoring System

The rapid technological convergence between Internet of Things(IoT),Wireless Body Area Networks(WBANs)and cloud computing has made e-healthcare emerge as a promising application domain,which has significant potential to improve the quality of medical care.In particular,patient-centric health monitoring plays a vital role in e-healthcare service,involving a set of important operations ranging from medical data collection and aggregation,data transmission and segregation,to data analytics.This survey paper firstly presents an architectural framework to describe the entire monitoring life cycle and highlight the essential service components.More detailed discussions are then devoted to {\em data collection} at patient side,which we argue that it serves as fundamental basis in achieving robust,efficient,and secure health monitoring.Subsequently,a profound discussion of the security threats targeting eHealth monitoring systems is presented,and the major limitations of the existing solutions are analyzed and extensively discussed.Finally,a set of design challenges is identified in order to achieve high quality and secure patient-centric monitoring schemes,along with some potential solutions.     

Cooperative Spectrum Allocation with QoS Support in Cognitive Cooperative Vehicular Ad Hoc Networks

To solve the contradiction between the increasing demand of diverse vehicular wireless applications and the shortage of spectrum resource, a novel cognitive cooperative vehicular ad-hoc network （CC- VANET） framework is proposed in this paper. Firstly, we develop an adaptive cognitive spectrum sensing （ACSS） mechanism which can help to trigger and adjust the spectrum sensing window according to network traffic load status and communication quality. And then, Generalized Nash Bargaining SoLution （GNBS）, which can achieve a good tradeoff between efficiency and weighted fairness, is proposed to formulate the asymmetric inter- cell resource allocation. Finally, GNBS- Safety （GNBS-S） scheme is developed to enhance the Quality of Service （QoS） of safety applications, especially in the heavy load status, where the bandwidth demanded and supplied cannot be matched well. Furthermore, the primary user activity （PUA） which can cause rate loss to secondary users, is also considered to alleviate its influence to fairness. Simulation results indicate that the proposed CC-VANET scheme can greatly improve the spectrum efficiency and reduce the transmission delay and packet loss rate on the heavy contention status. And GNBS spectrum allocation scheme outperforms both the Max-rain and Max-rate schemes, and canenhance the communication reliability of safety service considerably in CC-VANET.     

A NOVEL LINK ADAPTATION SCHEME TO ENHANCE PERFORMANCE OF IEEE 802.11G WIRELESS LAN

A novel link adaptation scheme using linear Auto Regressive （AR） model channel estimation algorithm to enhance the performance of auto rate selection mechanism in IEEE 802.11g is proposed. This scheme can overcome the low efficiency caused by time interval between the time when Received Signal Strength （RSS） is measured and the time when rate is selected. The best rate is selected based on data payload length, frame retry count and the estimated RSS, which is estimated from recorded RSSs. Simulation results show that the proposed scheme enhances mean throughput performance up to 7%, in saturation state, and up to 24% in finite load state compared with those non-estimation schemes, performance enhancements in average drop rate and average number of transmission attempts per data frame delivery also validate the effectiveness of the proposed schelne.     

OPTIMAL ANTENNA SUBSET SELECTION AND BLIND DETECTION APPROACH APPLIED TO ORTHOGONAL SPACE-TIME BLOCK CODING

An approach combining optimal antenna subset selection with blind detection scheme for Orthogonal Space-Time Block Coding （OSTBC） is proposed in this paper. The optimal antenna subset selection is taken into account at transmitter and/or receiver sides, which chooses the optimal antennas to increase the diversity order of OSTBC and improve further its performance. In order to enhance the robustness of the detection used in the conventional OSTBC scheme, a blind detection scheme based on Independent Component Analysis （ICA） is exploited which can directly extract transmitted signals without channel estimation. Performance analysis shows that the proposed approach can achieve the full diversity and the flexibility of system design by using the antenna selection and the ICA based blind detection schemes.     

RATE ADAPTIVE PROTOCOL FOR MULTIRATE IEEE 802.11 NETWORKS

In this paper, a rate adaptive protocol AMARF (Adaptive Multirate Auto Rate Fallback) for multirate IEEE 802.11 networks is proposed. In AMARF, each data rate is assigned a unique success threshold, which is a criterion to judge when to switch a rate to the next higher one, and the success thresholds can be adjusted dynamically in an adaptive manner according to the running conditions, such as packet length and channel parameters. Moreover, the proposed protocol can be implemented by software without any change to the current IEEE 802.11 standards. Simulation result shows that AMARF yields significantly higher throughput than other existing schemes including ARF and its variants, in various running conditions.     

Collinear holographic data storage technologies

In the era of information explosion,the demand of data storage is increased dramatically.Holographic data storage technology is one of the most promising next-generation data storage technologies due to its high storage density,fast data transfer rate,long data life time and less energy consumption.Collinear holographic data storage technology is the typical solution of the holographic data storage technology which owns a more compact,compatible and practical system.This paper gives a brief review of holographic data storage,introduces collinear holographic data storage technology and discusses phase modulation technology being used in the holographic data storage system to achieve higher storage density and higher data transfer rate.     

Modulating nitric oxide levels in dorsal root ganglion neurons of rat with low-level laser therapy

A novel fiber Bragg grating(FBG)rain gauge is proposed in this paper to achieve high precision rainfall measurement.One core sensitive FBG,a temperature compensation FBG and a mechanical transition system construct this novel FBG rain gauge.Sensing principle of this FBG rain gauge is explained in detail,and its theoretical calculation model is also established,which shows that the relationship between center wavelength of sensitive FBG and external rainfall has very good linearity.To verify its detection performance,the calibration experiment on one prototype of this FBG rain gauge is carried out.After experiment data analysis,the detection precision of this FBG rain gauge is 15.4μm which is almost two orders of magnitude higher than that of the existing rainfall measurement device.The experimental data confirm that this FBG rain gauge can achieve rainfall measurement with high precision.     

Automatic detection of breast nodule in the ultrasound images using CNN

Breast cancer is the most common cancer among women worldwide.Ultrasound is widely used as a harmless test for early breast cancer screening.The ultrasound network(USNet) model is presented.It is an improved object detection model specifically for breast nodule detection on ultrasound images.USNet improved the backbone network,optimized the generation of feature maps,and adjusted the loss function.Finally,USNet trained with real clinical data.The evaluation results show that the trained model has strong nodule detection ability.The mean average precision(mAP) value can reach 0.734 9.The nodule detection rate is 95.11%,and the in situ cancer detection rate is 79.65%.At the same time,detection speed can reach 27.3 frame per second(FPS),and the video data can be processed in real time.     

Outsourced Privacy-Preserving Anomaly Detection in Time Series of Multi-Party

Anomaly detection has practical significance for finding unusual patterns in time series.However,most existing algorithms may lose some important information in time series presentation and have high time complexity.Another problem is that privacy-preserving was not taken into account in these algorithms.In this paper,we propose a new data structure named Interval Hash Table(IHTable)to capture more original information of time series and design a fast anomaly detection algorithm based on Interval Hash Table(ADIHT).The key insight of ADIHT is distributions of normal subsequences are always similar while distributions of anomaly subsequences are different and random by contrast.Furthermore,to make our proposed algorithm fit for anomaly detection under multiple participation,we propose a privacy-preserving anomaly detection scheme named OP-ADIHT based on ADIHT and homomorphic encryption.Compared with existing anomaly detection schemes with privacy-preserving,OP-ADIHT needs less communication cost and calculation cost.Security analysis of different circumstances also shows that OP-ADIHT will not leak the privacy information of participants.Extensive experiments results show that ADIHT can outperform most anomaly detection algorithms and perform close to the best results in terms of AUC-ROC,and ADIHT needs the least time.     

Asymboost-based fisher linear classifier for face recognition

When using AdaBoost to select discriminant features from some feature space （e.g. Gabor feature space） for face recognition, cascade structure is usually adopted to leverage the asymmetry in the distribution of positive and negative samples. Each node in the cascade structure is a classifier trained by AdaBoost with an asymmetric learning goal of high recognition rate but only moderate low false positive rate. One limitation of AdaBoost arises in the context of skewed example distribution and cascade classifiers： AdaBoost minimizes the classification error, which is not guaranteed to achieve the asymmetric node learning goal. In this paper, we propose to use the asymmetric AdaBoost （Asym-Boost） as a mechanism to address the asymmetric node learning goal. Moreover, the two parts of the selecting features and forming ensemble classifiers are decoupled, both of which occur simultaneously in AsymBoost and AdaBoost. Fisher Linear Discriminant Analysis （FLDA） is used on the selected features to learn a linear discriminant function that maximizes the separability of data among the different classes, which we think can improve the recognition performance. The proposed algorithm is demonstrated with face recognition using a Gabor based representation on the FERET database. Experimental results show that the proposed algorithm yields better recognition performance than AdaBoost itself.     

Stochastic approximation based on-line algorithm for fairness in multi-rate wireless LANs

It is well known that IEEE 802.11 based MAC provides max–min fairness to all nodes even in a multi-rate WLAN. However, the max–min fairness may not always be the preferred fairness criteria as it significantly reduces overall system throughput. In this paper, we explore the proportional fairness and the time fairness. First, we obtain a condition that must be satisfied by the attempt probabilities to achieve proportional fairness. Using this condition, we propose a stochastic approximation based on-line algorithm that tunes attempt probabilities to achieve proportional fairness. The proposed algorithm can be implemented in a distributed fashion, and can provide optimal performance even when node uses a rate adaptation scheme. Next, we show that the time fairness is a special case of weighted max–min fairness with the weight for a node is equal to its transmission rate. Thus, the existing algorithms to achieve weighted max–min fairness can be used to achieve time fairness as well. This exposition also demonstrates that the proportional fairness and the time fairness are not the same contrary to what was conjectured. Performance comparison of various fairness criteria is done through ns-3 simulations. Simulation results show that time fair schemes achieve the highest throughput, and the sum of logarithm of individual node’s throughputs under the time fairness is close to that under a proportionally fair scheme.     

Analysis of fair rate calculations in resilient packet ring aggressive mode

Resilient packet ring (RPR) standardized as IEEE 802.17 is a new medium access control (MAC) protocol for metro-ring networks. RPR supports spatial reuse which increases the achieved throughput but it can also result in congestion and starvation of nodes on the ring. Therefore, it is necessary to employ mechanisms to enforce a fair allocation of the ring bandwidth in RPR. In order to maintain fairness among nodes, a fairness algorithm is deployed at each RPR node. When a node detects congestion, it calculates a fair rate which is advertised to all upstream nodes contributing to congestion. Upon receiving the fair rate, the upstream nodes limit the rate of their injected traffic to the advertised fair rate. Consequently, the congested node can utilize the unused capacity and add its local traffic to the ring. In this paper, we develop an analytical model for fair rate calculation in the RPR aggressive mode fairness algorithm in the parking-lot scenario. This model provides an insight on dynamics of the RPR fairness algorithm and can be used to evaluate its performance. We investigate this problem in two cases. First, we assume that the link propagation delay is zero and derive the fair rate equations for this ideal case. We then consider the link propagation delay and develop a more realistic model. We verify the accuracy of our model by simulation results. Furthermore, we use the developed model to study the impact of various parameters on convergence of the fair rate.     

信道公平分配的局部拥塞控制算法

提出基于信道公平分配的局部拥塞控制算法FCA(fair channel allocation),在缓解局部拥塞的同时增强信道分配的公平性。为减少获取邻居节点实时缓存信息的通信开销和提高以单一节点缓存是否溢出为检测模型的准确性,FCA采用以节点实时缓存长度预测为基础的邻居节点缓存总长度和分组平均传输延迟作为检测指标的拥塞检测模型。为避免使用独立拥塞通告消息增加信道负载,FCA采用在ACK控制帧中增加一个节点地址位携带拥塞信息。在去拥塞阶段,FCA采用基于实时缓存长度和队列优先权值的信道分配机制保证公平传输和防止部分节点因缓存增速过快导致溢出分组丢失。实验结果表明,FCA在碰撞次数、分组传递率、吞吐量和公平性等方面相比802.11、CODA和PCCP具有显著优势。     

Achieving inter-session fairness for layered video multicast

The Internet is increasingly used to deliver multimedia services. Since there are heterogeneous receivers and changing network conditions, it has been proposed to use adaptive rate control techniques such as layered video multicast to adjust the video traffic according to the available Internet resources. A problem of layered video multicast is that it is unable to provide fair bandwidth sharing between competing video sessions. We propose two schemes, layered video multicast with congestion sensitivity and adaptive join-timer (LVMCA) and layered video multicast with priority dropping (LVMPD), to achieve inter-session fairness for layered video multicast. Receiver-driven layered multicast (RLM), layer-based congestion sensitivity, LVMCA, and LVMPD are simulated and compared. Results show both proposed schemes, especially LVMPD, are fairer and have shorter convergence time than the other two schemes.     

Improving fairness of PGMCC

PGM congestion control (pgmcc), a single‐rate multicast congestion control scheme, is one of the most promising schemes which aim to solve the problem of multicast fairness with TCP. However, by deep investigation, we find that there exist two inappropriate mechanisms in this scheme, which are the fixed slow start threshold (ssthresh) and the mechanism of changing a group representative (acker). Our experiments have revealed the fact that these mechanisms can lead to the unfairness of pgmcc under some network conditions. In this paper, two new mechanisms have been proposed to replace the original ones. One mechanism is to make the sender adapt the value of ssthresh to the network conditions to mimic the action of TCP, and in order to avoid being more aggressive than TCP, the other one is to make the sender reduce the congestion window by half when the acker changes. Our experiment results, parts of which are discussed in this paper, show that the modified pgmcc can achieve better performance than the original one. Copyright © 2005 John Wiley & Sons, Ltd.     

On the performance and fairness of dynamic channel allocation in wireless mesh networks

Channel assignment in multichannel multiradio wireless mesh networks is a powerful resource management tool to exploit available multiple channels. Channels can be allocated either statically on the basis of long‐term steady state behavior of traffic or dynamically according to actual traffic demands. It is a common belief that dynamic schemes provide better performance; however, these two broad classes of channel allocation schemes have not been compared in detail. In this paper, we quantify the achievable performance gain and fairness improvement through an optimal dynamic channel allocation scheme. We develop optimal algorithms for a dynamic and three static schemes using mixed integer linear programming and compare them in the context of QoS provisioning, where network performance is measured in terms of acceptance rate of QoS sensitive traffic demands. Our extensive simulations show that static schemes should optimize channel allocation for long‐term traffic pattern and maintain max–min fairness to achieve acceptable performances. Although the dynamic and max–min fair static schemes accomplish the same fairness, the dynamic channel allocation outperforms the static scheme about 10% in most cases. In heavily overloaded regimes, especially when network resources are scarce, both have comparable performances, and the max–min fair scheme is preferred because it incurs less overhead. Copyright © 2011 John Wiley & Sons, Ltd.     

A reduced-power channel reuse scheme for wireless packet cellularnetworks

We present a novel reduced-power channel reuse scheme to improve the spectrum efficiency in wireless packet cellular networks. The basic idea is to reduce intercellular interference and improve the capture probability by an a priori assignment of power levels of channels used in different cells. We formulate and solve an optimal channel-selection problem for our scheme. We find that the optimal policy is in a form of bang-bang control. We illustrate our channel-selection solution by a case study with uniform fairness constraint. We evaluate, via numerical analysis and simulation, both throughput and delay of the new scheme, and compare them with other schemes. We find that our scheme can achieve significant performance improvements, in terms of both the maximum throughput and throughput-delay tradeoff, over a wide range of capture ratio values     

Distributed two‐hop proportional fair resource allocation in Long Term Evolution Advanced networks

In Long Term Evolution Advanced networks with Type I in‐band half‐duplex decode‐and‐forward relay nodes, proportional fair (PF) resource allocation is aiming at guaranteeing two‐hop match and optimising global proportional fairness. The two‐hop match is defined as equal data rates in the access links and the corresponding backhaul links. The global proportional fairness is between all the user equipments served by the evolved nodes B and the relay nodes. Existing centralised schemes achieve these targets at the cost of enormous channel state information (CSI) exchange. Existing distributed schemes focus on resource partitioning and employ a traditional single‐hop PF scheduling algorithm in access links, with less CSI exchange. The traditional PF scheduling algorithm maximises single‐hop proportional fairness between the data rates in the access links rather than two‐hop proportional fairness between the end‐to‐end data rates in the two hops. In order to reduce CSI exchange and at the same time to maximise the two‐hop proportional fairness, a distributed two‐hop PF resource allocation scheme is proposed. The proposed scheme includes two‐hop PF resource scheduling algorithms and adaptive resource partitioning algorithms, applied in different two‐hop transmission protocols. Simulation results demonstrate the proposed scheme is better than the existing distributed schemes in obtaining better proportional fairness and larger cell‐edge user equipment throughputs. Copyright © 2014 John Wiley & Sons, Ltd.     

Distributed Proportional Fair Scheduling for IEEE802.11 Wireless LANs

In the time varying wireless channel, opportunistic scheduling is one of the important techniques to achieving the rich diversities inherent in wireless communications. However, most existing scheduling schemes require centralized scheduling and little work has been done on developing distributed algorithms The proportional fair scheduling is one of the representative opportunistic scheduling for centralized networks. In this paper, we propose distributed proportional fair scheduling (DPFS) scheme for wireless LAN network. In the proposed DPFS scheme, each receiver estimates channel condition and calculates independently its own priority with probabilistic manner, which can reduce excessive probing overhead required to gather the channel conditions of all receivers. We evaluate the proposed DPFS using extensive simulation and simulation results show that DPFS obtains higher network throughput than conventional scheduling schemes while maintaining fairness among users.     

Predictive Congestion Control Protocol for Wireless Sensor Networks

Available congestion control schemes, for example transport control protocol (TCP), when applied to wireless networks, result in a large number of packet drops, unfair scenarios and low throughputs with a significant amount of wasted energy due to retransmissions. To fully utilize the hop by hop feedback information, this paper presents a novel, decentralized, predictive congestion control (DPCC) for wireless sensor networks (WSN). The DPCC consists of an adaptive flow and adaptive back-off interval selection schemes that work in concert with energy efficient, distributed power control (DPC). The DPCC detects the onset of congestion using queue utilization and the embedded channel estimator algorithm in DPC that predicts the channel quality. Then, an adaptive flow control scheme selects suitable rate which is enforced by the newly proposed adaptive backoff interval selection scheme. An optional adaptive scheduling scheme updates weights associated with each packet to guarantee the weighted fairness during congestion. Closed-loop stability of the proposed hop-by-hop congestion control is demonstrated by using the Lyapunov-based approach. Simulation results show that the DPCC reduces congestion and improves performance over congestion detection and avoidance (CODA) [3] and IEEE 802.11 protocols.