Energy efficient dispatch strategy for the dual-functional mobile sink in wireless rechargeable sensor networks

Scavenging energy from radio-frequency (RF) signals has drawn significant attention in recent years. By introducing the technology of RF energy harvesting into wireless sensor networks, a new type of network named mobile data gathering based wireless rechargeable sensor network (MGWRSN) is considered in this paper. In the MGWRSN, a dual-functional mobile sink (MS) which has the abilities of data collecting and RF energy generating is employed. Data sensed by sensor nodes is gathered at several selected head nodes (HNs). Through using the RF energy supplied by the MS, the HNs deliver the gathered data to the MS arriving at the corresponding rendezvous points (RPs). In our works, the network energy consumption model of the MGWRSN is built, and the energy efficient dispatch strategy for the MS is studied, aiming at cutting down the total network energy consumption. For the simplest case, i.e., the one-HN MGWRSN, the optimal location of the RP is provided to minimize the total network energy consumption. After that, the researches are extended into the case of multi-HN MGWRSN and a heuristic dispatch strategy named HEEDS is proposed. Theoretical analysis and numerical results show that: (1) in the one-HN MGWRSN, the optimal location of the RP is close related to the data bulk to be transmitted, the unit mobility energy cost, the required bit error rate, the modulation scheme, and the departure position of the MS; (2) comparing with the existing algorithm WRP which directly dispatches the MS to the locations of HNs to collect data, the proposed strategy HEEDS is shown to be more energy efficient. Moreover, when a high energy transfer power is available at the MS, HEEDS renders shorter packet delay compared to WRP.     

移动协助传感器网络中Sink的路径优化策略

在无线传感器网络中引入移动Sink来解决。静态无线传感器网络(所有节点均为静止)存在的能量空洞、冗余覆盖和热点等问题。传感器节点将数据发送给汇聚节点(CP,collection point),移动Sink访问CP节点收集数据。提出了一种最短移动距离最小能耗的路径优化模型(MEMD)。证明了该模型是一个NP-hard问题,给出了一种基于效用的贪心启发式方法用于确定最佳的CP节点队列。为了在规定的最大传输延时的范围内访问尽可能多的CP节点,提出了一种基于CP节点访问概率的路径选择算法。通过模拟实验以及实验床的真实数据,提出的算法能很好地在满足延时要求的同时节约网络的能量。     

Data gathering via mobile sink in WSNs using game theory and enhanced ant colony optimization

Optimal performance and improved lifetime are the most desirable design benchmarks for WSNs and the mechanism for data gathering is a major constituent influencing these standards. Several researchers have provided significant evidence on the advantage of mobile sink (MS) in performing effective gathering of relevant data. However, determining the trajectory for MS is an NP-hard-problem. Especially in delay-inevitable applications, it is challenging to select the best-stops or rendezvous points (RPs) for MS and also to design an efficient route for MS to gather data. To provide a suitable solution to these challenges, we propose in this paper, a game theory and enhanced ant colony based MS route selection and data gathering (GTAC-DG) technique. This is a distributed method of data gathering using MS, combining the optimal decision making skill of game theory in selecting the best RPs and computational swarm intelligence of enhanced ant colony optimization in choosing the best path for MS. GTAC-DG helps to reduce data transfer and management, energy consumption and delay in data delivery. The MS moves in a reliable and intelligent trajectory, extending the lifetime and conserving the energy of WSN. The simulation results prove the effectiveness of GTAC-DG in terms of metrics such as energy and network lifetime.

     

Efficient Approach for Maximizing Lifespan in Wireless Sensor Networks by Using Mobile Sinks

Recently, sink mobility has been shown to be highly beneficial in improving network lifetime in wireless sensor networks (WSNs). Numerous studies have exploited mobile sinks (MSs) to collect sensed data in order to improve energy efficiency and reduce WSN operational costs. However, there have been few studies on the effectiveness of MS operation on WSN closed operating cycles. Therefore, it is important to investigate how data is collected and how to plan the trajectory of the MS in order to gather data in time, reduce energy consumption, and improve WSN network lifetime. In this study, we combine two methods, the cluster‐head election algorithm and the MS trajectory optimization algorithm, to propose the optimal MS movement strategy. This study aims to provide a closed operating cycle for WSNs, by which the energy consumption and running time of a WSN is minimized during the cluster election and data gathering periods. Furthermore, our flexible MS movement scenarios achieve both a long network lifetime and an optimal MS schedule. The simulation results demonstrate that our proposed algorithm achieves better performance than other well‐known algorithms.     

Distributed trajectory design for data gathering using mobile sink in wireless sensor networks

Several studies have demonstrated the benefits of using a mobile sink (MS) to reduce energy consumption resulting from multi-hop data collection using a static sink in wireless sensor networks (WSNs). However, using MS may increase data delivery latency as it needs to visit each sensor node in the network to collect data. This is a critical issue in delay-sensitive applications where all sensed data must be gathered within a given time constraint. In this paper, we propose a distributed data gathering protocol utilizing MS for WSNs. The proposed protocol designs a trajectory for the MS, which minimizes energy consumption and delay. Our protocol operates in four main phases: data sensing, rendezvous point (RP) selection, trajectory design, and data gathering. In data sensing, a number of deployed sensor nodes keep sensing the target field for a specific period of time to capture events. Then, using a cluster-based RP selection algorithm, some sensor nodes are selected to become RPs based on local information. The selected RPs are then used to determine a trajectory for the MS. To do so, we propose three trajectory design algorithms that support different types of applications, namely reduced energy path (REP), reduced delay path (RDP), and delay bound path (DBP). The MS moves through the constructed path to accomplish its data gathering according to an effective scheduling technique that is introduced in this work. We validate the proposed protocol via extensive simulations over several metrics such as energy, delay, and time complexity.     

Energy efficient path selection for mobile sink and data gathering in wireless sensor networks

Mobile sink (MS) has drawn significant attention for solving hot spot problem (also known as energy hole problem) that results from multihop data collection using static sink in wireless sensor networks (WSNs). MS is regarded as a potential solution towards this problem as it significantly reduces energy consumption of the sensor nodes and thus enhances network lifetime. In this paper, we first propose an algorithm for designing efficient trajectory for MS, based on rendezvous points (RPs). We next propose another algorithm for the same problem which considers delay bound path formation of the MS. Both the algorithms use k-means clustering and a weight function by considering several network parameters for efficient selection of the RPs by ensuring the coverage of the entire network. We also propose an MS scheduling technique for effective data gathering. The effectiveness of the proposed algorithms is demonstrated through rigorous simulations and comparisons with some of the existing algorithms over several performance metrics.     

Scheduled power-saving mechanism to minimize energy consumption in IEEE 802.16e systems

A Mobile Station in IEEE 802.16e operates power management using sleep-mode operation with one or more connections supporting several applications. After all of the connections of an MS transit into the sleep state, the MS powers down and then goes into an unavailable state without communicating with the serving Base Station. To improve energy conservation, this letter proposes a new Scheduled Power-Saving Mechanism, which schedules sleep-mode operations for connections, which newly initiate sleep-mode, by controlling operating parameters, such as the minimum sleep interval (Tmin) and the maximum sleep interval (Tmax), and the initiation time of sleepmode operations of low Quality of Service (QoS) connections. Performance results show that the proposed mechanism can reduce the available state of an MS through this scheduling, and thus achieve better energy conservation of the MS than the standard mechanism.     

Single- and multi- user uplink energy-efficient resource allocation algorithms with users’ power and minimum rate constraint in OFDMA cellular networks

In this paper, single- and multi- user Resource Allocation (RA) optimization problems considering transmit power and minimum rate constraint of Mobile Station (MS) for maximizing MS’ energy efficiency, measured as bits-per-joule (bpj), are addressed. Assume channel state information of all MSs is known by base station. We propose uplink RA algorithms, performing subcarrier assignment and power allocation, for optimizing bpj of MS in a single-cell OFDMA-based cellular network for both single- and multi- user scenarios. In the single-user case, we propose RA algorithms, which utilize the closed-form solution derived by applying Lambert-W function and an iterative approach based on Karush–Kuhn–Tucker conditions respectively to achieve optimal bpj of MS. In the multi-user case, centralized iterative multi-user RA algorithms for maximizing sum of MS’ bpj, performing joint subcarrier assignment and power allocation iteratively, are proposed by utilizing the proposed single-user RA schemes. In particular, tradeoffs between energy efficiency and spectral efficiency are fully investigated, and the influence of MS’ power and minimum rate constraints on bpj performance is also studied. The effectiveness of proposed algorithms is presented by numerical experiments. Numerical results demonstrate the proposed algorithms can enhance bpj significantly with limited loss of total throughput compared to the sum-rate maximization algorithm (in Moretti et al., IEEE Trans Veh Technol 60(4):1788–1798, 2011).     

Self Organized,Flexible, Latency and Energy Efficient Protocol for Wireless Sensor Networks

This paper presents Self Organized, Flexible, Latency and Energy Efficient (SOFLEE) Protocol, a cross-layer protocol for Wireless Sensor Networks that uses TDMA based medium access scheme combined with multi-hop routing information during time slot allocation. Time slot allocation is done centrally by Master Station (MS) to provide a collision-free and fair media access. MS allocates same transmission slot to nodes that are two hops apart to increase channel spatial reuse and decrease data latency. For data gathering at MS, SOFLEE uses parenthood willingness to forward data to MS through unidirectional tree rooted at MS. Parenthood willingness of a node is decided using: (i) its location with respect to MS, to forward data in correct direction; (ii) its number of children, to prevent local congestion; (iii) its residual energy, to uniformly distribute energy load of being a parent node and (iv) its parent–child communication link reliability to guarantee consistent data delivery. The parenthood willingness requires simple comparisons against thresholds, and thus, is very simple to implement on memory and computationally constrained nodes. Unlike a conventional TDMA-based protocol, SOFLEE provides flexibility to transfer data slots among nodes and priority based slot scheduling to adapt to dynamic traffic patterns of various Wireless Sensor Network applications. Finally, simple, memory and energy efficient techniques for: (i) hop-by-hop congestion control; (ii) catering to orphan nodes, link breakdowns and node deaths are incorporated in SOFLEE. A comparative analysis of SOFLEE, FlexiTP, self organized TDMA protocol, energy efficient fast forwarding and D-MAC show that SOFLEE is 25 to 61 % more energy efficient compared to FlexiTP. Data latency of SOFLEE is 32 to 68 % less, delivery ratio is 7 to 19 %, goodput is 3 % and network lifetime is 253.784 s to 448.440 s more compared to FlexiTP.     

Optimized mobile sink based grid coverage-aware sensor deployment and link quality based routing in wireless sensor networks

Mobile sink (MS) has been used in wireless sensor networks (WSN) to increase the network lifetime by changing the location over time. The major quality of service given by WSN is coverage energy consumption (EC) and network lifetime. There are many methods implemented for enhance the coverage hole restoration and reduce the EC. We propose a novel MSCOLER (MS based Coverage Optimization and Link-stability Estimation Routing) protocol for Optimal Coverage restoration and Link stability Estimation. An optimization algorithm is used to optimize the coverage hole and move the redundant node besides the hole. During the routing process, link quality based routing is used to discover the relay nodes with the estimation of link stability to enhance the entire network lifetime and practically make the perfect transmission distance for energy saving. Experimental results demonstrate that proposed protocol can solve the coverage restoration problem, decrease the EC and reduce the network lifetime. The performance is evaluated regarding Average of residual energy (ARE), Receiving packets ratio (RPR), Moving energy consumption (MEC), Network lifetime (NL), Percentage of coverage (%C) and Average Energy Consumption (AEC).     

模糊分段光滑图像分割模型及其快速算法

灰度分布不均图像是图像分割中一个难点,为此提出一种模糊分段光滑(FPS)图像分割模型.借鉴分段光滑Mumford-Shah(MS)模型与模糊聚类思想,新模型通过两个定义在图像域的光滑函数描述区域特征,并利用模糊隶属度函数代替MS模型中的特征函数.同时,边界检测算子的引入能够有效保护图像中的边界信息.数值求解采用分裂Br...     

A 12-bit intrinsic accuracy high-speed CMOS DAC

A 12-bit intrinsic accuracy digital-to-analog (D/A) converter integrated in a standard digital 0.5 μm CMOS technology is presented. It is based on a current steering doubly segmented 6+2+4 architecture and requires no calibration, no trimming, or dynamic averaging. The differential nonlinearity (DNL) and integral nonlinearity (INL) are 0.3 and 0.6 least significant bits (LSB's), respectively. The measured glitch energy is 1.9 pV.s. For a 12-bit resolution, the converter reaches an update rate of 300 MS/s. By reducing the voltage supply of the latches to 2.0 V, the glitch energy is reduced to sub-pV.s, and the update rate reaches 500 MS/s, for a resolution of 8 bits. The worst case power consumption is 320 mW, and it operates from a single 3.3 V voltage supply. The die area is 3.2 mm²     

Electrical characteristics of GaAs MIS Schottky diodes

The current-voltage (I-V) and capacitance-voltage (C-V) characteristics of GaAs metal-insulator-semiconductor (MIS) Schottky barrier diodes are investigated over a wide temperature range and compared with MS diodes. The effects of the insulating layer on barrier height and carrier transport are delineated by an activation energy analysis. Excess currents observed at low forward and reverse bias have also been analyzed and their cause identified. A capacitance anomaly consistently noticed in MIS Schottky barriers is resolved by stipulating a non-uniform interfacial layer, and a self-consistent model of the GaAs MIS Schottky barrier is developed by analyzing I-V and C-V data of both MIS and MS diodes.     

802.16e系统中一种针对多用户实时业务的改进休眠算法

在802.16e系统中,当具有实时业务的多个移动站点(MS)同时进入休眠模式时,重叠的侦听窗口上数据调度的竞争将会影响MS的节能效率。该文对这种实时业务下多MS同时进入休眠模式的场景进行分析,提出了一种改进的休眠算法。该算法通过调整新加入连接休眠模式的启动时间,使得各MS的侦听窗口尽量分散,实现系统负载在OFDM帧上较为均匀的分布,从而提高网络的平均节能效果。仿真结果表明所提出算法不仅能够提高系统平均的节能效率,还能够降低系统的信令开销,同时在整体上提高系统的QoS保障。     

MultiTempGAN: Multitemporal multispectral image compression framework using generative adversarial networks

Multispectral satellites that measure the reflected energy from the different regions on the Earth generate the multispectral (MS) images continuously. The following MS image for the same region can be acquired with respect to the satellite revisit period. The images captured at different times over the same region are called multitemporal images. Traditional compression methods generally benefit from spectral and spatial correlation within the MS image. However, there is also a temporal correlation between multitemporal images. To this end, we propose a novel generative adversarial network (GAN) based prediction method called MultiTempGAN for compression of multitemporal MS images. The proposed method defines a lightweight GAN-based model that learns to transform the reference image to the target image. Here, the generator parameters of MultiTempGAN are saved for the reconstruction purpose in the receiver system. Due to MultiTempGAN has a low number of parameters, it provides efficiency in multitemporal MS image compression. Experiments were carried out on three Sentinel-2 MS image pairs belonging to different geographical regions. We compared the proposed method with JPEG2000-based conventional compression methods and three deep learning methods in terms of signal-to-noise ratio, mean spectral angle, mean spectral correlation, and laplacian mean square error metrics. Additionally, we have also evaluated the change detection performances and visual maps of the methods. Experimental results demonstrate that MultiTempGAN not only achieves the best metric values among the other methods at high compression ratios but also presents convincing performances in change detection applications.     

Dispersion of the Somatosensory Evoked Potential (SEP) in Multiple Sclerosis

A fast Fourier transform technique was used to quantitate the dispersion of the somatosensory evoked potential elicited by median nerve stimulation. The evaluation was proportional to the log of the SEP spectral energy between 380 and 1000 Hz. This was linearly scaled to a range of numbers between zero and five representing minimal mal to severe degrees of dispersion, respectively. In 21 controls, dispersion measured 1.5 ±0.6 with an upper normal limit of 2.5. In 24 MS suspects, dispersion ranged between 0.3 and 3.9. A Bayesian decision-maker, based only on spectral energy, correctly classified all of the control group and 63 percent of a patient group with definite, probable, or suspected MS. Dispersion of the SEP, when used along with other factors such as latency and shape, adds to overall diagnostic accuracy.     

Design of Predictive and Dynamic Energy-Efficient Mechanisms for IEEE 802.16e

Three predictive and dynamic sleep time planning (PDSTP) energy-efficient mechanisms are proposed in this paper to simultaneously improve energy efficiency and packet delay for IEEE 802.16e. To estimate the time instant when a mobile station (MS) should wake up for receiving downlink packets, a prediction method is designed. With the predicted time instant, an MS is then allowed to sleep as much as possible using multiple maximum sleep intervals followed by a smaller sleep interval before the predicted time instant. After the predicted time instant, a few smaller sleep intervals with a trend of constant level (CL), exponential decrease (ED), or linear decrease (LD) can be further arranged. To react to the outlier of prediction, exponential increase for sleep intervals can be extended. The combination of the aforementioned designs then forms our three proposed mechanisms, namely, PDSTP-CL, PDSTP-ED, and PDSTP-LD. Via simulations, we show that PDSTP-CL not only performs better than PDSTP-ED and PDSTP-LD under general situations but also outperforms the standard sleep mode operation of the type-I power saving class (PSC-I) in IEEE 802.16e and the exponential sleep time backoff mechanism (ESTBM) in the literature in terms of energy efficiency and packet delay.     

Energy efficient scheduling for downlink elastic traffic in wireless networks

In wireless networks, maximizing throughput and minimizing energy consumption are two conflicting objectives. For elastic traffic, it is the total completion time, not the delay constraint of a single packet or the short‐term throughput requirement, that directly affects the quality‐of‐service (QoS). At the same time, the energy consumption should be minimized in order to prolong the battery lifetime of the mobile station (MS). In this paper, we propose energy efficient schedulers that consider throughput and energy saving simultaneously. Through extensive simulations, we compare the proposed schemes with the conventional scheme where a mobile terminal stays awake until all the pending packets are completely serviced. The simulation results show that our schemes outperform the conventional one in terms of utility, i.e., user satisfaction, which is defined as inversely proportional to the multiplication of weighted service completion time and energy consumption. Copyright © 2009 John Wiley & Sons, Ltd.     

Two-step V<Subscript>cm</Subscript>-based MS switching method with dual-capacitive arrays for SAR ADCs

An ultra-low-power two-step merge and split (MS) switching method for a dual-capacitive arrays (DCAs) successive approximation register analogue-to-digital converter is presented. This method only requires two reference levels, i.e. Gnd and V_cm (V_cm = 1/2V_ref). Compared with the conventional method, the proposed method achieves 99.89 and 80.96% reduction in average switching energy and capacitors, respectively, meanwhile maintaining good linearity. In addition, it barely consumes reset energy and keeps common-mode voltage of DCAs almost constant.     

Multi‐Shell Porous TiO2 Hollow Nanoparticles for Enhanced Light Harvesting in Dye‐sensitized Solar Cells

An optimized configuration for nanomaterials in working electrodes is vital to the high performance of dye‐sensitized solar cells (DSSCs). Here, a fabrication method is introduced for multi‐shell TiO₂ hollow nanoparticles (MS‐TiO₂‐HNPs) via a sol–gel reaction, calcination, and an etching process. The prepared uniform MS‐HNPs have a high surface area (ca. 171 m² g^?1), multireflection, and facile electrolyte circulation and diffusion. During the MS‐HNP fabrication process, the amount of SiO₂ precursor and H₂O under reaction has a significant effect on aggregation and side reactions. The etching process to obtain pure TiO₂ is influenced by anatase crystallinity. Additionally, single‐shell (SS)‐TiO₂‐HNPs and double‐shell (DS)‐TiO₂‐HNPs are synthesized as a control. The MS‐TiO₂‐HNPs exhibit a high surface area and enhance light reflectance, compared with the SS‐ and DS‐TiO₂‐HNPs of the same size. The power conversion efficiency of the optimized MS‐TiO₂‐HNP‐based DSSCs is 9.4%, compared with the 8.0% efficiency demonstrated by SS‐TiO₂‐HNP‐DSSCs (a 17.5% improvement). These results enable the utilization of multifunctional MS‐HNPs in energy material applications, such as lithium ion batteries, photocatalysts, water‐splitting, and supercapacitors.