Ensuring Survivability of Resource-intensive Sensor Networks Through Ultra-Low Power Overlays

Ensuring Survivability of Resource-Intensive Sensor Networks Through Ultra-Low Power Overlays

Michele Magno,Member,IEEE,David Boyle,Member,IEEE,Davide Brunelli,Member,IEEE,

Emanuel Popovici,Senior Member,IEEE,and Luca Benini,Fellow,IEEE

Abstract—Nodes in wireless sensor networks(WSNs)typically have limited power supply and networks are often expected to be functional for extended periods.Therefore,the minimization of energy consumption and the maximization of network lifetime are key objectives in WSN.This paper proposes an overlay,energy optimized,sensor network to extend the functional lifetime of an energy-intensive sensor network application.The overlay network consists of additional nodes that exploit recent advances in energy harvesting and wake-up radio technologies,coupled with an appli-cation speci?c,complementary,ultra-low power sensor.The exper-imental results and simulations demonstrate that this approach can ensure survivability of energy-inef?cient sensor networks.Simulat-ing applications using energy-intensive video cameras and air quality sensors,combined with the proposed overlayed ultra-low power sensor network,demonstrates that this approach can in-crease functional lifetime toward perpetual operation and is suitable for WSN applications in which complementarity exists between the required energy-intensive sensors and low-cost sensors that can be used as triggers.

Index Terms—Energy ef?ciency,multi-source energy harvesters, overlay networks,power electronics,power management,wake-up radio,wireless sensor networks(WSNs).

I.I NTRODUCTION

W IRELESS SENSOR NETWORKS(WSNs)have been recognized as a fundamental enabling technology for a large variety of cyber-physical systems applications in environ-mental monitoring,healthcare,security,and industrial domains, due to the?exible distribution of WSN devices.Each device integrates computing,wireless communication,power manage-ment,and sensing capability in order to collect and process data from sensors,generally collaborating to coordinate activities[1]. Battery-powered nodes are faced with limited life-expectancy, whereby energy is considered a limited and precious resource. Thus,power consumption is a critical problem in many WSN scenarios where the network is expected to operate for several months,extending to many years.To achieve this goal,ef?cient energy management strategies must be devised at the device level (through selecting optimal circuits),and at the network level (through the implementation of optimized medium access con-trol,routing and data collection,and dissemination protocols). Traditionally,wireless transceivers have been reported to be the primary consumer of energy,and many power management policies have been investigated and applied to ef?ciently manage the radio and wireless communication.From an industrial per-spective,there exist many scenarios that require ad-hoc sensors, often leading to sensor nodes consuming more power during data acquisition and computation/processing phases than during the communication.For example,video[2]or gas sensors[3]are very power hungry and require a signi?cant amount of energy to function correctly.The power requirements of these sensors are generally in the tens to hundreds of milliWatts range[4],which is similar to,and often exceeds the transceiver’s power consump-tion.Furthermore,when these sensors are required to sample continuously,the energy requirements are unsustainable for long-term deployment.Thus,ef?cient power management tech-niques that minimize not only the radio activity but also the activity of energy-consuming sensors are necessary.For this reason,the use of low-duty cycle data acquisition and sleep-cycle algorithms can considerably increase the lifetime of a node [5]–[9].Such a sensor node can be supplied only few hours at 100%duty cycle with standard battery,and therefore,these optimization techniques are essential.Effective power manage-ment algorithms may be implemented when sensors tend not to need high-frequency data acquisition.For example,adaptive duty cycling can be used whereby the acquisition rate is increased only if there is some event,such as a complementary sensor reading,above or below,a certain,prede?ned,threshold[5]. Recent technological advances,such as wake-up radio(WUR) receiver circuits,can ef?ciently“wake”the node when a beacon is sent from a neighboring node.WURs can further reduce the power consumption of networked nodes as they allow persistent low-power listening without the need to engage the active mode of the primary transceiver[27],[14].

Combining similar circuit-level advances with improvements in ambient energy harvesting(EH)allows increased network lifetime by many orders of magnitude.This has the potential to achieve energy neutrality.However,particular attention must be

Manuscript received July26,2012;revised June21,2013;accepted

September27,2013.Date of publication December18,2013;date of current

version May02,2014.This work was supported in part by the FP7projects,in part

by3ENCULT(Grant agreement260162),and in part by P-SOCRATES(Grant

agreement611016).In addition,the research leading to these results has received

funding in part by the European Institute of Innovation and Technology(EIT)

Information and Communication Technology(ICT)Innovation Communities

Labs within the Activity#12149“From WSN Testbeds to CPS Testbeds,”in part

by the Digital City Exchange(EPSRC Grant EP/I038837/1),and in part by

Enterprise Ireland through project CF20111038.Paper no.TII-13-0022.

M.Magno and L.Benini are with the Department of Electrical,Electronic,and

Information Engineering(DEI),University of Bologna,40136Bologna,Italy,

and Eidgen?ssische Technische Hochschule(ETH)Zurich,8092Zurich,

Switzerland(e-mail:michele.magno@unibo.it;luca.benini@unibo.it).

D.Boyle is with the Department of Electrical and Electronic Engineering

(DEEE),Imperial College London,London SW72AZ,U.K.(e-mail:david.

boyle@https://www.wendangku.net/doc/b71710417.html,).

D.Brunelli is with the Department of Industrial Engineering(DII),University

of Trento,38123Trento,Italy(e-mail:davide.brunelli@unitn.it).

E.Popovici is with the Electrical and Electronic Engineering,University

College Cork,Cork,Irleland.(e-mail:e.popovici@ucc.ie).

Color versions of one or more of the?gures in this paper are available online at

https://www.wendangku.net/doc/b71710417.html,.

Digital Object Identi?er10.1109/TII.2013.2295198

1551-3203?2013IEEE.Personal use is permitted,but republication/redistribution requires IEEE permission.

See https://www.wendangku.net/doc/b71710417.html,/publications_standards/publications/rights/index.html for more information.

paid during the design process.For example,harvesting energy with high ef?ciency becomes particularly important to reduce the form factor and to reduce the cost.The increasing ef?ciency allows a harvester to collect more energy under the same conditions,implying that size can be reduced.The effective maximum power point tracking(MPPT)circuits usually require on-board real estate of few and permit gains of up to10%in conversion ef?ciency from the environment[29],[30].Further-more,alternative energy storage possibilities can be exploited to increase the robustness and autonomy of the systems.For instance,the possibility to use energy from high-density storage sources,such as electrochemical fuel cells(FCs)[32]–[34], becomes desirable in harsh or inaccessible deployment environ-ments.This is a recently explored option for recharging other local storage units when they are discharged,and environmental energy is unavailable[26].

These observations lead us to conceive a solution that solves the following problem:what hardware advances can be achieved by integrating the state of the art in EH with reducing the most resource-intensive operations of a WSN application(energy-inef?cient sensing and communication),in a way that is intuitive and complementary to existing application design methods and existing application deployments?

The contributions of this paper are as follows.

1)A methodology for deploying ultra-low power overlay

sensor networks to enhance the functional lifetime of energy-intensive applications using novel,ultra-low pow-er hardware architecture,EH,and WUR technology.Al-though the concept of overlay networks is not new,it has yet to be considered at design time or for retro?tting WSN applications.We describe this method as“ultra-low power overlay”(UPO)for resource-intensive sensor networks.

2)Quantitative,empirical validation of the proposed ap-

proach via simulation and experimentation.Functional lifetime improvements for each of a surveillance applica-tion,using power-hungry video camera sensors,and a gas detection application,are demonstrated.

The remainder of this paper is organized as follows.Section II describes recent related work in the area.Section III presents the application model of WSNs to be optimized for extended functional deployment.Section IV details the proposed ap-proach,describing the proposed node and the network archi-tectures.Section V describes the implemented approach,along with measurements,comparative evaluation,and validation. Section VI concludes the paper.

II.R ELATED W ORK

Research on power consumption and energy ef?ciency in the WSN domain has been proli?c in recent years,with a variety of methods and techniques to extend the lifetime of networked nodes proposed.Most efforts attempt to fundamentally reduce the RF energy requirements of the devices through a number of novel hardware(e.g.,WUR),software(i.e.,media access control (MAC)and routing algorithm),and duty cycle optimization approaches[5]–[13],[18].It has been highlighted that extending the lifetime of networks is a strategic enabler,if not a primary requirement,for a signi?cant number of applications;including,but not limited to surveillance,environmental monitoring, entertainment,and healthcare[15],[16],[35]–[37].Recently, the use of renewable energy and FC technology to generate electric power,thus extending battery life,has been a key research challenge.The main sources of ambient available energy considered suitable for use with WSNs are solar,me-chanical(vibration or strain),and thermal energy[17]–[29]. In[5]–[10],an energy ef?ciency is achieved by reducing the active periods of a node through changing the duty cycle and optimally waking the system from“deep-sleep”modes.An interesting way to increase the lifetime using heterogeneous wireless sensors is presented in[11].This approach proposes a similar idea to that presented in this paper,inserting low-power sensor nodes into a dense network to increase the lifetime.The authors do not,however,approach energy neutrality or consider recent technological advances,achieving only a4-time energy reduction through the use of mobile relay nodes in the network.A similar approach is proposed in[28]wherein the authors illus-trate the potential bene?ts of using powerful and normal sensors to achieve a similar objective,using an overlay-type topology. There exist some references to overlay architectures for WSNs that are implemented at an algorithmic level,rather than hetero-geneous devices,and,as such,are not further considered in this work.In[12]and[13],an adaptive duty cycling algorithm and power management scheme that allows EH sensor nodes to autonomously adjust their working parameters according to the energy availability in the environment are presented.This ap-proach fails when the application requires continuous sampling to enable transient event detection.

The research in[14]and[38]presents simple architectures for ultra-low power WURs for WSN devices to achieve a reduction of sensor node listening activities(e.g.,MAC layer receive checks),drastically reducing the overall network power con-sumption.In[15],a pyroelectric passive infrared(PIR)sensor is used as a trigger to wake the node from“sleep”mode to a power-hungry video capture mode.This paper exploits these techniques to take advantage of the bene?ts of each and to extend the lifetime of the network while maintaining similar(or improved)security. In[16],the authors present a methodology for carrying out dynamic recon?guration for regenerative energy sources based on statistical analysis of tasks and supply energy.The approach is evaluated on regenerative energy and dynamically recon?gur-able smart camera.This illustrates that further power reduction is an important problem.

The fundamental requirement for a WUR is the ability to continuously listen to a wireless channel and trigger events with negligible latency for signi?cantly(i.e.,one or more orders of magnitude)less power than the regular transceiver.This increases network?exibility and reduces overall power consumption.Many advantages of WUR are presented in[38],where it was estimated that a specialized radio interface could consume as little energy as .The WUR[27]used in this work is fully featured,with only300nW(@3.3V)power consumption,and it is hosted by a energy harvesters power unit.Features include addressing and command capabilities,in addition to serial peripheral interface (SPI)interfacing with the smart power unit(Section IV). Considering various ambient harvesting opportunities,the most commonly used harvesters are photovoltaic cells,wind

turbines,and/or mechanical EH from vibration or strain [15]–[32].It is noticeable that very few researchers have incor-porated multiple energy resources into a single unit or platform. Because multi-source harvesting is a relatively novel and prov-ably powerful technique to extend the lifetime of a WSN device, this section focuses on these efforts.The Ambimax system[19]is a viable alternative,combining EH from wind and solar sources, using batteries and super capacitors for storage.This system has the added value of being able to perform MPPT.The system in [21]describes a recon?gurable energy subsystem for WSNs, inclusive of solar and vibration energy scavenging,with Li-ion rechargeable batteries and super capacitor for storage.One of the most signi?cant features presented is?exibility and the option to select and?t the node in situ,in a Plug-and-Play manner.

In[23],the authors present a hybrid device with indoor light and thermal EH capability.This architecture is very similar to power unit presented in this paper,both of which use the MSP430 to perform MPPT.However,in[23],there is no possibility to recharge Li-ion batteries or incorporate FC technology.Addi-tionally,the system only supplies the nodes with no means to

provide status information such as the power unit presented in this work.This is particularly important for developing adapt-able,energy-aware algorithms further up the communications protocol stack.

In[20],the authors present a power unit with three energy scavengers(wind,sun,and water?ow)used to recharge NiMh batteries,which provides information on the status of the energy resources.The limitation is that the storage pack cannot be changed,implying limited?exibility,and the power unit pro-vides very little information(i.e.,battery voltage)relating to the status of its constituent components.

Electrochemical FC technologies that use fuel(e.g.,hydrogen) to generate electrical power are being considered due to their higher energy densities(comparable with batteries).Considering FC technologies,an interesting approach is presented in[32], wherein the authors describe a microbial FC with harvester system which is prospectively self-powered,sustainable,environment friendly,and maintenance free.This system,however,has very low-power output(0.8mW)compared to the FC subsystem ()proposed in this work.Furthermore,there is no?exibility to add harvesters or to recharge Li-ion batteries.Therefore,it is not powerful enough for resource-intensive WSN applications.

In[31]and[33],the authors describe a FC-battery hybrid(FC-Bh)system for use in portable microelectronic systems,also characterizing and analyzing the performance of the system. The proposed approach signi?cantly extends the state of the art with respect to UPO networks for energy-intensive sensor network applications through the novel integration state-of-the-art ambient EH circuits and nanoWatt WUR,in combination with an ad hoc low-power sensor.To the best of the authors’knowledge,this is the?rst hardware enabled,energy-neutral overlay network for WSNs proposed in the literature.

III.A PPLICATION M ODEL

Fig.1illustrates a typical WSN deployment consisting of multiple power-hungry sensor nodes,a base station,and sup-plementary sensing nodes.All“power-hungry”sensor nodes (i.e.,equipped with gas sensors,video cameras,etc.)consume hundreds of milliWatts.Meanwhile,the other nodes can be less resource-intensive sensors(e.g.,temperature,humidity,etc.) that consume power in the order of a few milliWatts.Additional heterogeneous sensors,with different power pro?les,could also be deployed in the network.However,it is suf?cient that most networks can be satisfactorily represented using this model. The nodes communicate wirelessly in the433-MHz ISM band, but the same will hold for alternatives.The primary objective of the proposed approach is to reduce the power consumption of a generic WSN(i.e.,considering as general a case as possible) using additional ultra-low power sensor nodes deployed in the same target?eld which can interact with the existing network shown in Fig.1.

A.Sensor Node Energy Model

This section shows the models of the energy characteristics of the considered hardware devices,inclusive of the component technologies previously described.It is assumed that each node has an integrated radio frequency integrated circuit(RFIC)that can be put into an ultra-low power deep-sleep mode when communication is not needed(e.g.,30–120nA for LPM2on the TI CC2520RFIC).The overall energy used by the node over time may be de?ned as

where is the power consumption of a component/node when it is working and when it is sleeping.and

are the working and sleeping times,respectively,for each component.Since each component of the node has a sleep power consumption signi?cantly lower than the idle one(2), it is very useful to reduce the activity time to extend the lifetime of the node,and then for the network which is comprised by the sensors node.Seeing as all the nodes are assumed to

be Fig.1.Assumed deployment?eld of an energy-inef?cient WSN.The base station node is required to provide higher-level network connectivity(i.e.,“Internet,”or TCP/IP,via Ethernet,or similar).

equipped with EH capability,the model must consider the intake energy which the harvesters can collect in the time where is the contribution of-sources(i.e.,solar,wind, kinetic)and is the sum of them in the time.The total energy at time is given by

From(4),will be positive and thus will increase the energy stored in the battery in the time if.Other-wise,it will be negative and the energy available from the battery will decrease.

IV.H ARDWARE A RCHITECTURE

In this section,the architectures of the PIR sensor node, proposed for the primary UPO exemplar,and the smart power

unit are presented.Both of them are equipped with an ultra-low power wake-up radio unit.A distributed power optimization method,exploiting these novel devices when inserted into an existing network,is then proposed.

A.Multi-Source Harvester Architecture

The architecture of the multi-source EH unit is shown in Fig.2. Additional details are available in[26]and[27].The prototype features multi-source harvesting from solar and wind sources,in addition to hosting a hydrogen FC that is activated to recharge the battery when environmental sources are insuf?cient and the battery depletes beyond a certain threshold.Furthermore,the ultra-low power WUR signi?cantly reduces the duty cycling of radio,and thus the node itself.For this reason,the power unit has an interface to the node that provides the supply energy,general purpose input output(GPIOs),SPI,and electrical interfaces, as shown in Fig.2.As a result,in addition to being supplied with the requisite energy,the primary microcontroller unit(MCU)of the node can communicate with the power unit in order to increase the battery life by performing power management policies such as changing the duty cycle parameters(or sleep/ wake techniques),or selectively choosing the optimal harvesting sub-unit.The power unit is described as“smart”because it is possible to monitor the current state of the harvesters,batteries, and FC.It is possible to change the operating frequency used by internal dc/dc converters and chargers.Additionally,the major advantage of the radio trigger WUR in this approach is that the on-board MCU can directly control the data and wake up the main node only when needed.

In order to improve?exibility and introduce the possibility to remotely control the advanced power management policies, included in the design of the power unit is a nanoWatt WUR [27].The WUR is directly connected to the MCU through an SPI interface.The MCU can evaluate the event and adapt autono-mously or wake up the main node.On the one hand,this can reduce false alarms and consequently,power consumption due to unnecessary wake up of main node which could be very power hungry.The ultra-low power microcontroller on the power unit can process the address of radio wake-up messages,and wake up the more power-hungry primary microcontroller only if the address matches.On the other hand,the network can use the ultra-low power radio receiver to send the information to the power unit in an asynchronous fashion.

Fig.2shows the architecture of the power unit including the energy supply subsystem and the wake-up subsystem.The WUR can communicate through GPIOs to wake up via interrupting the microcontroller if a radio wake up is detected.Furthermore,the SPI serial communication needs to provide information to such as the direction of movement of the detected object or addressing information useful to wake up only the right node.

B.Overlay Node Architecture

As discussed in Section III,a sensor node is complex in many respects.A microcontroller,transceiver,memory,and power supply,together with a variety of sensors and signal processing circuitry,form an embeddable system capable of collecting/ detecting events and information from the surrounding area.It may analyze the data and send a message,or data,to other nodes or system users(sinking data through a local base station node with extended connectivity).Fig.3shows the architecture of the overlay PIR sensor node with integrated ultra-low power WUR. The hardware architecture is divided into three physically dis-tinct modules,powered by a single power source:

1)the sensor module,which hosts a PIR sensor and the

conditioning circuitry to give an analog and a digital output;

2)microcontroller board,the controller module built around a

TI MSP430,which includes the power harvester module and batteries;

3)the communication module consisting of a nanoWatt

WUR circuit and an ADF7020transceiver to send infor-mation and/or to wake up the neighbors.

The architecture is modular,each

module implemented as stand-alone component to facilitate“plug and play”deployment. Fig.2.Block diagram of the power unit.The wake-up subsystem can receive events to wake up the power unit microcontroller.The energy subsystem is based on an MSP430F2274MCU,capable of providing real-time power information, enabling true energy awareness.

Although the PIR sensor node is an ultra-low power node and can survive for months with2xAA batteries,in order to approach perpetual operation and wake-up capabilities,it is equipped with

a simple solar harvester to recharge the battery.

1)Sensor Module:The PIRs translate incident infrared radiation into https://www.wendangku.net/doc/b71710417.html,mercial PIRs are sold in pairs with opposite polarization.This con?guration enables the sensor to detect variations of incident infrared radiation irradiated by bodies moving inside the coverage area that are not at thermal equilibrium with the environment.The PIRs are used with a Fresnel lens to enlarge and shape their area of sensitivity.They are passive sensors with minimal power consumption,ideal for battery powered systems.A single PIR sensor can detect direction of movement if the analog signal is processed by a microcontroller.Fig.4shows the analog signal detected by the sensor when a person passes through the area under control from left to right(the?rst peak is negative)and from right to left(?rst peak is positive).Acquiring this wave using ADC on the

microcontroller,one can easily determine the direction of the movements and can use this information to take decisions(e.g., to wake the next node).To reduce the power consumption,the ADC is switched OFF when there is no movement to analyze.For this reason,in addition to the analog output,the PIR board provides a digital output that,connected through GPIO,triggers a hardware interrupt to wake the system when motion is detected.

2)Microcontroller Board:The hardware used to collect, process data from the overlay(PIR)sensor,and send and receive wake-up information/messages,is a Texas Instruments (TI)eZ430-RF2500board.It uses an MSP430F2274MCU.The on-board CC2500was disconnected to reduce the power consumption.In addition,there are a number of free IO pins on the board to easily interface sensors and other devices,such as the radio module implemented(Fig.5).

As shown in Fig.3,the TI board is the core of the node.The microcontroller acquires and processes data from the PIR sensor through an analog output connected to an ADC input.The digital output of the PIR sensor in the overlay node is connected to a GPIO and can wake the node from deep sleep through hardware interrupt.The MSP430can control the sensor module through

serial port.On the radio side,the MCU uses the SPI to drive the RFIC.A GPIO is used from the radio board to wake the node. This module also includes the power supply.In fact,the PIR node is equipped with single solar EH device built around the LINE-AR3109chip which allows recharging batteries of PIR nodes using simple COTS solar panels with open-circuit voltage up to 5.5V.

3)Communication Module:Different from the power unit, which hosts only the WUR,the PIR board consists of two different ISM radios.The?rst one is the same nanoWatt WUR to listen for alarms and the second is a transceiver which sends the alarms.Since power-hungry nodes and overlay nodes should listen for the same alarms,then the receiver module is the exact the same for both.However,in order to send an alarm,the communication module uses the ADF7020from analog devices which performs the data transmission/receiving.It is used to send the wake-up signal to the next node(s).The transceiver is tuned to transmit with a data rate of5.5kbit/s in the433-MHz ISM band and was chosen for the low power consumption.The WUR has an SPI adapter to communicate information with the MSP and a wake-up interrupt connected

to Fig.4.Output of PIR sensor based on

direction.

Fig.5.Typical wakeup application with power-hungry

node. Fig.3.Architecture and image of implemented PIR sensor node.

the microcontroller(Fig.3).The range of the WUR receiver is adjustable from few meters to about10–20m line of sight,and its power consumption with this con?guration is approximately 300nW.Although the ADF7020can also receive information, it is employed solely to transmit data(48mW receive power against300nW of the WUR).The power consumption of this transceiver is approximately48.5mW to transmit the data. C.Proposed Method

An UPO for resource-intensive WSN applications,such as surveillance,can be constructed and implemented at design time or postdeployment(as a true overlay),in order to improve maintenance requirements,e.g.,in terms of the energy require-ments and longevity of the deployment in the?eld.We consider the following characteristics of resource-intensive applications whereupon improvement is possible:

1)a resource-intensive sensor(such as a video camera in a

surveillance application or a strain gauge in an environ-

mental monitoring application)with continuous monitor-ing requirements(i.e.,high sampling rate);

2)a resource-intensive primary RFIC for communication

between networked nodes(e.g.,TI CC2420/CC2520);

3)replacing batteries through the integration of next genera-

tion solutions for ambient available EH,storage,supply, and alternative(e.g.,FC)sources.

In order to address the?rst characteristic,it is desirable to consider a complementary sensor to the primary sensor that exhibits signi?cantly lower energy consumption.The main example presented in this work is that of a low-power PIR sensor that can detect presence through continuous low-power sam-pling.Once motion is detected,a signal is sent to turn on the video camera for higher resolution sensing of the phenomena. Another example scenario is the selection of a low-power accelerometer that can be used similarly as a trigger for a more resource-intensive strain gauge,inclinometer,or displacement transducer in the context of a structural monitoring application. Another(worked)example(Section V)is that of a gas sensing application.

Considering the second characteristic,the RF transceiver is a component of the node,and the power consumption follows(1). There are several WSN protocols that exploit clever sleep/wake techniques to allow the reduction of the transmission activities [5],[6],[12].In this work,the proposed method limits the usage of the primary RFIC by exploiting the nanoWatt WUR.This is to attempt to reduce power consumption by reducing unnecessary RF activity within the network,and recharging the batteries by scavenging energy from different environmental sources,sup-plemented by a?nite FC.Considering our application scenario,a node’s activity is strongly affected by the presence of people or objects in the target?eld.To achieve the power minimization goal,the PIR sensor nodes with WUR are used inside an existing network application.This approach keeps the main network unchanged and introduces an additional and transparent network which is ultra-low power,highly scalable,easy to deploy,and energy ef?cient.Furthermore,resulting from the use of the smart power unit instead of a normal battery,the power-hungry node can achieve self-sustainability and may be woken up based on complementary low-power sensor triggers(e.g.,from the PIR sensor in our surveillance example).

Fig.5shows how the power unit interfaces both the overlay network through radio transceiver with the power-hungry node through the power supply socket,using a standard GPIO as a wake-up pin.Since one signi?cant goal of proposed approach is the possibility to improve the lifetime of existing network unobtrusively,the power-hungry nodes do not need to change their architecture,and see the power unit as a normal battery, using only ground and.

However,to exploit the WUR capability,the node must provide an available GPIO to listen for the trigger from the power unit,and to change the state from sleep to awake.The power unit listens for radio trigger alarms by,e.g.,PIR sensors, through the radio trigger receivers,with the on-board MCU responsible for?ltering the alarms and waking the main node only if required.This approach saves a signi?cant amount of energy,due to false positive alarms which could wake up the main node when it is not necessary.This is avoided if the microcontroller processes the address form the radio wake-up alarm and wakes up the main node only if the address is valid. Usually,in this kind of application,the main nodes primary intelligence is much more power intensive than an MSP430(e.g., required for running image processing algorithms),and thus power saved is proportional to the false positive alarm received.

D.Illustrative Example:UPO for Video Surveillance

Fig.6illustrates the augmented deployment scenario for an existing energy-intensive sensor network application where the PIR sensor network is overlayed to achieve functional lifetime extension.As illustrated,comparatively with Fig.1,the existing network is not modi?ed through the insertion of supplementary PIR nodes.In this augmented network,every node covers a radio range for which there is a number of reachable neighbors.When a node detects an intruder,it sends a broadcast message to neighbors to wake them up such that they are ready to detect/record information.The nodes can detect the direction of movement and strategically wake other neighbors as relevant based on

direction Fig. 6.Illustration of ultra-low power sensor network overlayed on an existing WSN.

of motion.To reduce the overhead due to sending messages,two cost functions are introduced.A cost function,such as (5),ensures that the node is woken when required and for the minimal possible time.Furthermore,the radio activity has the cost function (6)

where and are two binary variables which represent the PIR detection and the radio trigger signal.is 1if the direction of movement is changed,0otherwise.and are binary variables,according to wake time and most recent message time,respectively.is 0if a ?xed time ()has not elapsed since the last message transmission (1otherwise),and is 1if the wake time ()has not elapsed from the previous interrupt from the PIR sensor or radio trigger.Thus,a node sends a wake-up message only the ?rst time it detects the movement (),or when it detects a change of direction ().It then waits for the next message.

In the same way,the node goes to “sleep mode ”when has elapsed and is woken by PIR ()or radio trigger ().

Directional information could be very useful in numerous applications,e.g.,in the video surveillance application to im-prove the accuracy of the video processing algorithm or the activation of the gas sensors in a room.In addition,two or more PIR sensors ?elds of view could overlap to give more informa-tion and ensure the waking of the right camera(s)in a cooperative video surveillance system (described in the previous work [36]).Fig.7presents the state machine representation with the current consumption of PIR sensor in accordance with (5)and (6).

V.E XPERIMENTAL R ESULTS

This section describes an experimental evaluation of the method as applied to the video surveillance application previ-ously described.It is also applied to a gas sensing application.First,the measurements of power consumption of the overlay device exploiting the PIR sensor and resource-intensive sensor node,in different states,are presented.Evaluation of the lifetime of the network is investigated for different application scenarios with a gas sensor and video sensor in order to show the ?exibility of the proposed method.Second,through simulation,lifetime extension achievable using the proposed approach is compara-tively evaluated for each scenario.

A.Power Consumption

Table I shows the sensor nodes ’current consumption in different states with 3V supply.The PIR sensor board has 10times lower power consumption than the power-hungry node.Measurement of the PIR sensor ’s power consumption was performed setting the clock of the MCU at 1MHz and assuming that the node can be in one of the three con ?gurations shown in Fig.7.The power-hungry sensor is a smart camera that consists of an embedded processor and CMOS video sensor with wireless communication (ZigBee or Bluetooth)[36].Additionally,it can receive wireless messages from the host to change some settings.The nanoWatt WUR board is connected through GPIO to wake the smart camera,since its power consumption is negligible with respect to the power of camera node.The camera nodes are now associated with two networks:the ?rst one with higher band-width is used to send images or alerts to the remote host,and the second one is the overlayed ultra-low power PIR sensor network.The core of the gas sensor node is the Jennic JN5148module,an ultra-low-power,high-performance wireless microcontroller targeted at ZigBee PRO networking applications with a com-mercially available sensor (MiCS-5121from e2v technologies)[17].It detects VOC (including )and CO.This sensor has characteristic power consumption of 30mA,mostly attributable to the power-hungry radio module.B.PIR Direction Algorithm

This section describes the performance evaluation of the directional analysis algorithm performed by the PIR node.For the experiments,detection ?rmware was developed to evaluate the peak of the analog signal of PIR as shown in Fig.4to

achieve

Fig.7.State machine with current consumption of PIR sensor.

TABLE I

N ODES ’C URRENT C

HARACTERISTICS

Current consumption of nodes in different con ?gurations.

the peak detection,which is made using threshold.In particular,a positive peak is detected when the signal is lower than a certain threshold under a previously detected local maximum.Con-versely,a negative peak is detected when the signal breaks a certain threshold above a previous local minimum.After the algorithm detects a maximum,it will look for a minimum and vice versa;the ?rst peak depending on the direction of movement in the ?eld of view.The PIR node was deployed on the ?oor of authors ’lab and a total of 128detections of passers-by were observed.Table II shows the detection rate is 100%.This is not surprising,as it is widely reported in the literature that this is quite common for PIR sensors.About 96.87%accuracy was achieved for passers-by in the right direction;achieving a 93.75%accura-cy in the left direction.The average accuracy of the algorithm is 95.3%.

C.Simulation

In order to evaluate the potential extension of operational lifetime,the measurements of the current consumption in each state inform the used energy for each type of node using (1)and (2).In the same way,we used (3)and (4)with experimental measurement on the energy harvesters to evaluate the intake energy.Due to these four equations,the status of available energy is known in all the time per each node.Finally,(5)and (6)are used to evaluate the radio activities and thus the radio energy.As explained in Section IV,to evaluate the radio activity,the simulation has to ?x the times to resend a message ()or to be awake ().The simulation settings and .Due to all the equations,the simulation can evaluate the battery level during the simulation time for each node according to the intake energy,energy used due to the node activity.

The simulation assumes that the camera nodes are equipped with a battery of 1600mAh,and the gas sensor nodes and PIR nodes with a battery of 550mAh.Tests were performed with the same event density for each PIR sensor (75,150,450ev/h,consecutively).The simulation assumes 20PIR nodes and 4camera nodes for the video surveillance scenario and 20PIR nodes and 4gas sensor nodes in the quality of air (gas sensing)scenario.A lookup table binds each node with the neighbors to be woken up (?xing a maximum of three possibilities).For exam-ple,the PIR node 1is associated to wake up nodes 2,3,and 4.Node 2wakes nodes 3,1,and 5,and so on.Similarly,the table de ?nes which PIR node wakes which camera node or gas node (i.e.,Camera 1is woken up by PIR node 5).MATLAB was used as the simulation tool,with a random distribution of

TABLE II

PIR N ODE

D IRECTION D ETECTION P

ERFORMANCE

Fig.8.Solar energy harvested during 11consecutive days from the smart power unit with the PV

panel.

Fig.9.Wind energy harvested during 11consecutive days from the smart power unit by the 7-cm

turbine.

Fig.10.Wireless sensor nodes used for the testbed deployed in the

lab.

Fig.11.Deployed network in two adjacent rooms used for the experimental results.

events on the target ?eld,assuming that the next event must be detected by one of the neighbors of the previous node,or again by the same node.

In order to evaluate the intake energy of the nodes and the EH data from solar and wind sources,measured data of the proposed power unit acquired in 11days consecutive days in a deployment of the power unit board (Figs.8and 9)was used.Fig.12shows the lifetime of both camera and gas sensor node comparing the presented approach with the same system without the PIR on board and with the PIR on board and only the energy harvester unit including the FC.

To compare the proposed approach with the same system with a PIR sensor on board,the simulation considers 75ev/h detected by the PIR sensor in the surveillance scenario and 150ev/h in the air quality scenario.It can be seen that the lifetime of the power-hungry node is 2days for the camera node and 3.5days for the gas sensor.This is because the power consumption of the camera is higher than the gas sensor node.The situation improves adding to this system the energy harvester unit that recharges the battery from wind and solar energy.

The lifetime is extended in critical situations when the battery falls below 10%and the power unit recharges the battery with the FC.For simulation,the recharge time is ?xed at 3h.This is the experimentally veri ?ed recharge time for the tested battery.However,in real deployments,this time depends on the size of the battery selected.Finally,the simulation illustrates the bene ?ts of the proposed approach even as events per hour were increased to 450.Interpreting the results of the simulation study,the advantages of the proposed approach are clear.Fig.12shows the bene ?t of the proposed method in terms of lifetime extension.It exploits the combination of power harvester and signi ?cant reduction of duty cycle resulting from the insertion of the overlay PIR network.The simulation shows that the lifetime of a system with the combined methods including the WUR,PIR nodes,and EH capable smart power unit is a feasible and powerful way to achieve self-sustainability.

As illustrated,the system is able to perpetually maintain operation using solar or wind harvesting without FC power (used with 450ev/h).This is because the PIR sensor network does not activate the camera for every motion event,as a single PIR would,but only according to (5),(6),and the lookup table.This reduces the false alarm rate by approximately 33%.Finally,

as shown in Table I,the power consumption of the PIR node is extremely low and in the worst case,where for the radio transceiver the energy consumption is 4320J,this facilitates selecting an appropriately sized solar panel.D.Real Deployment Evaluation

A lab deployment was used to evaluate the activities reduction of the power-hungry sensors with the proposed approach.The four PIR nodes with wake-up radio and the TI-MSP430micro-controller were used as sentinel nodes and a smart camera and a gas sensor node as power-hungry node (Fig.10).

All the nodes were deployed in two different adjacent rooms with two PIR nodes and one power-hungry sensor per room (Fig.11).Due to the size of the rooms,each node is far around 5m from the next one.All the PIR nodes used,implement the direction algorithm presented in Section V-B together with the cost functions (5),(6),and the lookup table to know the neigh-bors.The deployment uses the same setup than the simulation in the Section V-C in order to be evaluated in the same conditions.Table III shows the lookup tables for each PIR nodes.As the table shows the node PIR1is linked with the node PIR2and with the camera node,so PIR1is in charge to wake up the camera if it detected the right to left direction.In the same way,the node PIR4is in charge to wake up to the gas node and it is linked to the PIR3.

The system was tested for 420passes in the room,moving from the Desk1position to the Desk2position (Fig.11).In order to detect the numbers of activations,the power-hungry sensors used an event counter.At the end of the session,

the

https://www.wendangku.net/doc/b71710417.html,parison of lifetime through simulation of battery level of camera and gas sensor.The proposed system performs self-sustainability with 450ev/h (red lines).The same nodes with PIR sensor on board instead of the proposed UPO and much less events per hour need the help of fuel cell after few days (blue lines).Finally,the power-hungry nodes with only the PIR sensor on board and only 75ev/h died after few days (back lines).

T ABLE III

PIR N ODES L OOKUP T

ABLE

counter for the camera node was233and the counter of the gas sensor was239.So,this means we saved the45%of the activation for the camera and the43%for the gas sensor.This result is close to the best case of50%saving(since there can only be left to right and right to left movement detections).The discrepancy is due to the inability of PIR1and PIR4to detect direction with100%accuracy.This means that some false wake ups of the power-hungry node are unavoidable.Future work will seek to improve the accuracy of the direction detection algorithm.

VI.C ONCLUSION AND F UTURE W ORK

A novel method to extend the lifetime of an energy-inef?cient WSN through the deployment of an UPO network has been proposed.The method requires the deployment of ultra-low power,complementary sensors with radio trigger capabilities that generate alarms on events of interest,which can signi?cantly reduce activities of the main network(when the WSN uses power-hungry sensors,such as in surveillance applications).The use of a multi-source EH smart power unit with WUR allows the power-hungry sensor to extend its lifetime without architectural alteration.Because many applications do not require continuous monitoring using energy-intensive sensors,requiring only monitoring of the target?eld for trigger-type events,this ap-proach reduces signi?cantly the power consumption in the network.

Experimental results indicate that the proposed system out-performs the state of the art with a signi?cant increment of the network lifetime,potentially extending to perpetual operation (depending,of course,on the number of expectable triggering events over time).It showed that this approach increases appli-cation lifetime from10h,with75ev/h,to perpetual operation with up to450ev/h.Moreover,the real deployment evaluation was performed to validate the proposed approach.These mea-surements showed the reduction of the activities up to the45%. Future work will focus on the re?nement and exploitation of these results.Further improvements to both the lifetime(e.g., choosing the best time and location of camera-based detection depending on the events speed and location)and the accuracy of surveillance and monitoring applications(e.g.,waking nodes depending on the direction of motion)are achievable.

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236.

Michele Magno(M’13)received the Master’s and

Ph.D.degrees in electronic engineering from the

University of Bologna,Bologna,Italy,in2004and

2010,respectively and Postdoctoral from ETH

Zurich,Zurich,Switzerland.

He is a Research Fellow at the University of

Bologna.The most important themes of his research

are on power management techniques and extension

of the lifetime of wireless sensor networks(WSN).In

this?eld,he has worked actively both on the energy

ef?ciency of the nodes and the network,and on the use of harvesters,such as solar panels and wind,and using the fuel cells to hydrogen to feed the nodes and recharge the batteries.He has collaborated with several universities and research centers,such as the University of Cork and Tyndall Institute,Cork,Ireland,University of Trento,Trento,Italy,Politecnico di Torino, Torino,Italy,and the University of British Columbia,Vancouver,Canada.He has

published more than30papers in international journals and

conferences.

David Boyle(M’07)received the B.Eng.degree in

computer engineering in2005and the Ph.D.degree in

2009from the University of Limerick,Limerick,

Ireland.

He worked in the?eld of security for wireless

sensor networks at the University of Limerick.He is

a Research Fellow with the Department of Electrical

and Electronic Engineering at Imperial College

London,London,U.K.Before joining Imperial,he

was a Postdoctoral Researcher at Tyndall National

Institute,Cork,Ireland,a Research Engineer with Orange Labs(France Telecom R&D),and a Visiting Postdoctoral Scholar in the Telecommunications Engineering School at the Technical University of Madrid,Madrid,Spain.His current research interests include networked embed-ded monitoring and control systems in the urban environment at the con?uence of various disciplines.He has authored patents and papers in international peer-reviewed journals and conference proceedings,contributed to the peer-review process,and collaborated internationally with industry and

academia.

Davide Brunelli(M’10)received the Master’s

(summa cum laude)and the Ph.D.degrees in electrical

engineering from the University of Bologna,Bologna,

Italy,in2002and2007,respectively.

Since2010,he has been an Assistant Professor at

the University of Trento,Trento,Italy.He was leading

the industrial cooperation activities with Telecom

Italia,Torino Italy.His research interests concern the

development of new techniques of energy scavenging

for WSNs and embedded systems,optimization of

low-power and low-cost WSNs,and interaction and design issues in embedded personal and wearable

devices.

Emanuel Popovici(SM’08)received the Dipl.Ing.

degree in computer engineering from the Politehnica

University,Timisoara,Romania,in1997and the

Ph.D.degree in microelectronic engineering from the

National University of Ireland,Cork,Ireland,in2002.

Since2002,he has been a Lecturer with the

Department of Microelectronic Engineering,National

University of Ireland.Between1997and2001,he did

his research on ef?cient algorithms and architectures

for encoding/decoding of block codes within the

National Microelectronics Research Centre,Cork, Ireland(now the Tyndall National Institute),Ireland.Prior to his appointment as Lecturer,he was a Postdoctoral Research Engineer with University College Cork,Cork,Ireland,working on hardware accelerators for e-commerce cryptog-raphy.His research interests include embedded system design for reliable and secure computing and

communications.

Luca Benini(F’07)received the Ph.D.degree in

electrical engineering from Stanford University,

Standford,CA,USA,in1997.

He is a Professor of digital circuits and systems at

ETH Zurich(ETHZ),Zürich,Switzerland,and at the

University of Bologna,Bologna,Italy.His research

interests are in energy-ef?cient system design and

multi-core SoC design.He is also active in the area

of energy-ef?cient smart sensors and sensor networks

for biomedical and ambient intelligence applications.

He has published more than600papers in peer-reviewed international journals and conferences,four books and several book chapters.

Dr.Benini is a member of the Academia Europaea and has served for two terms as a member of the steering board of the ARTEMISIA European Association on Advanced Research&Technology for Embedded Intelligence and Systems.

五年级上册成语解释及近义词反义词和造句大全.doc

五年级上册成语解释及近义词反义词和造句大全 囫囵吞枣；【解释】：囫囵：整个儿。把枣整个咽下去，不加咀嚼，不辨味道。比喻对事物不加分析考虑。【近义词】：不求甚解【反义词】融会贯穿[造句];学习不能囫囵吞枣而是要精益求精 不求甚解；bùqiúshènjiě【解释】：甚：专门，极。只求明白个大概，不求完全了解。常指学习或研究不认真、不深入【近义词】：囫囵吞枣【反义词】：精益求精 造句；1；在学习上，我们要理解透彻，不能不求甚解 2；学习科学文化知识要刻苦钻研，深入领会，不能粗枝大叶，不求甚解。 千篇一律；【解释】：一千篇文章都一个样。指文章公式化。也比喻办事按一个格式，专门机械。 【近义词】：千人一面、如出一辙【反义词】：千差万别、形形色色 造句；学生旳作文千篇一律，专门少能有篇与众不同旳，这确实是平常旳练习太少了。 倾盆大雨；qīngpéndàyǔ【解释】：雨大得象盆里旳水直往下倒。形容雨大势急。 【近义词】：大雨如柱、大雨滂沱【反义词】：细雨霏霏牛毛细雨 造句；3月旳天说变就变，瞬间下了一场倾盆大雨。今天下了一场倾盆大雨。 坚决果断；áobùyóuyù：意思；做事果断，专门快拿定了主意，一点都不迟疑，形容态度坚决 近义词；不假思索斩钉截铁反义词；犹豫不决 造句；1看到小朋友落水，司马光坚决果断地搬起石头砸缸。2我坚决果断旳承诺了她旳要求。 饥肠辘辘jīchánglùlù【近义词】：饥不择食【反义词】：丰衣足食 造句；1我放学回家已是饥肠辘辘。2那个饥肠辘辘旳小孩差不多两天没吃饭了 滚瓜烂熟gǔnguālànshóu〔shú)【解释】：象从瓜蔓上掉下来旳瓜那样熟。形容读书或背书流利纯熟。【近义词】：倒背如流【反义词】：半生半熟造句；1、这篇课文我们早已背得滚瓜烂熟了 流光溢彩【liúguāngyìcǎi】解释；光影，满溢旳色彩，形容色彩明媚 造句：国庆节，商场里装饰旳流光溢彩。 津津有味；jīnjīnyǒuwèi解释：兴趣浓厚旳模样。指吃得专门有味道或谈得专门有兴趣。 【近义词】：兴致勃勃有滋有味【反义词】：索然无味、枯燥无味 造句；1今天旳晚餐真丰富，小明吃得津津有味。 天长日久；tiānchángrìjiǔ【解释】：时刻长，生活久。【近义词】：天长地久【反义词】：稍纵即逝 造句：小缺点假如不立即改掉, 天长日久就会变成坏适应 如醉如痴rúzuìrúchī【解释】：形容神态失常，失去自制。【近义词】：如梦如醉【反义词】：恍然大悟造句；这么美妙旳音乐，我听得如醉如痴。 浮想联翩【fúxiǎngliánpiān解释】：浮想：飘浮不定旳想象；联翩：鸟飞旳模样，比喻连续不断。指许许多多旳想象不断涌现出来。【近义词】：思绪万千 造句；1他旳话让人浮想联翩。2:这幅画饱含诗情，使人浮想联翩，神游画外，得到美旳享受。 悲欢离合bēihuānlíhé解释；欢乐、离散、聚会。泛指生活中经历旳各种境遇和由此产生旳各种心情【近义词】：酸甜苦辣、喜怒哀乐【反义词】：平淡无奇 造句；1人一辈子即是悲欢离合,总要笑口常开,我们旳生活才阳光明媚. 牵肠挂肚qiānchángguàdù【解释】：牵：拉。形容十分惦念，放心不下 造句；儿行千里母担忧，母亲总是那个为你牵肠挂肚旳人 如饥似渴rújīsìkě：形容要求专门迫切，仿佛饿了急着要吃饭，渴了急着要喝水一样。 造句；我如饥似渴地一口气读完这篇文章。他对知识旳如饥似渴旳态度造就了他今天旳成功。 不言而喻bùyánéryù【解释】：喻：了解，明白。不用说话就能明白。形容道理专门明显。 【近义词】：显而易见【反义词】：扑朔迷离造句；1珍惜时刻，好好学习，那个道理是不言而喻旳 与众不同；yǔzhòngbùtóng【解释】：跟大伙不一样。 〖近义词〗别出心裁〖反义词〗平淡无奇。造句； 1从他与众不同旳解题思路中，看出他专门聪慧。2他是个与众不同旳小孩

成语大全及解释造句[1]

安然无恙：很平安，没有受到损失和伤害 - 造句：那次智利大地震，许多城市都毁灭了，但我叔父全家安然无恙，非常幸运。 - 拔苗助长：比喻违反事物的发展规律，急于求成，反而坏事 - 造句：“抢先教育”违背了儿童成长的客观规律，这种拔苗助长的办法结果必将造成对孩子身体和心灵的双重伤害。 - 跋山涉水：形容旅途的艰辛劳苦 - 造句：地质勘探队员不怕艰苦，跋山涉水，为祖国寻找地下的报藏。 - 百看不厌：对喜欢的人，事物等看多少遍都不厌倦。比喻非常喜欢。 -造句：到了节日里，各个景区摆设的花朵真是让人百看不厌。 - 班门弄斧：比喻在行家面前卖弄本领，不自量力 -造句：你在著名华文作家的面前卖弄华文,岂不是班门弄斧。

- 搬弄是非：把别人的话传来传去，有意挑拔，或在背后乱加议论，引起纠纷 - 造句：他们到处搬弄是非,传播流言、破坏组织内部的和谐。 - 变本加厉：指比原来更加发展。现指情况变得比本来更加严重 -造句;的坏习惯不但没有改正，反而变本加厉了. -变幻莫测：变化不可测度。变化很多，不能预料 -造句：草地的气候变幻莫测,一会儿烈日当空,一会儿大雨倾盆,忽而雨雪交加,忽而狂风怒吼。 - 别具匠心：指在技巧和艺术方面具有与众不同的巧妙构思- 造句：这篇小说让人看了回味无穷，作者确实是别巨匠心。 -不耻下问：指向地位比自己低、学识比自己少的人请教，也不感到羞耻（耻辱） -造句：学习，不仅要做到虚怀若谷，还要做到不耻下问。 -不可救药：比喻人或事物坏到无法挽救的地步 - 造句：他的问题很严重，已经不可救药。

- 不可思议：原有神秘奥妙的意思。现多指无法想象，难以理解 - 造句：我看这那座小山觉得不可思议。 -不期而遇：没有约定而遇见 -造句：高兴与悲伤总是不期而遇，或许这就是上帝再捉弄世俗吧！ -不屈不挠：形容顽强斗争,在敌人或困难面前不屈服,不低头那种不屈不挠的、要征服一切的心情 -造句：战士们不屈不挠的坚守在抗震第一线。 - 不速之客：指没有邀请而自己来的客人 - 造句：也不必说有时趁你不防钻进防盗铁门登堂入室的不速之客。 - 不屑置辩：认为不值得辩论 - 造句：孔乙己对那些嘲笑他的人显出不屑置辩的神情。 -不言而喻：形容道理很明显 -造句：你想他们这朋友之乐，尽可不言而喻了。

悲惨的近义词反义词和造句

悲惨的近义词反义词和造句 导读：悲惨的近义词 悲凉(注释:悲哀凄凉：～激越的琴声。) 悲惨的反义词 幸福(注释:个人由于理想的实现或接近而引起的一种内心满足。追求幸福是人们的普遍愿望，但剥削阶级把个人幸福看得高于一切，并把个人幸福建立在被剥削阶级的痛苦之上。无产阶级则把争取广大人民的幸福和实现全人类的解放看作最大的幸福。认为幸福不仅包括物质生活，也包括精神生活;个人幸福依赖集体幸福，集体幸福高于个人幸福;幸福不仅在于享受，而主要在于劳动和创造。) 悲惨造句 1.一个人要发现卓有成效的真理，需要千百个人在失败的探索和悲惨的错误中毁掉自己的生命。 2.贝多芬的童年尽管如是悲惨，他对这个时代和消磨这时代的地方，永远保持着一种温柔而凄凉的回忆。 3.卖火柴的小女孩在大年夜里冻死了，那情景十分悲惨。 4.他相信，他们每个人背后都有一个悲惨的故事。 5.在那次悲惨的经历之后，我深信自己绝对不是那种可以离家很远的人。 6.在人生的海洋上，最痛快的事是独断独航，但最悲惨的却是回头无岸。 7.人生是艰苦的。对不甘于平庸凡俗的人那是一场无日无夜的斗

争，往往是悲惨的、没有光华的、没有幸福的，在孤独与静寂中展开的斗争。……他们只能依靠自己，可是有时连最强的人都不免于在苦难中蹉跎。罗曼·罗兰 8.伟大的心胸，应该表现出这样的气概用笑脸来迎接悲惨的厄运，用百倍的勇气来应付开始的不幸。鲁迅人在逆境里比在在顺境里更能坚强不屈。遇厄运时比交好运时容易保全身心。 9.要抓紧时间赶快生活，因为一场莫名其妙的疾病，或者一个意外的悲惨事件，都会使生命中断。奥斯特洛夫斯基。 10.在我一生中最悲惨的一个时期，我曾经有过那类的想法：去年夏天在我回到这儿附近的地方时，这想法还缠着我;可是只有她自己的亲自说明才能使我再接受这可怕的想法。 11.他们说一个悲惨的故事是悲剧，但一千个这样的故事就只是一个统计了。 12.不要向诱惑屈服，而浪费时间去阅读别人悲惨的详细新闻。 13.那起悲惨的事件深深地铭刻在我的记忆中。 14.伟大的心胸，应该用笑脸来迎接悲惨的厄运，用百倍的勇气来应付一切的不幸。 15.一个人要发现卓有成效的真理，需要千百万个人在失败的探索和悲惨的错误中毁掉自己的生命。门捷列夫 16.生活需要爱，没有爱，那些受灾的人们生活将永远悲惨;生活需要爱，爱就像调味料，使生活这道菜充满滋味;生活需要爱，爱让生活永远充满光明。

常用成语造句大全及解释

常用成语造句大全及解释 导读：常用成语及造句大全： 【马到功成】形容事情顺利，一开始就取得胜利。 朋友要去参加考试我发自内心的祝她马到功成。 【安常守故】习惯于日常的平稳糊口，保保守的一套。指保守不知厘革。 他持久以来安常守故，缺乏锻炼，故而经不起挫折。 【挨门逐户】挨家挨户，一家也没有遗漏。 倾销员挨门逐户地倾销产物，可是并没有多少人愿意买 【破釜沉舟】比喻下决心悍然不顾地干到底。 只要咱们有破釜沉舟的决心，就能克服进修上的各类困难。 【大千世界】三昧，世界的千倍叫小千世界，小千世界的千倍叫中千世界，中千世界的千倍叫大千世界。后指广大无边的人世。 大千世界无奇不有，充满了抵牾。 【空手发迹】一切靠自己艰辛奋斗，创立了一番事业。 王董事长空手发迹，如今是王氏集团的总裁。 【卷土重来】卷土：人马奔跑时卷起的尘土。形容失败后组织力量，重图恢复。 这次角逐虽则表现不佳，但我决定明天卷土重来。 【晨钟暮鼓】古代梵宇中晨敲钟，暮伐鼓以报时，用以使人惊悟的言论。 每当我想坏事时，就会想起母亲对我的晨钟暮鼓的叮咛。

【力争上游】起劲争取长进求学做人都要力争上游，不要自满於近况 【投笔从戎】一小我私家抛弃文职而插手卫国的行列。 大伯父高中结业后投笔从戎，步入军校就读，负起保家卫国的责任。 【前车之鉴】比喻前人的失败，可以作为后人的借鉴。 有了这个前车之鉴，我下次出门一定会带雨具。 【金石为开】至诚可感动任何事物。 表哥相信精诚所至，金石为开，他的成意一定可以感动王小姐的。 【勤能补拙】指勤勉起劲能弥补天资上的不足。 勤能补拙，只要你多付出心思，一定有乐成的机会。 【揠苗助长】揠：拔起。把苗拔起，以助其生长。后用来比喻违反事物的发展规律，操之过急，反倒坏事。 对学生的教育既不能揠苗助长，也能任其自然。 【闻鸡起舞】听见鸡鸣就起身，比喻人发奋勇前进修，励精图治。 老爷爷在乡间修养，天天闻鸡起舞，打太极健身。 【哀鸿遍野】哀鸿：哀鸣的鸿雁。比喻饥寒交迫的灾民。比喻在天灾人祸中到处都是流离失所、呻吟呼号的饥民。 旧社会，每逢水灾战乱，人民就被迫四处逃亡，～，一片凄凉。 【联袂登台】同台演出 今晚的演出听说会有两位名角联袂登台献艺。 【使人咋舌】令人惊讶

成语解释及例句

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(12) 他这种放弃原则、瓦鸡陶犬的行径已经被揭露出来了。 (13) 适当放弃，做出斩钉截铁的决定，才能成为人生的赢家。 (14) 他委曲求全地放弃自己的主张，采纳了对方的意见。 (17) 我们要有愚公移山一样的斗志，坚持不懈，永远不放弃，去登上梦想的彼岸!(18) 只要有希望，就不能放弃。 (19) 为了大局着想，你应该委曲求全地放弃自己的看法。 (20) 既然考试迫在眉睫，我不得不放弃做运动。 (21) 即使没有人相信你，也不要放弃希望。 (22) 无论通往成功的路途有多艰辛，我都不会放弃。 (23) 在困难面前，你是选择坚持，还是选择放弃?(24) 无论前路多么的漫长，过程多么的艰辛，我都不会放弃并坚定地走下去。 (25) 你不要因为这点小事就英雄气短,放弃出国深造的机会。 (26) 像他这样野心勃勃的政客，怎么可能放弃追求权力呢?(27) 鲁迅有感于中国人民愚昧和麻木,很需要做发聋振聩的启蒙工作,于是他放弃学医,改用笔来战斗。 (28) 我们对真理的追求应该坚持不懈，锲而不舍，绝不能随便放弃自己的理想。 (29) 感情之事不比其他，像你这样期盼东食西宿，几个男友都捨不得放弃，最后必定落得一场空。 (30) 爷爷临终前的话刻骨铭心，一直激励着我努力学习，无论是遇到多大的困难险阻，我都不曾放弃。

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成语及解释造句 爱不释手：形容对某种东西喜爱得舍不得放下。《西游记》这本书有趣极了，叫人看了～。 爱屋及乌：比喻爱一个人连带地爱与他有关系的人或事物。祖父最疼爱大哥，～，连带也把大哥的女儿当心肝宝贝。 按部就班：指依着一定的次序，按着一定的步骤来计划行事。你不肯～地学习，老是想一步登天，难怪最后什么也学不成。 百年树人：比喻培养人才是长久大计。教育是～的大计，各国政府都投下大量人力、财力在教育事业上。 百折不挠：形容意志坚强，遇到任何挫折都不退缩或屈服。阿辉凭着～的精神，历经多次挫折，终于开创了自己的事业。 班门弄斧：比喻不自量力，在专家或行家面前卖弄本事。有时用来表示自谦。我这篇小说，在各位作家面前，只是～之作，还请大家多指教。 半途而废：指事情做到一半便停止。做任何事一定要有恒心，千万不可～。 包罗万象：内容丰富，形形色色，应有尽有。人们都爱到这家购物中心购物，因为这里的货物～，应有尽有。 闭门造车：比喻人的行为与现实情况脱节。作家想要写一部好作品，就不能～，必须去体验生活。 变本加厉：比喻变得比原来更加厉害。小文时常偷同学的钱，后来还～，偷老师的钱，结果被学校开除了。 标新立异：作出新奇、独特的事，和别人不一样。她为了表现自己，整天在装扮上～，浪费了不少时间和金钱。 别出心裁：表示新奇的、与众不同的手法。李明设计的服装～，在本地服装界十分突出，所以很受消费者欢迎。 宾至如归：形容招待客人周到、殷勤，使客人感到温暖。这家酒店服务周到，让人有～之感。不耻下问：指乐意向那些学问、地位比自己低的人请教与学习，一点也不觉得羞耻。老师虚心地向一位工友请教，同学都很敬佩她这种～的精神。 不攻自破：形容说话靠不住，不用攻击，自己就站不住脚了。当我们以行动证明自己的行为时，谣言便～了。事实是客观存在的，谎言在事实面前将～。 不可救药：比喻情况严重到无法挽救。【无可救药】大财不但抽烟赌博，现在还染上毒瘾，简直～了。 不可思议：形容无法想象或很难理解。他蒙住眼睛，也能画出这么美丽的山水画，真是～。 不劳而获：不劳作而占有别人劳动的成果。你这个懒惰虫老是想～，我才不让你得逞！ 不务正业：指不从事正当的职业。大哥自从退学后就～，整天在街头游荡，把爸爸气得差点断气。 不省人事：指昏迷过去，什么也不知道。宇平被车撞倒后就～，司机吓得连忙电召救护车。 不遗余力；

成语解释及造句

1一夫当关，万夫莫开:意思是山势又高又险，一个人把着关口，一万个人也打不进来。形容地势十分险要。示例:剑阁峥嵘而崔嵬，～。 2草木皆兵:把山上的草木都当做敌兵。形容人在惊慌时疑神疑鬼。 示例:这一天大家都是惊疑不定，～，迨及到了晚上，仍然毫无动静。 3赤膊上阵 光着膀子上阵。比喻亲身上场，不加掩饰地进行活动。 示例:他终于～，亲自出马了。 4乌合之众 释义:象暂时聚合的一群乌鸦。比喻临时杂凑的、毫无组织纪律的一群人。 示例:外边虽有些人，也是～，不相统摄。 :5打草惊蛇 释义:原比喻惩甲菟乙。后多比喻做法不谨慎，反使对方有所戒备。 示例:空自去“～”，倒吃他做了手脚，却是不好。 6四面楚歌 释义:比喻陷入四面受敌、孤立无援的境地。 示例:在这～里，凭你怎样伶牙俐齿，也只得服从了 :7用兵如神 释义:调兵遣将如同神人。形容善于指挥作战。 示例:三国时期的诸葛亮神机妙算，～。 :8有勇无谋 释义:只有勇气，没有计谋。指做事或打仗只是猛打猛冲，缺乏计划，不讲策略。示例:毕丰～，极贪酒色，不恤下人，喽罗尽皆离心。 9声东击西 释义:声：声张。指造成要攻打东边的声势，实际上却攻打西边。是使对方产生错觉以出奇制胜的一种战术。 示例:蜀人或～，指南攻北，吾兵必须分头守把。 10:坚壁清野 释义:对付强敌入入侵的一种方法。使敌人既攻不下据点，又抢不到物资。 示例:不许出战，只是～，待这干贼寇粮尽力弛，方可追他。 11揭竿而起 释义:砍了树干当武器，举起竹竿当旗帜，进行反抗。指人民起义。 示例:一时各路人马，～，不分昼夜，兼水路纷纷入鄂。 12豁然开朗 豁然：开阔敞亮的样子；开朗：地方开阔，光线充足、明亮。指顿时现出宽敞明亮的境界 听了他的话,我的心中豁然开朗,所有的忧愁都烟消云散了 13怡然自乐 怡然：安闲、愉快的样子。形容高兴而满足的样子 伸出双手，感受着花瓣飘落在手心的感觉，怡然自乐。 14鸡犬相闻 指人烟稠密 两个村子离得很近,简直是鸡犬相闻

体面的近义词-反义词及造句

体面的近义词|反义词及造句 我们还必须迅速采取行动，为实现社会包容和人人体面工作营造有利的环境。下面是小编精选整理的体面的近义词|反义词及造句，供您参考，欢迎大家阅读。 体面的近义词： 面子、合适、美观、颜面、场合、场面、排场、得体、好看、局面 体面的反义词： 难听、寒碜、邋遢、寒酸、难看 体面造句 1、我认为，帖在墙面上的证书，并不能使你成为一个体面的人。 2、他是那里唯一的看上去很体面的人;我认为他从来没有这样好看过。 3、所有的美国人都是好的，体面的人们每天都在践行着他们的责任。 4、美国人民慷慨、强大、体面，这并非因为我们信任我们自己，而是因为我们拥有超越我们自己的信念。 5、工人就是工人，无论他们来自哪里，他们都应该受到尊重和尊敬，至少因为他们从事正当的工作而获得体面的工资。 6、然而反之有些孩子可能就是多少有些体面的父母的不良种子这一概念却令人难以接受。

7、如果奥巴马能够成就此功，并且帮助一个体面的伊拉克落稳脚跟，奥巴马和民主党不仅是结束了伊拉克战争，而是积极从战争中挽救。 8、而且，等到年纪大了退休时，他们希望能得到尊重和体面的对待。 9、爸爸，您倒对这件事处理得很体面，而我想那可能是我一生中最糟糕的一个夜晚吧。 10、有一些积极的东西，低于预期的就业损失索赔和零售销售是体面的。 11、如果你努力工作，你就能有获得一份终生工作的机会，有着体面的薪水，良好的福利，偶尔还能得到晋升。 12、体面的和生产性的工作是消除贫困和建立自给自足最有效的方法之一。 13、同时，他是一个仁慈、温和、体面的人，一个充满爱的丈夫和父亲，一个忠实的朋友。 14、几周前我们刚讨论过平板电脑是如何作为一个体面且多产的电子设备，即使它没有完整的键盘，在进行输入时会稍慢些。 15、什么才是生活体面的标准? 16、我们还必须迅速采取行动，为实现社会包容和人人体面工作营造有利的环境。 17、她告诉我人们都担心是不是必须把孩子送到国外去学习，才能保证孩子们长大后至少能过上体面正派的生活。

成语解释和成语造句

1.孜孜不倦→勤勉不知疲倦。 他孜孜不倦的钻研学问。 2.坚持不懈→坚持到底不松懈。 他努力工作，坚持不懈，深受老板器重 3.变本加厉→变得比原来更加严重， 事隔二年，他的坏习惯不但没有改，反而变本加厉。 4.饱读诗书→读了很多诗书。 王老师饱读诗书，知识渊博，同学们都很尊重他。 5.反败为胜→从失败转为胜利。 下午的篮球赛，有了亮亮的上场，才反败为胜。 6.响彻云霄→声响透过云层，形容声音非常响亮。 我们的歌声响彻云霄。 7.汗流浃背→形容出汗多，背上的衣服都湿透了。 哥哥打完篮球，回家时总是汗流浃背的。 8.锦上添花→比喻美上加美，好上加好。 家里已经有了电视机，现在又买了电脑，真是锦上添花。 9.气喘如牛→比喻气喘得很厉害。 他刚跑完400米，就气喘如牛的问：「我是第一名吧？」 10.能跑善钻→形容动作灵活。 小强的动作很敏捷，能跑善钻，这次比赛应该是稳操胜券。 11.狂吠不已→狗不停地叫。 狗见到陌生人时，往往会狂吠不已。 12.提高警觉→要有敏锐的感觉。 在陌生的地方，夜间外出要提高警觉，尽量结伴而行。以策安全，13.呼朋引伴→招呼朋友，吸引伙伴。 鸟儿们在和煦的春风中呼朋引伴，唱出宛转的曲子。 14.大打出手→比喻逞凶打人或殴斗。 他们原本是好朋友，想不到竟为了一件小事而大打出手。 15.千变万化→形容变化极多。 天上的云，会随着气候的改变而千变万化，人们看云往往可以识天气。 16.五花八门：比喻变化多端或花样繁多。 这次趣味运动会的项目五花八门，妙趣横生，太棒了。 17.风吹草动→比喻轻微的动荡或变动。 敌人吃了败仗后，成了惊弓之鸟，一有风吹草动就惊惶逃窜。 18.生生不息→不停地繁衍生息。 我们伟大的中华民族就在中国这片神奇的土地上生生不息、代代相传。 19.欣欣向荣→草木生机旺盛的样子，比喻事业蓬勃发展，兴旺昌盛。我们的祖国到处是一派欣欣向荣、生机勃勃的新气象。 20.寸草不生→连小草也不能生长的地方，比喻荒凉贫瘠之地。 我们要把寸草不生的大沙漠改造成造福人民的绿洲 首尾乖互：相互违背，前后自相矛盾。