Optimize Power Consumption Research Articles

A Comparative Analysis of Energy-Efficient Protocols for WBAN on Heterogeneous Transceivers

Abstract Wide use of wireless sensors in medical services has given rise to another field called wireless body area networks (WBANs). WBANs consist of networks of wearable or implanted sensors that continuously capture and measure the vital parameters of the body. These sensor nodes have limited resources in terms of processing power, battery, and memory. Thus, the use of power has to be controlled for prolonging the network lifetime of WBAN systems. For this purpose, various energy-efficient protocols and their respective energy optimization techniques were developed to optimize power consumption, which consequently results in high energy efficiency. This article explores a power optimization model of three low-power routing protocols, namely, mobility-supporting adaptive threshold based thermal-aware energy-efficient multi-hop protocol (M-ATTEMPT), MBSTAR, and distance aware relaying energy-efficient (DARE), for WBAN. These protocols are implemented on three different test beds, and their conserved energy is compared for a varying number of sensors. Test beds were equipped with an ARM7 processor with different transceivers, namely, Bluetooth, Zigbee, and Wi-Fi. These protocols were implemented with varying transceivers taken for local case studies. Results are analyzed for the uniqueness of each protocol and their potential to support quick development and deployment of low-power WBAN systems.

Mars habitat power consumption constraints, prioritization, and optimization

The Hawai'i Space Exploration Analog and Simulation (HI-SEAS) is an experiment simulating long-duration life in a Mars habitat. Power for the habitat is generated by a photovoltaic system that exhibits daily variation in production rates. During days with cloud cover, the crew need to adapt their work schedule and support systems to ensure they can continue to function under low-power constraints. This paper accordingly presents the development and implementation of power budget profiles for low-, medium-, and high-power production days during Mission 5 of the HI-SEAS experiment. The applied power budget profiles limit which systems and devices can be used and for what duration. To generate these profiles, the HI-SEAS power subsystem was first characterized though power audits and data from daily crew use trends. The methods used to determine a prioritized list of habitat equipment for crew-member usage and compliance with restrictions are then discussed. Finally, an optimization method is proposed to determine the most efficient schedule to match each power usage profile with respect to crew preferences. The data from this experiment provide a novel opportunity to gain insight into power usage in space exploration habitats, establishing a foundation for the development of proper power generation and management technologies. Thus, this research can be used to provide meaningful guidance to most manned space systems in ensuring optimal power consumption under a variety of power generation conditions.

Optimization of Power Consumption Associated with Surface Roughness in Ultrasonic Assisted Turning of Nimonic-90 Using Hybrid Particle Swarm-Simplex Method.

These days, power consumption and energy related issues are very hot topics of research especially for machine tooling process industries because of the strict environmental regulations and policies. Hence, the present paper discusses the application of such an advanced machining process i.e., ultrasonic assisted turning (UAT) process with the collaboration of nature inspired algorithms to determine the ideal solution. The cutting speed, feed rate, depth of cut and frequency of cutting tool were considered as input variables and the machining performance of Nimonic-90 alloy in terms of surface roughness and power consumption has been investigated. Then, the experimentation was conducted as per the Taguchi L9 orthogonal array and the mono as well as bi-objective optimizations were performed with standard particle swarm and hybrid particle swarm with simplex methods (PSO-SM). Further, the statistical analysis was performed with well-known analysis of variance (ANOVA) test. After that, the regression equation along with selected boundary conditions was used for creation of fitness function in the subjected algorithms. The results showed that the UAT process was more preferable for the Nimconic-90 alloy as compared with conventional turning process. In addition, the hybrid PSO-SM gave the best results for obtaining the minimized values of selected responses.

Delay and Power Tradeoff With Consideration of Caching Capabilities in Dense Wireless Networks

Enabling caching capabilities in dense small cell networks (DSCNs) has a direct impact on file delivery delay and power consumption. Most existing work studied these two performance metrics separately in cache-enabled DSCNs. However, file delivery delay and power consumption are coupled with each other and cannot be minimized simultaneously. In this paper, we investigate the optimal tradoff between these two performance metrics. Firstly, we formulate the joint file delivery delay and power consumption optimization (JDPO) problem where power control, user association and file placement are jointly considered. Then we convert it to a form that can be handled by Generalized Benders Decomposition (GDB). with GDB, we decompose the converted JDPO problem into two smaller problems, i.e., primal problem related to power control and master problem related to user association and file placement. An iterative algorithm is proposed and proved to be $\epsilon$-optimal, in which the primal problem and master problem are solved iteratively to approach the optimal solution. To further reduce the complexity of the master problem, an accelerated algorithm based on semi-definite relaxation is proposed. Finally, the simulation results demonstrate that the proposed algorithm can approach the optimal tradeoff between file delivery delay and power consumption.

Application of Big Data Analysis and Internet of Things to the Intelligent Active Robotic Prosthesis for Transfemoral Amputees

With the advent and rising usage of Internet of Things (IoT) eco-systems, there is a consequent, parallel rise in opportunities where technology can find its place to improve a number of human conditions. However, this is nothing new - we have been perfecting the usage of tools to aid our daily living throughout history. The true evolution lies in the interaction between us and the tools we create. Tools are now smart devices, yielding an opportunity where human-device interaction is giving us the very knowledge on how to improve that particular synthesis. From improving our fitness to detecting bradycardia and response of traumatic brain injury patient, we have come to a point where we are able to gain actionable insight into a lot of aspects of our health and condition. This creates a certain autonomy in understanding the unique make-up of every single person, in addition to yielding information that can be used by health practitioners to help in diagnosis, determination of medical approach and right recovery and follow-up methods. All of this supported by two major factors: IoT platforms and Big Data Analysis (BDA). This paper takes a deep dive into exemplary set-up of IoT platform and BDA framework necessary to support the improvement of human condition. Our SmartLeg prosthetic device integrates advanced prosthetic and robotic technology with the state-of-the-art machine learning algorithms capable of adapting the working of the prosthesis to the optimal gait and power consumption patterns, which provide means to customize the device to a particular user.

Thermodynamic optimization of composite insulation system with cold shield for liquid hydrogen zero-boil-off storage

The study of zero-boil-off (ZBO) storage is of great significance for the long-term storage of liquid hydrogen (LH2). Preliminary experimental research on the utilization of cryocooler to achieve ZBO storage has been reported, but the optimization of the total power consumption has barely been considered. This paper will fully consider the working characteristics of the cryocooler, that is, refrigerator efficiency increases with the increase of its working temperature. A novel method to realize the cascade utilization of the cooling power of cryocooler is proposed, which can effectively reduce the total power consumption of ZBO system. A thermodynamic model has been developed to optimize the input power of cryocooler in LH2 ZBO storage with cold shied and multilayer insulation (MLI). Thermal coupling characteristics of cryocooler, cold shield and MLI has been studied at the minimum input power. The mechanism and optimization strategy have been explained quantitatively. By optimizing position and temperature of cold shield, the input power of cryocooler can be reduced by 69.5%–74.4%. In addition, the effects of MLI thickness and boundary temperature on the optimization of the cold shield have been studied. The influence of LH2 pressure in tank on cryocooler input power has also analyzed.

QoS-Based Robust Power Optimization for SWIPT NOMA System With Statistical CSI

Simultaneous wireless information and power transfer (SWIPT) that can prolong the lifetime of energy-limited wireless users has drawn considerable attention. In this paper, the power consumption optimization problem is investigated in SWIPT non-orthogonal multiple access (NOMA) system based on statistical channel state information (SCSI) to meet the probabilistic constraints of users’ quality of service (QoS) and energy harvesting. We assume that the strong user can decode information and harvest energy at the same time by employing power splitting, the harvested energy is used to communicate with other users, and the number of communication in a slot follows Poisson distribution. We derive the closed-form expressions of optimal power consumption with given users’ QoS by classification discussion. Simulation results are investigated to demonstrate the validity of closed-form expressions and that the SWIPT NOMA can outperform the SWIPT OMA in terms of the outage performance.

Low Power 32-Bit Floating Point Adder/Subtractor Design using 50nm CMOS VLSI Technology

In many DSP applications, generally multipliers and adders are two key components which are highly complex and consume more power. Out of that the design of adder circuitry is quite complex compared to multiplier which consumes more power. Hence optimization of power consumption of adder circuits is a challenging task in the recent year and is a need of today’s world. In order to give a justice to this problem, work presented in this paper describes the technique of designing floating point adder and subtractor using low power pipelining technique which leads to a reduction in power consumption by a significant amount. Moreover, the presented work in the paper deals with the design of low power transistorized architecture for 32-bit floating point adder/ subtractor without and with pipelining approach in 50nm CMOS VLSI technology. The experimental results demonstrated that, the dynamic power consumption of the floating point adder/subtractor architectures is reduced significantly by employing pipelining technique as compared to the without pipelining technique. Also, in this work a significant improvement has been achieved in the critical path for pipelined approach compared to without pipeline approach. The proposed design is a full custom design prepared and analyzed using cadence 6.15 tool.

Resource Allocation in Cloud Computing for Energy Efficiency

Cloud computing is a paradigm in which we have virtualized computer systems that deliver services, processing, storage, network, and other fundamental computing resources. Cloud computing enables low cost, device location independence, high reliability, scalability and sustainability. This paper describes the present state of cloud computing research by examining literature, identifying current study trends. We have analyzed the resource allocation method and concluded. It typically designs for high performance that supports the peak resource requirements. After several analyses the power consumption of data center and cloud systems as increased almost several times. There is a lack of research that addresses challenges of managing multiple resources with objective of allocating enough resources for each work load to optimizing power consumption. These papers survey various types of resource allocation algorithms that improve the cloud Infrastructure.

A Lightweight Algorithm To Optimize Power Consumption in Sensor Node Through Parametric Tuning of Communication Interface

Wireless sensor network is widely used to monitor sparsely generated events through a centralized system. The coverage provided by the network to monitor region of interest vary and rely on the system components of sensor node. While monitoring events from cluster head or sink through sensor nodes located at a distant, it experiences increased communication cost due to prone errors which are proportional to losses due to distance and interferences. Biotelemetry application is reviewed for the derivation of the research problem which is worked upon in the present paper. The animals move around in their habitat performing various activities which are to be monitored. The sensing tags are mounted on the animals to study the behaviour of the animals. These animals roam around in their habitat generating variation in the interferences caused for communication. Due to wide variations, the inefficiency of the sensor node in communication results in draining battery rapidly and thereby life of sensor node. So in order to improve lifetime the optimization at the sensor node is very essential to keep network alive. The technique that performs optimization needs to be lightweight in terms of processing required as well as tuning of parameter which are required for model based optimization methods. In the paper, we proposed a technique which is lightweight and can dynamically optimize operating state. It is done by adaptively configuring communication parameters to patch losses and conserve energy to enhance Sensor node lifetime. The optimization technique proposed, does parameter tuning to minimize the communication cost in sensor node through efficient search method. The results are compared with traditionally employed technique with static setting and Online Greedy Optimization Algorithm. NI LabVIEW is used to do simulation of the model and for estimating the effect of parameter reconfiguration upon application of optimization techniques.

Power Consumption Optimization and Home Automaton using Smart Sensor Networks

The process of obtaining power consumption optimization and home automation has been accounted. We are making use of various sensors for this purpose. All the sensors used are negative coefficient sensors. Unnecessary wastage of electricity is reduced with the help of sensors. Sensors are used to get information such as light intensity,temperature, humidity, harmful gases using LDRs, thermistors, humidity sensors and gas sensors respectively. The data is given to the GSM from controller with the help of Max232 IC. With the help of GSM,one can monitor the conditions in the environment from long distance also. The model has been broadly tried, in actuality, circumstances and exploratory outcomes are exceptionally reassuring. At first Zigbee wireless sensor network is used to monitor and control the system, but because of some limitations of the Zigbee network such as its inability for long range communications, GSM system is used in the extension part of the project

TAEO-A Thermal Aware & Energy Optimized Routing Protocol for Wireless Body Area Networks.

Wireless Body Area Networks (WBANs) are in the spotlight of researchers and engineering industries due to many applications. Remote health monitoring for general as well as military purposes where tiny sensors are attached or implanted inside the skin of the body to sense the required attribute is particularly prominent. To seamlessly accomplish this procedure, there are various challenges, out of which temperature control to reduce thermal effects and optimum power consumption to reduce energy wastage are placed at the highest priority. Regular and consistent operation of a sensor node for a long-time result in a rising of the temperature of respective tissues, where it is attached or implanted. This temperature rise has harmful effects on human tissues, which may lead to the tissue damage. In this paper, a Temperate Aware and Energy Optimized (TAEO) routing protocol is proposed that not only deals with the thermal aspects and hot spot problem, but also extends the stability and lifetime of a network. Analytical simulations are conducted, and the results depict better performance in terms of the network lifetime, throughput, energy preservation, and temperature control with respect to state of the art WBAN protocols.

Optimal power consumption control of sensor node based on (N, D)-policy discrete-time queues

In this paper, we consider two types of power consumption control policies for the long lifetime of wireless sensor node based on the discrete-time Geo/G/1 queue. One is the max(N, D)-policy, which triggers transmission mode of radio server when the N and D policies are met simultaneously, and another is the min (N, D)-policy, which restarts transmission function of radio server when either of the N and D policies is first satisfied. Under two control policies, the steady-state queueing analysis of sensor node is mathematically carried out. The mean queueing measures of sensor node, such as the mean number of data packets, mean transmission time backlog, mean waiting time, mean busy period, mean busy cycle period, and so on, are derived. Two power consumption functions are constructed through the queueing measures obtained. Numerical experiments validate that two policies are feasible and efficient for power consumption control of sensor node. At a minimum power consumption, the superiority of the N-policy, D-policy, and two dyadic (N, D) policies is numerically compared. Some practical insights on the operation of two (N, D) polices in power consumption control of sensor node are obtained.

A novel cost-aware algorithm for dynamic task placement problem in a heterogeneous Internet-scale data center

In recent years, data centers have deployed many rapidly growing Internet-scale services. As the size of the data center continues to expand, it not only causes huge energy consumption, but also brings environmental problems such as huge carbon emissions. However, for an Internet-scale data center, it is a challenge to optimize power consumption while meeting the growing demands of Internet-scale applications. Moreover, current data centers usually have heterogeneous servers (with different power consumption and computing capacity), which causes the dynamic task placement problem more complicated. In this work, we first observe two kinds of heterogeneity from the analysis of a public trace that was collected from a Google data center. Considering the demands in energy consumption and performance, we model the dynamic task placement problem in a heterogeneous Internet-scale data center and propose a heuristic cost-aware algorithm to solve it. By simulating and comparing with the other two scheduling algorithms, our proposed heuristic algorithm can gain a well energy saving and keep application performance within acceptable limits.

Design of a Solar-Powered Portable ECG Device with Optimal Power Consumption and High Accuracy Measurement

One of the best ways to monitor the health of the heart is to regularly record its electrical activity by using an electrocardiogram (ECG). Abnormal ECG signals may indicate conditions such as heart attack, arrhythmia, or heart defects. There are many ECG devices available which can detect and amplify this differential biological signal from the heart, allowing a lot of information to be collected quickly. The ECG is often small and easy to use, but its power is supplied from regular batteries, which need to be replaced after a certain period of use. This causes discomfort for elderly users. To overcome this limitation, in this paper, we aim to develop a solar-powered, portable Bluetooth device for ECG measurements. The device can be interfaced with smartphones or other wireless devices via Bluetooth by a distance up to 100 m. The ECG device was designed to use solar energy, which is also the main power source. Following the solar energy harvesting circuit is a solar panel with an output voltage of 2.4 V and a power out of 0.25 W. We optimized the design to have a very low power consumption and in sleep mode the current consumption is only around 40 µA. The device was designed with 24-bit resolution and a sampling frequency of up to 2133 Hz, which can allow high accuracy ECG measurements. The device is not only used for heart rate monitoring, but it can also assist doctors in analyzing ECG signals with a high accuracy via embedded operating software.

A Novel Approach to Optimize Power Consumption in Orchard WSN: Efficient Opportunistic Routing

In orchard wireless sensor networks (WSN) application, the network link quality is unstable due to the shielding effect caused by the growth of branches and leaves. Aiming at the energy constrains of orchard WSN, an expecting lowest-residue-energy maximization opportunistic routing (ELMOR) method is proposed. The method combined link connective probability to forwarding list construction optimization so that, one-hop transmission success rate and the balance of network energy consumption are taken into account during the forwarding list construction. In order to improve the energy balance between network nodes, the opportunistic path is chosen not only considering the transmission cost but also lowest node energy. In this paper, we also proposed an efficient/reliable topology management opportunistic routing which considers Packet Drop Rate with considering network interference and energy loss. Through extensive performance evaluation, results show that the one hop power consumption of ExOR (extremely opportunistic routing) is about 3 times of EEOR (Energy Efficient Opportunistic Routing), 4 times of ELMOR (Expecting Lowest-residue energy Maximization Opportunistic Routing), with a 60% one-hop link success rate. The end-to-end power consumption of ExOR is about 1.3 times of EEOR and 1.4 times of ELMOR. In addition, according to achieved results, network performance significantly improved.

Miniaturization of Monopole Patch Antenna with Extended UWB Spectrum via Novel Hybrid Heuristic Approach

Many of the wireless systems employ ultra wide band (UWB) for its efficient data rate and optimal power consumption. However, all the wireless devices need to have antenna size as small as possible. It is therefore important to design an antenna having the desired UWB features along with highest possible degree of miniaturization. In addition, it gives sufficient flexibility if different geometrical shaped antennas have the same physical and/or electro-magnetic characteristics. To jointly design such multi featured antennas is a complex multi objective optimization problem. These types of problems cannot be solved through classical numerical approaches; instead they require soft computing techniques to find the optimum results. This paper proposes a novel hybrid genetic particle swarm optimization algorithm to jointly optimize three printed monopole antennas for high degree of miniaturization. Moreover, attempt is also made to extend UWB spectrum to have more room for data transmission. The results are effective and promising.

Reduced carbon emission and optimized power consumption technique using container over virtual machine

Environmental warning is caused by IT industry which critically leads the global pollution with huge amount of toxic carbon emission which is drastically increasing day by day due to demand and usage raised. Due to the environmental warning the industries are in awful need of reducing the carbon foot print by inducing green computing. This paper has achieved green computing by implementing two different algorithms (1) Water Shower Model (WSM) and (2) Trigger—WSM load balancing algorithms, and two different techniques (3) Recommending Containers over virtual machine techniques and 4. DVFS (Dynamic Voltage Frequency Scaling) modeling. The observation between the recommendation systems for container over virtual machine for a sample of four containers with one application each and four virtual machine with one application each is monitored for carbon emission equivalent in kg co2 for about 1 week is 14 kg co2 for container and 84.4 kg co2 for virtual machine, where a drastic difference in the amount of carbon emission is seen. So recommending container will be the best possible solution for the IT based on applications, by enforcing these ideas and techniques the carbon emission can be drastically decreased and the amount of carbon footprint in the atmosphere will also be reduced. The amount of power consumption utilized for the same model is 15.71367 W for container and 94.72667 W for virtual machine is also observed; in the field of IT the power consumption also to be taken into consideration for reducing carbon emission. The recommendation system along with the proposed algorithm will reduce the amount of carbon footprint in the environment.

Optimal power consumption and surface quality in the circular sawing process of Douglas-fir wood

Optimal cutting conditions that result in high cutting accuracy and low power consumption are critical in lumber recovery and quality for sustainable wood manufacturing. Despite the many research on wood machining for secondary processing applications, less emphasis has been put on the challenges faced in primary sawing applications. These challenges are associated with online monitoring of surface quality through waviness measurement and conducting full-scale wood cutting experiments under extreme conditions. This paper investigated the effect of feed speed, rotation speed, depth of cut, and the average chip thickness on the power consumption and waviness during the sawing process of green Douglas-fir wood. Power consumption and waviness were measured to find the optimal cutting conditions for energy efficient cutting with high cutting accuracy. Waviness was monitored online using laser displacement sensors and the acquired signals were filtered using the wavelet denoising method. The results showed that cutting power and waviness increased with feed speed. While increasing the rotation speed accounted for higher cutting power, it resulted in less waviness. The impacts of rotation speed on cutting power and the waviness of the sawn lumber were discussed. The waviness is significantly greater at the board top as it is close to saw rim, which is characterized by higher blade deflection. For an identical chip thickness, energy efficient cutting was obtained under low-speed conditions, whereas high-speed conditions improved the waviness. There is a trade-off between productivity, cut quality, and power consumption.

Dynamic dispatch of thermostatically controlled loads using phase oscillator model

Heating Ventilation and Air Conditioning (HVAC) units are ubiquitous to any modern day infrastructure. HVACs are largely used for refrigeration/cooling and heating demands which are controlled using thermostatically controlled loads (TCLs). TCLs are a valuable resource for providing demand flexibility to the power system through demand response (DR) programs. One of the ways of attaining demand flexibility is by manipulating the set point temperatures or adjusting phase lag to achieve aggregate power reduction following a centrally broadcasted signal by the utility. These control actions though leading to DR management may lead to undesirable synchronization of ON/OFF cycle of loads. In this work we propose a novel Kuramoto based phase oscillator framework to provide distributed phase locking using time delays and thereby de-synchronization. These Kuramoto type interactions between the TCLs allows them to settle down to an optimum aggregate power consumption even in the case utility communication fails. Subsequently, it has been shown how such model can be realized using Boolean fundamentals and hence allow room for practical implementation. The model is proposed for homogeneous as well as heterogeneous set of TCLs and the results are verified using computer simulations. On a concluding note, the model is extended for a population of TCLs as well as for load following case driven by a utility signal.