Power Management

Deploying deep learning models for autonomous driving on resourceconstrained edge devices, such as the Raspberry Pi, presents significant challenges due to strict limitations on inference latency and memory capacity. To address these constraints, this study conducts a comprehensive comparative evaluation of lightweight convolutional neural networks (CNNs) optimized for dual-output regression of steering angle and driving speed. We benchmark a task-specific end-to-end baseline (NVIDIA CNN) against representative classification-oriented architectures-including MobileNet, ShuffleNet, Ef-ficientNet, GhostNet, and SqueezeNet-all reformulated for this regression task. Experiments were conducted on a physical Raspberry Pi-based autonomous RC car platform to assess prediction accuracy, inference speed, and real-world closed-loop driving stability using quantitative metrics such as the normalized jerk ratio. Experimental results demonstrate a clear trade-off: while Ghost-NetV1 0.5× achieved the highest regression accuracy with a Total R 2 score of 95.8% and MobileNetV1 recorded a competitive MAE of 1.95, they failed to provide stable control due to severe high-frequency steering jitter. Conversely, the NVIDIA CNN proved to be the most practical solution for general edge deployment, achieving the lowest inference latency of 61.1 ms (16.4 FPS) and a minimal memory footprint of 2.78 MB, ensuring stable autonomous navigation (1.50× jerk ratio). Furthermore, ShuffleNetV2 0.5× emerged as the superior architecture for trajectory precision, recording the lowest weighted MAE of 1.60. These findings underscore that theoretical accuracy does not guarantee real-world drivability on embedded systems, providing practical guidelines for hardware-aware model selection in edge-based autonomous driving.

In today's fast-paced business environment, efficient document management plays a critical role in maintaining productivity. Whether it's printing contracts, scanning invoices, or managing high-volume workflows, organizations need dependable office equipment that can handle daily demands. This is where Kyocera business copiers have earned a strong reputation among businesses of all sizes. Known for their durability, cost efficiency, and advanced document management features, Kyocera copiers help organizations streamline operations while reducing printing expenses. From small offices to large enterprises, these multifunction devices provide a practical solution for modern workplace requirements. What Are Kyocera Business Copiers? Kyocera business copiers are multifunction office devices designed to perform printing, copying, scanning, and document distribution tasks from a single machine. Unlike traditional standalone copiers, modern Kyocera systems integrate advanced technologies that support digital workflows, cloud connectivity, and enhanced security features. Businesses use Kyocera copiers to manage everyday document processes efficiently while minimizing maintenance costs and downtime. Key Features of Kyocera Business Copiers 1. Multifunction Capabilities Kyocera devices combine multiple office functions into one system. Employees can print, copy, scan, and fax documents without requiring separate machines, helping businesses save office space and reduce equipment costs.

In today's fast-paced business environment, efficient document management plays a critical role in maintaining productivity. Whether it's printing contracts, scanning invoices, or managing high-volume workflows, organizations need dependable office equipment that can handle daily demands. This is where Kyocera business copiers have earned a strong reputation among businesses of all sizes. Known for their durability, cost efficiency, and advanced document management features, Kyocera copiers help organizations streamline operations while reducing printing expenses. From small offices to large enterprises, these multifunction devices provide a practical solution for modern workplace requirements. Kyocera business copiers are multifunction office devices designed to perform printing, copying, scanning, and document distribution tasks from a single machine. Unlike traditional standalone copiers, modern Kyocera systems integrate advanced technologies that support digital workflows, cloud connectivity, and enhanced security features. Businesses use Kyocera copiers to manage everyday document processes efficiently while minimizing maintenance costs and downtime. Kyocera devices combine multiple office functions into one system. Employees can print, copy, scan, and fax documents without requiring separate machines, helping businesses save office space and reduce equipment costs.

The rapid growth of electric vehicles (EVs) demands intelligent, efficient, and reliable charging infrastructure. Conventional EV charging systems suffer from high switching losses, grid instability, thermal stress, and poor energy management. This paper proposes an AI-based adaptive power electronics control system for smart EV fast charging stations. The proposed system integrates a multi-layer neural network controller with an interleaved bidirectional DC-DC converter using Silicon Carbide (SiC) MOSFETs and a three-phase grid-connected inverter. The AI controller optimizes switching frequency, charging current, thermal management, and reactive power compensation in real time. Simulation results in MATLAB/ Simulink demonstrate 96.4% peak converter efficiency, Total Harmonic Distortion (THD) below 3.5% (compliant with IEEE Std 519-2022), a 26.9% reduction in charging time, 18°C maximum battery temperature rise, and a 44.7% reduction in converter power losses compared to conventional PI controllers. The system supports bidirectional energy flow for Vehicle-to-Grid (V2G) operation and seamless renewable energy integration, contributing toward future intelligent EV ecosystems for smart cities.

One of the biggest challenges for an IT administrator in a private or public data centre is to ensure a fair usage of resources between different Virtual Machines (VMs). If a particular VM does excessive network traffic, I/O or memory access, then other VMs running on that same server will experience a slowdown in their access of the same resource. This phenomenon is called noisy neighbours and results in a performance variation experienced by users over time, due to over consumption of shared resources by other VMs. This interference will occur even if each VM has adequate resources for its assigned workload due to conflict in the shared server resources. In this paper, we look at real-life data from Cloud based VMs showing the performance variability and present methods to detect it. A variation of this phenomenon is when a noisy neighbours can decipher confidential contents of a victim VM. We term it as a nosy neighbour, which can pose security risks. We present specific methods to prevent both noisy and nosy neighbours.

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A batteryless power management circuit incorporating an energy aware interface (EAI) for wireless sensor nodes (WSNs) powered by piezoelectric energy harvester (PEH) has been proposed and implemented. Traditional power management usually requires two DC-DC converters, each for maximum power point tracking (MPPT) and voltage regulation functionalities. The proposed circuit requires only one DC-DC converter for both the MPPT and voltage regulation. The EAI also provides a means to voltage regulation. This allows the circuit to have higher efficiency as the energy transfer does not have to go through two stages to reach the load. A PEH connected to the proposed circuit was tested under various vibration conditions. The circuit was found to have end-to-end efficiency of about 66% under most of the test conditions.

A batteryless power management circuit incorporating an energy aware interface (EAI) for wireless sensor nodes (WSNs) powered by piezoelectric energy harvester (PEH) has been proposed and implemented. Traditional power management usually requires two DC-DC converters, each for maximum power point tracking (MPPT) and voltage regulation functionalities. The proposed circuit requires only one DC-DC converter for both the MPPT and voltage regulation. The EAI also provides a means to voltage regulation. This allows the circuit to have higher efficiency as the energy transfer does not have to go through two stages to reach the load. A PEH connected to the proposed circuit was tested under various vibration conditions. The circuit was found to have end-to-end efficiency of about 66% under most of the test conditions.

This study develops and evaluates a quantum-inspired optimization framework integrated with artificial intelligence (AI)-driven smart grid analytics for improving renewable energy storage system performance in Pakistan. The increasing penetration of renewable energy sources such as solar and wind has created significant challenges related to intermittency, load balancing, energy dispatch, and grid stability. To address these issues, the study employs a simulation-based quantitative design to analyze the effectiveness of hybrid AIquantum optimization in enhancing storage efficiency, forecasting accuracy, and overall smart grid operational performance. The framework utilizes AI-based predictive models for energy demand forecasting and quantum-inspired optimization algorithms for optimal energy storage allocation and real-time decision-making. The results indicate that the proposed hybrid model significantly improves renewable energy storage efficiency, reduces operational costs, enhances load forecasting accuracy, and strengthens grid stability compared to conventional optimization approaches. Furthermore, energy storage efficiency is found to partially mediate the relationship between AI-driven analytics, quantum-inspired optimization, and smart grid performance, confirming its central role in system optimization. The findings demonstrate that quantum-inspired techniques outperform traditional heuristic methods in handling complex, nonlinear energy optimization problems, while AI enhances predictive intelligence in dynamic energy environments. This study contributes to the growing literature on intelligent energy systems by integrating AI and quantum-inspired computation within a unified optimization framework for renewable energy systems in emerging economies. It provides practical insights for policymakers, energy planners, and utility operators in Pakistan to improve energy sustainability, efficiency, and resilience.

Now a days, mobile networks is increasingly becoming important part of everyday life due which there is a rapid evolution mobile phone. Mobile phone comes into a powerful sensing platform. There are many scientists which are engaged in the emerging field of mobile sensing from a variety of existing communities, such as, mobile systems, machine learning and human computer interaction. The research and development in this field is rapid resulting in indispensable carry-on of daily life. But with the increase in development, data integrity and security has also become an important factor to take into consideration. Importantly, today's smart phones are programmable and come with a growing set of cheap powerful embedded sensors, which are enabling the emergence of personal, group, and community scale sensing applications. The mobile sensing platform provides many facilities like, it helps to communicate to Wireless sensor networks through a mobile sensor router Which attached to a users mobile phone. It helps in analysis of the sensed data which is derived from networks by cooperating with sensor middle-ware on a remote server to capture ones contexts. It also helps in providing context aware services for mobile users of cellular telephones. In this paper, we will discuss about different mobile sensing platforms that provides context-aware services for mobile users by accessing the surrounding wireless sensor networks. Along with this, we will briefly discuss some of the emerging sensing paradigms.

The pest namely coffee white stem borer (CWSB) has harmed the economic progress of many emerging countries as a result of arabica coffee’s agricultural products. The boring activity causes the stem to shrink, fade in color, and acquire translucent margins across the stem. The pest multiplier can be controlled by capturing the location with the utilization of a wireless sensor networks (WSNs) and blocking its exit point at the user end. In this work, we propose an integrated data aggregation with fault tolerance and lifetime energy-aware adaptive routing (IDALAR) approach to transfer the sensed pest location data. The efficient packet format and statistical models based routing between clusterheads (CHs) and base station (BS) is proposed considering the availability of resources such as message overhead, algorithmic complexity, residual energy, and control overhead are all used to calculate its performance.

We present the receiver in the first single-chip GSM/GPRS transceiver that incorporates full integration of quad-band receiver, transmitter, memory, power management, dedicated ARM processor and RF built-in self test in a 90-nm digital CMOS process. The architecture uses Nyquist rate direct RF sampling in the receiver and an all-digital phase-locked loop (PLL) for generating the local oscillator (LO). The receive chain uses discrete-time analog signal processing to down-convert, down-sample, filter and analog-to-digital convert the received signal. A feedback loop is provided at the mixer output and can be used to cancel DC-offsets as well to study linearization of the receive chain. The receiver meets a sensitivity of 110 dBm at 60 mA in a 1.4-V digital CMOS process in the presence of more than one million digital gates. Index Terms-All-digital phase-locked loop (ADPLL), built-in self-test (BIST), cellular, GPRS, GSM, low-area, low-cost, mobile phones, multi-tap direct sampling mixer (MTDSM), radio frequency (RF), sigma-delta, single-chip, system-on-chip (SoC), transceiver. L OW-COST wireless handsets are expected to find wide- spread use in the next few years in Asia and Africa. Investment in cellular infra-structure is now the preferred choice in developing and under-developed nations for improving the communication infrastructure and consequently, improving the standard of living of their people. Cost reduction is traditionally achieved by developing highly integrated solutions in addition to reducing the cost of individual components that make up the solution. A wide spectrum of choices exist ranging from highly integrated system in a package (SIP) to highly integrated system on a chip (SoC). The entire phone solution includes SAW filters, RF switches, power amplifiers, RF transceivers for several indoor and cellular standards, power management ICs, audio and video codecs, baseband processors, application processors, FLASH memory and several peripherals. Considering the diverse technologies needed to construct a mobile phone,

Panduit, a manufacturer of communication infrastructure products, requested a receiver be designed and implemented to harvest wireless RF energy to power remote sensors. In the first iteration, the RF signal will be transmitted from a base station operating at 915 MHz with future iterations using the RF energy in the digital TV bands. This report describes the design, simulation, and implementation of multiple RF-DC charge-pump circuits. Recent published literature describes the efficacy of such topologies for RF energy harvesting. Both a 2-stage charge-pump and a 5-stage charge-pump, optimized for different incoming power levels, are presented. These circuits, consisting of matching circuits, diode-capacitor stages, and a load, were designed and simulated using SPICE® and ADS®. The microstrip circuit boards were fabricated by Micro Circuits based on ADS® designs and components inserted by the team members. The report compares simulated results to experimental results.

Plan Opportunities Coordination Kit), a decision support system for long-term mission planning. The work was carried out within the Advanced Planning and Scheduling Initiative (APSI), a project funded by ESA which aims at creating the basis for a general, flexible and reusable software framework (named here APSI-TRF -APSI Timeline-based Representation Framework) to facilitate injection of AI Planning and Scheduling in space missions to enhance ESA mission operation management performance. The paper first overviews the framework features then shows them at work in supporting the realization of MrSPOCK. The paper shows how to solve an interesting multi-objective optimization problem requiring the satisfaction of various temporal and causal constraints. It then shows how the modeling capabilities of the APSI-TRF supports both the synthesis of an end-to-end approach to the problem, and open the possibility to flexible extensions of the application with added value in terms of modularity, extensibility and reusability. To this purpose, the main steps for the development of an extended application, which includes a model of the satellite power management subsystem are also described.

Inter-firm power often plays a critical role in the supply chain. This research seeks to expose the detrimental and beneficial effects of power on the ability to build integrated, high performance buyer-supplier relationships. In doing so, the research highlights the need for power awareness and promotes the benefit of effective power management. *** indicates significance at α = .01 ** indicates significance at α = .05 * indicates significance at α = .10

Thermal management of DRAM memory has become a critical issue for server systems. We have done, to our best knowledge, the first study of software thermal management for memory subsystem on real machines. Two recently proposed DTM (Dynamic Thermal Management) policies have been improved and implemented in Linux OS and evaluated on two multicore servers, a Dell PowerEdge 1950 server and a customized Intel SR1500AL server testbed. The experimental results first confirm that a system-level memory DTM policy may significantly improve system performance and power efficiency, compared with existing memory bandwidth throttling scheme. A policy called DTM-ACG (Adaptive Core Gating) shows performance improvement comparable to that reported previously. The average performance improvements are 13.3% and 7.2% on the PowerEdge 1950 and the SR1500AL (vs. 16.3% from the previous simulation-based study), respectively. We also have surprising findings that reveal the weakness of the previous study: ...

The Linux kernel underpins Android, and the gap between what the kernel is capable of and what most devices actually deliver is wider than it should be. This paper examines kernel-level optimizations across three interconnected domains: power management, network efficiency, and hardware integration, specifically within the Android ecosystem from Android 14 through current stable and beta releases, covering kernel versions 6.1 and 6.6 under Google's Generic Kernel Image (GKI) initiative. The analysis extends to custom Android distributions, including GrapheneOS, CalyxOS, and LineageOS, running on Qualcomm Snapdragon, Samsung Exynos, and MediaTek SoC platforms. Techniques discussed include Dynamic Voltage and Frequency Scaling (DVFS), Energy-Aware Scheduling (EAS), TCP/IP stack tuning, I/O scheduler selection, memory management strategies, and kernel security hardening. Rather than presenting experimental results, this paper synthesizes existing research, identifies the current theoretical state of these optimizations, and outlines directions where controlled experimental work would yield the most meaningful contributions. The goal is to establish a grounded theoretical foundation that future researchers and kernel engineers can use as a starting point for targeted, reproducible experiments. CCS Concepts: • Computer systems organization → Embedded systems; Real-time systems; • Software and its engineering → General programming languages.

This work introduces and aim to overcome the potential challenges while deploying automated tuning of relational database as a service for a Platform as a Service (PaaS) provider. Some of the major challenges identified in this work include (i) automated detection of performance throttling (figure out when the performance of the system is affected due to incorrect configurations of knobs) of a database and identify potential points where a database requires a tuning, (ii) scalability and accuracy of tuning service and (iii) applying the recommendations obtained from tuning services wherein applying an obtained recommendation might require a database restart. In this work, we present a generic tuning service architecture for PaaS providers. To deal with the above challenges, we introduce performance throttling engine which is responsible to detect potential points when a relational database actually needs a knob tuning, which helps in increasing the scalability and accuracy of the tuner deployments (responsible for tuning production landscapes). This work also proposes approaches that facilitate efficiently applying the recommendations without causing much disruption in Quality of Service (QoS) of the underlying database system. Lastly, the results are obtained by evaluation of the proposed methods and modules on multiple cloud native provisioners against various set of metrics. * Produces the permission block, and copyright information † The full version of the author's guide is available as acmart.pdf document

To enhance the fuel efficiency of fuel cell hybrid electric vehicles (FCHEVs), we propose a hierarchical energy management strategy (HEMS) to efficiently allocate power to a hybrid system comprising a fuel cell and a battery. Firstly, the upper-layer supervisor employs a fuzzy faulttolerant control and prediction strategy for the battery and fuel cell management system, ensuring vehicle stability and maintaining a healthy state of charge for both the battery and fuel cell, even during faults. Secondly, in the lower layer, dynamic programming and Pontryagin's minimum principle are utilized to distribute the necessary power between the fuel cell system and the battery. This layer also incorporates an optimized proportional-integral controller for precise tracking of vehicle subsystem set-points. Finally, we compare the economic and dynamic performance of the vehicle using HEMS with other strategies, such as the equivalent consumption minimization strategy and fuzzy logic control strategy. Simulation results demonstrate that HEMS reduces hydrogen consumption and enhances overall vehicle energy efficiency across all operating conditions, indicating superior economic performance. Additionally, the dynamic performance of the vehicle shows significant improvement.

Server power and cooling power amount to a significant fraction of modern data centers&#39; recurring costs. While data centers provision enough servers to guarantee response times under the maximum loading, data centers operate under much less loading most of the times (e.g., 30-70% of the maximum loading). Previous server-power proposals exploit this under-utilization to reduce the server idle power by keeping active only as many servers as necessary and putting the rest into low-power standby modes. However, these proposals incur higher cooling power due to hot spots created by concentrating the data center loading on fewer active servers, or degrade response times due to standby-to-active transition delays, or both. Other proposals optimize the cooling power but incur considerable idle power. To address the first issue of power, we propose PowerTrade , which trades-off idle power and cooling power for each other, thereby reducing the total power. To address the second issue of r...

This paper studies a Hybrid Renewable Energy System (HRES) as a reliable source of the power supply in the case of the connection to the grid. The grid connection imposes restrictions to the power delivered and harmonic content on the HRES. This causes the HRES to use multiple control systems and subsystems, as the normalization of the measurements, the current control, active harmonic compensation, synchronization, etc., described in this paper. Particular attention was paid to interactions in the storage system of the HRES. The durability of the HRES can be increased by the combination of the supercapacitors and batteries. This requires a power management solution for controlling the energy storage system. The aim of the supercapacitors is to absorb/inject the high-frequency fluctuations of the power and to smooth out the power of the batteries system of the HRES. This can be possible owing to the use of a low-pass second order filter, explained in this paper, which separates the ...

a 100 Gfps camera system for laser fusion research by sweeping an electron beam bundle in a streak tube in a direction slightly slanted to a grid of holes on a metal light shield in front of the photoelectron conversion layer 1) . The year 2014 was an epoch-making year for ultra-high-speed imaging. Three reports on 100 Gfps to 1 Tfps imaging were presented: (1) a 100 Gfps camera system with a streak camera and random-dot illumination 2) , (2) a 1 Tfps imaging apparatus using chirping and detaching a short laser pulse and multi-spectrum imaging 3) , and (3) a 1 Tfps imaging method consisting of femtosecond laser illumination, picosecond-accurate detectors and mathematical reconstruction techniques, though this is not consecutive imaging 4) . In practice, multi-framing cameras for burst-imaging at about 1 Gfps are available. The camera splits an incident light beam with a mirror set to make the same images as the incident one, sends them to built-in multi-high-speed gating cameras, and gates the cameras in turn at an interval of about 1 ns. The fundamental problem of the camera system is that the light incident to each gating camera reduces proportionately to the inverse of the number of the built-in cameras. Therefore, the sensitivity is less than 1/N of that of the built-in camera, where N is the number of the built-in cameras. Higher sensitivity is crucial in ultra-high-speed imaging. Other methods also have disadvantages, such as lower spatial resolution, bulky systems, and lower sensitivity. On the other hand, no solid-state image sensor has allowed for imaging at the frame rate more than 1 Gfps. Recently, Mochizuki, Kagawa et al. presented a CMOS imager with groups of multiple pixels, each operated with different shuttering patterns, which stores compressed consecutive images. Solving the inverse problem of the compressed image data provided burst images at the frame rate of 200 Mfps 5) . We proposed a structure of a 3D-stacked image sensor consisting of a BSI MCG image sensor a) chip and a driver chip with in-situ ROXNOR b) drivers, which enables burst imaging faster than 1 Gfps with a 100% fill factor 6) . To achieve a higher frame rate, the limiting factors of the frame rate of the sensor chip are analyzed in this paper. The performance of the ROXNOR driver chip is analyzed in the sister paper 7) . The test chip is under process in IMEC. (Notes: a) Backside Illuminated Multi-Collection-Gate image sensor, b) A driver consisting of Ring Oscillator with XNOR circuits)

The number of cloud computing users has been steadily increasing in recent years as it has become a very important technology in the computing landscape. It provides customers with decentralized services and a pay-as-you-go approach to resource usage. The growing demand for cloud services is forcing providers to deploy an increased data center infrastructure with thousands of hosts and servers to store and process data. As a result, these large servers generate a lot of heat with visible carbon emissions in the air as well as high energy consumption and higher operating costs. For this reason, research is continuing in the field of energy management, including techniques for saving energy in servers, networking, cooling, renewable energy, etc. In this paper, we address the existing energy-efficient methods in the field of green cloud computing and present our green cloud solution for dynamic resource management in data centers. Our proposed approach aims to reduce the energy consumption of the infrastructure and maintain the required performance.

Solar power is amongst the better renewable options for making power in a way that can go on for good. Being in the tropics means India gets sun all the time, and so systems using solar PV are very likely to work well. This research looks at the weather and how solar radiation falls, in order to work out how much solar power could be made in Ayodhya district, Uttar Pradesh, India. We looked at data from NASA POWER and PVGISboth based on satellitesto work out how much solar radiation there is. This included important things like Global Horizontal Irradiance, or GHI, Direct Normal Irradiance, or DNI, radiation that isn't direct, temperature, how damp it is, and cloud. Maths models of solar radiation were used to work out the angles of the sun and how much electricity photovoltaic systems might be able to make. The results showed that Ayodhya gets, on average, 5.3 to 5.5 kWh/m2/day of solar radiation each year; it's at its highest before the monsoon, and drops when the monsoon is on because of cloud. Modelling photovoltaic systems suggests that the district is very good for solar power to be developed, and that it could make 1650-1750 kWh/kWp per year. The results show that solar power is possible in Ayodhya, using either solar on roofs, or large solar farms.

This paper presents a novel method for directly computing the sharing of each generator in a power system using the Power Division Theorem (PDT) within the Energy Management System (EMS) of Supervisory Control and Data Acquisition SCADA. Real time operational data acquired in actual values are converted into per unit values for load flow and state estimation analysis. Using these normalized quantities, the proposed approach enables immediate estimation of generator contributions to loads and losses at d ifferent system levels. The method introduces the concept of Common Source Node Voltage (CSNV) to achieve minimum-loss operation. An illustrative example demonstrates reduced system losses under the proposed constraint. The approach provides a simple and computationally efficient enhancement for real time monitoring and control in modern power systems.

Power management is one of the key design challenges in the design of Portable Multimedia Devices (PMD). Existing power management techniques are limited to hardware based DVFS (Dynamic schemes and do not take into account application states and many usage scenarios. In this correspondence, a new Unified Power Management Framework (UPMF) is proposed which describes a software architecture for a unified hardware and software controlled power management. The framework provides a set of rules for classifying the several devices on a PMD into device classes. Each of these device classes has a set of well-defined states based on the application state. The power management framework contains a power manager module that monitors the application and maintains the states of the devices and based on the power management strategy, controls the states of the devices. The proposed UPMF is very simple to implement and is well suited to handle power management strategies for several classes of applications. Performance of this proposed scheme for a Portable Media Player and Recorder device is also presented.

Kashim Ibrahim University, Maiduguri faces persistent energy shortages due to unreliable grid supply and reliance on diesel generators. Earlier proposals for standalone solar PV systems overlooked wind resources and full techno-economic optimization, highlighting the need for a more resilient hybrid approach. This study aims to evaluate and optimize an off-grid wind-solar hybrid power system for reliable and sustainable electricity supply at Kashim Ibrahim University. The assessment was carried out using hourly electrical load data and validated sitespecific meteorological data, including solar irradiance, wind speed, and temperature, modeled and optimized in HOMER Pro software. The optimal configuration includes 9.25 MW PV, 678 kW wind, lead-acid storage, and a bidirectional converter, which could provide 100% renewable energy with negligible unmet load. With a levelized cost of energy (LCOE) of ₦85.18/kWh and a 3.9year payback period, the system outperforms grid and diesel alternatives by producing 17.63 GWh yearly to satisfy the 3.21 GWh demand. Over a 25-year period, the system prevents more than 308,000 tonnes of CO₂ emissions and reduces air and noise pollution. Strong temperature resilience is confirmed by sensitivity analysis, where temperature variation between 25-35°C results in only a 3.5% reduction in energy production. The optimized wind-solar hybrid system offers a cost effective, reliable, and environmentally sustainable energy solution for institutional power supply in northeastern Nigeria. Phased implementation is recommended for Kashim Ibrahim University and other institutions facing persistent energy insecurity.

Mobile ad hoc networking offers convenient infrastructure-less communication over the shared wireless channels. The major research efforts in the area of Mobile Ad hoc Network (MANET) focus on developing efficient routing protocols assuming that IP addresses of mobile hosts have been already configured before joining the network. Providing security for IP address auto-configuration in MANET is still an open problem. Existing solutions for IP address autoconfiguration in MANET do not address security issues. However, it may disserve network security if there is not a reliable authentication mechanism, e.g. an attacker may spoof other nodes and hijack their traffic. Unlike their wired counterpart, infrastructure-less ad hoc networks do not have a clear line of defense, and every node must be prepared for encountering with an adversary. Therefore, a centralized or hierarchical network security solution does not work well. This paper describes the state of research in secure address auto-configuration problem and analyzes the current existing solutions.

The design and development of a smart monitoring and controlling system for household electrical appliances in real time has been reported in this paper. The system principally monitors electrical parameters of household appliances such as voltage and current and subsequently calculates the power consumed. The novelty of this system is the implementation of the controlling mechanism of appliances in different ways. The developed system is a low-cost and flexible in operation and thus can save electricity expense of the consumers. The prototype has been extensively tested in real-life situations and experimental results are very encouraging.

Various constraints of Static Random Access Memory (SRAM) are leading to consider new memory technologies as candidates for building on-chip shared last-level caches (SLLCs). Spin-Transfer Torque RAM (STT-RAM) is currently postulated as the prime contender due to its better energy efficiency, smaller die footprint and higher scalability. However, STT-RAM also exhibits some drawbacks, like slow and energy-hungry write operations, that need to be mitigated before it can be used in SLLCs for the next generation of computers. In this work we address these shortcomings by leveraging a new management mechanism for STT-RAM SLLCs. This approach is based on the previous observation that although the stream of references arriving at the SLLC of a Chip MultiProcessor (CMP) exhibits limited temporal locality, it does exhibit reuse locality, i.e., those blocks referenced several times manifest high probability of forthcoming reuse. As such, conventional STT-RAM SLLC management mechanisms, mainly focused on exploiting temporal locality, result in low efficient behavior. In this paper, we employ a cache management mechanism that selects the contents of the SLLC aimed to exploit reuse locality instead of temporal locality. Specifically, our proposal consists in the inclusion of a Reuse Detector between private cache levels and the STT-RAM SLLC. Its mission is to detect blocks that do not exhibit reuse, in order to avoid their insertion in the SLLC, hence reducing the number of write operations and the energy consumption in the STT-RAM. Our evaluation using multiprogrammed workloads in both a quad-core and a eight-core system reveals that our scheme reports on average, energy reductions of 40% (quad-core) and 35% (eight-core) in the SLLC, an additional 6.5% (in both quad and eight-core) energy reduction in the main memory, and improving performance by 3% (quadcore) and 7% (eight-core) compared to a STT-RAM SLLC baseline where no reuse detector is employed. More importantly, our approach outperforms DASCA, the state-of-the-art STT-RAM SLLC management, reporting energy savings in the range of 6-11% higher than those of DASCA, delivering higher performance in the range of 1.5-9%, and an additional improvement in DRAM energy consumption in the range 2-9% higher than DASCA -all these ranges depending on the specific scenario and the kind of applications used-.

Power consumption became a crucial problem in the development of mobile devices, especially those that are communication intensive. In these devices, it is imperative to reduce the power consumption devoted to maintaining a communication link during data transmission/reception. The application of dynamic power management methodologies has contributed to the reduction of power consumption in general purpose computer systems. However, to further reduce power consumption in communication intensive real-time embedded devices we have to consider the state of the computation and external events in addition to power management policies. In this paper we propose a model of an Extended Power State Machine (EPSM), where we adapt a Power State Machine to include the state of an embedded program in the power state machine formulation. This EPSM model is used to adapt the Quality of Service (QoS) in communication intensive devices to ensure low power consumption. In such development, a middleware layer fits in the system's architecture, being responsible for intercepting the data communication and implementing the EPSM. Also, a software tool was developed, allowing the Middleware Code to be generated based on the State Machine. A case study demonstrates the application of the proposed model to a real situation.

Imbalance and out-of-range input signals can cause inaccuracy in fully differential successive approximation (SAR) analog to digital converter (ADC). Therefore, implementation of an ADC driver can solve the problem since the input can be properly adjusted to suit with an ADC input. AD8139 single to differential amplifier was chosen as an ADC driver in this design and placed on a printed circuit board (PCB) to drive differential input signal of SAR ADC. The result shows each of output amplitude of the amplifier remains equal and is 180° out of phase for DC and AC input signal. The fabricated 10 bit SAR ADC is capable to digitize full code from analog input produced by the ADC driver.

The authors would like to thank the support and founding from the EU 6th framework, and the collaboration with the project partners of Intelligent DC/DC Converter for Fuel Cell Road Vehicles (INTELLICON) and the project partners of Hybrid High Energy Electrical Storage (HYHEELS).

The authors would like to thank the support and founding from the EU 6th framework, and the collaboration with the project partners of Intelligent DC/DC Converter for Fuel Cell Road Vehicles (INTELLICON) and the project partners of Hybrid High Energy Electrical Storage (HYHEELS).

Energy-aware computing is gaining more and more attention in high performance computing (HPC) environment. As an outcome of this, various energy-aware techniques are existing and many are being proposed. But it is difficult to have a technique which saves energy without compromising the performance. This paper talks about a novel energy optimization approach for Message Passing Interface (MPI) applications running on HPC systems. Our approach relies on applying Dynamic Voltage Frequency Scaling (DVFS) at node level by an optimization agent. Whenever MPI processes are idle or busy with I/O operations, the corresponding CPU cores run at higher frequencies, which results in wastage of power. During this time, CPU cores frequencies can be reduced using DVFS so that the energy can be saved. Our approach is based on a Multi-agent based intelligent energy management framework, which uses an optimization agent for implementing energy optimization algorithm. The key advantage of the proposed approach is that the performance will not be compromised while achieving energy savings.

The increasing penetration of renewable energy and the growing demand for cross-border electricity transfer through interconnection pose significant challenges to voltage stability in modern smart grids operation. Among the various Flexible AC Transmission Systems (FACTS) devices in power system management, the Static Synchronous Compensator (STATCOM) has emerged as an effective solution for dynamic voltage regulation and reactive power control. This paper presents a review of STATCOM applications in smart grids operation, focusing on its role in maintaining voltage stability and enhancing power flow. To complement the review, a case study is developed on a 500 kV, 150 km British Columbia (Canada) and Washington (USA) grid interconnection line. A MATLAB/Simulink model is implemented to evaluate system behavior under normal operation and fault conditions, both with and without STATCOM. Simulation results demonstrate that STATCOM significantly improves voltage recovery, reduces oscillations, provides rapid reactive power support, and stabilizes the DC link voltage. These findings confirm the practical importance of STATCOM in smart grid operations, particularly in long-distance and high voltage interconnections. Future directions are also highlighted, including advanced control strategies and renewable energy integration in Energy Management Systems of Smart Cities.

1 Faculty of Engineering, Minia University, Email: [email protected] 2 Telecom Egypt Co. Email: [email protected] ---------------------------------------------------------------------***--------------------------------------------------------------------Abstract In this paper a hybrid power system of photovoltaic / regenerative fuel cell (PV/RFC) is introduced. The role of this system is the production of electricity without interruption for a remote telecom station. The studied system is proposed PV subsystem work as a primary source that converting a solar irradiation into electricity. The second working subsystem is the electrolyzer part in RFC which produces hydrogen and oxygen from water as a result of an electrochemical process using surplus energy. Produced hydrogen is sent to a storage tank. The produced hydrogen is used by fuel cell part for producing electrical energy to supply loads during deficit times. Optimum sizing of this hybrid power system is introduced and the ...

Esta comunicação descreve o desenvolvimento do protótipo de um repetidor para ambientes interiores, que será usado com a tecnologia CDMA2000 na faixa dos 460 MHz. O protótipo, que fica intercalado entre 2 antenas, consiste num módulo activo que efectua amplificação bi-direccional. Foram realizadas medidas de campo com este sistema, mostrando-se uma clara melhoria de cobertura.

In this paper, we present Chameleon-an application-level power management approach for reducing energy consumption in mobile processors. Our approach exports the entire responsibility of power management decisions to the application level. We propose an operating system interface that can be used by applications to achieve energy savings. We consider three classes of applications-soft real-time, interactive and batch-and design user-level power management strategies for representative applications such as a movie player, a word processor, a web browser, and a batch compiler. We implement our approach in the Linux kernel running on a Sony Transmeta laptop. Our experiments show that, compared to the traditional system-wide CPU voltage scaling approaches, Chameleon can achieve up to 32-50% energy savings while delivering comparable or better performance to applications. Further, Chameleon imposes small overheads and is very effective at scheduling concurrent applications with diverse energy needs.

Power constrained systems, dierent from traditional low power systems, are becoming more recognized. The operation of these systems is not constrained only by the availability of traditional resources such as software or hardware, but is limited by applicable power. Designing such systems poses new challenges. We meet these challenges by departing from the classical low power design approach and taking a power elastic system view. In this paper we present an architectural level solution based on real-time feedback control to t system operation into power constraint proles. Investigations into concurrency management as the main method for such real-time control are carried out. As part of this methodology we present a new approach, called `soft arbitration', which can be applied to solving the problem of energy resource allocation and power capping. This work provides a concrete foundation for the power elastic methodology through developing a set of modelling, analysis, design and implementation techniques covering both theoretical and practical issues. Microelectronic system design is becoming more energy conscious, because of limited energy supply (scavenged energy or low battery) and excessive heat with associated thermal stress and device wear-out. At the same time, the high density of devices per die and potentially high parallelism, coupled with environmental variations, create almost permanent instability in voltage supply (cf. Vdd droop), making systems highly power variant. Conventional low power design was targeted merely at the reduction of capacitance, Vdd and switching activity, whilst maintaining the required system performance. In many current applications, the design objectives are changing to maximising the performance within the dynamic power constraints from energy supply and consumption regimes. Such systems can no longer be simply regarded as low power systems, but rather as power-adaptive or power-resilient systems. Under varying environmental conditions, with voltage and thermal uctuations, timing tends to be the rst issue aected. Most systems are still designed with global clocking and are overly pessimistic to avoid failures due to timing variations. To reduce these margins designers now consciously allow parts of systems to fail, albeit rarely, to maintain the overall balance between performance gains and reasonably low error rate [6][12]. Elsewhere designers are moving towards timing elasticity and a wider use of asynchronous design methods. It has been shown that the latter, materialised into `elastic voltage scaling', can lead to 30-40% average power savings under the same level of performance . The former technique suits CPU pipelines but the latter seems to be more universal and appropriate for more heterogeneous systems such as SoCs and 3D die-stacks. This trend is set to continue in a widening scope of embedded applications and multi-core and heterogeneous systems. These methods are generally based on the assumption of relatively rigid energy supply levels. Computations tend to be scheduled based on a prior knowledge NCL-EECE-MSD-TR-2010-155, University of Newcastle upon Tyne

SMT processors are widely used in high performance computing tasks. However, with the improved performance of the SMT architecture, the utilization of their functional units is significantly increased, straining the power budget of the processor. This increases not only the dynamic power consumption, but also the leakage power consumption due to the increased temperature. In this paper, a comparison of the static and dynamic sleep signal generation techniques for SMT processors is presented. This is conducted under various workloads to assess their effectiveness in leakage power management. Results show that the dynamic approach exhibits a three-fold increase in leakage savings, compared with that of the static approach for certain functional units.

In this paper, a power management technique based on dynamic frequency scaling is proposed. The proposed technique targets digital receivers employing adaptive sampling. Such circuits over-sample the analogue input signal, in order to succeed timing synchronization. The proposed technique introduces power savings by forcing the receiver to operate only on the "correct" data for the time intervals during which synchronization is achieved. The simple architectural modifications, needed for the application of the proposed strategy, are described. As test-vehicle a number of FIR filters, which are the basic components of almost every digital receiver, are used. The experimental results prove that the application of the proposed technique introduces significant power savings, while negligibly increasing area and critical path.

In this work, Wireless Sensor Network (WSN) applications that require long-term sustainability are considered. Energy harvesting forms a promising technology to address this challenge, by allowing each node to be entirely powered by energy harvested from its environment. To be sustainable, each node must dynamically adapt its Quality of Service (QoS), regarding the harvested energy using a power management strategy. This strategy is implemented on each node by the Power Manager (PM). In this paper, GRAPMAN (GRAdual Power MANager) is proposed, a novel PM for Energy-Harvesting WSN (EH-WSN) powered by pseudo-periodic energy sources. Unlike most state of the art PMs, GRAPMAN aims to achieve high average throughput while maintaining consistent QoS, i.e. with low fluctuations with respect to time, by looking for the highest throughput that can be supplied by the node over a finite time horizon while remaining sustainable. We show through extensive trace-driven network simulations that GRAPMAN outperforms state of the art PMs in both average throughput and throughput consistency.

Energy harvesting is a promising approach to enable autonomous long-life wireless sensor networks. As typical energy sources present time-varying behavior, each node embeds an energy manager, which dynamically adapts the power consumption of the node to maximize the quality of service, while preventing power failure. In this work, RLMan, a novel energy management scheme based on reinforcement learning theory, is proposed. RLMan dynamically adapts its policy to timevarying environment by continuously exploring, while exploiting the current knowledge to improve the quality of service. The proposed energy management scheme has a very low memory footprint, and requires very few computational power, which makes it suitable for online execution on sensor nodes. Moreover, it only necessitates the state of charge of the energy storage device as an input, and therefore is practical to implement. RLMan was compared to three state-of-the-art energy management schemes, using simulations and energy traces from real measurements. Results show that using RLMan can enable almost 70 % gains regarding the average throughput.