Limited Power Source Research Articles

Towards Ensemble Feature Selection for Lightweight Intrusion Detection in Resource-Constrained IoT Devices

The emergence of smart technologies and the wide adoption of the Internet of Things (IoT) have revolutionized various sectors, yet they have also introduced significant security challenges due to the extensive attack surface they present. In recent years, many efforts have been made to minimize the attack surface. However, most IoT devices are resource-constrained with limited processing power, memory storage, and energy sources. Such devices lack the sufficient means for running existing resource-hungry security solutions, which in turn makes it challenging to secure IoT networks from sophisticated attacks. Feature Selection (FS) approaches in Machine Learning enabled Intrusion Detection Systems (IDS) have gained considerable attention in recent years for having the potential to detect sophisticated cyber-attacks while adhering to the resource limitations issues in IoT networks. Apropos of that, several researchers proposed FS-enabled IDS for IoT networks with a focus on lightweight security solutions. This work presents a comprehensive study discussing FS-enabled lightweight IDS tailored for resource-constrained IoT devices, with a special focus on the emerging Ensemble Feature Selection (EFS) techniques, portraying a new direction for the research community to inspect. The research aims to pave the way for the effective design of futuristic FS/EFS-enabled lightweight IDS for IoT networks, addressing the critical need for robust security measures in the face of resource limitations.

Low power techniques for internet of things implementation: A review

The motive of designing a low-power system is to have a long battery life. One can carefully apply low-power design techniques to achieve low power consumption with proper system functioning to increase battery life. One such system where many devices are generally battery-operated and connected to the internet is the Internet of Things (IoT). IoT devices are used widely to gather data to propel actions and transmit the data for data analysis, connectivity, and automation. So much research is focused on IoT communication and computation in IoT devices, which increases power consumption. This survey explores low-power design strategies used at the architectural level. Additionally, it highlights the IoT features that give opportunities to apply low-power design methodologies to achieve less power consumption in IoT. Low-power design techniques are critical for the efficient functioning of Internet of Things (IoT) applications, where devices often operate in resource-constrained environments with limited power sources like batteries. Many applications of IoT are noticed including the domains such as industry, environment, and society, which are highly power-consuming because of the features such as computation, communication, security, and fault tolerance. Researchers have already reported the usefulness of many such techniques including architecture-level low-power design techniques. Still, it is observed that the work carried out is inadequate regarding power consumption, and communication bandwidth bottlenecks. In the present work, a rigorous literature survey is carried out based on low-power design techniques to support sustainable growth of IoT applications across various domains and power optimization.

Extending the Capacity of IoT Devices with Serverless Services for a Face Detection Application: A practical evaluation

IoT systems have limitations and challenges in many ways, such as performance, energy consumption, memory footprint and data storage. One possible solution to minimize these limitations is to integrate IoT devices with the serverless cloud computing model. In this context, this work aims to analyze the integration of these two technologies to determine if it can help overcome the limitations of IoT devices, most notably energy consumption and performance. A face detection application was adapted to run on an IoT device and the AWS Serverless Lambda service. Through experimentation, some metrics like latency, execution time and energy consumption were collected to evaluate the impact of serverless technology on the scope of IoT systems development. Results show that serverless technology is superior to the IoT device used in terms of performance, but it is directly related to the quality of the network connection to which the device is connected. Serverless technology can also be very useful when power supply to an IoT device is an issue, as these devices are usually battery-connected and have limited power source.

Performance enhancement of the solar still using textiles and polyurethane rollers

The acquisition of clean drinking water in regions with limited power sources has been a challenge of paramount concern. Solar stills have emerged as a popular and sustainable option for obtaining clean water in such regions. This process involves employing solar radiation to heat up water, which is then condensed to obtain potable water. The present study introduces a solar still system that is both cost-effective and energy-efficient, while simultaneously ensuring sustainability. Fabric-coated polyurethane rollers with capillary action enhance evaporation area, leading to notable performance improvements. Water vapour condensed on the cooling chamber's inclined aluminium plate and collected in the distillate chamber within the solar still. The thermal, energetic, and economic performance and productivity of the proposed model were evaluated. The fabricated solar still boasted maximum instantaneous system efficiency and exergy efficiency of approximately 62.16% and 7.67%, respectively. This system's cost-effectiveness and performance improvements are particularly noteworthy. The daily average distillate productivity of the proposed still was estimated at 1.14 L/m2, resulting in an annual production rate of 416.54 L/year. The estimated cost of producing 1 L of distillate was 0.023 $.

Adaptive Maximization of the Harvested Power for Wearable or Implantable Sensors With Coulomb Force Parametric Generators

Miniaturized wearable or implantable medical sensors (or actuators) are important components of the Internet of Things (IoT) in healthcare applications. However, their limited source of power is becoming a bottleneck for pervasive use of these devices, specially, as their functionality increases. Kinetic-based micro-energy harvesters can generate power through the natural human body motion. Therefore, they can be an attractive solution to supplement the source of power in medical wearables or implants. The architecture based on the Coulomb force parametric generator (CFPG) is the most viable micro-harvester solution for generating power from the human motion. This paper proposes three methods, namely, linear estimation approach, multi-armed bandit, a min-max-based approach to adaptively estimate the desirable electrostatic force in a CFPG using the input acceleration waveform. Through extensive simulations, the performance of the proposed methods in maximizing the output power of the micro-harvester is evaluated.

Motion control of mechanical systems under conditions of force-moment uncertainty of the external environment based on the principle of the Archimedes’ lever

If it is impossible to directly control the movement of a heavily loaded mechanical system with a limited power source of energy (HM-motor) under the condition of a force-torque uncertainty of the medium, it is shown that an effective solution to this problem is the transition to robust control, the technical implementation of which is achieved by embedding a gearbox-variator in the control system, which is one of the modern modifications of the classic Archimedes’ lever. Keywords: source of limited mechanical power, force-torque uncertainty, force-torque robustness, inherent robustness, mechanical characteristic, gearbox-variator, power sources, robustness index, dynamic self-levelling, d'Alembert's principle, Archimedes' lever equation. lutikovaolga@mail.ru

Enhanced lightweight and secure certificateless authentication scheme (ELWSCAS) for Internet of Things environment

The Internet of Things (IoT) is a fast-growing technology that enable existing systems to communicate with one another by using new devices such as sensors and other smart devices. The IoT devices such as wireless sensors and other smart devices are often very cheap, very small, and have limited power sources, memories, and processing capabilities. These devices are used in numerous critical applications, in which confidential information is sent across wireless channels among other devices participating in the system. This communication is vulnerable to multiple cyber-attacks due to the insecure wireless channel between them and without strong security mechanism, the important credential can be stolen by network attackers. One of the most important aspects of securing IoT communication is the authentication mechanism, used to validate the identity of authorized devices and users in IoT networks and to ensure data confidentiality, integrity, and authenticity for secure communication. Several authentication schemes for IoT environment have been proposed in the literature, none of these approaches entirely fulfil the necessary security and lightweight feature requirements. Some schemes fulfill the required security features but are unable to provide lightweight features. Similarly, other schemes provide lightweight features, but their security features are unsatisfactory. Therefore, it is necessary to design an effective security mechanism to ensure secure communication in IoT environments. In this paper, we propose Authenticated Encryption with Associated Data (AEAD) and Elliptic Curve Cryptography (ECC) based Enhanced Lightweight and Secure Certificateless Authentication Scheme (ELWSCAS) for IoT environment to fulfill the required security and lightweight performance features. The security of the proposed solution is evaluated using formal and informal security analysis. For formal security analysis we used RoR model and AVISPA tool. We have implemented the proposed solution in network simulator (NS3.35) by using Python and C++ to measure the network parameters such as throughput and packet delivery ratio (PDR). The computational and communication cost of the proposed scheme shows that in comparison to the existing state-of-the-art, our approach is considerably less costly and is a viable option for constrained IoT environment.

WIRELESS ENVIRONMENTAL QUALITY MONITORING SYSTEM

Advances in commercial compact integrated circuit technology have made it possible to integrate wireless transceivers, signal processing, and sensors in a single integrated circuit package. Such solutions provide a low-cost means of communication with the physical world and can have applications in areas as diverse as security, production management, research and environmental monitoring. We outline the challenges of system design for a distributed sensor network in which each node has a limited power source and communication channel. The nodes must establish a synchronous network with multiple hops, determine locations, and communicate for purposes such as relaying a signal and transmitting data to a server device. The confluence of low-cost wireless, computing, and sensors has created a new generation of smart devices. The use of tens and thousands of such devices in self-organizing networks has led to the creation of a new technology called wireless sensor networks. In this article, we will consider an example of the use of such a network based on the Bluetooth Low Energy (BLE) wireless data transfer protocol, which gave a serious impetus to the development of wireless sensors. Together with organic polymers, which are used as a sensor layer, it is possible to achieve high energy efficiency and selective sensitivity in monitoring. It is also worth noting the fast and cheap production of electronics based on organic polymers. Due to the semiconductor and flexible properties of organic semiconductor materials, flexible organic electronics has become the core of our technology. The field of organic electronics is entering a commercial phase. The appearance on the market of the first prototypes based on organic transistors made from solutions is intended to expand the existing presence in the market of organic electronic devices. We'll look at some of the key performance requirements for working devices. We will also look at some of the important advances in semiconductor design and device manufacturing technologies and discuss some of the technical challenges that are needed to optimize next generation products.

Hybrid Muddy Soil Fish Optimization-Based Energy Aware Routing in IoT-Assisted Wireless Sensor Networks

The seamless operation of interconnected smart devices in wireless sensor networks (WSN) and the Internet of Things (IoT) needs continuously accessible end-to-end routes. However, the sensor node (SN) relies on a limited power source and tends to cause disconnection in multi-hop routes because of a power shortage in the WSN, eventually leading to the inefficiency of the total IoT network. Furthermore, the density of available SNs affects the existence of feasible routes and the level of path multiplicity in the WSN. Thus, an effective routing model is predictable to extend the lifetime of WSN by adaptively choosing the better route for the data transfers between interconnected IoT devices. This study develops a Hybrid Muddy Soil Fish Optimization-based Energy Aware Routing Scheme (HMSFO-EARS) for IoT-assisted WSN. The presented HMSFO-EARS technique majorly focuses on the identification of optimal routes for data transmission in the IoT-assisted WSN. To accomplish this, the presented HMSFO-EARS technique involves the integration of the MSFO algorithm with the Adaptive β-Hill Climbing (ABHC) concept. Moreover, the presented HMSFO-EARS technique derives a fitness function for maximizing the lifespan and minimizing energy consumption. To demonstrate the enhanced performance of the HMSFO-EARS technique, a series of experiments was performed. The simulation results indicate the better performance of the HMSFO-EARS algorithm over other recent approaches with reduced energy consumption, less delay, high throughput, and extended network lifetime.

Active voltage damping method with negative DC link current feedback in electric and hybrid electric transmissions

Electric and hybrid electric transmissions in traction drive have a limited capacity power source. Since the traction drive operates in the torque source mode, the DC link voltage becomes unstable and goes into oscillatory mode. This leads to the software protection reaction which prevents the traction inverter overvoltage breakdown. The transition boundary to the oscillatory mode is determined by the power and the value of the capacitance installed in the electric transmission DC link. To increase reliability of the traction inverters, large-capacity electrolytic capacitors are replaced with small-capacity film capacitors which makes the system more prone to oscillations. To solve this problem, active damping methods are used allowing changing the engine dynamic characteristics by means of the control system. The software methods with power and torque proportional control are most widely used. Proportional power control is the simplest method in which the traction drive simulates an RL load. The torque proportional control method adjusts the torque reference according to the change in the DC link voltage. This paper proposes a new negative DC link feedback method. In this case, the torque is adjusted dynamically depending on the current consumed by the traction inverter from the electric transmission common DC link. Mathematical modeling methods were used to compare the known and proposed methods of DC link voltage active damping. Mathematical models have been developed in the MATLAB Simulink environment which makes it possible to investigate the damping capacity at various values of the power consumed by the traction inverter. It is shown that the proposed method with negative DC link current feedback demonstrated tuning simplicity. In comparison with proportional power and torque control methods, the proposed option is robust when setting parameters, provides a large damping coefficient over the entire range of traction drive power, and has a short duration of the transient process. The proposed method can be used to suppress DC link voltage oscillations on any type of hybrid electric and all-electric vehicles traction inverters and ensures stable and reliable equipment operation.

A Dual Cluster-Head Energy-Efficient Routing Algorithm Based on Canopy Optimization and K-Means for WSN

Wireless sensor networks (WSN) are widely used in various applications, such as environmental monitoring, healthcare, event detection, agriculture, disaster management, and so on. Due to their small size, sensors are limited power sources and are often deployed in special environments where frequent battery replacement is not feasible. Therefore, it is important to reduce the energy consumption of sensors and extend the network lifetime. An effective way to achieve this is clustering. This paper proposes a dual cluster-head energy-efficient algorithm (DCK-LEACH), which is based on K-means and Canopy optimization. Considering that the K-means algorithm is sensitive to the location of the initial clustering centers, this paper uses both the dynamic Canopy algorithm and K-means algorithm for clustering. For cluster-head election, this algorithm uses a hierarchy to minimize the cluster-head burden and balance the network load. The primary cluster-head is selected by two objectives: the node's residual energy and the distance from the node to the clustering center. The vice cluster-head is selected by the residual energy of the node, and the distance from the nodes to the base station. Simulator results show that DCK-LEACH significantly prolongs the energy-critical node lifetime and the network lifetime compared with existing protocols.

Negative Impact Mitigation on the Power Supply System of a Fans Group with Frequency-Variable Drive

The technological installations’ characteristics are possible to improve by equipping fans with a frequency-controlled electric drive. However, it can lead to an electromagnetic compatibility problem in the electrical supply system. This problem becomes worse if a large number of fans are included in the technological installation and the electric drives are powered from a substation connected to a limited power source. As an example, in this article we investigate the power supply system of a gas cooling unit with variable-frequency electric drives for fans. The electric drives’ operating mode dependences characterizing the non-sinusoidal voltages and currents of the power source are obtained with the help of simulation modeling in the MATLAB environment with the Simulink expansion package. The typical substation circuit usage for the power supply of a group of fans with a frequency-controlled drive does not meet the requirements of IEEE Standard 519-2014. We can solve the problem of electromagnetic compatibility by changing the substation topology and organizing DC busbars and replacing frequency converters with inverters. We proposed forming DC busbars using 12-pulse rectifiers powered by transformers with two secondary windings with different connection schemes. The simulation results confirmed that the proposed substation topology provides the voltage and current harmonics level on the substation power busbars in accordance with the IEEE Standard 519-2014 requirements over the entire frequency range of the fans’ motor control.

Quality of Service-Based Cross-Layer Protocol for Wireless Sensor Networks

Sensor nodes in wireless sensor networks (WSN) are used for perceiving, monitoring, and controlling a wide range of applications. Owing to the small size of sensor nodes and limited power sources, energy saving is critical for ensuring network longevity. Protocols in different layers consume energy for their function. It is possible to significantly reduce energy usage by including energy-efficiency measures in the protocol design. Most protocols in the literature focus on the energy efficiency in individual layers. Recent studies have shown that cross-layer designs are more energy efficient than individual layer designs. Therefore, this study presents a cross-layer protocol design that combines network and data link layers to minimize energy consumption. This article proposes a novel "Quality of Service Based Cross-layer (QSCL) Protocol" by combining the IEEE 802.15.4-based MAC protocol and the LEACH-based routing protocol. The dynamic duty cycle of the IEEE 802.15.4 protocol was modified based on the amount of data present in the node, which minimized the energy consumption of the data-transfer mechanism. The cluster head (CH) selection of the LEACH-based protocol was modified to consider the average residual energy (RE) of the nodes and their distance from the sink. This helps preserve the energy in the CH, thereby extending the network lifetime. Simulation studies demonstrated that the proposed QSCL outperformed the existing protocols by prolonging the network lifetime.

Socially-aware and energy-efficient resource allocation and power control for D2D multicast content distribution

Nowadays, a significant portion of the base station's traffic is dedicated to the increasing demand for the same multimedia content in local area services. Device-to-device (D2D) multicast communications are considered an effective and practical approach for tackling such a challenge in 4G/5G cellular networks. Due to the limited power source of the devices, this paper aims to jointly maximize their energy efficiency and lifetime while satisfying the quality of service (QoS) and the minimum battery power of users. To accomplish this aim, D2D multicast clusters are first formed considering the information of the physical distance, the social distance, and the energy levels of the devices' batteries. Then, cluster-head selection, power control, and resource allocation are carried out to maximize the product of energy efficiency and lifetime, which converts the multi-objective problem to a single-objective one. This optimization problem is non-convex and nonlinear; thus, it is divided into two convex sub-problems. In the first sub-problem, for each candidate cluster-head and corresponding cellular user, the power allocation is performed to maximize energy efficiency. Then, the resource allocation and the cluster-head selection are performed by solving the second sub-problem using the one-to-one Hungarian matching algorithm to maximize the life-energy efficiency. Results of extensive evaluation show that our proposed scheme improves energy efficiency and increases the cluster-head life in D2D multicast services.

Exploiting user grouping and energy harvesting in downlink cellular system

A mobile communication system combining energy harvesting with a cooperative nonorthogonal multiple access (NOMA) system is presented in this research. In the proposed scheme, the relay is assumed to have a limited power source, and it will harvest radio energy from the base station (BS) to serve the near and far users. In this scenario, we consider two possible situations during information transmission in the NOMA application system: perfect successive interference cancellation (SIC) and imperfect successive interference cancellation. The system performance is assessed primarily based on closed-form outage probability expressions. Numerical simulations are conducted to examine the outage probability of the proposed scheme and to verify the derived formulas. The study results have proved that the system performance is still good under the imperfect SIC condition, and several optimal parameters to improve the system performance have been found. Moreover, our research results have shown the superior performance of the proposed model compared with current orthogonal multiple access (OMA) networks.

Novel Scoring for Energy-Efficient Routing in Multi-Sensored Networks.

The seamless operation of inter-connected smart devices in Internet of Things (IoT) wireless sensor networks (WSNs) requires consistently available end-to-end routes. However, the sensor nodes that rely on a very limited power source tend to cause disconnection in multi-hop routes due to power shortages in the WSNs, which eventually results in the inefficiency of the overall IoT network. In addition, the density of the available sensor nodes affects the existence of feasible routes and the level of path multiplicity in the WSNs. Therefore, an efficient routing mechanism is expected to extend the lifetime of the WSNs by adaptively selecting the best routes for the data transfer between interconnected IoT devices. In this work, we propose a novel routing mechanism to balance the energy consumption among all the nodes and elongate the WSN lifetime, which introduces a score value assigned to each node along a path as the combination of evaluation metrics. Specifically, the scoring scheme considers the information of the node density at a certain area and the node energy levels in order to represent the importance of individual nodes in the routes. Furthermore, our routing mechanism allows for incorporating non-cooperative nodes. The simulation results show that the proposed work gives comparatively better results than some other experimented protocols.

Kesiapan Siswa SMP Negeri 2 Siberut Utara dalam Menghadapi Asesmen Nasional Berbasis Komputer

The Computer-Based National Assessment (ANBK) is a government program that aims to map the education quality of primary and secondary school in Indonesia. The purpose of this study was to find out: (1) a description of the student’s readiness in facing the ANBK, (2) what factors were the obstacles for student in preparation for ANBK. This type of research is qualitative research with a case study approach regarding the student’s readiness Utara in facing ANBK. Preparations made by students in facing ANBK include participating in the socialization carried out by teachers who serve as proctors and technicians. Then students participating in computer use training accompanied by teachers which are carried out after school. During this training the teacher provides motivational support to students to stay motivated, enthusiastic, and not worried in facing ANBK There are several obstacles to students' readiness to face ANBK, namely students have low technological literacy, limited available computer equipment, limited power sources as a resource for using computer equipment, and limited internet networks causing students to not be able to participate in simulations on the ANBK website. Although accompanied by obstacles during the preparation process, students have good readiness to participate in the implementation of ANBK, this can be proven by the implementation of ANBK well.

Enhanced Inf-TESLA Protocol: A Continuous Connectivity and Low Overhead Authentication Protocol via IoT Devices

Continuous and low-cost broadcast authentication is a fundamental security service for distributed sensor networks. This paper presents a novel development of a continuous and low-overhead broadcast authentication protocol named enhanced Infinite timed-efficient stream-loss tolerant authentication (enhanced Inf-TESLA) protocol, based on the Inf-TESLA protocol, whose continuous authentication is limited to the duration of its keychains. The enhanced Inf-TESLA protocol satisfies important security properties, including lower communication and computational overhead; a continuous generation of keychains without the need to establish synchronization packets; scalability to a large network; and resistance to masquerading, modification, man-in-the-middle, and replay attacks. We also highlighted an unaddressed authentication issue in the last packets of the original TESLA protocol and proposed a corresponding solution. We performed a simulation analysis using JAVA and proved that, compared to the Inf-TESLA protocol, the enhanced Inf-TESLA protocol can continuously authenticate packets for the entire lifetime of the receiver. We also compared the enhanced Inf-TESLA protocol with the original TESLA protocol in terms of time complexity and critical authentication processes. The results revealed the superiority of the enhanced Inf-TESLA protocol over the original TESLA protocol in terms of the message authentication code (MAC) value generation time and packet authentication time, which we believe can significantly improve the lifetime and lower the energy expenditure of Internet of Things devices with limited power sources.

Localization in Wireless Sensor Networks with Mobile Anchor Node Path Planning Mechanism

Determining the accurate locations of randomly deployed sensors in a given geographical region is a critical problem in the field of Wireless Sensor Networks. Various approaches have been proposed in the past to tackle this problem. Most of the existing techniques rely on the use of a beacon node which traverses throughout the region with limited power sources. Sensors use the beacon node positions for self localization. The trajectory of the beacon node has an influence on the accuracy, time and efficiency of the localization algorithm. In this paper, we propose Cosine Rule based Localization (CRL) algorithm for static trajectories of the mobile beacon node. Existing schemes use trilateration for position estimation of sensor nodes. The proposed method uses the Cosine rule on received beacon positions and distances obtained from RSSI in such a way that lines representing distances intersect at one point for the application of the Cosine rule. Simulation results reveal that CRL enables the unknown sensors to locate themselves with better accuracy in comparison with the existing trilateration technique for all the trajectories.

TEI-DTA: Optimizing a Vehicular Sensor Network Operating with Ultra-Low Power System-on-Chips

In the era of the Internet of Things (IoT), the interest and demand for embedded systems have been explosively increasing. In particular, vehicular sensor networks are one of the fields where IoT-oriented embedded devices (also known as IoT devices) are being actively used. These IoT devices are widely deployed in and out of the vehicle to check vehicle conditions, prevent accidents, and support autonomous driving, forming a vehicular sensor network. In particular, such sensor networks mainly consist of third-party devices that operate independently of the vehicle and run on their own batteries. After all, like all battery-powered embedded devices, the IoT devices for the vehicular sensor network also suffer from limited power sources, and thus research on how to design/operate them energy-efficiently is drawing attention from both academia and industry. This paper notes that the vehicular sensor network may be the best application for ultra-low power system on-chips (ULP SoCs). The ULP SoCs are mainly designed based on ultra-low voltage operating (ULV) circuits, and this paper aims to realize the energy-optimized driving of the network by applying state of the art (SoA) low-power techniques exploiting the unique characteristics of ULV circuits to the IoT devices in the vehicular sensor network. To this end, this paper proposes an optimal task assignment algorithm that can achieve the best energy-efficient drive of the target network by fully utilizing the SoA low power techniques for ULV circuits. Along with a detailed description of the proposed algorithm, this paper demonstrates the effectiveness of the proposed method by providing an in-depth evaluation process and experimental results for the proposed algorithm.