Power Consumption Of Nodes Research Articles

Multi-Junction Solar Module and Supercapacitor Self-Powering Miniaturized Environmental Wireless Sensor Nodes

A novel prototype based on the combination of a multi-junction, high-efficiency photovoltaic (PV) module and a supercapacitor (SC) able to self-power a wireless sensor node (WSN) for outdoor air quality monitoring has been developed and tested. A PV module with about an 8 cm2 active area made of eight GaAs-based triple-junction solar cells with a nominal 29% efficiency was assembled and characterized under terrestrial clear-sky conditions. Energy is stored in a 4000 F/4.2 V supercapacitor with high energy capacity and a virtually infinite lifetime (104 cycles). The node power consumption was tailored to the typical power consumption of miniaturized, low-consumption NDIR CO2 sensors relying on an LED as the IR source. The charge/discharge cycles of the supercapacitor connected to the triple-junction PV module were measured under illumination with a Sun Simulator device at selected radiation intensities and different node duty cycles. Tests of the miniaturized prototype in different illumination conditions outdoors were carried out. A model was developed from the test outcomes to predict the maximum number of sensor samplings and data transmissions tolerated by the node, thus optimizing the WSN operating conditions to ensure its self-powering for years of outdoor deployment. The results show the self-powering ability of the WSN node over different insolation periods throughout the year, demonstrating its operation for a virtually unlimited lifetime without the need for battery substitution.

A hybrid path finder-based vortex search algorithm for optimal energy-efficient node placing and routing in UWSN

In recent times, the research community has demonstrated significant interest in Underwater Wireless Sensor Networks (UWSNs), where extensive sensor deployments in oceans and rivers aim to monitor the underwater environment. Energy consumption poses a primary challenge due to the difficulty of replacing or recharging batteries in these environments. Existing studies have employed K-Means technology to minimize power consumption in underwater transmission nodes. However, these studies have often overlooked the consideration of residual energy and void region creation in their optimization approaches. To address these challenges, we introduce a novel Hybrid path finder-based vortex search (HPF-VS) algorithm, utilized for cluster head selection and optimization of node locations and remaining energy. To extend network coverage beyond limited transmission ranges, inaccessible nodes at the network periphery employ the improved Dwarf Mongoose Optimization (IDMO) algorithm. Our proposed techniques demonstrate superior performance compared to existing methods, showcasing minimized energy consumption, reduced delay, improved packet delivery ratio, and enhanced throughput. Specifically, the proposed approach achieves a delay of 2.01 s and a throughput of 32.21 Kbps, surpassing the performance of state-of-the-art methodologies we benchmarked against.

AIoT in Agriculture: Safeguarding Crops from Pest and Disease Threats.

A significant proportion of the world's agricultural production is lost to pests and diseases. To mitigate this problem, an AIoT system for the early detection of pest and disease risks in crops is proposed. It presents a system based on low-power and low-cost sensor nodes that collect environmental data and transmit it once a day to a server via a NB-IoT network. In addition, the sensor nodes use individual, retrainable and updatable machine learning algorithms to assess the risk level in the crop every 30 min. If a risk is detected, environmental data and the risk level are immediately sent. Additionally, the system enables two types of notification: email and flashing LED, providing online and offline risk notifications. As a result, the system was deployed in a real-world environment and the power consumption of the sensor nodes was characterized, validating their longevity and the correct functioning of the risk detection algorithms. This allows the farmer to know the status of their crop and to take early action to address these threats.

Algorithm for ensuring the minimum power consumption of the end node in the LoRaWAN network

Algorithm for ensuring the minimum power consumption of the end node in the LoRaWAN network

Deep learning based relay selection and precoders design for IoT cognitive relay networks

This paper focuses on designing a multiple-input multiple-output (MIMO) Internet-of-Things (IoT) oriented cognitive multi relay network (CMRN), where the secondary system (SS) consists of IoT nodes. Randomly placed multiple IoT nodes help in data transmission between two IoT users, i.e., a secondary transmitter (ST) and a secondary receiver (SR). Specifically, the problem of designing energy-efficient precoders at ST and SR is considered. The problem is addressed in two steps, first, a closed-form solution for the precoders is derived. Secondly, optimal precoders weight are used to select the best relay that assists the transmission between ST and SR nodes, ensuring maximum end-to-end energy efficiency (E2E-EE) at the SS. However, as the number of relays increases, the computational complexity of the solution also increases. Therefore, achieving a balance between the number of relays and computational feasibility is essential for optimal performance. To ensure fast communication system, deep learning (DL) based framework is employed for precoder design and relay selection, which offers solution with high precision and fast execution time. This approach effectively minimizes power consumption in the IoT nodes while maintaining the Quality of Service (QoS) of the primary and secondary systems. Numerical results demonstrate the impact of relay selection and precoder design on the achievable E2E-EE at SS. The DL scheme achieves comparable performance and much lower complexity than the conventional method while demonstrating lower runtime, particularly when the number of relays is large.

SamurAI: A Versatile IoT Node With Event-Driven Wake-Up and Embedded ML Acceleration

Increased capabilities such as recognition and self-adaptability are now required from IoT applications. While IoT node power consumption is a major concern for these applications, cloud-based processing is becoming unsustainable due to continuous sensor or image data transmission over the wireless network. Thus optimized ML capabilities and data transfers should be integrated in the IoT node. Moreover, IoT applications are torn between sporadic data-logging and energy-hungry data processing (e.g. image classification). Thus, the versatility of the node is key in addressing this wide diversity of energy and processing needs. This paper presents SamurAI, a versatile IoT node bridging this gap in processing and in energy by leveraging two on-chip sub-systems: a low power, clock-less, event-driven Always-Responsive (AR) part and an energy-efficient On-Demand (OD) part. AR contains a 1.7MOPS event-driven, asynchronous Wake-up Controller (WuC) with a 207ns wake-up time optimized for sporadic computing, while OD combines a deep-sleep RISC-V CPU and 1.3TOPS/W Machine Learning (ML) for more complex tasks up to 36GOPS. This architecture partitioning achieves best in class versatility metrics such as peak performance to idle power ratio. On an applicative classification scenario, it demonstrates system power gains, up to 3.5x compared to cloud-based processing, and thus extended battery lifetime.

Research on Control Theory System Based on Computer Artificial Intelligence Technology

This paper designs a temperature control system. AT90S8535 is a kind of excellent performance and has the development potential of microcontrollers. In this paper, the artificial intelligence algorithm and PID adaptive algorithm are used to optimize the system control process. Fuzzy rules are used to adjust PID in the control system. Control parameters can be set automatically. This new algorithm can eliminate the phenomenon of PID saturation integral and improve the response speed while reducing overshoot. The system is stable, reliable, and easy to install. It can effectively realize remote temperature acquisition and control with low cost and low power consumption of terminal nodes. The system achieves the purpose of safe and reliable data transmission.

The error rate analyze and parameter measurement on LoRa communication for health monitoring

During LoRaWAN data transmission, the Bit Rate transmitted from the transmitter to the Receiver experiences attenuation from the object being passed, so Packet Loss (Bytes) may occur due to diffraction, scattering, and reflection in the LoRa data transmission process. LoRa data that has errors is researched and further developed with a formula and method to minimize data rate errors in LoRa communication. Analysis development lies in the gateway's ability to accommodate LoRa data from end nodes. This condition requires a development method of Adaptive Data Rate, which is helpful for Battery Power Saving or power consumption of sensor nodes, especially in data communication with LoRa servers, i.e., the uplink and downlink processes that are correct, regular, and on-time. We use pulse data in the existing case examples to monitor the patient's health status. This data is applied to elderly patients and patients from victims of natural disasters. The development is the use of extra small and comfortable LoRa for all patients in the hospital. One of the mechanism developments is Blind-ADR, which is used for unpredictable Mobile LoRa data transmission, e.g., Blind-ADR is intended to monitor the movement of the patient's changing position. This research also examines the effects of increasing the number of end-nodes that cause health data collisions and the mechanisms used to avoid collisions, including the Adaptive Data Rate.

A Study Regarding Power Consumption of An IoT Node For Image Retrieval and its Optimization

Abstract This paper analyses the power consumption of an IoT node that captures images and transmits them to a cloud storage. Various implementation versions of the IoT node are proposed, focusing on the utilization of common components to achieve cost-effectiveness and minimize the maintenance requirements. The realised node variants were initially tested in laboratory conditions and then commissioned and deployed outdoors, being located in an orchard where they remained operational during 7 months under different meteorological conditions. The proposed solution utilizes an ESP32 microcontroller and a camera with a resolution of 1.3 Megapixels as a data acquisition node whose energy is assured by a Li-Po battery, charged through a solar panel. Wi-Fi communication was employed to transmit the images to the server. The power consumption of the node was evaluated for different variants of software optimization using the HTTP or the MQTT transmission modes. The instantaneous current consumption of the nodes was measured in laboratory to identify the power consumption for each phase of the program execution. The experiments revealed that the MQTT transmission mode consumed considerably less power than the HTTP mode. Additional experiments have been performed in which the variation of the battery voltage, the solar panel voltage and the number of daily emissions in the examined period, as well as correlations between these quantities have been analyzed.

An artificial bee colony algorithm with a balance strategy for wireless sensor network

As a popular population based evolutionary computation algorithm, artificial bee colony (ABC) algorithms have attracted many researchers to do further works. In this paper, by utilizing a linkage detection strategy to distinguish nonseparable and separable functions, we present new balance strategies for the updating equations of ABC on the two types of functions respectively. First, for accelerating convergence rate, we propose a historic array to preserve the best individual which the population ever achieved. Second, for the different role of employed and onlooker bees during iterations, compared with the traditional algorithm, we present two updating equations for the two types of bees on the nonseparable and separable functions respectively. Third, a new multi-dimensional updating mechanism for the worst individual and a new updating strategy for scout bees are presented respectively. At last, for verifying its effectiveness, we apply the improved algorithm to optimize the power consumption of sensor nodes in a wireless sensor network. In this paper, verified by the test on the network, the basic benchmark functions and CEC2014, our algorithm shows superior performance with the compared modern algorithms.

基于无线传感器网络的农业温室环境的低功耗监测方法

In order to improve the reliability of wireless sensor networks and reduce the power consumption in the monitoring process, the low power consumption monitoring method of agricultural greenhouse environment based on wireless sensor networks is studied. The terminal node of wireless sensor network is constructed by using CO2 sensor, temperature and humidity sensor and illumination sensor. In the sensor network layout stage, in order to reduce the node power consumption, considering the number of nodes and network coverage, the cuckoo search algorithm is used to optimize the node layout model. The communication module uses LEACH protocol to transmit the environmental data collected by the terminal node to the monitoring center. The cluster head link is selected in LEACH protocol to save energy. After receiving the environmental data collected by the terminal node, the monitoring center uses multi-dimensional data to identify and locate abnormal environmental data according to the correlation between multi-modal data streams in the same node, so as to realize the environmental monitoring of agricultural greenhouse. The experimental results show that the data transmission of the research method is stable and reliable, and the node’s power consumption in the process of internal environment monitoring of the research object is effectively reduced.

An End-to-End IP Header Compressed Packet Forwarding Framework for Bandwidth-Constrained Networks

IP header compression technologies such as Robust Header Compression (ROHC) are well-known to improve bandwidth efficiency strategy using resource-constrained communication links. However, ROHC is a point-to-point approach so it must be maintained by the per-flow and per-hop, which is disadvantageous for bandwidth constrained networks (BCNs) featured by multi-hops transmission. In order to solve this problem, an efficient end-to-end IP header compressed packet forwarding framework for BCNs is proposed in this paper. Firstly, an end-to-end ROHC tunnel is established through the multi-hop transmission scheme. Then, based on the offer/answer model, a fast negotiation mechanism is established to ensure the context identifier (CID) is globally unique. Finally, the intermediate forwarder determines the next hop forwarding path according to CID. Therefore, besides reducing the transmission bandwidth and time consumption of compression and decompression per hop, it can also speed up forwarding the packets among BCNs. The simulation results show that the proposed framework improves forwarding efficiency and reduces end-to-end delivery latency and node power consumption in a BCN, which is independent of the channel conditions and the bit error rate.

A Full-Duplex Directional MAC Framework for Underwater Acoustic Sensor Networks

Underwater acoustic communication plays an essential role in underwater wireless information exchange, and nodes with such an ability constitute an underwater acoustic sensor network (UASN). However, UASNs face many challenges, such as high bit error rate and high propagation delay, significantly reducing network performance. Because of the challenging nature of underwater environments, the power consumption and battery energy efficiency of sensor nodes need to be considered. Directional communication technology can conserve energy by restraining beam directivity and diminishing interference between nodes by enabling peer-to-peer communication with intended neighbors. However, the technology suffers from the problems of neighbor discovery, deafness effect, and hidden/exposed terminal. To address these challenges, we propose a full-duplex directional medium access control (MAC) framework based on the vector hydrophone and multimodal transducer in this paper, along with a benchmark MAC protocol, which enables adaptive power control to achieve spatial reuse and energy conservation. Simulation results show that the benchmark MAC protocol outperforms existing representative protocols in terms of throughput, end-to-end delay, and energy efficiency.

Artificial intelligence‐enabled distributed energy conservative model for mobile internet of things using software‐defined network

SummaryThe Internet of things (IoT) is an emerging technology for many smart applications due to its efficient resource utilization, scalability, and fast interaction with the physical world. Software‐defined network (SDN), on the other hand, provides dynamic services for controlling and managing real‐time systems. However, collected data are sent to a central location, which requires balancing energy resources with redundant channels to maximize the availability of smart functions. Furthermore, the IoT network faces numerous security vulnerabilities as a result of its open communication space, including malicious messages and privacy concerns. Thus, this paper presents a distributed and artificial intelligence‐based energy‐efficient model for IoT‐SDN architecture, which aims to improve data aggregation and power distribution. It also provides security and authentication for smart communication systems. First, the proposed model introduces the heuristic evaluation using artificial intelligence and decreases the power consumption for sensor nodes in a real‐time system. Moreover, it optimizes the paradigm of distributed processing and efficiently increases the green energy technology with nominal management costs using the mobile edges. Second, the aggregated data of the environment is secured using a centralized controller to attain the most trustworthy data availability. The experimental results show a comparative analysis of the proposed model in terms of energy efficiency, packet drop ratio, and waiting time by 22%, 23%, 40%, and 49% as compared to existing studies.

Energy‐efficient routing in low power and lossy networks with concurrent overlapping RPL instances

AbstractThe popularity of the Internet of Things (IoT) has cut across different fields in the information and communication technology domain. Such a remarkable surge in popularity has indeed marked its stamp in the number of IoT applications getting developed. These applications rely on a solid backing in the low power and lossy networks (LLNs), which is a crucial IoT‐enabling technology. This results in more than one application being performed on top of the same network. Such a scenario is mentioned by the Internet Engineering Task Force, in its description regarding the IPv6 routing protocol for LLNs (RPL), as multiple active routing instances sharing an LLN. The issue becomes more interesting when these instances have overlapping sets of nodes. This article presents a novel objective function (OF) named Multi‐OF that enables the creation of an energy‐efficient RPL instance in an LLN with concurrent overlapping instances. The optimization achieved by Multi‐OF can be attributed to the inclusion of a novel metric named packet energy correlation index (PECI) along with expected transmission count. The correlation provided by PECI gives an estimate regarding the ability of a node, in terms of the available residual energy, to handle the packets waiting in its queue (ie, packet buffer). The efficiency of the proposed OF has been justified through simulations conducted using Contiki‐COOJA, the results of which show improvements in terms of power consumption of nodes, packet delivery ratio, number of preferred parent changes per node, packet overhead, end‐to‐end delay, and jitter.

Разработка алгоритма повышения эффективности протокола маршрутизации С-LEACH

In the process of studying wireless sensor network protocols and communication mechanisms, the extension of network service life and minimization of node power consumption have become important indicators. In order to reduce the energy consumption caused by communication in a wireless sensor network, improve network scalability and extend the network lifecycle, it is important to intelligently connect network nodes using a certain clustering algorithm. The paper proposes an improved routing protocol for wireless sensors with low power consumption LEACH, based on data aggregation (C-LEACH). The Kalman filter algorithm was used to solve the problem of data accuracy on cluster member nodes. The principle of operation of the Kalman filter is explained by the example of the noise signal of the sensor. The above data modification model can be performed continuously to achieve the optimal evaluation and filtering effect. Thus, the volume of data sent by the node is reduced. Experimental results have shown that the proposed LEACH protocol based on data fusion (C-LEACH) effectively reduces data redundancy, reduces the power consumption of sensor nodes and prolongs the life cycle of wireless sensor networks compared to the traditional LEACH algorithm, significantly improves network integrity.

Hardware Implementation of Effective Framework for the Trade-off between Security and QoS in Wireless Sensor Networks

The trade-off between security and quality of service (QoS) in wireless networks has attracted great attention in recent years. This paper presents a hardware implementation of a novel framework for realizing the trade-off between security and QoS in wireless sensor networks (WSNs) regarding the hostility of the operating environment and the available resources of our objects. For evaluating the hostility of the operating environment, we developed an effective intrusion detection unit that sends an alarm signal to a control unit that also collects the data-carrying information about the available resources. As our work is concerned with WSNs, we focus on the power consumption of sensor nodes as the considered object resources. According to the collected data from the intrusion detection unit and resources status unit, the control unit can evaluate the situation of the object in the operating environment and sends control signals to a security unit to select the appropriate level of security among three levels (low, medium, and high) available in our developed framework. The three security levels consider different combinations of the cryptographic algorithms Hash-based Message Authentication Code (HMAC) and Advanced Encryption Standard (AES), with different key lengths, regarding the required security services (confidentiality, authentication and integrity) and available resources. To reinforce the QoS, we considered the advantages of hardware implementation in addition to maintaining the object resources. Our framework has been implemented using Field Programmable Gate Array (FPGA), Virtex-7 (xc7v585tffg1761–3), which helps in achieving reasonable performance with a maximum operating frequency of 206.838 MHz and throughput of 2.3 Gbps.

MES-FPMIPv6: MIH-Enabled and enhanced secure Fast Proxy Mobile IPv6 handover protocol for 5G networks[Formula: see text

Fast Proxy Mobile IPv6 (FPMIPv6) is an extension of the PMIPv6 mobility management deployed as part of the next-generation internet protocol. It allows location-independent routing of IP datagrams, based on local mobility to IPv6 hosts without involvement of stations in the IP address signaling. A mobile node keeps its IP address constant as it moves from link to link, which avoids signaling overhead and latency associated with changing IP address. Even though local mobility requirements hold, it entails security threats such as Mobile Node, Mobile Access Gateway, as well as Local Mobility Anchor impersonation that go beyond those already exist in IPv6. As mobile station keeps moving across different serving networks, its IP remains constant during handover, and location privacy may not also be preserved. Moreover, homogeneous network dependence of PMIPv6 is one of the gaps, which FPMIPv6 could not mitigate. FPMIPv6 does not support heterogeneous network handover, for which numerous researchers have proposed Media Independent Handover (MIH) enabled FPMIPv6 schemes to allow fast handover among heterogeneous networks, but in the absence of security solutions. As a comprehensive solution, we propose a new handover authentication scheme and a key agreement protocol for the ‘MIH-enabled Network Only FPMIPv6’ model. As one of the basic requirements, mobility management should minimize signaling overhead, handover delay and power consumption of the mobile node. The proposed scheme improves wireless link overhead (mobile node overhead) by 6-86% as cell radius, wireless failure probability and number of hop vary. The security of the proposed scheme has also been analyzed under BAN logic and Automated Validation of Internet Security Protocols and Applications (AVISPA) tool and its performance has numerically been evaluated through a pre-determined performance matrix and found to be effective and preferably applicable compared with other schemes.

A Cross-Layer Green Information-Centric Networking Design Toward the Energy Internet

To address the energy-efficiency issue in Information-Centric Networking (ICN), this article proposes a novel Green ICN design, which adapts the power consumption of network nodes to the optimized utilization level proportionally. By learning over the consumers’ interactive data traffic pattern/behavior, we introduce a new concept of cross-layer power adaption conducted through dynamically adjusting link rate corresponding to content popularity to reduce the wasteful power consumption of Content Routers (CRs). We also develop a controlling policy for each content provider to map its status to the most suitable operating mode to diminish power consumption. Moreover, we propose a smart Selective Caching Scheme (SCS) so that the caching portion in a CR's cache memory is adjusted according to content popularity and available spaces of two customized content cache spaces, namely hot and cold caching queues, for storing popular and unpopular content objects. This scheme can further decrease the power from caching since it is diminished when the traffic load is reduced via the proposed CRs' adaptive mechanism. The evaluation results with practical insights in several distinct scenarios show that the proposal can provide considerably higher energy efficiency and network performance at the same time, typically achieving at least 20% power-saving with a higher hop reduction ratio, compared to existing Internet designs with relevant state-of-the-art caching strategies.

An Efficient Energy Management Routing and Scalable Topology in Wireless Sensor Network Using Virtual Backbone

The wireless sensor network (WSN) approach is one of the fastest growing approaches in the world of communications and engineering. The primary objective of a WSN is to discover the important information about the environment, depending on the nature of the applications under which it is implemented, and to communicate this information to a single base station (BS) so that appropriate measures can be taken. These sensor nodes communicate via a variety of protocols. The difficulty with the traditional system is that while collecting the observed data, each node transmits its felt information directly to a base station, which quickly exhausts its power. This study suggests a Backbone Energy-Efficient Sleeping (BEES) management strategy with two appealing features: (i) the capacity of backbone is scalable by basic parameters, and (ii) the backbone nodes were distributed equally, implying that the backbone on its own is energy efficient during routine activities. Reliable connections are expected to obtain QoS and routing protocols of such backbone nodes in wireless multihop systems. As a result, present localized routing in virtualized backbone schedule cannot ensure energy-efficient paths. An energy-efficient routing scheme for Virtual Back Bone Nodes (VBS) increases life of node and switches off its radio while in sleep state to spend less power. BEES’ performance is evaluated by comparing it to two different topology management techniques. The results show that BEES performs better algorithms. It ensures optimal routing with minimal node power consumption but also implements the essential communication range for backbone networks.