Transmission Time Research Articles

Remote monitoring of cardiac implantable electronic devices using smart device interface versus radiofrequency-based interface: a systematic review

Abstract Background Guidelines recommended remote monitoring (RM) in managing patients with Cardiac Implantable Electronic Devices (CIED). In recent years, smart device (phone or tablet) monitoring-based RM (SM-RM) was introduced. SM-RM is a specifically developed application (app) which can be downloaded from app stores using smart devices. The app uses Bluetooth low-energy to communicate automatically and securely with the patient’s CIED. The app then uses a cellular or Wi-Fi internet connection to transfer the data securely to the manufacturer’s repository. Purpose This study aims to systematically review SM-RM versus bedside monitor RM (BM-RM) using radiofrequency in terms of compliance, connectivity, and episode transmission time. Methods We conducted a systematic review, searching three international databases from inception until July 2023 for studies comparing SM-RM (intervention group) versus BM-RM (control group). Results Two propensity score-matched studies with a total of 21978 patients were retrieved (9642 patients in the SM-RM arm and 12336 patients in the BM-RM arm) (1, 2). There is significantly higher compliance among patients using SM-RM compared with patients using BM-RM in both pacemaker and defibrillator patients. There were higher enrolment rates and completed scheduled transmissions among SM-RM compared to BM-RM. Higher connectivity was also seen in patients with SM-RM, and more SM-RM patients transmitted at least once compared to BM-RM patients. Additionally, SM-RM patients had more patient-initiated transmissions compared to BM-RM patients. Younger patients (aged <75) had more patient-initiated transmissions, and a higher proportion had ≥10 such transmissions compared with older patients (aged ≥75) in both SM-RM and BM-RM groups. The episode transmission time of SM-RM patients was also shorter than that of BM-RM patients. Conclusion SM-RM is a step in the right direction, with good compliance, connectivity, and shorter episode transmission time. It allows patients to feel empowered and in control of their health. Further research on cost-effectiveness and long-term clinical outcomes can be carried out in the future.

Acoustic performance prediction by means of a statistical energy analysis of two adjacent workrooms used for conferences and educational proposes

AbstractThe current design of workspaces for companies is focused on minimalistic and modern styles prioritizing the aesthetic appearance with illuminated open spaces and the use of glass walls. If the acoustic performance is not considered, inappropriate Reverberation Times (RT) might lead to difficulties for hearing a speaker or teacher during courses and conferences, causing problems in the learning process. Additionally, there might be high sound transmission between adjacent work rooms. This paper presents the development and experimental validation of numerical models using Statistical Energy Analysis (SEA) to calculate the sound reduction index through a glass wall that separates two adjacent work rooms. These structures are dedicated to conferences and educational uses but cannot be properly used due to their high sound transmission and inappropriate reverberant time. The sound insulation prediction results are validated with experimental measurements carried out in the adjacent rooms under the standard ISO-140. Afterwards, a SEA model is used to provide some acoustic correction design guidelines for these types of constructions. To improve the acoustical performance in the rooms, the acoustic effects of different absorbent panels placed on the walls and ceiling were investigated, choosing a suitable material that complies with the recommended ranges of RT and with less amount of absorption area. The SEA model is then used to understand the effects of openings size between the panels that make up the glass wall on the sound insulation capacity between rooms. Finally, a SEA model is reformulated to quantify the effect of the application of double walls for sound insulation between rooms, which implies the increase of weighted sound reduction index in 9 dB with respect to measured data.

Latency Analysis of Drone-Assisted C-V2X Communications for Basic Safety and Co-Operative Perception Messages

Drone-assisted radio communication is revolutionizing future wireless networks, including sixth-generation (6G) and beyond, by providing unobstructed, line-of-sight links from air to terrestrial vehicles, enabling robust cellular cehicle-to-everything (C-V2X) communication networks. However, addressing communication latency is imperative, especially when considering autonomous vehicles. In this study, we analyze different types of delay and the factors impacting them in drone-assisted C-V2X networks. We specifically investigate C-V2X Mode 4, where multiple vehicles utilize available transmission windows to communicate the frequently collected sensor data with an embedded drone server. Through a discrete-time Markov model, we assess the medium access control (MAC) layer performance, analyzing the trade-off between data rates and communication latency. Furthermore, we compare the delay between cooperative perception messages (CPMs) and periodically transmitted basic safety messages (BSMs). Our simulation results emphasize the significance of optimizing BSM and CPM transmission intervals to achieve lower average delay as well as utilization of drones’ battery power to serve the maximum number of vehicles in a transmission time interval (TTI). The results also reveal that the average delay heavily depends on the packet arrival rate while the processing delay varies with the drone occupancy and state-transition rates for both BSM and CPM packets. Furthermore, an optimal policy approximates a threshold-based policy in which the threshold depends on the drone utilization and energy availability.

Research on Parallel Task Scheduling Algorithm of SaaS Platform Based on Dynamic Adaptive Particle Swarm Optimization in Cloud Service Environment

To efficiently realize the parallel task scheduling of SaaS platform in large-scale cloud service environment, this paper studies the parallel task scheduling algorithm of SaaS platform based on dynamic adaptive particle swarm optimization in cloud service environment. Users access the cloud through the user access interface module, and issue task scheduling instructions or send task scheduling requests. After the service management module provides diversified application service support according to the scheduling requirements, the core service module determines the SaaS platform parallel scheduling objective function, and uses dynamic adaptive particle swarm optimization to solve the objective function to obtain the SaaS platform parallel task scheduling results. The test results show that the algorithm has better multi-objective solving ability and can obtain higher quality objective solutions, and the test results of the total execution time of parallel scheduling tasks and the total transmission time of task data on SaaS platform are all within 30 s. The results of virtual machine resource load balancing degree are all below 15%; the utilization rate of virtual machine resources is above 92.2%.

Pengembangan Mesh Network Sebagai Ekspansi Protokol LoRaWAN di Politeknik Negeri Malang

In realizing a smart campus, Politeknik Negeri Malang (Polinema) has implemented digital technology in its learning and administrative processes with the goal of improving efficiency, speed, and operational ease. One of the key areas being developed is the Internet of Things (IoT), which is expected to function autonomously to support various campus activities. However, the main challenges in IoT implementation are the limitations in communication range and device power consumption, which cause issues in sensor and actuator data transmission, especially when data cannot be optimally received between nodes. To address these challenges, Polinema is ex-ploring the application of LoRaWAN technology. Although LoRaWAN is effective, it experiences a decline in data transmission quality when the sender and receiver are located in multi-story buildings, which can lead to delays, packet loss, or other disruptions. As a solution, the use of a Mesh Network is proposed to enhance the range and stability of data transmission. This study collected data using RSSI, SNR, and delay parameters in the civil engineering building at Polinema, with sensor data visualized through Grafana. The results show that the system can be well-integrated without conflicts between WiFi and LoRa. The average transmission time was approximately 29 seconds, with no packet loss detected. Additionally, changing the transmission method to confirmed uplink was necessary to maintain data integrity, while adjusting transmis-sion intervals was crucial to avoid scheduling issues. These findings indicate that implementing a Mesh Network as an extension of the LoRaWAN protocol can significantly improve the perfor-mance of IoT systems in Polinema’s indoor environment.

A simulation analysis on the internal and external application of new silica-aerogel-based (Quartzene) coatings effects on energy use in a typical building in two different climates

The study investigates the impact of improved synthetic amorphous silica, specifically developed aerogel-based insulating coatings, Quartzene (Qz), on energy efficiency in buildings across cold and warm climate zones. Simulations were conducted on various coatings and thicknesses for exterior and interior wall surfaces, as well as roofs. These were evaluated using a prototype residential building under dynamic thermal conditions. Wall coatings were analyzed, including a base plaster and a mixture with 10%Wt aerogel-based Quartzene. Additionally, three roof coating samples were tested: Qz 12.5%Wt, TiO2 3.3%Wt, and a blend of aerogel-based mixtures and TiO2. Mixtures containing Qz exhibited the lowest thermal conductivity (0.05 W/(m·K)) and high short-wave reflectance (up to 0.93 μm), impacting transmission loads, time lag, and decrement factor. Energy savings of up to 11% were observed in warm climates when implementing the coatings (unaged performance). Overall, the coated surfaces increased time lag and reduced decrement factor compared to uncoated surfaces. Aerogel-based coatings showed enhanced effectiveness in lowering transmission loads.

Link-Quality Aware Routing for Software-Defined Vehicular Networks

The routing protocol for Vehicular Ad Hoc Networks (VANETs) uses hop-count as a routing metric to determine the shortest route from source to destination. The presence of unstable links in the selected route may cause packet failures, resulting in an increase in packet retransmissions, causing network congestion, increasing total end-to-end delay, and reducing throughput. Thus, route selection based on hop count may not always be optimal in terms of route link quality. In Software-Defined Vehicular Networks (SDVN), the global view of link-state information for the vehicular networks is created at the controller; thus, a better route can be computed. Our study proposes an SDVN routing technique that considers link quality while determining the route. Our proposed framework examines the link quality using two metrics: Expected Transmission Count (ETX) and Expected Transmission Time (ETT), and this information is used by the controller to compute the flow rule. The routing performance of the proposed scheme is compared to traditional VANETs and other existing works with the help of network simulations using the NS-3 simulator. The obtained simulation results for our proposed scheme outperform in terms of performance metrics such as packet delivery ratio, average throughput, and end-to-end delay.

Non-coherent short-packet communications: Novel z-domain user multiplexing

In the evolution of fifth generation (5G) and beyond wireless communication systems, non-coherent (NC) short packet communication (SPC) is crucial for achieving ultra-reliable low-latency communication (URLLC). Frame design, latency, and reliability are some of the challenges associated with short-packet communication. Recently, to address these challenges, a novel modulation scheme known as modulation on conjugate-reciprocal zeros (MOCZ) has been proposed. MOCZ modulates information on conjugate reciprocal zeros in the z-domain, thereby eliminating the need for channel estimation and providing a robust solution for NC communication. However, in multi-user MOCZ (MU-MOCZ) scheme, adding guard intervals to each short packet to mitigate channel impact remains an issue, as it increases the transmission time and consequently reduces efficiency. To address the aforementioned problem, this paper introduces a novel frame design approach called z-domain user multiplexing MOCZ (ZDUM-MOCZ or ZDM-MOCZ). Unlike traditional time division multiplexing (TDM), which serves users consecutively in the time domain, this method multiplexes users in the z-domain. In this approach, each user is allocated a specific set of zeros in the z-domain, which collectively form a unique sequence in the time domain. The findings illustrate the potential for reduced latency in downlink transmission, highlighting the benefits of this novel methodology over conventional MU-MOCZ method. The proposed ZDUM-MOCZ scheme not only addresses the existing issues in the frame design of the MU-MOCZ scheme but also facilitates more efficient and reliable short packet communication in 5G and beyond wireless systems.

Assessing vaccine strategies for mpox outbreak in New York City using an age-structure model

BackgroundSince May 7 2022, mpox has been endemic in many countries which has attracted the attention of health authorities in various countries and made control decisions, in which vaccination is the mainstream strategy. However, the shortage of vaccine doses and the reduction of protective efficacy have led to unresolved issues such as vaccine allocation decisions and evaluation of transmission scale.MethodsWe developed an epidemiological model to describe the prevalence of the mpox virus in New York City and calibrated the model to match surveillance data from May 19 to November 3, 2022. Finally, we adjusted the model to simulate and compare several scenarios of non-vaccination and pre-pandemic vaccination.ResultsRelative to the status quo, if vaccination is not carried out, the number of new infections increases to about 385%, and the transmission time will be extended to about 350%, while if vaccinated before the epidemic, the number of new infections decreases to 94.2-96%.ConclusionsThe mpox outbreak in New York City may be linked to the Pride event. However, with current vaccine coverage, there will be no more large-scale outbreaks of mpox, even if there is another similar activity. For areas with limited vaccines, priority is given to high-risk groups in the age group [34–45] years as soon as possible.

Survey on Unmanned Aerial Vehicle Communications for 6G

Although the application of the fifth-Generation (5G) mobile communication has brought tremendous innovations to the daily life of human beings, e.g., autonomous vehicles and internet of everything, the upcoming huger data requirement leads to the emergence of the sixth-Generation (6G) mobile communication. Compared to 5G, the transmission rate, time delay, and wireless coverage need to be improved significantly. Thus, in this paper the applications of Unmanned Aerial Vehicles (UAVs) to the ubiquitous, intelligent and coupling 6G network are surveyed. First, the utilization of UAVs in the framework of space-air-ground-sea integrated network is demonstrated, and the roles and functions of UAVs in different scenarios are emphasized, e.g., the swarm base stations, the deployment for holographic projection, the long-distance relaying and the data collection. Then, the potential 6G key techniques of terahertz, ultra-massive multiple-input and multiple-output, endogenous artificial intelligence, Intelligent Reflecting Surface (IRS), intelligent edge computing, blockchain and integrated sensing and communication for UAV communications are investigated. Finally, the future challenges of UAV communications for 6G, including the limited duration, integration of networks, compatibility of IRS, development of THz communications, and user security are discussed.

Pulse transmission time and amplitude of digital pulse wave determined by fingertip plethysmography as a surrogate marker of brachial artery flowmediated dilatation.

To assess the changes in blood vessel stiffness and digital pulse wave amplitude because of flowmediated dilatation, and to explore how these two variables change when endothelial dysfunction is experimentally induced. The experimental study was conducted at the departments of physiology at the College of Medicine, Mustansiriyah University, and the College of Medicine, Al-Iraqia University, Baghdad, Iraq, from October 14, 2021, to May 31, 2022, and comprised healthy young males who were subjected to the flow-mediated dilatation technique on the left brachial artery. Pulse transit time and the amplitude of the digital pulse wave were measured during reactive hyperaemia for 2.5 minutes from the left middle finger using a piezoelectric pressure sensor and a simultaneous Lead I electrocardiogram. Endothelial dysfunction (ED) was induced by oscillatory and retrograde shear rates. The correlation between variables was calculated in Excel running on the Windows operating system. There were 10 second-year medical students with mean age 22±0 years and mean body mass index 25.7±4.8kg/m2. During reactive hyperaemia, pulse transit time was significantly increased by 3-5% in both normal endothelium and experimentally induced endothelial dysfunction relative to the pre-occluded artery, and the difference was not significant (p>0.05). Digital pulse wave amplitude increased significantly in normal endothelium relative to the pre-occluded artery (p<0.05), but not in experimentally-induced endothelial dysfunction (p>0.05). The pulse transit time and digital pulse wave amplitudes of the photo plethysmography signal may be used to detect changes in vessel wall diameter and tone throughout the reactive hyperaemia process. Digital pulse wave amplitude was better able to detect experimentally-induced endothelial dysfunction, as assessed by the flowmediated dilatation protocol, than pulse transit time.

Rapid and Resilient LoRa Leap: A Novel Multi-Hop Architecture for Decentralised Earthquake Early Warning Systems.

We introduce a novel LoRa-based multi-hop communication architecture as an alternative to the public internet for earthquake early warning (EEW). We examine its effectiveness in generating a meaningful warning window for the New Zealand-based decentralised EEW sensor network implemented by the CRISiSLab operating with the adapted Propagation of Local Undamped Motion (PLUM)-based earthquake detection and node-level data processing. LoRa, popular for low-power, long-range applications, has the disadvantage of long transmission time for time-critical tasks like EEW. Our network overcomes this limitation by broadcasting EEWs via multiple short hops with a low spreading factor (SF). The network includes end nodes that generate warnings and relay nodes that broadcast them. Benchmarking with simulations against CRISiSLab's EEW system performance with internet connectivity shows that an SF of 8 can disseminate warnings across all the sensors in a 30 km urban area within 2.4 s. This approach is also resilient, with the availability of multiple routes for a message to travel. Our LoRa-based system achieves a 1-6 s warning window, slightly behind the 1.5-6.75 s of the internet-based performance of CRISiSLab's system. Nevertheless, our novel network is effective for timely mental preparation, simple protective actions, and automation. Experiments with Lilygo LoRa32 prototype devices are presented as a practical demonstration.

Testing Algorithms for Controlling the Distributed Power Supply System of a Railway Signal Box

Trends in the use of renewable energy sources to power buildings do not bypass objects for which maintaining a power supply is critical. This also applies to railway signal boxes. The aim of the research work was to test the multisource power supply system for a railway signal box with power electronic converter systems and a DC bus, built as part of the research project. The assumption for powering the railway signal box building was to use renewable sources, energy storage devices, and a 3 kV DC traction network as the second required power supply grid. Both power grids were connected by power electronic converters, and the power values of the converters were set based on the calculated power balance values using the values measured at the system nodes and the set constraints. The tests primarily tested the response of the power supply system to changes in load power and power generated by the photovoltaic source, as well as the charge level of the energy storage devices. The correctness of the control algorithm’s operation was assessed based on the recorded power values in the power supply system nodes. The tests were carried out for 60 scenarios that covered all normal and emergency operating conditions. During the tests, delays in response to changes in the power supplied to the converters and the values of circular power flow between the power grid connections were recorded. The recorded delays ranged from 2 to about 50 s and the circular power flows did not exceed 1500 W. Based on the results of the tests, it was found necessary to improve the power measurement system in the power supply system nodes and to improve the quality of communication and the transmission time of measurement data transmission time.

Theoretical Study of the Steady Time of Thermal Transmission in Materials That Have Engineering Uses

General Background: Understanding the time required to achieve steady-state heat transfer in construction materials is crucial for various engineering applications, including construction, architecture, and electronics. Specific Background: This study investigates the steady time of thermal transmission in engineering materials using both theoretical and experimental approaches. Knowledge Gap: Despite existing research on heat transfer, there is a lack of comprehensive studies that integrate both simulation and experimental validation for a wide range of building materials.Aims: The primary aim is to evaluate the steady-state time of heat transfer in fifteen construction materials through theoretical models and simulations using MATLAB and ANSYS, and to experimentally validate these findings with four selected materials. Results: The study finds that the steady time for heat transfer varies significantly among materials, with wood packaging requiring the longest time (32.49 hours) and aluminum the shortest (0.49 hours). Theoretical results, validated by simulations, show close agreement between MATLAB and ANSYS (0.087% deviation) and between numerical and experimental results (9.5% deviation). Brick demonstrated a 61.18% longer heat transfer time compared to concrete, while thermostone showed a 17.45% and 89.31% increase over brick and concrete, respectively. Novelty: This research provides new insights into the comparative stability of heat transfer times across a broad spectrum of materials, highlighting significant performance variations and validating simulation methods against experimental data. Implications: These findings are vital for optimizing material selection in construction to enhance thermal efficiency. The study’s methodologies can aid in developing more accurate predictive models for heat transfer in construction materials, thereby contributing to improved design and energy performance in building applications.

Secured Public Health data Management Framework using the Internet of Things in a Smart City Environment

The Internet of Things (IoT) is being embraced and impacts various aspects of lives. Integrating IoT technology in the healthcare sector paves the way for continuous remote monitoring of individuals' health status. The healthcare (HC) sector has traditionally produced substantial data. Due to the implementation of the IoT, this quantity has significantly increased. Ensuring proper HC storage is imperative to derive meaningful insights from the data. This study presents a public health (PH) framework that utilizes cloudlets and IoT technology. The primary objective of this PH architecture is to facilitate the retrieval of real-time data by using cloudlets. The research provides and executes an HC data management system to store vast HC data and handle consumer queries to retrieve HC information. The efficacy of the proposed model has been evaluated in terms of data transmission time, energy usage, query response time, and data packet loss. The proposed model outperforms existing PH systems by comparing the assessment findings of the proposed approach with the performance of typical PH systems.

HAC-SAGIN: High-altitude computing enabled space–air–ground integrated networks for 6G

The space–air–ground integrated networks (SAGINs) provide a new paradigm for the development of the Internet of Things (IoT) networks by enhancing coverage and deploying computing resources near IoT devices, especially in emergency situations and disaster-hit regions. In the context of the IoT networks, aerial platforms such as unmanned aerial vehicles (UAVs) and high-altitude platforms (HAPs) present in the air layer of SAGINs with access and aerial computing (AC) capabilities have the potential to significantly expand coverage, enhance performance, reduce delay and handle complex computation tasks for IoT devices. Seeking the stated prospect, we propose a high-altitude computing (HAC)-enabled SAGIN leveraging millimeter waves (mmWave) frequency range in which the IoT devices are provided access services by low-earth orbit satellites (LEO-SATs) and HAPs while the HAPs offer AC facility as well. Non-orthogonal multiple access (NOMA) is used as a multiple-access technique with different clustering mechanisms in uplink (UL) and downlink (DL) communication. We aim to establish high-rate data transmission in DL along with minimizing the execution time of IoT devices offloading their data to the HAPs in UL communication. The mmWaves range is targeted to have high-rate data transmissions and NOMA implementation further enhances the bandwidth available for an individual IoT device. For efficient offloading in UL communication, we formulate an optimization problem aiming to minimize the execution time by using the Lagrangian function-based approach. Execution time is minimized by reducing the transmission and computation time, which is attained by the optimization of allocated power and computation resources. Simulation results demonstrate that the proposed HAC-SAGIN is able to establish high-rate transmissions in DL and exhibits a significant decrease in execution time in UL in contrast to the no optimization case. Optimum power assignment improves the achievable rate, leading to reduced transmission times, while optimum core assignment efficiently reduces the computation time. In addition, the offloaded data size-driven NOMA implementation in UL prominently improves the system effective throughput.

Fast and fair split computing for accelerating deep neural network (DNN) inference

Conventional split computing approaches for AI models that generate large outputs suffer from long transmission and inference times. Due to the limited resources of the edge server and selfish MDs, some MDs cannot offload their tasks and sacrifice their performance. To address these issues, we formulate an optimization problem to determine one or two split points that minimize inference latency while ensuring fair offloading among MDs. Additionally, we devise a low-complexity heuristic algorithm called fast and fair split computing (F2SC). Evaluation results demonstrate that F2SC reduces inference time by 3.8%∼20.1% compared to the conventional approaches while maintaining fairness.

The Effects of the StartReact on Reaction Time, Rate of Force Development, and Muscle Activity in Biceps Brachii

ABSTRACTThe StartReact test, increasingly popular for assessing cortico‐reticular functioning, is a valid method to influence the firing of reticulospinal tract neurons noninvasively. However, there remains limited evidence on how different stimuli employed in the StartReact test impact motor output in humans. The present study tested elbow flexor responses of 33 adults (aged 26–48 years) to visual stimuli only (LED light), audio‐visual (80 dB) stimuli, and startle‐inducing audio‐visual (120 dB) stimuli sitting with the arm supinated in an electromechanical dynamometer. Surface electromyogram (EMG) recorded muscle activity from the right biceps brachii muscle. Participants were presented with 20 stimuli for each of the three conditions in pseudorandom order with interstimulus intervals of ~8 s. Reaction times were calculated from the stimulus trigger to the initial rise in the EMG signal above 7 × SD from baseline. Rate of torque development (RTD) and EMG signals were recorded throughout and analyzed over their initial 50 ms and 100 ms time‐windows. Reaction times were reduced from visual (169 ± 23) to audio‐visual (140 ± 23) and further reduced to startle‐inducing audio‐visual stimuli (108 ± 19, p &lt; 0.001). While RTD and EMG were consistently greatest following startle‐inducing stimuli (p &lt; 0.001), they were also enhanced following all audio‐visual stimuli over 100 ms (p &lt; 0.05). It appears that startle‐inducing audio‐visual stimuli result in shorter reaction times, increased RTD, and enhanced muscle activity within the initial 50 ms, likely from subcortical upregulation. However, the 100 ms time‐window suggests cortical upregulation following all audio‐visual stimuli considering the longer transmission times.

A WSN and vision based smart, energy efficient, scalable, and reliable parking surveillance system with optical verification at edge for resource constrained IoT devices

As urbanization accelerates, the demand for efficient parking surveillance solutions has increased. However, existing solutions often face challenges related to energy consumption, scalability, and reliability. This paper introduces a smart hybrid parking surveillance system integrating wireless sensor networks (WSNs) with vision based solution at the edge for resource constrained IoT devices to address these challenges. The solution leverages WSNs for periodic readings of parking space occupancy and introduces a low power sleep mode in the network for energy efficiency, along with optical verification strategies using computer vision models like R-CNN and Faster R-CNN FPN on ResNet50 and MobileNetv2 backbones for distinguishing between true and false positives in the WSN data for a greater accuracy in parking space occupancy. The system utilizes edge for computing on edge servers resulting in increased responsiveness of the system, reduced data transmission and real time processing of data. The proposed solution is formulated in such a way that it automatically switches between WSN and vision based sensing resulting in less energy consumption and longer lifespan of the system without compromising on accuracy. Through experimental results it is observed that models trained on the MobileNetv2 backbone demonstrated at least twice faster for both processing the images and training compared to those models trained on the ResNet backbone. On the other hand, both Faster R-CNN FPN (input resolution: 1440) and R-CNN (input resolution: 128) models trained on the MobileNetv2 backbone have slightly lower accuracies than the same models trained on the ResNet50 backbone.

An electricity price and energy-efficient workflow scheduling in geographically distributed cloud data centers

The cloud computing platform has become a favorable destination for running cloud workflow applications. However, they are primarily complicated and require intensive computing. Task scheduling in cloud environments, when formulated as an optimization problem, is proven to be NP-hard. Thus, efficient task scheduling plays a decisive role in minimizing energy costs. Electricity prices fluctuate depending on the vending company, time, and location. Therefore, optimizing energy costs has become a serious issue that one must consider when building workflow applications scheduling across geographically distributed cloud data centers (GD-CDCs). To tackle this issue, we have suggested a dual optimization approach called electricity price and energy-efficient (EPEE) workflow scheduling algorithm that simultaneously considers energy efficiency and fluctuating electricity prices across GD-CDCs, aims to reach the minimum electricity costs of workflow applications under the deadline constraints. This novel integration of dynamic voltage and frequency scaling (DVFS) with energy and electricity price optimization is unique compared to existing methods. Moreover, our EPEE approach, which includes task prioritization, deadline partitioning, data center selection based on energy efficiency and price diversity, and dynamic task scheduling, provides a comprehensive solution that significantly reduces electricity costs and enhances resource utilization. In addition, the inclusion of both generated and original data transmission times further differentiates our approach, offering a more realistic and practical solution for cloud service providers (CSPs). The experimental results reveal that the EPEE model produces better success rates to meet task deadlines, maximize resource utilization, cost and energy efficiencies in comparison to adapted state-of-the-art algorithms for similar problems.