Dynamic resource allocation in 5G networks using hybrid RL-CNN model for optimized latency and quality of service.

The rapid deployment of 5G networks necessitates innovative solutions for efficient and dynamic resource allocation. Current strategies, although effective to some extent, lack real-time adaptability and scalability in complex, dynamically-changing environments. This paper introduces the Dynamic Resource Allocator using RL-CNN (DRARLCNN), a novel machine learning model addressing these shortcomings. By merging Convolutional Neural Networks (CNN) for feature extraction and Reinforcement Learning (RL) for decision-making, DRARLCNN optimizes resource allocation, minimizing latency and maximizing Quality of Service (QoS). Utilizing a state-of-the-art "5G Resource Allocation Dataset", the research employs Python, TensorFlow, and OpenAI Gym to implement and test the model in a simulated 5 G environment. Results demonstrate the effectiveness of DRARLCNN, showcasing an impressive R2 score of 0.517, MSE of 0.035, and RMSE of 0.188, surpassing existing methods in allocation efficiency and latency. The DRARLCNN model not only outperforms existing methods in allocation efficiency and latency but also sets a new benchmark for future research in dynamic 5G resource allocation. Through its innovative approach and promising results, DRARLCNN opens avenues for further advancements in optimizing resource allocation within dynamic 5G networks.

Provision of prostate cancer services in Tanzania: perspectives from five tertiary hospitals.

BACKGROUND: Access to quality prostate cancer services remains a global challenge, particularly in Low- and Middle-Income countries. This is often due to weak health systems that struggle to meet the population's needs. The provision of quality health services to patients with prostate cancer requires a comprehensive approach involving multiple stakeholders and structural inputs. However, few studies have comprehensively assessed the relationship between these structural inputs and prostate cancer treatment outcomes. This study, therefore, aimed to determine the availability of selected structural inputs and descriptions of how they influence the provision of quality services to patients with prostate cancer in Tanzania. METHODS: We conducted a cross-sectional study using an explanatory sequential mixed-method approach to collect data from five tertiary hospitals providing cancer services in Tanzania. A validated checklist was used to collect information on available structural inputs for prostate services at tertiary hospitals. A semi-structured interview guide was used to conduct 42 in-depth interviews with 20 healthcare providers, five hospital managers, and 17 patients undergoing treatment for prostate cancer. Descriptive analysis was performed for the quantitative data, and thematic analysis was conducted with the aid of NVivo 14 qualitative software for the interview transcripts. RESULTS: All five assessed tertiary hospitals had inadequate human resources for health to provide prostate cancer services. Only one had 70% of the required HRH, while none had above 40% of the required HRH. Within the hospitals, the skill mix imbalance was severe across cadres. Five themes emerged: inadequate infrastructure, delays in diagnosis, delays in treatment, shortage of human resources for health (HRH), and inefficient organization of prostate cancer services. CONCLUSION: The findings of this study, underscore the major health system deficiencies for the provision of prostate cancer services in tertiary hospitals. With the increased aging population, strong health systems are vital in addressing conditions of old aging, including prostate cancers. Studies on optimization of the available HRH and infrastructure are needed to improve the provision of prostate cancer in tertiary hospitals as an interim solution while long-term measures are needed for improving the HRH availability and conducive infrastructure.

Quality of Service-Aware Multi-Objective Enhanced Differential Evolution Optimization for Time Slotted Channel Hopping Scheduling in Heterogeneous Internet of Things Sensor Networks.

The emergence of the Internet of Things (IoT) has attracted significant attention in industrial environments. These applications necessitate meeting stringent latency and reliability standards. To address this, the IEEE 802.15.4e standard introduces a novel Medium Access Control (MAC) protocol called Time Slotted Channel Hopping (TSCH). Designing a centralized scheduling system that simultaneously achieves the required Quality of Service (QoS) is challenging due to the multi-objective optimization nature of the problem. This paper introduces a novel optimization algorithm, QoS-aware Multi-objective enhanced Differential Evolution optimization (QMDE), designed to handle the QoS metrics, such as delay and packet loss, across multiple services in heterogeneous networks while also achieving the anticipated service throughput. Through co-simulation between TSCH-SIM and Matlab, R2023a we conducted multiple simulations across diverse sensor network topologies and industrial QoS scenarios. The evaluation results illustrate that an optimal schedule generated by QMDE can effectively fulfill the QoS requirements of closed-loop supervisory control and condition monitoring industrial services in sensor networks from 16 to 100 nodes. Through extensive simulations and comparative evaluations against the Traffic-Aware Scheduling Algorithm (TASA), this study reveals the superior performance of QMDE, achieving significant enhancements in both Packet Delivery Ratio (PDR) and delay metrics.

A Survey on Green Enablers: A Study on the Energy Efficiency of AI-Based 5G Networks.

In today's world, the significance of reducing energy consumption globally is increasing, making it imperative to prioritize energy efficiency in 5th-generation (5G) networks. However, it is crucial to ensure that these energy-saving measures do not compromise the Key Performance Indicators (KPIs), such as user experience, quality of service (QoS), or other important aspects of the network. Advanced wireless technologies have been integrated into 5G network designs at multiple network layers to address this difficulty. The integration of emerging technology trends, such as machine learning (ML), which is a subset of artificial intelligence (AI), and AI's rapid improvements have made the integration of these trends into 5G networks a significant topic of research. The primary objective of this survey is to analyze AI's integration into 5G networks for enhanced energy efficiency. By exploring this intersection between AI and 5G, we aim to identify potential strategies and techniques for optimizing energy consumption while maintaining the desired network performance and user experience.

Enhancing Cybersecurity in Distributed Microgrids: A Review of Communication Protocols and Standards.

The effective operation of distributed energy sources relies significantly on the communication systems employed in microgrids. This article explores the fundamental communication requirements, structures, and protocols necessary to establish a secure connection in microgrids. This article examines the present difficulties facing, and progress in, smart microgrid communication technologies, including wired and wireless networks. Furthermore, it evaluates the incorporation of diverse security methods. This article showcases a case study that illustrates the implementation of a distributed cyber-security communication system in a microgrid setting. The study concludes by emphasizing the ongoing research endeavors and suggesting potential future research paths in the field of microgrid communications.

Maternal satisfaction on quality of childhood vaccination services and its associated factors at public health centers in Addis Ababa, Ethiopia.

BACKGROUND: Vaccination is one of the most important public health interventions to reduce child mortality and morbidity. In Ethiopia, about 472,000 children die each year by vaccine-preventable diseases. A satisfied mother is assumed to use the services and complies with the service provider for better health care outcomes. However, there was no adequate evidence regarding maternal satisfaction with quality of childhood vaccination services. This study aimed to assess maternal satisfaction on quality of childhood vaccination services and its associated factors at public health centers in Addis Ababa, Ethiopia. METHODS: A facility-based cross-sectional study was conducted from 12 July to 12 August 2021 at public health centers in Addis Ababa, Ethiopia. A total of 366 mothers (caretakers) of under one-year-old children participated in the study. A systematic sampling technique with an interviewer-administered questionnaire and inventory checklist were used to collect the data. A binary logistic regression model was fitted. Adjusted Odds Ratio (AOR) with 95% confidence interval (CI) and p-value < 0.05 were used to identify the factors associated with the outcome. RESULTS: Nearly two-thirds (61.2%) of mothers (caretakers) were satisfied with the quality of childhood vaccination services. Service providers' greeting [AOR = 1.60; 95%CI: 1.37-1.99] and information about the types of vaccines [AOR = 1.54; 95%CI: 1.32-1.89] were positively associated with maternal satisfaction. On the contrary, long waiting time of mothers (caretakers) to receive services [AOR = 0.29; 95%CI: 0.14-0.62] was negatively associated with services. CONCLUSION: The overall maternal satisfaction towards the quality of childhood vaccination services in this study was found to be low. Minimizing waiting time at the health facility, enhancing greetings and providing adequate information regarding childhood vaccination for mothers (caretakers) improved their satisfaction with the services.

The Age of Information in Wireless Cellular Systems: Gaps, Open Problems, and Research Challenges.

One of the critical use cases for prospective fifth generation (5G) cellular systems is the delivery of the state of the remote systems to the control center. Such services are relevant for both massive machine-type communications (mMTC) and ultra-reliable low-latency communications (URLLC) services that need to be supported by 5G systems. The recently introduced the age of information (AoI) metric representing the timeliness of the reception of the update at the receiver is nowadays commonly utilized to quantify the performance of such services. However, the metric itself is closely related to the queueing theory, which conventionally requires strict assumptions for analytical tractability. This review paper aims to: (i) identify the gaps between technical wireless systems and queueing models utilized for analysis of the AoI metric; (ii) provide a detailed review of studies that have addressed the AoI metric; and (iii) establish future research challenges in this area. Our major outcome is that the models proposed to date for the AoI performance evaluation and optimization deviate drastically from the technical specifics of modern and future wireless cellular systems, including those proposed for URLLC and mMTC services. Specifically, we identify that the majority of the models considered to date: (i) do not account for service processes of wireless channel that utilize orthogonal frequency division multiple access (OFDMA) technology and are able to serve more than a single packet in a time slot; (ii) neglect the specifics of the multiple access schemes utilized for mMTC communications, specifically, multi-channel random access followed by data transmission; (iii) do not consider special and temporal correlation properties in the set of end systems that may arise naturally in state monitoring applications; and finally, (iv) only few studies have assessed those practical use cases where queuing may happen at more than a single node along the route. Each of these areas requires further advances for performance optimization and integration of modern and future wireless provisioning technologies with mMTC and URLLC services.

Toward QoS Monitoring in IoT Edge Devices Driven Healthcare-A Systematic Literature Review.

Smart healthcare is altering the delivery of healthcare by combining the benefits of IoT, mobile, and cloud computing. Cloud computing has tremendously helped the health industry connect healthcare facilities, caregivers, and patients for information sharing. The main drivers for implementing effective healthcare systems are low latency and faster response times. Thus, quick responses among healthcare organizations are important in general, but in an emergency, significant latency at different stakeholders might result in disastrous situations. Thus, cutting-edge approaches like edge computing and artificial intelligence (AI) can deal with such problems. A packet cannot be sent from one location to another unless the "quality of service" (QoS) specifications are met. The term QoS refers to how well a service works for users. QoS parameters like throughput, bandwidth, transmission delay, availability, jitter, latency, and packet loss are crucial in this regard. Our focus is on the individual devices present at different levels of the smart healthcare infrastructure and the QoS requirements of the healthcare system as a whole. The contribution of this paper is five-fold: first, a novel pre-SLR method for comprehensive keyword research on subject-related themes for mining pertinent research papers for quality SLR; second, SLR on QoS improvement in smart healthcare apps; third a review of several QoS techniques used in current smart healthcare apps; fourth, the examination of the most important QoS measures in contemporary smart healthcare apps; fifth, offering solutions to the problems encountered in delivering QoS in smart healthcare IoT applications to improve healthcare services.

Multiple Mobile Sinks for Quality of Service Improvement in Large-Scale Wireless Sensor Networks.

The involvement of wireless sensor networks in large-scale real-time applications is exponentially growing. These applications can range from hazardous area supervision to military applications. In such critical contexts, the simultaneous improvement of the quality of service and the network lifetime represents a big challenge. To meet these requirements, using multiple mobile sinks can be a key solution to accommodate the variations that may affect the network. Recent studies were based on predefined mobility models for sinks and relied on multi-hop routing techniques. Besides, most of these studies focused only on improving energy consumption without considering QoS metrics. In this paper, multiple mobile sinks with random mobile models are used to establish a tradeoff between power consumption and the quality of service. The simulation results show that using hierarchical data routing with random mobile sinks represents an efficient method to balance the distribution of the energy levels of nodes and to reduce the overall power consumption. Moreover, it is proven that the proposed routing methods allow for minimizing the latency of the transmitted data, increasing the reliability, and improving the throughput of the received data compared to recent works, which are based on predefined trajectories of mobile sinks and multi-hop architectures.

Application-Aware Scheduling for IEEE 802.15.4e Time-Slotted Channel Hopping Using Software-Defined Wireless Sensor Network Slicing.

Given the improvements to network flexibility and programmability, software-defined wireless sensor networks (SDWSNs) have been paired with IEEE 802.15.4e time-slotted channel hopping (TSCH) to increase network efficiency through slicing. Nonetheless, ensuring the quality of service (QoS) level in a scalable SDWSN remains a significant difficulty. To solve this issue, we introduce the application-aware (AA) scheduling approach, which isolates different traffic types and adapts to QoS requirements dynamically. To the best of our knowledge, this approach is the first to support network scalability using shared timeslots without the use of additional hardware while maintaining the application's QoS level. The AA approach is deeply evaluated compared with both the application traffic isolation (ATI) approach and the application's QoS requirements using the IT-SDN framework and by varying the number of nodes up to 225. The evaluation process took into account up to four applications with varying QoS requirements in terms of delivery rate and delay. In comparison with the ATI approach, the proposed approach enhanced the delivery rate by up to 28% and decreased the delay by up to 57%. Furthermore, even with four applications running concurrently, the AA approach proved capable of meeting a 92% delivery rate requirement for up to 225 nodes and a 900 ms delay requirement for up to 144 nodes.

"In the Wild" Video Content as a Special Case of User Generated Content and a System for Its Recognition.

In the five years between 2017 and 2022, IP video traffic tripled, according to Cisco. User-Generated Content (UGC) is mainly responsible for user-generated IP video traffic. The development of widely accessible knowledge and affordable equipment makes it possible to produce UGCs of quality that is practically indistinguishable from professional content, although at the beginning of UGC creation, this content was frequently characterized by amateur acquisition conditions and unprofessional processing. In this research, we focus only on UGC content, whose quality is obviously different from that of professional content. For the purpose of this paper, we refer to "in the wild" as a closely related idea to the general idea of UGC, which is its particular case. Studies on UGC recognition are scarce. According to research in the literature, there are currently no real operational algorithms that distinguish UGC content from other content. In this study, we demonstrate that the XGBoost machine learning algorithm (Extreme Gradient Boosting) can be used to develop a novel objective "in the wild" video content recognition model. The final model is trained and tested using video sequence databases with professional content and "in the wild" content. We have achieved a 0.916 accuracy value for our model. Due to the comparatively high accuracy of the model operation, a free version of its implementation is made accessible to the research community. It is provided via an easy-to-use Python package installable with Pip Installs Packages (pip).

Paediatric emergency medicine practice in Nigeria: a narrative review.

The practice of paediatric emergency medicine in Nigeria is still evolving, and laden with enormous challenges which contribute to adverse outcomes of childhood illnesses in emergency settings. Deaths from childhood illnesses presenting as emergencies contribute to overall child mortality rates in Nigeria. This narrative review discusses existing structures, organization, and practice of paediatric emergency in Nigeria. It highlights some of the challenges and suggests ways of surmounting them in order to reduce deaths in the children emergency units in Nigerian hospitals. Important aspects of this review include current capacity and need for capacity development, equipment needs for emergency care, quality of service in the context of inadequate healthcare funding and the need for improvement.

[Technology «Care assistant¼: organization of care assistant' activities and quality of service (based on materials of the Volgograd region).]

The organization of the activity of сare assistant using the «Care Assistant¼ technology in the Volgograd region is the subject of consideration in this study. The provisions of E.Giddens' structural theory help to determine the specifics of the organization of the care assistant's activities. The analysis of the activities of care professionals and the assessment of the quality of service is based on the results of an expert survey of сare assistant and a questionnaire survey of service recipients in the region. The formal rules governing the activities of the subjects of the long-term care system constitute the macro-level of the «Care Assistant¼ technology. The meso-level includes the forms and methods of care professionals' activities within a separate social service organization. The micro-level is the interaction of сare assistant with various specialists at all stages of providing social services in long-term care. The survey results showed that care assistants provide free services included in the social package of long-term care. Defining the specifics of the organization of the care assistants, the author identified problems related to working conditions, the provision of additional services, paperwork, education. The results of the questionnaire survey of service recipients indicate that respondents are satisfied with the quality of service, availability and timeliness of social services.

Factors affecting public transport performance due to the COVID-19 outbreak: A worldwide analysis.

In this paper we investigate the public transport trip frequency variations, as well as the reasons that led to the shift away from public transport means, due to the COVID-19 pandemic. We studied relevant data from the Moovit platform, and we compared operational and trip frequency characteristics of public transport systems before and after the outbreak of the pandemic in 87 cities worldwide. On average, waiting times at public transport stops/stations increased while trip distances decreased, apparently due to the mobility restriction and social distancing measures implemented in 2020. Most of the Moovit users who said that they abandoned public transport in 2020 were found in Italy and Greece. We developed linear regression analysis models to investigate (among the 35 variables examined in the study) the relationship between public transport abandonment rates and socioeconomic factors, quality of service characteristics, and indicators of pandemic's spread. Empirical findings show that public transport dropout rates are positively correlated with the COVID-19 death toll figures, the cleanliness of public transport vehicles and facilities, as well as with the income inequality (GINI) index of the population, and thus reconfirm previous research findings. In addition, the waiting time at stops/stations and the number of transfers required for commute trips appeared to be the most critical public transport trip segments, which significantly determine the discontinuation of public transport use under pandemic circumstances. Our research findings indicate specific aspects of public transport services, which require tailored adjustments in order to recover ridership in the post-pandemic period.

Periodic Optimization of Bus Dispatching Times and Vehicle Schedules Considering the COVID-19 Capacity Limits: A Dutch Case Study.

The COVID-19 pandemic has had serious adverse impacts on public transport service providers. Most public transport lines exhibit reduced ridership levels while, at the same time, some of them may exhibit passenger demand levels beyond the pandemic-imposed capacity limitations. This study models the problem of bus dispatching time optimization within a periodic rolling horizon optimization framework that reacts to travel time and passenger demand variations. This model allows public transport service providers to adjust their bus schedules periodically to avoid in-vehicle crowding beyond the pandemic-imposed capacity limit. The proposed model is a mixed-integer linear program that considers the possible changes to vehicle schedules and tries to minimize the number of vehicles required to perform the service while adhering to the COVID-19 capacity restrictions. Case study results from the implementation of our model on bus Line 2 in the Twente region in the Netherlands are provided demonstrating the potential gains when rescheduling the trip dispatching times and vehicle schedules.

[Assessment of patient satisfaction with orthodontic services provided in medical organizations of various forms of ownership]. / Otsenka udovletvorennosti patsientov ortodonticheskimi uslugami v meditsinskikh organizatsiyakh razlichnoi formy sobstvennosti.

OBJECTIVE: The study of expectations and satisfaction with the quality of orthodontic care provided to children in public and private dental organizations. MATERIAL AND METHODS: The study was conducted at the clinical bases of the Borovsky Institute of Dentistry of the Sechenov First Moscow State Medical University, Vladimirsky Moscow Regional Research Clinical Institute, Videntis LLC in the period from January to April 2022. An anonymous questionnaire was developed for the study: "Questionnaire for patients to assess the quality and conditions of orthodontic medical services in a medical organization". All data are processed using the statistical software SPSS v. 20. RESULTS AND DISCUSSION: According to respondents, the quality of service in both public and private dental organizations depends on the material and technical equipment of the medical organization, the attitude of medical personnel, the duration of treatment and the qualifications of orthodontists. Satisfaction of orthodontic care in public dental organizations corresponded to a high level in 73.4% of cases, an average level of 15.6% of cases, a low level in 11.0% of cases; in private dental organizations, a high level was noted in 98.8% of cases, an average level in 1.2% of cases, a low level in 0% of cases (in private dental organizations, not a single respondent noted the quality of services provided as low). Among the main reasons for dissatisfaction with the service of patients, the lack of diagnostic equipment, the unfriendly attitude of the secondary medical and administrative staff, as well as the duration of treatment should be highlighted. CONCLUSION: A sociological survey to assess patient satisfaction is a tool for determining the effectiveness of any medical organization, while the assessment of the quality of service of respondents depends on the material and technical equipment of the dental organization, the attitude of medical personnel, the duration of treatment and the qualifications of orthodontists. In this regard, it is very important to apply this method of satisfaction assessment when providing high-quality orthodontic care to children both in public and private dental organizations in order to improve the quality of service in a dental medical organization.

Measuring the quality of life of long-term care service users in Japan: a cross-sectional questionnaire study.

BACKGROUND: In Japan's super-aging society, the number of long-term care service providers is increasing, and the quality of care is a matter of concern. One aspect of the quality of care is the user's quality of life. The questionnaires EQ-5D and WHO-5 are representative indicators of quality of life. Herein, we aimed to measure the quality of life in long-term care service users in Japan and to clarify the relationship between quality of life and the level of care required. METHODS: A questionnaire study was conducted in 106 facilities of 22 corporations. In addition to the EQ-5D and WHO-5, sex, age, and the level of care required were assessed by descriptive statistics. Bonferroni's multiple comparison test was used to analyze each quality of life score, and the differences by sex and age were analyzed multiple regression analyses, with each quality of life score as the objective variable. RESULTS: Of 4647 cases collected, 2830 were analyzed, with no missing data. Both indicators tended to be lower than the general older population. Those scores tended to be higher in females than males (EQ-5D: males, 0.58 ± 0.26; females, 0.60 ± 0.24; P = 0.06 and WHO-5: males, 13.8 ± 5.92; females 14.9 ± 5.70; P < 0.001). In terms of age, those under 65 years old with specific diseases had lower EQ-5D scores than those in other age groups (P < 0.001); however, WHO-5 scores did not differ by age. Multiple regression analysis showed a significant association between the EQ-5D score and level of care required, except for support-required level 1, which tended to worsen as the level of care required increased. Conversely, the WHO-5 score was significantly lower for care need levels 2, 4, and 5. CONCLUSIONS: The quality of life of long-term care service users was worse than that of the general older population, it tended to be low among males and those under 65 years old with specific diseases. Furthermore, it gradually decreased as the level of care required increased. It is important to monitor users' quality of life as a quality indicator of care, to improve and manage it.

The quality of service provision to newborns in the primary healthcare, West Gojjam zone, North-West of Ethiopia: a cross-sectional survey.

BACKGROUND: During 2019, neonatal conditions in Ethiopia accounted for 55% of under-5 deaths, with 33 neonatal deaths occurring for every 1000 live births. More than 80% of all newborns deaths are caused by preventable and treatable conditions with available interventions. In Ethiopia, mortality rates for newborn babies have remained stubbornly high over the decades. OBJECTIVE: This research aimed to assess the quality-of-service provision for newborns in the primary healthcare units in the North-West of Ethiopia. METHODS: A cross-sectional survey design was employed. Interviewer-administered questionnaires were administered to 221 health workers and health extension workers, and health facility readiness assessment was done in 142 health facilities including 3 Primary hospitals, 76 Health centres and 63 Health posts from April to July 2017. Data was entered into the EpiData 3.1, exported to SPSS and STATA for analysis. Descriptive and regression multivariate analysis was applied. RESULTS: Out of the 10 quality of newborn care variables, 8.7 [95%CI: 6.03-11.303], the highest mean was achieved by primary hospitals, followed by urban health centres with a 6.4 mean [95%CI:5.168-7.601]. However, nearly half of the rural health centres were providing quality of newborn care at the mean of 5.7 [95%CI: 5.152-6.18], and below half was provided by health posts, 4.5 [95%CI: 3.867-5.116]. From the seven emergency newborn care signal functions, primary hospitals had a higher mean score, 6.3 [95%CI: 6.007-7.325] and rural health centres had the lowest mean score, 2.3 [95%CI: 2.043-2.623]. The availability of essential equipment is also significantly associated with the quality of neonatal care provision in the health facilities (p < 0.05). Overall, the effectiveness of the neonatal healthcare services has a significant association with the health facility readiness score [95%CI: 0.134-0.768]. CONCLUSION: The quality of newborn care was high at the higher-level health facilities and lower in the lower-level health facilities such as rural health centres and health posts, where these facilities are an entry point to the health system and are expected to provide the essential newborn care services to the majority of the rural communities. In addition, the provision of emergency newborn care signal functions was critically low in rural health centres where these are referral receiving health facilities from health posts. Thus, rural health centres and health posts should be targeted to improve their readiness to provide the quality of services for newborns as per their expected level of care.

Quality of Service Aware Orchestration for Cloud-Edge Continuum Applications.

The fast growth in the amount of connected devices with computing capabilities in the past years has enabled the emergence of a new computing layer at the Edge. Despite being resource-constrained if compared with cloud servers, they offer lower latencies than those achievable by Cloud computing. The combination of both Cloud and Edge computing paradigms can provide a suitable infrastructure for complex applications' quality of service requirements that cannot easily be achieved with either of these paradigms alone. These requirements can be very different for each application, from achieving time sensitivity or assuring data privacy to storing and processing large amounts of data. Therefore, orchestrating these applications in the Cloud-Edge computing raises new challenges that need to be solved in order to fully take advantage of this layered infrastructure. This paper proposes an architecture that enables the dynamic orchestration of applications in the Cloud-Edge continuum. It focuses on the application's quality of service by providing the scheduler with input that is commonly used by modern scheduling algorithms. The architecture uses a distributed scheduling approach that can be customized in a per-application basis, which ensures that it can scale properly even in setups with high number of nodes and complex scheduling algorithms. This architecture has been implemented on top of Kubernetes and evaluated in order to asses its viability to enable more complex scheduling algorithms that take into account the quality of service of applications.

A High-Robust Sensor Activity Control Algorithm for Wireless Sensor Networks.

In wireless sensor networks, it is important to use the right number of sensors to optimize the network and consider the key design and cost. Due to the limited power of sensors, important issues include how to control the state of the sensor through an automatic control algorithm and how to power-save and efficiently distribute work. However, sensor nodes are usually deployed in dangerous or inaccessible locations. Therefore, it is difficult and impractical to supply power to sensors through humans. In this study, we propose a high reliability control algorithm with fast convergence and strong self-organization ability called the sensor activity control algorithm (SACA), which can efficiently control the number of sensors in the active state and extend their use time. In the next round, SACA considers the relationship between the total number of active sensors and the target value and determines the state of the sensor. The data transmission technology of random access is used between the sensor and the base station. Therefore, the sensor in the sleep state does not need to receive the feedback packet from the base station. The sensor can achieve true dormancy and power-saving effects. The experimental results show that SACA has fast convergence, strong self-organization capabilities, and power-saving advantages.