Network Services Research Articles

Virtualized network functions resource allocation in network functions virtualization using mathematical programming

Network Functions Virtualization (NFV) revolutionizes network services by eliminating the need for dedicated hardware. This virtualization enables flexible and efficient deployment of various network functions like proxies, firewalls, and load balancers. Providing the service requested by the user in the network is done by a sequence of virtual network functions, which are known as service functions chain. One of the main challenges in the development of network functions virtualization architecture is the allocation of resources to the requested network services in network infrastructures, this challenge is called network function virtualization resource allocation problem. Therefore, this paper addresses the resource allocation problem in Network Functions Virtualization (NFV) architectures using mathematical programming techniques. A multi-objective mixed-integer linear programming (MILP) model is proposed to optimize resource allocation for virtual network functions (VNFs). The model incorporates constraints related to node and link resource capacities, as well as delay requirements. The objective functions focus on maximizing network throughput, minimizing node resource costs (CPU cores and memory), reducing capital and operational expenses, and ensuring efficient execution time. These constraints and objective functions are formally defined by mathematical functions. The proposed mathematical model is implemented and solved using the Cplex solver. To evaluate the effectiveness of the proposed mathematical model, various network topologies were evaluated under different parameters. These parameters included the length of Service Function Chains (SFCs), the number and length of flows, node resource capacities, the number of nodes and VNFs. The experimental results demonstrated the model’s ability to efficiently allocate resources to VNFs across these different scenarios.

Effects of meteorological variables on the quality of service of mobile networks in Yenagoa – southern Nigeria

The nexus of this study is to investigate the dependencies of CSSR and DCR on Meteorological parameters for four mobile networks in Yenagoa. The Meteorological parameters used, temperature and relative humidity, were obtained from Nigerian Meteorological Agency. These data which span from January 2014 to December 2023 were averaged to obtain monthly mean temperature and relative humidity for Yenagoa. CSSR and DCR monthly data from January 2014 to December 2023 for Yenagoa were obtained from NCC, Abuja. Correlation coefficients between CSSR and Temperature, CSSR and relative humidity, DCR and temperature, DCR and relative humidity were 0.49, -0.47, -0.35, 0.29 for MTN network, 0.56, -0.02, -0.47, 0.31 for Airtel network, 0.21, -0.34, -0.11, -0.26 for 9mobile and 0.69, -0.04, -0.25, 0.00 for Globacom network. Graphs were plotted using QoS KPIs as the dependent variable while the weather parameters were the independent variables. Regression models were developed for predicting CSSR and DCR, provided, the temperature or relative humidity at that particular time is known. It was concluded that an increase in temperature and relative humidity led to an increase in CSSR and vice versa, while an increase in temperature and relative humidity led to a decrease in DCR and vice versa. This result will be useful to network operators and planners, enabling them to develop an efficient link margin in order to achieve a better QoS. Researchers should investigate QoS KPIs and how they are affected by other meteorological parameters.

Energy Optimization Approach in Wireless Sensor Network

In recent years, the importance of routing protocols in wireless sensor networks and the Internet of Things has been demonstrated by the numerous studies that have been presented in this area. because it is crucial to the network's functionality and effectiveness. Among routing's main goals are lowering latency, enhancing reliability, and averting network collisions. Additionally, it can be claimed that the type of network routing affects service quality, network longevity, and network traffic load control. Thus, in order to lower routing error and boost network performance and efficiency, the firefly is employed in this study to identify the best information transmission path within the network. It is also employed to reduce energy consumption. Taking into account the ability of evolutionary algorithms to optimize specified objective functions, we attempted to lower the network's energy consumption. The network can enhance the number of sending packets with the beginning energy of 3 joules from 1480 rounds to 1798 rounds, based on the proposed algorithm's results. Additionally, by contrasting the approaches described in the same article, it was discovered that the suggested approach can send roughly 40.11% more packets than the RM-LB algorithm and 1.9573% more than the OMS-LB technique. Additionally, it was discovered that by raising the starting energy to 150 joules, the suggested technique outperformed the other two algorithms by 51.23% and 45.17%, respectively, and was able to lengthen the longevity. This was in comparison to the RM-LB method and the OMS-LB method.

대학생의 온라인 대인관계 발달과정과 경험에 관한 내용분석 연구

This study intends to suggest a way to help college students build healthy interpersonal relationships in online space by looking at the online interpersonal development process and what they experience in the process. To this end, in-depth interviews were conducted with 10 college students who have been in a relationship for more than six months online and analyzed using a qualitative content analysis method. As a result, the participants of this study began to establish relationships through games and social networking services (SNS), and began to communicate naturally by adding friends or sharing the same interests in the game. Participants gradually formed an inner intimacy by self-opening with those they met online but shared more daily life by sharing personal contact information or favorite activities together. As the number of times met while feeling inner intimacy increased, they became close and special to each other. Participants gained confidence through online relationships and expanded their relationships by meeting various people non-face-to-face. Because it was non-face-to-face, I was able to treat the other relationships more comfortably, by listening to each other, asking for advice, and experiencing growth and development together. This study suggests that being online is a place for active relationship formation for college students.

End-to-End Resource Allocation Management Model in Next-Generation Network: Survey

Network communication has grown rapidly with massive demands of services. Moreover, resource allocation in networking is a fundamental and crucial issue that cannot ensure the network's stability and efficiency with the myriad requirements of different services. Various vertical businesses may seek varied network services, particularly in the Fifth-Generation networks and Beyond (5G+). The pros of Fifth-Generation communication networks are to outperform 4G in performance by having higher bandwidth, minimum latency, more capacity, and QoS (Quality of Service). Software-Defined Network (SDN) and Network Function Virtualization (NFV) are two technologies that are combined in the next generation cellular network to provide improved network management. The primary idea behind resource allocation (RA) in the next generation network is the concept of network slicing where the network resources are virtually partitioning into many separate networks. Each separated network must satisfy the unique needs of the required service to achieve the required QoS. In this survey, we focus on resource management issues related to network slicing and tackling the biggest obstacles in this field while offering a thorough and up-to-date overview of this field. Thus, thorough analysis of the allocation of resources on the access side and core side of the network communication was sought. Also, demonstrates how revolutionary techniques that are used to support the management of sliced networks which are based on Machine Learning (ML) and Artificial Intelligence (AI). Importantly, use appropriate ML techniques such as deep learning for predicting the network condition and Reinforcement learning to learn optimal allocation policy without depending on prior knowledge and other techniques such as classification and clustering to aggregate the similar needs of users into separate slices. This could help to enhance resource utilization by allocating a sufficient amount of resource as needed based on ML algorithms and optimal utilization of resources and reducing operational costs by real-time adjustment of it based on user demands and network conditions

The methods and tools of ensuring information security of networks

Currently, there is an increase in the number of information threats that lead to unstable operation of data networks. This is due to the mass use, the complication of the hierarchy of area networks, the increase in the heterogeneity of software tools, and the complication of the functionality of network services. In such cases, the development and improvement of methods for determining information security in data transmission networks has a great importance. The article discusses ways to increase the information security of the data network by increasing the reliability of detecting deviations in the operation of the main nodes of the data network and reducing the number of false starts when automating the detection of threats. Experimental verification and evaluation of the effectiveness of the methods were considered, it was shown that the developed methods allow skipping the anomaly of the first type and minimizing errors of the second type. The methods were implemented software in the form of a prototype access detection system (ADS).

Advancements in Wireless Communication Technology: A Comprehensive Analysis of 4G to 7G Systems

This paper presents a comprehensive analysis of the advancements in wireless communication technology from 4G to 7G systems, focusing on critical aspects such as network architecture, spectrum allocation, data rates, security, and coverage. The evolution of wireless communication technology has been remarkable, with each generation introducing significant improvements to meet the growing demands of users and applications in an increasingly connected world. From the early adoption of 4G technology to the anticipated rise of 7G systems, sweeping changes have reshaped the landscape of wireless communications and changed the way we communicate, work and interact with our surroundings we are surrounded by communication. These changes signal a shift towards more efficient, high-speed and high-capacity systems designed to meet the needs of a variety of industries. Furthermore, the need to strengthen security measures and expand network services highlights the importance of ensuring reliability and security in networks in the face of competition and threats Continued research and innovation are essential and for further developments in this area and to realize and enable new work capabilities and services to benefit people, businesses and businesses This article examines the proposed mobile communication features from 4G to 7G in. Each generation brings unique spectrum allocation, usage and operational challenges. Each generation presents unique spectrum allocation, utilization, and efficiency challenges. Furthermore, this paper investigates network architecture aspects, data rates, and throughput, emphasizing latency and reliability improvements. Advancements in spectral efficiency, MIMO scheme usage, cell size, used frequency bands, and coverage enhancement strategies are considered. Additionally, the integration of energy efficiency with economic and social sustainability is analyzed. Security challenges, including privacy protection, new services, access control models, and security monitoring, are classified for each generation. One of the main objectives of this study is to identify the primary applications, impact areas, and overall impact of 4G to 7G technologies.

인스타그램 웹툰 이용 동기와 상호작용성이 이용 만족에 미치는 영향에 관한 연구

In recent times, there has been a notable surge in interest surrounding social networking service (SNS) webtoons, with Instagram webtoons emerging as a particularly popular phenomenon. The popularity of Instagram webtoons can be attributed to three key factors: ease of accessibility, a concise format, and storylines that resonate with users on an everyday level. This study aims to identify the motivations of Instagram webtoon users and to empirically analyze the impact of these motivations and the interactivity factor, as a characteristic of social networking service (SNS) webtoons, on their satisfaction with Instagram webtoons. To this end, a survey was conducted among 216 individuals between the ages of 10 and 30 who have experience using Instagram webtoons. The findings revealed that there are multiple dimensions of motivation (information and trend seeking, convenience, social connection, emotional relaxation, content loyalty, and efficiency) underlying the use of Instagram webtoons. Additionally, the results indicated that interactivity factors have a notable impact on user satisfaction. This study aims to provide theoretical and practical implications by empirically examining the factors that influence satisfaction with Instagram webtoons. The findings can be utilized as a basis for the continued growth of Instagram webtoons and the improvement of the user experience.

A Companion Robots AAL Service Network based on Message Server

A Companion Robots AAL Service Network based on Message Server

Retracted: The Geographical Location Of Nursing Homes: How Accessible Is Care In Our Ageing Society

Abstract Background With ageing demographics, the demand for residential nursing care is increasing. Some evidence and anecdotal experience suggests that nursing home care is often not available locally, resulting in individuals moving from their homes, communities and psychosocial support systems. Methods To evaluate if residential care in Ireland meets demand the number of residential care beds per 1000 adults>65years were estimated from publicly available data. Persons who sought access to the nursing home support scheme over a 6month period were reviewed. Their home location and nursing home location were analysed with respect to locality (city/suburban/town/rural), distance (km), travel time (minutes) and public service networks. Ethically approved. Results Nationally, the lowest availability of nursing home beds was Wicklow and highest Longford. Galway has 0.90 nursing home beds per1000 adults >65years. Of 262 consecutive cases presented to one local placement forum between July–December2023, 133 availed of the scheme and were resident in a nursing home at 3month follow-up. Exclusions included remained at home, deceased, or unknown. Nursing home location was city 6%(n=8), suburb 21%(n=28), town 16.5%(n=22) or rural 56%(n=75). All city placements were public. Drving distance from home to nursing home was 15km (IQR7,31) with a car driving time of 18mins (IQR11,35). No public transport service link from home to nursing home for visiting purposes was available to 38%(n=51), and when available incurred more than one bus change in 65.2%. City dweller was residing in a city located nursing home in 13%(n=5). Of the 87%(n=33) relocated out of the city, over half (n=19) were to rural locations (p<0.001). Conclusion Nursing home availability is insufficient to meet demands. The location of public and private nursing homes is creating deficits in accessing care close to home and community. Current public transport services to nursing home locations is poor.

Relationship Between Social Networking Service Addiction and Occupational Dysfunction in Young Adults.

Social networking services (SNSs) are useful tools; however, problematic use leads to mental health problems. This study aimed to examine whether SNS addiction is associated with occupational dysfunction while considering the effects of depression. This cross-sectional study included 268 undergraduates who responded to the questionnaire on the frequency and time of SNS use, the Center for Epidemiologic Studies Depression Scale (CES-D), SNS-X scale, and the Classification and Assessment of Occupational Dysfunction (CAOD). Hierarchical multiple regression analysis showed effect of the SNS-X score for Instagram was significant (β = 0.174, p = .001) adjusted by the CES-D total score. However, the effect of frequency and time of SNS use were not significant. This suggests that SNS addiction, and not SNS use, is a factor associated with occupational dysfunction that should be emphasized and depression.

Food insecurity, subjective well-being and the use of social networking services in Brazil between 2014 and 2018

The great Brazilian recession was the most marked drop in economic activity in Brazil between the end of the Second World War and the Covid-19 pandemics. This economic crisis may have long lasting and non-anticipated negative consequences on Food Insecurity (FI) and on Subjective Well-Being (SWB). In addition, SWB is increasing linked to the use of Social Networking Services (SNS). The paper used data from World Value Survey (WVS) and logistic and ordered logistic models to empirically test a few hypotheses. The empirical results showed that: FI is negatively correlated with life satisfaction, but not with happiness; FI is unrelated to SNS use as still few people use them and the population groups that suffer from FI insecurity poorly overlap with the one that use SNS daily; SWB had positive relationships with SNS when the use was not very widespread; Associations between SWB and SNS use became negative as SNS use became more widespread.

Literature Review on Cloud Computing: A Paradigm Combining Service-Oriented Architecture with Internet-Based Solutions

Cloud computing, a paradigm combining service-oriented architecture with Internet-based network solutions, has rapidly transformed the IT industry by offering on-demand access to shared resources. Key models of cloud services include Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). These models provide cost-effective, scalable, and flexible alternatives to traditional IT infrastructure, enabling enterprises to outsource hardware, software, and network services. Cloud systems such as Amazon EC2, Google App Engine, and IBM’s Blue Cloud illustrate these benefits, significantly lowering costs through pay-as-you-go pricing structures. However, data security and privacy have become critical concerns, as cloud users must entrust sensitive information to third-party providers. Ensuring data confidentiality and implementing fine-grained access control are essential to maintaining user trust and enabling compliance with legal and organizational regulations. The success of cloud computing in the future depends on overcoming these security challenges, allowing enterprises to fully embrace its potential

INTEGRATION OF TELEGRAM BOT AND UPTIME KUMA FOR WI-FI NETWORK MONITORING USING MIKROTIK

Wi-Fi network monitoring is a crucial aspect in ensuring the availability and security of widely used internet services. This research confirms the use of Telegram bots for notification integration with the Uptime-Kuma monitoring program and proxy devices for Wi-Fi network monitoring. The main router and network controller in this study were Mikrotik devices, while Uptime Kuma was used as a monitoring tool to track the performance and availability of the Wi-Fi network. When important events are discovered on the network, network administrators can receive quick notifications through integration with Telegram bots. In the context of Wi-Fi networks, the Security Policy Development Life Cycle (SPDLC) method is used to design relevant and effective security policies. It includes the stages of planning, implementation, monitoring, evaluation and regular updating of security policies to maintain optimal levels of security. The results show that the integration of Telegram bots with the Kuma Uptime monitoring tool can improve network availability. This allows quick reaction to Uptime and Downtime reports in network conditions, which record the percentage of time network services are available. Thus, administrators do not need to wait for complaints from users if the connection is suddenly lost, because changes in connection status will automatically send a notification to Telegram.

Online Incentive Protocol Design for Reposting Service in Online Social Networks

Reposting plays an essential role in boosting visibility on online social networks (OSNs). In this paper, we study the problem of designing “reposting service” in an OSN to incentivize “transactions” between requesters (users who seek to enhance visibility) and suppliers (users who are willing to repost if certain incentives are given), and maximize the welfare increase accumulated through a given time horizon. We formulate a mathematical model for reposting which captures various factors like click-through rates (CTRs), requesters’ valuations and suppliers’ costs. We formulate the problem of maximizing the welfare increase via judiciously assigning suppliers to requesters from two aspects: (a) “user-centric” and (b) “platform-centric”. The user-centric aspect deals with situations where requesters and suppliers collaborate and share valuations and costs. To address the challenge of unknown CTRs, we propose an online learning protocol and achieve a sub-linear regret. The platform-centric aspect corresponds to the scenario where users keep their valuations or costs private. To address the challenges of unknown CTRs, valuations and costs, we design an “explore-then-commit” online protocol. We prove the truthfulness of the proposed online protocol, and we also prove that this protocol has a sub-linear regret. Lastly, we conduct extensive experiments on six public datasets to evaluate the effectiveness and scalability of the proposed protocols.

Formal estimation of wireless network services for signal strength and electromagnetic wave association in an International Green University

The United Nations focuses on 17 urgent problems to call for action in all countries. Goal 7 of the 17 urgent problems is based on affordable and clean energy. Since 2017, National Taitung University (NTTU) has dedicated more time and effort to attain the wisdom, health, sustainability and aesthetics as an international green university. To accomplish this, we adhere and construct a safe radiofrequency and electromagnetic wave environment to achieve healthy and sustainable campus objectives. According to the UI GreenMetric World University Rankings, NTTU was ranked 74th in 2021, 67th in 2022 and 58th in 2023. In this study, we propose a formal estimation of wireless network services for classrooms or smart spaces to achieve the goal of safe radiofrequency and electromagnetic waves. Inside classrooms or smart spaces, better wireless signal strength and safer electromagnetic waves are achieved. Moreover, the proposed method can be used to determine the quantity of wireless access points for a given classroom or smart space to avoid unsafe electromagnetic waves and inappropriate energy consumption. The experimental results show that all benchmarks meet the wireless exposure limits of the WHO and physician safe technologies in the NTTU.

The prediction of urban growth boundary based on the ANN-CA model: An application to Guangzhou

Urban growth boundary (UGB) delineation is critical not only for China's urban planning policies, such as the "three control lines" of the Ministry of Natural Resources, but also for addressing global challenges related to sustainable urban development. This study contributes to the international discourse on urban growth management by developing an innovative artificial neural network-cellular automata (ANN-CA) model, tailored for cities experiencing rapid expansion. Using Guangzhou as a case study, we constructed an impact factor model that incorporates a wide range of factors, including urban spatial terrain, natural environment, current urban land classification, and industrial and economic conditions, along with the layout of modern service networks. The ANN-CA model was then employed to simulate urban spatial expansion and UGB delineation for the year 2030 under various constraints, such as strict protection zones and sustainable development scenarios. Our findings indicate that between 2020 and 2030, Nansha, Panyu, and Zengcheng districts will witness the most significant urban expansion, with respective area increases of 13.81 km2, 8.94 km2, and 5.8 km2, marking them as key growth areas. Furthermore, we propose that future urban expansion in Guangzhou should prioritize the southern and eastern regions, aligning with the city's strategic spatial objectives of "moving east, expanding south, connecting west, and optimizing north." By emphasizing ecological protection and intensive land use, this study provides a robust framework for urban planning in Guangzhou and offers insights applicable to rapidly urbanizing regions worldwide.

Qualitative assessment of the enablers and barriers of COVID-19 vaccination integration, into routine immunization Programme at primary health care facilities in Ekiti state, Nigeria

BackgroundThe introduction of the COVID-19 vaccine influenced discussions to explore integrating COVID-19 vaccination into routine immunization (RI) programs. Subsequently, the WHO Strategic Advisory Group Experts (SAGE) on immunization plausibly advised countries to leverage the COVID-19 vaccination rollout as a transformative opportunity to establish a resilient immunization system, through an integrated immunization system, resulting in strengthened primary healthcare services.ObjectiveThis study assessed the enablers and barriers to integrating COVID-19 vaccination into the routine immunization programme in Ekiti state, Nigeria.MethodsThis study utilized a qualitative research approach to obtain information from 40 participants selected purposively across the primary healthcare facilities, LGA, and state levels. A three-tier approach was employed to select the LGAs. At the same time, In-depth interviews were conducted to elicit relevant information on the assessment of enablers and barriers to integrating COVID-19 vaccination into routine immunization through an interview guide. All the audio interview files were transcribed into English Language, coded, and presented using a thematic approach.ResultsA total of 40 healthcare workers across Ekiti state were selected to participate in this study. Our study found the enablers of integrating COVID-19 into routine immunization to include demand generation and social mobilization, health education, health workers training, data validation, financing, and supervision. However, rumors, demand for incentives, Adverse Events Following Immunization (AEFI), manpower shortage, poor internet network services, and bad road networks were reported as barriers to integrating COVID-19 vaccination into routine immunization in Ekiti state.ConclusionWhile the enablers of integrating COVID-19 vaccination into routine immunization may outweigh its barriers, it is pertinent to know that the efforts towards integrating COVID–19 vaccination in the RI Program is a call to all stakeholders to ensure sustainability. The identified barriers in the study must be addressed to ensure a strengthened health system. Therefore, achieving a successful integration and uptake of vaccination/immunization is anchored on driving demand generation, social mobilization, health education, availability of healthcare workers, integrated supervision, and financing.

Territorial-based mental health in Brazil: a systematic review of the literature

The research aims to investigate the actions of territorial and community-based services focused on mental health, with the participation of the Psychosocial Care Network, focusing on the family health strategy team. The Systematic Review methodology is used. The analysis of the key characteristics listed in the RAPS and the synthesis of the data were carried out according to the availability of data from the 10 eligible studies, covering topics such as Psychosocial Care Center, referral and matrix support, medicalization, care strategies in the territory, public policies, stigma/prejudice, training and social reintegration. Through the analyzed studies, it could be concluded that this service network is still under development, pointing out the importance of territorial-based care, and the need for expansion and implementation of extra-hospital infrastructure closer to the daily lives of mental health users, to that does not overload the insufficient substitutive services of assistance that are characteristically community, inadequate assistance approaches to the point of lack of assistance in some cases.

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.