Network Service Providers Research Articles

Agile roadmap for application‐driven Multi‐UAV networks: The case of COVID‐19

Drones, also known as Unmanned Aerial Vehicles (UAVs), are about to bring drastic transformations to our world and daily lives. News thinking and efficient deployment are required to boost the adoption of UAV‐augmented commercial/civil applications. Yet, network service providers are still facing several design challenges of UAV‐assisted application, due to lack of a roadmap allowing to meet the target service level agreement requirements. In this paper, we propose a complete framework for the UAV as a service paradigm, integrating all the actors/stakeholders contributing to the UAV‐augmented service, and draw their interactions using data/service/money flows. Next, we instantiate our framework on the COVID‐19‐like pandemics, and discuss how to use it force social distancing, spray disinfectants, broadcast messages, deliver medical supplies and enhance surveillance. Computer simulation provide insights on how to set the multi‐UAV network to combat COVID‐19.

Business transformation from connectivity to digital: case study “PT. MNO Indonesia”

The telecommunications industry plays a role in meeting the needs of digital connectivity services to the community, especially in line with the community's need for internet connections which is increasing rapidly. As one of the telecommunications service operators in Indonesia, "PT. MNO Indonesia" must meet this need to get maximum profit and the best service to the customers with the right business strategy. However, the current connectivity business model is still the mainstay, with revenue levels that tend to stagnate and even experience a decline. The provision of network services and investment in infrastructure development are still the main concerns, so a change in business strategy is needed. This study proposes several recommendations for business strategies to increase revenue based on reviewing and analyzing financial data and statistics for Indonesian and international telecommunications businesses. In this study, financial report data and digital sector statistical data were analyzed and divided into four aspects: traffic, finance, network development, and digital service with the min-max method, standard deviation, and average. From the analysis conducted in this research, "PT. MNO Indonesia" needs to transform its business into digital business model.

Internet Service Providers and Intermediary Liabilities

Just as the provision of goods in the physical world necessitates the involvement of numerous entities that act as intermediaries, the internet supply chain involves several online intermediaries that provide the infrastructure via which customers can exchange information. These can include but are not limited to, telecom and internet service providers, web hosting, Internet search engines, social networking, instant messaging, and so on. It is now impossible to consider life without the internet. The internet, which connects billions of people globally, is a key pillar of the modern information society for creating and trading material. The way we connect and share information has changed, with many negative consequences, and it's not every day that intermediaries are neutral. The judicial process has continued to shape and solidify legislation relating to intermediaries over the years. In India section 79, of the Information technology Act, 2000 governs intermediaries (service providers), under this law no person providing any service as a network service provider shall be liable, rules or regulations made thereunder for any third-party information or data made available by him if he proves that the offense or contravention was committed without his knowledge or that he had exercised all due diligence to prevent the commission of such offense or contravention(the information technology act, 2000, 2000). In 2017, UNESCO published the book “Fostering Freedom Online: The Role of Internet Intermediaries”. It aimed to shed light on how internet intermediaries both foster and restrict freedom of expression across a range of jurisdictions, circumstances, technologies, and business models. (MacKinnon Rebecca et al., 2015). In Ghana, the (Data Protection Act, 2012) was borne by the constitution to protect the privacy of the individual and personal data by regulating the processing of personal information, providing the process to obtain, hold, use or disclose personal information, and for related matters. Serving as a check to these internet intermediaries. In the (electronic transactions act, 2008 (ACT 772)), section 90 is dedicated to the Liability of service providers and intermediaries. “Liability” means that intermediaries must prevent the occurrence of unlawful or harmful activity by users of their services. Failure to do so may result in legal orders compelling the intermediary to act or expose the intermediary to civil or criminal legal action (APC). Keywords: intermediaries, Internet Service Providers, liable, jurisdictions, internet BOOK Chapter ǀ Research Nexus in IT, Law, Cyber Security & Forensics. Open Access. Distributed Free Citation: Anna Asunka (2022): Internet Service Providers and Intermediary Liabilities Book Chapter Series on Research Nexus in IT, Law, Cyber Security & Forensics. Pp 113-118 www.isteams.net/ITlawbookchapter2022. dx.doi.org/10.22624/AIMS/CRP-BK3-P19

Toward consumer-centric energy network regulation: Australia's experience

Understanding the objective of economic regulation as mimicking the process of competition, rather than the outcome of theoretical competitive markets, recognises the need for regulated energy transmission and distribution network service providers to respond to consumer preferences. The regulator, network service providers, and consumer advocates in Australia have conducted experiments on ways consumer preferences can shape regulatory proposals. These experiments demonstrate that agreements about regulatory proposals between the network service provider and a counterparty representing the interests of consumers are effective in ensuring that the proposal reflects consumer preferences. The paper demonstrates that in this process, consumers can also design output-oriented incentive schemes proposed by performance-based regulation.

Research on the restriction of "new" pocket crime under the background of the Internet- from the Amendment of Criminal Law (IX)

With the release of the criminal law amendment (9), refusing to fulfill the obligation of network security crime and helping information network crime, as two important new charges, have improved the criminal law because the responsibility of "network service provider" was introduced for the first time in the field of criminal responsibility. However, in the implementation of relevant charges, due to its limitations in legislation and the similar problems in judicial practice, the scope of related crimes is improperly expanded forming the so-called "new pocket crime". Based on this situation and the legislation in Germany, combined with our own judicial practice, the systematization of related charges should be promoted in network service providers on the legislative level of special legislation. In the judicial level, specification of "knowing" standard and expanding the application of interpretation should be adopted. These two ways can realize the reduction of pocket crime and produce positive effect on the disadvantages of the rule of law construction in China. This paper proposes the method to solve the restriction of pocket crime from two aspects. At the legislative level there are three initiatives. Firstly, special legislation network service providers should be implemented. Secondly, the criminal law charges should be set systematically based on the typing of network service providers. Lastly, the criminal responsibility should be apportioned hierarchically based on the typing of network service providers. As for the judicial level, the identification standard of "knowing" should be clarified in judicial practice. In the process of applying the extended interpretation, it is important to adhere to the same kind of interpretation. In addition, the judicial authorities should organically combine the crackdown on crime with the development of the Internet in the process of cracking down on cybercrimes.

Issues on Sentencing of Network Service Providers in Cybercrime

With the continuous progress of science and technology, the problem of conviction and sentencing of network service providers in the field of cybercrime has become increasingly prominent. In judicial practice, there are often different judgments in the same case, ambiguous sentences in the judgment, and ambiguous qualitative nature of the subject of the crime, which shows that the path of conviction and sentencing of network service providers needs to be improved. Through analyzing the current laws and regulations concerning network service providers in China, the lack of classification of network service providers and the application of relevant sentencing laws are the main obstacles to the conviction and sentencing of network service providers. It is suggested to solve the practical obstacles of conviction and sentencing of network service providers by classifying network service providers, limiting the crime of helping information network crimes, strictly controlling the information network security management obligations of network service providers, and perfecting the relevant legal provisions on the obligations of network service providers.

Link Stability aware Reinforcement Learning based Network Path Planning

Along with the growing popularity of 5G technology, providing flexible and personalized network services suitable for requirements of customers has also become a lucrative venture and business key for network service providers. Therefore, dynamic network provisioning is needed to help network service providers. Moreover, increasing user demand for network services meets specific requirements of users, including location, usage duration, and QoS. In this paper, a routing algorithm, which makes routing decisions using Reinforcement Learning (RL) based on the information about link stability, is proposed and called Link Stability aware Reinforcement Learning (LSRL) routing. To evaluate this algorithm, several mininet-based experiments with various network settings were conducted. As a result, it was observed that the proposed method accepts more requests through the evaluation than the past link annotated shorted path algorithm and it was demonstrated that the proposed approach is an appealing solution for dynamic network provisioning routing.

Linking Organisational Performance and Corporate Social Responsibility

Purpose: Business organisations are at the core of sustainable development, and they can be no longer isolated from social concerns and issues where they operate and exist. While many firms have applied CSR practices successfully and made it fruitful for both business and society, many others are still struggling as no one strategy can usually fit all and CSR initiatives does not promise the same payoffs among different companies and sectors. In this context, the study aims to examine the link between organisational performance and CSR and provide a milestone that would help business organisations to successfully apply CSR initiatives. Design/methodology/approach: Drawing upon field research, 378 questionnaires were collected from various managerial and non-managerial employees of the mobile network operators in Egypt to examine the research hypotheses. Findings: Extending the relation between organisational performance and CSR, this paper demonstrates the heterogeneous ways in which organisational performance can be a key determinant for being engaged in successful CSR initiatives. It argued how organisational performanceــmaterialised in integrating business-related social issues into the organisational strategy, financial performance, CSR capability responsiveness, and social performanceــ can help business organisation establish a win-win situation and create a business-society shared value. Research limitations/implications: The research focuses on four business organisations operating as mobile network service providers in Egypt. Practical implications: The research findings have important implications, more specifically, for firms willing to engage for successful CSR practices, and how social issues and concerns can be translated into business opportunities to motivate business organisations to address them. Social implications: CSR is still controversial to a great extent; especially from an empirical perspective in less developed and developing countries like Egypt, where environmental and social considerations are limited; regarded as a task to be done by a few (Gov., NGOs, NPO, etc.); and where CSR activities are carried through philanthropic perspective. This research implies the possibility to look at social issues and concerns as an opportunity for strategic CSR that create a shared value for business and society and formulate a win-win situation. Originality/value: This paper’s contribution is threefold. First, theoretically, the literature on organisational performance and CSR is extended by considering how they can complement one another. The nuanced focus on this relation provides a “zoom in” that organisational performance is a key success factor while considering CSR. Second, the literature on shared value is deepened by identifying a diverse range of imbricating logics that can be used to discern a more nuanced connection between business and society. Last, these ideas are grounded in a relevant field study context –that of CSR activities in Egypt–, providing more knowledge, over time, of specific actors’ translations of CSR policies into business organisations’ strategies and practices.

Open Communication About Reproductive Health Is Associated With Comprehensive HIV Knowledge and a Non-stigmatising Attitude Among Indonesian Youth: A Cross-sectional Study.

ObjectivesHuman immunodeficiency virus (HIV) prevention among youth seems under-prioritised compared to other key populations. HIV knowledge and stigma are important parts of HIV prevention. To inform HIV prevention among youths, this study quantitatively analysed the associations between open communication regarding sexuality and sexual health, comprehensive HIV knowledge, and non-stigmatising attitudes in Indonesia.MethodsThis study used data from the Indonesian Demographic and Health Survey (IDHS) 2017. The analysis included unmarried men and women aged 15–25 years old. Comprehensive HIV knowledge and a stigmatising attitude were defined according to the IDHS 2017. Open communication about sexuality and sexual health was defined as the number of people with whom participants could openly discuss these topics in their direct network of friends, family, and service providers, with a scale ranging from 0 to a maximum of 7. Primary analysis used binomial logistic regression with weighting adjustments.ResultsThe final analysis included 22 864 respondents. Twenty-two percent of youth had no one in their direct network with whom to openly discuss sexual matters, only 14.1% had comprehensive HIV knowledge, and 85.9% showed stigmatising attitudes. Youth mostly discussed sex with their friends (55.2%), and were less likely to discuss it with family members, showing a predominant pattern of peer-to-peer communication. Multivariate analysis showed that having a larger network for communication about sexuality and sexual health was associated with more HIV knowledge and less stigmatising attitudes.ConclusionsHaving more opportunities for open sex communication in one’s direct social network is associated with more HIV knowledge and less stigmatising attitudes.

A Layered Approach to Threat Modeling for 5G-Based Systems

The rise of 5G networks promises a wide range of cutting-edge services with the aim of achieving high performance and reliability. Cutting-edge applications facilitated by 5G architecture make use of various enabling technologies, which introduce various new and emerging security threats and attacks. Threat modeling is a proactive approach to identify security requirements, as well as potential threats and vulnerabilities, and prioritize remediation methods. In addition, 5G networks are complex and are usually divided into separate layers to foster the understanding and management of different functionalities. The open nature of 5G envisages that multiple vendors and service providers might be working on network deployment and service provisioning; it is therefore necessary to address and categorize the threats at each layer distinctly. This paper presents a threat model for 5G-based systems. It leverages the layered 5G architecture, identifying threat categories and mapping these to corresponding layers. It also analyzes enabling technologies affected by identified threats along with threat actors, entry points, and the impact of threat categories. Through the development of this threat model, we envisage facilitating further research into specific threats and mechanisms to protect against them.

Size and attributes of probation officers’ service provider networks: connecting individuals with mental illnesses to community-based supports

This exploratory study examines inter-organizational communication patterns and information sharing between probation officers and service providers when coordinating services for people with mental illnesses on probation. Thirty-four probation officers from one rural (n = 12) and one urban (n = 22) county completed a researcher-administered questionnaire pertaining to the size of probation officers’ service provider networks and the frequency and nature of contacts with those networks. Egocentric network analysis and bivariate inferential statistics were used to examine direct relational ties between each officer and the service providers within their communities. Probation officers in both counties reported high frequency of contact with service providers and indicated that service providers and officers were more likely to share information if reciprocated by their dyad counterpart. Probation agencies may consider enhancing probation officers’ service provider networks and fostering reciprocal and mutually-beneficial relationships to ensure timely access to services for adults with mental illnesses who are on probation.

A reinforcement learning-based approach for availability-aware service function chain placement in large-scale networks

By decoupling network service functions from custom-built hardware, network function virtualization is transforming network service provisioning, making large scale telecommunications more flexible, scalable, and agile. Service function chaining often requires network traffic to flow through a specific sequence of virtual network functions (VNFs) to comply with network policies. The dependencies between VNFs in such a chain can significantly and negatively impact the availability of an end-to-end service function chain (SFC) when one or more VNFs malfunction or fail. While redundancy strategies can be used to reduce the impact of such failure, this can increase operational expenditure and energy consumption. In this paper, we propose a solution for SFC placement based on reinforcement learning (RL) taking into account SFC availability, operational costs, and energy consumption. The Cand-RL algorithm uses RL based on proximal policy optimization (PPO) to select the suitable candidate node and define the redundancy strategy to meet availability requirements. We compare Cand-RL against two greedy algorithms in a variety of simulated scenarios. The results show that the Cand-RL outperforms the greedy algorithms, achieving a higher acceptance rate and a good balance between availability, placement cost, and energy consumption.

Analysis of Network Slicing for Management of 5G Networks Using Machine Learning Techniques

Consumer expectations and demands for quality of service (QoS) from network service providers have risen as a result of the proliferation of devices, applications, and services. An exceptional study is being conducted by network design and optimization experts. But despite this, the constantly changing network environment continues to provide new issues that today’s networks must be dealt with effectively. Increased capacity and coverage are achieved by joining existing networks. Mobility management, according to the researchers, is now being investigated in order to make the previous paradigm more flexible, user-centered, and service-centric. Additionally, 5G networks provide higher availability, extremely high capacity, increased stability, and improved connection, in addition to quicker speeds and less latency. In addition to being able to fulfil stringent application requirements, the network infrastructure must be more dynamic and adaptive than ever before. Network slicing may be able to meet the present stringent application requirements for network design, if done correctly. The current study makes use of sophisticated fuzzy logic to create algorithms for mobility and traffic management that are as flexible as possible while yet maintaining high performance. Ultimately, the purpose of this research is to improve the quality of service provided by current mobility management systems while also optimizing the use of available network resources. Building SDN (Software-Defined Networking) and NFV (Network Function Virtualization) technologies is essential. Network slicing is an architectural framework for 5G networks that is intended to accommodate a variety of different networks. In order to fully meet the needs of various use cases on the network, network slicing is becoming more important due to the increasing demand for data rates, bandwidth capacity, and low latency.

Routing and spectrum assignment employing long short-term memory technique for elastic optical networks

With the prevalence of some high bandwidth-demanding applications, such as cloud computing, traditional wavelength-division-multiplexing passive optical networks have difficulties in satisfying such growing bandwidth demands due to its limited allocation-flexibility and utilization-efficiency. Therefore, elastic optical networks (EONs). In order to realize the flexibility in EONs, sophisticated routing and spectrum allocation (RSA) algorithms areone of the keyenabling technologies. However, most of the previous RSA algorithms were proposed with invariant routing and spectrum allocation strategies, which ignored considering the time-varying characteristics of EONs due to the variable network architecture and service provisioning. And such time-varying characteristics can deteriorate the spectrum fragmentation and the service blocking performances of EONs, which stimulates the application of various machine-learning technologies in EONs. In this paper, a long short-term memory based routing and spectrum assignment (LSTM-RSA) algorithm is proposed for EONs. By employing the long short-term memory technique to sense the complex status of EONs (e.g. spectral usage on the selected paths), the proposed LSTM-RSA algorithm gradually learns successful strategies through accumulating operation experience in the process of interaction and obtains higher returns through enhanced operation, which helps improve the spectrum fragmentation and the service blocking performances in EONs. Simulation results show that the spectrum fragmentation rate and the blocking rate of the proposed LSTM-RSA algorithm are reduced by about 6% and 8.9%, respectively, when compared to the traditional shortest-path-routing first-fitting RSA algorithm.

On Efficient Service Function Chaining in Hybrid Software Defined Networks

To minimize operating expenses (OPEX) and enhance flexibility for network service provisioning, network function virtualization (NFV) is used to chain an ordered sequence of virtualized network functions (VNFs), also known as service function chain (SFC), which can be placed on commodity servers. As a highly complementary to NFV, software-defined networking (SDN) can offer an agile way of VNF orchestration with the capability of fine-granularity network control over flows. However, one-step migration to SDN is impossible in ISP networks. Thus, in this paper we resort to hybrid SDN to implement SFC provisioning. By jointly optimizing SDN deployment that largely determines capital expenditures (CAPEX) and VNF placement that decides OPEX, we manage to make a tradeoff between CAPEX and OPEX, and to find out an appropriate SDN deployment rate for network operator. We first formulate the problem as an integer linear programming (ILP) model <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\boldsymbol {P}$ </tex-math></inline-formula> , then, reformulate it with column generation technique and decomposition theory to develop a distributed approximation algorithm CGPD which obtains a tight upper bound of optimal solution to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\boldsymbol {P}$ </tex-math></inline-formula> . In order to better decrease CAPEX, a dynamic programming-based heuristic EOES giving importance to effective resource sharing is further designed based on a hidden Markov model. The simulation results indicate that, the difference between <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\boldsymbol {P}$ </tex-math></inline-formula> and CGPD is marginal. CGPD outperforms EOES in terms of total cost, average delay and bandwidth utilization, and EOES on the other hand demands 20% SDN deployment rate which is half of that of CGPD.

Research on Digital Information Privacy Behavior of Social Network Users Based on Evolutionary Game

This article takes social network services as the research object and mainly conducts two aspects of research: first, based on previous research, combining the behavior characteristics of users in the social network environment related to digital information privacy, the digital information privacy of users pays attention to the influential factors of users’ digital information privacy information disclosure behavior, summarize and refine them, establish theoretical research models, and then use structural equation modelling to empirically analyze the significance of each influence path; then, based on the first part of the empirical research, the evolutionary game theory was used to analyze the interests of digital information privacy between social network users and service providers. This paper also studies the evolution of the willingness of each parameter to provide digital information to users under variable expected return conditions and uses MATLAB to analyze its evolutionary trends. It is found that the regulatory intensity coefficient, information leakage loss, and information sensitivity are both for users and websites. It has an important impact, and the loss of information leakage and information sensitivity can affect the evolution direction of users’ willingness to provide digital information and change the speed of website evolution, and the regulatory intensity coefficient is the opposite.

Clinical profile of children and adolescents diagnosed with anorexia nervosa in Indian context.

This study was conducted to assess the trends observed in the prevalence pattern, clinical presentation, psychosocial profile and treatment profile of anorexia nervosa in children and adolescents who presented to a tertiary care child and adolescent psychiatry centre over a period of ten years. Case records of children and adolescents diagnosed with anorexia nervosa at the department of child and adolescent psychiatry from 1st April 2009-31st March 2019 were obtained from the medical records department of the National Institute of Mental Health and Neurosciences (NIMHANS). Standardized data abstraction forms were developed and used for the purpose of this study. Pseudo-anonymization was done to ensure confidentiality and clinical characteristics of the sample were studied using frequency analysis and central tendencies. Prevalence of anorexia nervosa in a clinic-based population is estimated to be 0.07% over the 10-year period. The mean age at presentation was 13.96 years (SD-2.3) and the male to female ratio was 1:12. The majority (80.8%) were admitted and only one patient (3.8%) received treatment on an outpatient basis. Two or more psychosocial stressors were associated with the onset of illness in 88.5% (n=23) of the patients and dysfunctional family dynamics was noted to be a significant issue in the majority of cases. All the patients received pharmacotherapy and CBT-based individual therapy. The overall outcome was favourable based on the CGI-I scores. Prevalence of anorexia nervosa in the clinic-based setting is rising in the Indian context. Sample characteristics are similar to those seen in the west. There is a huge demand-supply gap that calls for creating a service provider network to ensure community-based care.

RAFALE: Rethinking the provisioning of virtuAl network services using a Fast and scAlable machine LEarning approach

RAFALE: Rethinking the provisioning of virtuAl network services using a Fast and scAlable machine LEarning approach

Quasi Real-Time Intermodulation Interference Method: Analysis and Performance

Establishing interference-free wireless networks has become essential requirement with theadvent of 5G networks as wireless carriers becoming eager to start transmitting high volume of voice anddata to meet enterprise demands and consumers for dispersed information. Indeed, reduction of interferencelevel now emerges as one of the most viable solutions for the service provider networks, as 5G networksuse is increasingly on the rise. Therefore, a comprehensive interference solution is needed to enable serviceproviders (e.g., cellular, PCS, Wi-Fi and Broadband, and LTE wireless LAN/WAN services) to identify andresolve network interference quickly and reliably. However, currently existing methods and tools, used toconduct interference detection and analysis lack the necessary performance required in the RF engineeringand spectrum optimization fields, and hence, fast, and reliable networks. This paper presents a new highperformancemethod for detecting and mitigating intermodulation interference in various wireless networks.Clearly, reducing the level of interference in wireless communication contributes directly to having animproved and reliable signal to noise ratio (C/I). We will discuss the complexity of the intermodulationinterference problem. We will further compare the performance of the new approach with different existinginterference detection methods. We will show that the presented method intermodulation complexity isreduced to a near linear one, compared to the current non-linear methods.

Machine-Learning-Based Uplink Throughput Prediction from Physical Layer Measurements

The uplink (UL) throughput prediction is indispensable for a sustainable and reliable cellular network due to the enormous amounts of mobile data used by interconnecting devices, cloud services, and social media. Therefore, network service providers implement highly complex mobile network systems with a large number of parameters and feature add-ons. In addition to the increased complexity, old-fashioned methods have become insufficient for network management, requiring an autonomous calibration to minimize utilization of the system parameter and the processing time. Many machine learning algorithms utilize the Long-Term Evolution (LTE) parameters for channel throughput prediction, mainly in favor of downlink (DL). However, these algorithms have not achieved the desired results because UL traffic prediction has become more critical due to the channel asymmetry in favor of DL throughput closing rapidly. The environment (urban, suburban, rural areas) affect should also be taken into account to improve the accuracy of the machine learning algorithm. Thus, in this research, we propose a machine learning-based UL data rate prediction solution by comparing several machine learning algorithms for three locations (Houston, Texas, Melbourne, Florida, and Batman, Turkey) and determine the best accuracy among all. We first performed an extensive LTE data collection in proposed locations and determined the LTE lower layer parameters correlated with UL throughput. The selected LTE parameters, which are highly correlated with UL throughput (RSRP, RSRQ, and SNR), are trained in five different learning algorithms for estimating UL data rates. The results show that decision tree and k-nearest neighbor algorithms outperform the other algorithms at throughput estimation. The prediction accuracy with the R2 determination coefficient of 92%, 85%, and 69% is obtained from Melbourne, Florida, Batman, Turkey, and Houston, Texas, respectively.