A quadri-dimensional approach for poor performance prioritization in mobile networks using Big Data

Abstract The Management of mobile networks has become so complex due to a huge number of devices, technologies and services involved. Network optimization and incidents management in mobile networks determine the level of the quality of service provided by the communication service providers (CSPs). Generally, the down time of a system and the time taken to repair [mean time to repair (MTTR)] has a direct impact on the revenue, especially on the operational expenditure (OPEX). A fast root cause analysis (RCA) mechanism is therefore crucial to improve the efficiency of the operational team within the CSPs. This paper proposes a quadri-dimensional approach (i.e. services, subscribers, handsets and cells) to build a service quality management (SQM) tree in a Big Data platform. This is meant to speed up the root cause analysis and prioritize the elements impacting the performance of the network. Two algorithms have been proposed; the first one, to normalize the performance indicators and the second one to build the SQM tree by aggregating the performance indicators for different dimensions to allow ranking and detection of tree paths with the worst performance. Additionally, the proposed approach will allow CSPs to detect the mobile network dimensions causing network issues in a faster way and protect their revenue while improving the quality of the service delivered

Quadri-dimensional approach for data analytics in mobile networks

The telecommunication market is growing at a very fast pace with the evolution of new technologies to support high speed throughput and the availability of a wide range of services and applications in the mobile networks. This has led to a need for communication service providers (CSPs) to shift their focus from network elements monitoring towards services monitoring and subscribers’ satisfaction by introducing the service quality management (SQM) and the customer experience management (CEM) that require fast responses to reduce the time to find and solve network problems, to ensure efficiency and proactive maintenance, to improve the quality of service (QoS) and the quality of experience (QoE) of the subscribers. While both the SQM and the CEM demand multiple information from different interfaces, managing multiple data sources adds an extra layer of complexity with the collection of data. While several studies and researches have been conducted for data analytics in mobile networks, most of them did not consider analytics based on the four dimensions involved in the mobile networks environment which are the subscriber, the handset, the service and the network element with multiple interface correlation. The main objective of this research was to develop mobile network analytics models applied to the 3G packet-switched domain by analysing data from the radio network with the Iub interface and the core network with the Gn interface to provide a fast root cause analysis (RCA) approach considering the four dimensions involved in the mobile networks. This was achieved by using the latest computer engineering advancements which are Big Data platforms and data mining techniques through machine learning algorithms.Electrical and Mining EngineeringM. Tech. (Electrical Engineering

Cyber Security and Critical Infrastructures 2nd Volume

The second volume of the book contains the manuscripts that were accepted for publication in the MDPI Special Topic "Cyber Security and Critical Infrastructure" after a rigorous peer-review process. Authors from academia, government and industry contributed their innovative solutions, consistent with the interdisciplinary nature of cybersecurity. The book contains 16 articles, including an editorial that explains the current challenges, innovative solutions and real-world experiences that include critical infrastructure and 15 original papers that present state-of-the-art innovative solutions to attacks on critical systems

Applications of Artificial Intelligence in Battling Against Covid-19: A Literature Review

© 2020 Elsevier Ltd. All rights reserved.Colloquially known as coronavirus, the Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2), that causes CoronaVirus Disease 2019 (COVID-19), has become a matter of grave concern for every country around the world. The rapid growth of the pandemic has wreaked havoc and prompted the need for immediate reactions to curb the effects. To manage the problems, many research in a variety of area of science have started studying the issue. Artificial Intelligence is among the area of science that has found great applications in tackling the problem in many aspects. Here, we perform an overview on the applications of AI in a variety of fields including diagnosis of the disease via different types of tests and symptoms, monitoring patients, identifying severity of a patient, processing covid-19 related imaging tests, epidemiology, pharmaceutical studies, etc. The aim of this paper is to perform a comprehensive survey on the applications of AI in battling against the difficulties the outbreak has caused. Thus we cover every way that AI approaches have been employed and to cover all the research until the writing of this paper. We try organize the works in a way that overall picture is comprehensible. Such a picture, although full of details, is very helpful in understand where AI sits in current pandemonium. We also tried to conclude the paper with ideas on how the problems can be tackled in a better way and provide some suggestions for future works.Peer reviewe

Business Intelligence and Analytics in Small and Medium-Sized Enterprises

This thesis presents a study of Business Intelligence and Analytics (BI&A) adoption in small and medium-sized enterprises (SMEs). Although the importance of BI&A is widely accepted, empirical research shows SMEs still lag in BI&A proliferation. Thus, it is crucial to understand the phenomenon of BI&A adoption in SMEs. This thesis will investigate and explore BI&A adoption in SMEs, addressing the main research question: How can we understand the phenomenon of BI&A adoption in SMEs? The adoption term in this thesis refers to all the IS adoption stages, including investment, implementation, utilization, and value creation. This research uses a combination of a literature review, a qualitive exploratory approach, and a ranking-type Delphi study with a grounded Delphi approach. The empirical part includes interviews with 38 experts and Delphi surveys with 39 experts from various Norwegian industries. The research strategy investigates the factors influencing BI&A adoption in SMEs. The study examined the investment, implementation, utilization, and value creation of BI&A technologies in SMEs. A thematic analysis was adopted to collate the qualitative expert interview data and search for potential themes. The Delphi survey findings were further examined using the grounded Delphi method. To better understand the study’s findings, three theoretical perspectives were applied: resource-based view theory, dynamic capabilities, and IS value process models. The thesis’ research findings are presented in five articles published in international conference proceedings and journals. This thesis summary will coherently integrate and discuss these results.publishedVersio

Game Theory for Multi-Access Edge Computing:Survey, Use Cases, and Future Trends

Game theory (GT) has been used with significant success to formulate, and either design or optimize, the operation of many representative communications and networking scenarios. The games in these scenarios involve, as usual, diverse players with conflicting goals. This paper primarily surveys the literature that has applied theoretical games to wireless networks, emphasizing use cases of upcoming multiaccess edge computing (MEC). MEC is relatively new and offers cloud services at the network periphery, aiming to reduce service latency backhaul load, and enhance relevant operational aspects such as quality of experience or security. Our presentation of GT is focused on the major challenges imposed by MEC services over the wireless resources. The survey is divided into classical and evolutionary games. Then, our discussion proceeds to more specific aspects which have a considerable impact on the game's usefulness, namely, rational versus evolving strategies, cooperation among players, available game information, the way the game is played (single turn, repeated), the game's model evaluation, and how the model results can be applied for both optimizing resource-constrained resources and balancing diverse tradeoffs in real edge networking scenarios. Finally, we reflect on lessons learned, highlighting future trends and research directions for applying theoretical model games in upcoming MEC services, considering both network design issues and usage scenarios

Neuroimaging of human motor control in real world scenarios: from lab to urban environment

The main goal of this research programme was to explore the neurophysiological correlates of human motor control in real-world scenarios and define mechanism-specific markers that could eventually be employed as targets of novel neurorehabilitation practice. As a result of recent developments in mobile technologies it is now possible to observe subjects' behaviour and monitor neurophysiological activity whilst they perform natural activities freely. Investigations in real-world scenarios would shed new light on mechanisms of human motor control previously not observed in laboratory settings and how they could be exploited to improve rehabilitative interventions for the neurologically impaired. This research programme was focussed on identifying cortical mechanisms involved in both upper- (i.e. reaching) and lower-limb (i.e. locomotion) motor control. Complementary results were obtained by the simultaneous recordings of kinematic, electromyographic and electrocorticographic signals. To study motor control of the upper-limb, a lab­based setup was developed, and the reaching movement of healthy young individuals was observed in both stable and unstable (i.e. external perturbation) situations. Robot-mediated force-field adaptation has the potential to be employed in rehabilitation practice to promote new skills learning and motor recovery. The muscular (i.e. intermuscular couplings) and neural (i.e. spontaneous oscillations and cortico­muscular couplings) indicators of the undergoing adaptation process were all symbolic of adaptive strategies employed during early stages of adaptation. The medial frontal, premotor and supplementary motor regions appeared to be the principal cortical regions promoting adaptive control and force modulation. To study locomotion control, a mobile setup was developed and daily life human activities (i.e. walking while conversing, walking while texting with a smartphone) were investigated outside the lab. Walking in hazardous environments or when simultaneously performing a secondary task has been demonstrated to be challenging for the neurologically impaired. Healthy young adults showed a reduced motor performance when walking in multitasking conditions, during which whole-brain and task-specific neural correlates were observed. Interestingly, the activity of the left posterior parietal cortex was predictive of the level of gait stability across individuals, suggesting a crucial role of this area in gait control and determination of subject specific motor capabilities. In summary, this research programme provided evidence on different cortical mechanisms operative during two specific scenarios for "real­world" motor behaviour in and outside the laboratory-setting in healthy subjects. The results suggested that identification of neuro-muscular indicators of specific motor control mechanisms could be exploited in future "real-world" rehabilitative practice

Strategies Used by IT Project Managers to Integrate ICTs in the Eastern Caribbean

Current practices used to guide information and communication technology (ICT) projects in the Caribbean and developing countries lead to high project failure rates. Project managers must adopt new innovative approaches for transformation towards a 21st-century information society and sustainable digital economies. Grounded in the technology acceptance model (TAM), the purpose of this qualitative multiple-case study was to explore strategies information technology (IT) project managers use to implement IT frameworks designed to guide Caribbean ICT integration. Data were collected from face to face interviews and company documents and analyzed using coding, thematic analysis, and methodological triangulation. The participants were 12 IT project managers in 2 Eastern Caribbean countries. Thematic analysis was used to analyze, report patterns, and to identify emerging themes in the data. The themes that emerged were (1) management of organizational structure, (2) implementing a government wide area network to facilitate the innovations of an ICT-enabled services industry, business, and education, and (3) ICT integration budget, buy-in, and challenges. A key recommendation is that IT project managers develop an IT implementation framework that aligns with an IT project management methodology by incorporating project management body of knowledge remedial measures to achieve defined project objectives. The implications for positive social change include the potential to share knowledge and dramatically lower barriers to starting a business, creating e-commerce, innovation, and online e-learning opportunities for empowering citizens and improving their socio-economic position