Mobile Edge Computing to Assist the Online Ideological and Political Education

With the rapid development of mobile Internet technology, mobile network data traffic presents an explosive growth trend. Especially, the proportion of mobile video business has become a large proportion in mobile Internet business. Mobile video business is considered as a typical business in the 5G network, such as in online education. The growth of video traffic poses a great challenge to mobile network. In order to provide users with better quality of experience (QoE), it requires mobile network to provide higher data transmission rate and lower network delay. This paper adopts a combined optimization to minimize total cost and maximize QoE simultaneously. The optimization problem is solved by ant colony algorithm. The effectiveness is verified on experiment.

A Survey on Client Throughput Prediction Algorithms in Wired and Wireless Networks

Network communication has become a part of everyday life, and the interconnection among devices and people will increase even more in the future. Nevertheless, prediction of Quality of Service parameters, particularly throughput, is quite a challenging task. In this survey, we provide an extensive insight into the literature on Transmission Control Protocol throughput prediction. The goal is to provide an overview of the used techniques and to elaborate on open aspects and white spots in this area. We assessed more than 35 approaches spanning from equation-based over various time smoothing to modern learning and location smoothing methods. In addition, different error functions for the evaluation of the approaches as well as publicly available recording tools and datasets are discussed. To conclude, we point out open challenges especially looking in the area of moving mobile network clients. The use of throughput prediction not only enables a more efficient use of the available bandwidth, the techniques shown in this work also result in more robust and stable communication.

Principle of 6G Wireless Networks: Vision, Challenges and Applications

The 5G mobile communication has now become commercially available. Furthermore, research across the globe has begun to improve the system beyond 5G and it is anticipated that 6G will deliver higher quality services and energy efficiency than 5G. The mobile network architecture needs to be redesigned to meet the requirements of the future. In the wake of the commercial rollout of the 5G model, both users and developers have realized the limitations of the system when compared to the system's original premise of being able to support the vast applications of connected devices. The article discusses the related technologies that can contribute to a robust and seamless network service. An upheaval in the use of vast mobile applications, especially those powered and managed by AI, has opened the doors to discussion on how mobile communication will evolve in the future. 6G is expected to go beyond being merely a mobile internet service provider to support the omnipresent AI services that will form the rock bed of end-to-end connected network-based devices. Moreover, the technologies that support 6G services and comprehensive research that enables this level of technical prowess have also been identified here. This paper presents a collective wide-angle vision that will facilitate a better understanding of the features of the 6G system.

A Multifractal Analysis and Machine Learning Based Intrusion Detection System with an Application in a UAS/RADAR System

The rapid development of Internet of Things (IoT) technology, together with mobile network technology, has created a never-before-seen world of interconnection, evoking research on how to make it vaster, faster, and safer. To support the ongoing fight against the malicious misuse of networks, in this paper we propose a novel algorithm called AMDES (unmanned aerial system multifractal analysis intrusion detection system) for spoofing attack detection. This novel algorithm is based on both wavelet leader multifractal analysis (WLM) and machine learning (ML) principles. In earlier research on unmanned aerial systems (UAS), intrusion detection systems (IDS) based on multifractal (MF) spectral analysis have been used to provide accurate MF spectrum estimations of network traffic. Such an estimation is then used to detect and characterize flooding anomalies that can be observed in an unmanned aerial vehicle (UAV) network. However, the previous contributions have lacked the consideration of other types of network intrusions commonly observed in UAS networks, such as the man in the middle attack (MITM). In this work, this promising methodology has been accommodated to detect a spoofing attack within a UAS. This methodology highlights a robust approach in terms of false positive performance in detecting intrusions in a UAS location reporting system.

Measuring and Assessing Performance of Mobile Broadband Networks and Future 5G Trends

Mobile broadband (MBB) is one of the critical goals in fifth-generation (5G) networks due to rising data demand. MBB provides very high-speed internet access with seamless connections. Existing MBB, including third-generation (3G) and fourth-generation (4G) networks, also requires monitoring to ensure good network performance. Thus, performing analysis of existing MBB assists mobile network operators (MNOs) in further improving their MBB networks’ capabilities to meet user satisfaction. In this paper, we analyzed and evaluated the multidimensional performance of existing MBB in Oman. Drive test measurements were carried out in four urban and suburban cities: Muscat, Ibra, Sur and Bahla. This study aimed to analyze and understand the MBB performance, but it did not benchmark the performance of MNOs. The data measurements were collected through drive tests from two MNOs supporting 3G and 4G technologies: Omantel and Ooredoo. Several performance metrics were measured during the drive tests, such as signal quality, throughput (downlink and unlink), ping and handover. The measurement results demonstrate that 4G technologies were the dominant networks in most of the tested cities during the drive test. The average downlink and uplink data rates were 18 Mbps and 13 Mbps, respectively, whereas the average ping and pong loss were 53 ms and 0.9, respectively, for all MNOs.

Design and Evaluation of Remote Driving Architecture on 4G and 5G Mobile Networks

Despite the progress in the development of automated vehicles in the last decade, reaching the level of reliability required at large-scale deployment at an economical price and combined with safety requirements is still a long road ahead. In certain use cases, such as automated shuttles and taxis, where there is no longer even a steering wheel and pedals required, remote driving could be implemented to bridge this gap; a remote operator can take control of the vehicle in situations where it is too difficult for an automated system to determine the next actions. In logistics, it could even be implemented to solve already more pressing issues such as shortage of truck drivers, by providing more flexible working conditions and less standstill time of the truck. An important aspect of remote driving is the connection between the remote station and the vehicle. With the current roll-out of 5G mobile technology in many countries throughout the world, the implementation of remote driving comes closer to large-scale deployment. 5G could be a potential game-changer in the deployment of this technology. In this work, we examine the remote driving application and network-level performance of remote driving on a recently deployed sub-6-GHz commercial 5G stand-alone (SA) mobile network. It evaluates the influence of the 5G architecture, such as mobile edge computing (MEC) integration, local breakout, and latency on the application performance of remote driving. We describe the design, development (based on Hardware-in-the-Loop simulations), and performance evaluation of a remote driving solution, tested on both 5G and 4G mobile SA networks using two different vehicles and two different remote stations. Two test cases have been defined to evaluate the application and network performance and are evaluated based on position accuracy, relative reaction times, and distance perception. Results show the performance of the network to be sufficient for remote driving applications at relatively low speeds (<40 km/h). Network latencies compared with 4G have dropped to half. A strong correlation between latency and remote driving performance is not clearly seen and requires further evaluation taking into account the influence of the user interface.

Mobile Money for the Unbanked in Emerging Markets

Mobile money, together with mobile broadband, is likely to be the primary growth engine for emerging market mobile network carriers. The service is gaining popularity and is beginning to contribute considerably to telecom income. There are still 2 billion individuals worldwide who do not have a bank account. This group is primarily located in less developed areas (Africa, part of Asia, and Latin America). A typical use case of a distant worker sending money to the family for living expenses is highly expensive for persons who do not have financial inclusion. Mobile penetration is substantially higher, allowing for these remittances to be sent in a cost-effective and simple manner. Because the system is based on feature phones and 2G technology, end users do not need to have the most recent smartphone or mobile broadband (SMS or Unstructured Supplementary Service Data-USSD channel). The most common application is domestic remittance. Bill payments and merchant payments are two others. International remittances are now feasible across various operators as well (cross-MNO agreements). Globally, there were already more than 100 million active mobile money accounts in 2014, with services available in around 90 countries.

Mobile Payment Services, Government Involvement, and Mobile Network Operator Performance

Problem definition: Recent developments in mobile payment services (MPS) have shown an increasing role of mobile-government (m-government) initiatives in improving the market performance of mobile network operators (MNOs) and financial inclusion. High costs and operational challenges have discouraged MNOs from fully committing to the development of MPS, but government involvement under m-government may increase MNO user bases by providing the scale and scope necessary to incentivize MNOs. Academic/practical relevance: Extant research on mobile payment has ignored the role of governments as important stakeholders in the mobile financial ecosystem. Our research contributes to the literature by examining the role of governments as business partners in MPS launches and the effect of government involvement on MNO user bases. Methodology: Using a unique proprietary data set from the mobile network industry, we design a quasi-experiment to examine the causal effects of government involvement in MPS on MNOs’ total mobile connections. More importantly, we adopt a changes-in-changes (CIC) estimation approach to further establish nonlinear treatment effects of government involvement based on MNO size and MPS type. Results: We find that government involvement expands MNO user bases beyond MPS launches. Such effects increase with MNO size and MPS variety, favoring larger MNOs and, to a certain degree, MNOs with diverse offerings of government-involved MPS. Government involvement in MPS launches also directly benefits MNOs with microloan services. In addition, government regulations and policies to encourage financial inclusion can also expand MNO user bases. Managerial implications: Governments play a critical role in promoting technologies and financial services both as a regulator and as a business partner. To improve market performance, MNOs should take advantage of the scale and scope of government services by partnering with government agencies in launching MPS. MNOs should also embrace government policies and regulations to increase user bases.

Enabling Intelligence in Spectrum Sharing

We argue that the capital expenditures made by an individual mobile network operator is extremely high and risky. Also, radio spectrum sharing still lacks intelligence in the current architecture of mobile networks and needs to be rethought. We propose that the goal for a disruptive innovation, in the future mobile network architecture, that shall be able to free mobile network operators from having to hold spectrum licenses and natively enable intelligent radio spectrum sharing among multiple mobile network operators. On the basis of the design principles, the duty of a single mobile network operator is split into two roles, one focuses on infrastructure development, the other only contains authorizations on the radio spectrum usage. We introduce a new role to the mobile network architecture, named Spectrum Trader, is a primary broker for spectrum trading, and it is used to coordinate with the demand-side requests and the supply-side resources to drive demand in a \emph{real-time bidding} manner. We also introduce a spectrum embedding technique that shall enable efficient and intelligent spectrum allocation by recommending the right spectrum bands based on user scenario. Finally, several significant challenges that need to be addressed in practical deployment are investigated.