Cyber-Physical Systems Security: Limitations, Issues and Future Trends

With the proliferation of wireless devices, wireless networks in various forms have become global information infrastructure and an important part of our daily life, which, at the same time, incur fast escalations of both data volumes and energy demand. In other words, energy-efficient wireless networking is a critical and challenging issue in the big data era. In this paper, we provide a comprehensive survey of recent developments on energy-efficient wireless networking technologies that are effective or promisingly effective in addressing the challenges raised by big data. We categorize existing research into two main parts depending on the roles of big data. The first part focuses on energy-efficient wireless networking techniques in dealing with big data and covers studies in big data acquisition, communication, storage, and computation; while the second part investigates recent approaches based on big data analytics that are promising to enhance energy efficiency of wireless networks. In addition, we identify a number of open issues and discuss future research directions for enhancing energy efficiency of wireless networks in the big data era.

Towards Energy-Efficient Wireless Networking in the Big Data Era: A Survey

The coronavirus disease 2019 (COVID-19) pandemic has led to a massive rise in survey-based research. The paucity of perspicuous guidelines for conducting surveys may pose a challenge to the conduct of ethical, valid and meticulous research. The aim of this paper is to guide authors aiming to publish in scholarly journals regarding the methods and means to carry out surveys for valid outcomes. The paper outlines the various aspects, from planning, execution and dissemination of surveys followed by the data analysis and choosing target journals. While providing a comprehensive understanding of the scenarios most conducive to carrying out a survey, the role of ethical approval, survey validation and pilot testing, this brief delves deeper into the survey designs, methods of dissemination, the ways to secure and maintain data anonymity, the various analytical approaches, the reporting techniques and the process of choosing the appropriate journal. Further, the authors analyze retracted survey-based studies and the reasons for the same. This review article intends to guide authors to improve the quality of survey-based research by describing the essential tools and means to do the same with the hope to improve the utility of such studies.

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Reporting Survey Based Studies - a Primer for Authors.

The operation condition of wireless system directly impacts both the system performance and the quality of experience (QoE). On the basis of telecom operator data, this paper designs a comprehensive operation and revenue analysis (CORA) algorithm for LTE/5G wireless system. The objective of the proposed CORA algorithm is to analyze and evaluate both the operation state and the revenue of base station (BS) in the wireless system. The designed CORA algorithm is applied in the realistic 4G wireless system. The CORA algorithm can assist telecom operator to effectively analyze and evaluate the BS comprehensive state of operation and revenue.

A Comprehensive Operation and Revenue Analysis Algorithm for LTE/5G Wireless System Based on Telecom Operator Data

User perception is the key for telecom operators. In order to keep good user perception, telecom operators employ network optimization and construction. In this paper, a novel user perception aware network management (UPNM) algorithm is designed for LTE/LTE-Advanced cellular networks. Initially, UPNM algorithm integrates a series of telecom data, which relates to users and cellular networks. On the basis of data, user perception is analyzed to find the cells with low quality of service (QoS). Then, UPNM algorithm analyzes the network interference and coverage and takes methods to deal with the interference and coverage problem. Finally, both the cell total service and capacity are analyzed, in order to manage the network capacity. We implement the proposed UPNM algorithm to the realistic cellular systems in a Chinese city. The UPNM algorithm can help telecom operators manage the mobile cellular networks.

User Perception Aware Telecom Data Mining and Network Management for LTE/LTE-Advanced Networks

Big data has been arising a growing interest in both scientific and industrial fields for its potential value. However, before employing big data technology into massive applications, a basic but also principle topic should be investigated: security and privacy. In this paper, the recent research and development on security and privacy in big data is surveyed. First, the effects of characteristics of big data on information security and privacy are described. Then, topics and issues on security are discussed and reviewed. Further, privacy-preserving trajectory data publishing is studied due to its future utilization, especially in telecom operation.

A survey of security and privacy in big data

WCDMA data based LTE site selection scheme in LTE deployment

Recently, a series of approaches have been developed to mitigate the interference and improve the system capacity in LTE networks. However, due to the diversity of data source, existing approaches have their own limitations in supervised and unsupervised learning. To deal with the downlink inter-cell interference which is caused by the frequency reuse and the characteristics of the OFDMA, an interference management algorithm using big data is proposed. Since big data analytics has become more and more popular in wireless optimization, it is a very effective approach to mitigate the interference and the outage probability by analyzing the huge amount of wireless network measurements and diagnosis data. By obtaining and analyzing the measurement report (MR) and counters (records of the performance indicators of networks) from existing networks, an interference management algorithm (IMA) is proposed based on big data analytics. The numerical results show that the interference management process is low cost and high-efficiency for telecom operators.

An interference management algorithm using big data analytics in LTE cellular networks

Due to the diverse services and high rate requirements of telecom users, mobile cellular systems envisage the challenges of high resource usage, especially the base station (BS) in the hot-spot area. This paper investigates on telecom big data of LTE/5G systems, and then we design a telecom big data assisted comprehensive BS resource analysis (CBSRA) algorithm. CBSRA algorithm considers six categories of resource data/indicators. Then, CBSRA algorithm judges the usage level of each indicator. Finally, CBSRA algorithm takes the comprehensive analysis and outputs the results. We implement the CBSRA algorithm in a realistic cellular system in China, and the proposed algorithm can assist operator to effectively detect BS with high resource usage.

Jie Gao

Papers

User Perception Aware Telecom Data Mining and Network Management for LTE/LTE-Advanced Networks

A survey of security and privacy in big data

WCDMA data based LTE site selection scheme in LTE deployment

An interference management algorithm using big data analytics in LTE cellular networks

Telecom Big Data Assisted BS Resource Analysis for LTE/5G Systems