Emerging ICT applications and services—Big data, IoT, and cloud computing
Jong Hyuk Park, Muhammad Younas, Hamid Reza Arabnia, Naveen Chilamkurti · International Journal of Communication Systems · 2020
In the last few decades, new technologies are continuously growing in next-generation applications, such as smart energies, smart grid, and smart transportation. Big data, Internet of things (IoT), and cloud computing (BIC) are the distinct three domains taking the lead role in the modernized variant of applications with information communication and technology (ICT). They provide different types of communication networks and technologies for sharing data all over the world. However, each of these domains has some challenges, such as scalability, access control, accuracy, low performance, computational bandwidth, energy consumption, security, and privacy. IoT applications collect and process a massive amount of data from the diverse communication system (CS). Thus, we need to find BIC-based solutions for addressing the above challenges with the convergence of ICT applications and services. The emerging ICT paradigm and BIC are developing future human requirements and provide innovation possibilities, scalable productivity, and industrial application efficiency. ICT-based cloud computing will leverage big data analytics anytime, anywhere, collecting and processing IoT data by cloud servers and CS services. ICT has opened up various security and privacy issues in BIC, such as unauthorized software updates, weak password authentication, and insecure communication, which have become key research challenges. Artificial intelligence (AI) and blockchain are also recent advanced technologies for facilitating automation and streamlined functioning of IoT devices, security, and privacy with the convergence of ICT principles and BIC. It also provides technological magic for innovation in ICT applications with BIC, when adequately designed and implemented. This special issue focuses on the most recent advances in smart communications and information communication technology, design, and development of emerging ICT applications and services, including big data, IoT, and cloud computing for advanced applications. We invited technical articles that have a broad scope and general interest to an engineering audience. We selected 15 outstanding accepted papers for publication in this special issue of the International Journal of Communication Systems (IJCS). All accepted papers are categorized into 10 different dimensions: access control, accuracy, scalability, big data analysis, task scheduling, interoperability, portability, energy consumption, security, and privacy. The brief contributions of these papers are discussed as follows. With the continuous development of biometric applications, the image sets and single-image methods are essential for face recognition technology. Wu and Liu1 compared and analyzed both methods' recognition accuracy based on local binary patterns (LBPs) algorithm. It utilized Honda and the USCD video database. With the image sets, face recognition has better accuracy than a single image; the experimental results show it. This face recognition uses various applications, including vehicle access systems, access control systems, intelligent security, and identity recognition. Zhang et al.2 proposed a clustering model of vehicle-driving data generation, where the data-augmentation method is used to expand the driving data sets. They then generated various groups as clusters, and the affinity propagation (AP) algorithm is used to cluster the driving data, and these data are converted into the images. If the proposed model has a large number of figures, the AP algorithm has one demerit that it has high complexity and long calculation time. The convolutional neural networks (CNNs) are utilized for training the groups (clusters) of data sets in the proposed model. As a result of the training process, they obtained better classification after 5,000 iterations and got an average accuracy of 97.06%. Based on the rail transit–land use system analysis from various parameters, Liu and Wang3 provided a new evaluation index system that obtained extensive coordination within urban rail transit and land use. With the efficacy function's help, they calculated the comprehensive development level between urban rail transit and land use, then constructed the coupling coordination degree model. This model did not describe the absolute level; it only gives harmonious development at a particular time period between rail transit and land use. The growth of this model in Shagai is a long-term and gradual process. Nowadays, the rapid development of autonomous flight technology, the emergence of an unmanned aerial vehicle (UAV), and information and communication technology (ICT) is essential for sharing the data. The authors proposed the UAV control process for surveillance of autonomous flight.4 They described surveillance with UAV's help, introduced strategies for optimal flight routes, and analyzed preceding flight record works. These records give the advantages of intuitive and more adequate specifications. Je and Huh5 studied and provided the scheme for maximum profit and predicted future power demands for smart grid application with a genetic algorithm. This algorithm is dependent on the game theory-based fuzzy logic. They determine and calculate the exact number of access nodes in the mesh network with greedy and dynamic algorithms and provided a more efficient smart grid network environment without executing unneeded estimation works. Hwang et al.6 proposed a novel algorithm for predicting indoor condensation time with a minimal number of IoT nodes in a residential environment. The test bed collected an essential data set in the condensation environment and evaluated it with a machine learning model. Experimental evaluation results estimated the surface temperature based on changes in the internal and external temperatures realized high accuracy with 0.97 RMSE. Based on this temperature, they predicted the occurrence of indoor condensation time within an error interval of 20 min after an average of 2 h. Jang et al.7 studied a new type of k-nearest reliable neighbor (kNRN) query, Q = (LQ, θ, δ, k), with many real applications in crowdsourced location-based services (cLBSs), and provided efficient methods to search for objects that are available in the real world. These reliable objects of the kNRN query determined by the parameters (θ, δ). It is given by the user's ad-hoc query and efficiently searched by precomputing data or index. The experimental results showed that proposed algorithms are effective in improving query performance. Kumar et al.8 proposed a secure and efficient biometric-based authentication protocol framework for vehicle cloud computing (VCC) with the help of the elliptic curve cryptography (ECC). It provided secure communication in vehicular applications with various security features and attributes, including password authentication, vehicular data protection, and vehicle driver's identity authentication satisfied by the proposed protocol (SEBAP). It also facilitated efficient resource utilization in terms of communication and computation cost for vehicular communication. Hence, it is implemented in real-life applications in VCC. According to the heterogeneous and 5G network's services, Kim et al.9 provided location-aware network virtualization methods for minimizing network load and resource cost by software-defined networking (SDN) and network function virtualization (NFV). Secure isolation of virtualized network with mobile core entities and edge cloud resources establishment by packet data network (PDN) connection in proposed methods. Data transmission between user and edge cloud by NFV for the requirement of user services, and used in various cases such as automated cars, remote health care, and streaming video. To address decision latency and real-time data computation, security concerns such as trust, authentication, mobility, intrusion, network security, Khalid et al.10 discussed privacy and access control scheme for fog computing. This scheme shows how users can overcome different secure data storage and retrieval issues in fog computing. They also performed comprehensive discussion on open research issues related to the same domain and classified and analyzed the similarities and variances concerning other research studies. Ksentini et al.11 introduced the quality of services requirements such as latency and sensitivity for big data analysis in smart applications, including augmented reality and E-healthcare. They also presented a novel approach based on the priority classification technique. They deployed IoT/cloud-based use case applications in a fog computing ecosystem and distinguished QoS metrics, including latency, bandwidth, energy consumption, and real-time processing. Naik et al.12 extended secure virtual machine (VM) allocation against attacks by using support value-based game policy. The main objective of this paper provided more security for cloud data with various parameters, including VM efficiency, coverage, and maximum link utilization (MLU). Support value-based game policy is used to find the best VM allocation in the cloud environment. They were also compared with existing methods, including the ant colony system algorithm, max–min algorithm, and Nash equilibrium; the proposed work is better with 90% to 96% accuracy. Premkamal et al.13 proposed DTCP-ABE (dynamic traceable ciphertext-policy attribute-based encryption) scheme for outsourced big data in cloud storage and mitigated efficiency, security, and privacy issues. This scheme extracts the user ID dynamically with a secret key and is stored into a log file and finds the malicious users. It revokes malicious users when they are found in the cloud. They proved that this scheme is secure against secrete key forging, malicious revoked user's unauthorized access, and others. Martinez-Caro and Cano14 proposed a novel holistic approach for performance evaluation in IoT (Internet of things) services and applications with four quality measures, namely, quality of data (QoD), quality of information (QoI), quality of user experience (QoE), and quality of cost (QoC). They also enhanced the simulation tools framework LoRa simulations (FLoRa), including cryptographic mechanisms based on the Advanced Encryption Standard (AES). They used an IoT case study based on an air-quality monitoring system with real data sets using LoRa/LoRaWAN technology and obtained results for three different environments (rural, suburban, and urban). Finally, they evaluated and measured the performance of services in the IoT environment. Based on the large volume of the data, Rubi and de Lira Gondim15 provided an IoT-based environment for data sharing in smart city applications. It proposed three-layered IoT architecture and used the collection, storage, and processing of data functions in a smart city environment by using fog resources and services dynamically deployed in the cloud. Sensor Markup Language (SenML) has been adopted for the sake of compatibility in terms of data representation. International Resource Identification (IRI) is used for reducing message overload and the consumption of resources in IoT devices. Latency and resource consumption were analyzed by three communication protocols, namely, MQTT, CoAP, and REST. The CoAP protocol provided the best results regarding latency, RAM, and CPU consumption. In conclusion, we provide emerging ICT applications and services for innovation in ICT applications with BIC in several parameters, including access control, scalability, big data analysis, task scheduling, interoperability, portability, energy consumption, security, and privacy. In the current ICT applications, AI and blockchain are crucial in ensuring secure communication in IoT devices in a sustainable manner. AI and blockchain techniques are more flexible and robust than new information security solutions. The contributions to the research and the results of this special issue will help the reader better understand the role of emerging ICT applications and services in ICT applications with BIC and guide future research. Finally, we hope that the readers will find this special issue to be relevant to their research and daily work. We would also like to thank the authors for considering this journal as a venue for disseminating their research efforts as well as reviewers for their valuable comments during the review process. We also express our deepest gratitude to the editor-in-chief of IJCS, for allowing us to work together on this special issue. Finally, we thank the external reviewers for their invaluable help in reviewing the papers.