Machine-to-machine Research Articles

QoS‐Aware Optimal Radio Resource Allocation Method for Machine‐Type Communications in 5G LTE and beyond Cellular Networks

In this paper, we consider the saturation problem in the 3GPP LTE cellular system caused by the expected huge number of machine‐type communication (MTC) devices, leading to a significant impact on both machine‐to‐machine (M2M) and human‐to‐machine H2H traffic. M2M communications are expected to dominate traffic in LTE and beyond cellular networks. In order to address this problem, we proposed an advanced architecture designed for 5G LTE networks to enable the coexistence of H2H/M2M traffic, supported by different priority strategies to meet QoS for each traffic. The queuing strategy is implemented with an M2M gateway that manages four queues allocated to different types of MTC traffic. The optimal radio resource allocation method in LTE and beyond cellular networks was developed. This method is based on adaptive selection of channel bandwidth depending on the QoS requirements and priority traffic aggregation in the M2M gateway. Additionally, a new simulation model is proposed which can help in studying and analyzing the mutual impact between M2M and H2H traffic coexistence in 5G networks while considering high and low priority traffics for both M2M and H2H devices. This simulator automates the proposed method of optimal radio resource allocation between the M2M and H2H traffic to ensure the required QoS. Our simulation results proved that the proposed method improved the efficiency of radio resource utilization to 13% by optimizing the LTE frame formation process.

Secured SECS/GEM: A Security Mechanism for M2M Communication in Industry 4.0 Ecosystem

The manufacturing industry has been revolutionized by Industry 4.0, vastly improving the manufacturing process, increasing production quality and capacity. Machine-to-Machine (M2M) communication protocols were developed to strengthen and bind this ecosystem by allowing machines to communicate with each other. The SECS/GEM protocol is at the heart of the manufacturing industry, thriving as a communication protocol and control system for years. It is a manufacturing equipment protocol used for equipment-host data communications. However, it is not without drawbacks, despite being a widely adopted communication protocol used by leading industries. SECS/GEM does not offer any type of security features as it was designed to work in a closed network. Such shortcomings in the protocol will allow attackers to steal secrets such as manufacturing processes by looking at recipes, perform reconnaissance prior to sabotage attempts, and can have severe implications on the entire industry. This paper proposes a mechanism to secure SECS/GEM data messages with AES-GCM encryption and evaluate the performance with the standard SECS/GEM protocol. The results from our evaluations showed that the proposed mechanism achieves data confidentiality and authenticity with a negligible overhead of 0.8 milliseconds and 0.37 milliseconds when sending and receiving a message, respectively, compared to the standard protocol.

Cyberattacks and Vociferous Implications on SECS/GEM Communications in Industry 4.0 Ecosystem

Information and communications technology (ICT) is prevalent in almost every field of industrial production and manufacturing processes at present. A typical industry network consists of sensors, actuators, devices, and services to connect, track, and manage production processes to increase performance and boost productivity. The SEMI Equipment Communications Standard/Generic Equipment Model (SECS/GEM) is SEMI's Machine-to-Machine (M2M) protocol for equipment-to-host data communications. It is the most popular and profoundly used M2M communication protocol operating in the manufacturing industry. With Industry 4.0 as a guiding factor, connectivity to business networks is required for accessing real-time data whenever and wherever needed. This openness of connectivity raises security concerns as SECS/GEM protocol offers no security, which endangers exposing the manufacturing industries' business secrets and production processes. This paper discusses the key processes involved in SECS/GEM communications and how potential attackers can manipulate these processes to obtain illegal or unauthorized access. The experiments' results indicate that the SECS/GEM processes are entirely vulnerable to numerous attacks, including DoS attack, Replay attack, and False-Data-Injection-Attack. Thus, the future direction involves developing a prevention mechanism that aims at securing the SECS/GEM processes in the industrial network. This study's findings are useful as preliminary guidance for the infrastructure owners to plan for appropriate security measures to protect the industrial network.

A Review on SECS/GEM: A Machine-to-Machine (M2M) Communication Protocol for Industry 4.0

Industry 4.0 has imminently emerged as the fourth industrial revolution. It garners emphasis primarily on the interaction between factory equipment and machines involved in entire value-chain activities for boosting efficiency and production with limited human intervention. The M2M communication protocols have gained significant prominence amidst sage minds in recent years, particularly in the manufacturing industries. Several M2M communication protocols have been developed for the industry, such as SECS/GEM, OPC UA, DDS, and MQTT. Among these protocols, SECS/GEM is a semiconductor’s equipment interface protocol for equipment-to-host data communications. It is not a modern, but decades-long protocol, and has been again brought to the fore by Industry 4.0. Thereupon, it was imperative to review amenability of SECS/GEM protocol in the context of adaptation of features depicted by industry 4.0, and limelight plethora of shortcomings and limitations. In this paper, comparisons of prominent features and limitations of the aforementioned M2M communication protocols in general and review of the SECS/GEM protocol in particular, have been made. Findings include deficiencies in security, point to point communication, discovery mechanism, fixed message format, interoperability, extendibility, and manual integration.

Wireless Resource Management and Resilience Optimization of the M2M‐Oriented Mobile Communication System

Machine‐to‐machine (M2M) communication technology is an emerging technology that can connect smart wireless devices. The most obvious feature of M2M is that the communication between devices does not require human intervention. Therefore, ensuring the low‐energy consumption of M2M devices is a necessary condition for prolonging the survival time of their devices. This paper first considers the coexistence of M2M and H2H scenarios. Aimed at the energy efficiency of M2M equipment and the channel capacity of H2H equipment, a multiobjective problem is constructed for joint spectrum and power resource management, and a weighted Chebyshev algorithm is proposed to solve this problem. Secondly, in view of the additional interference problems caused by the introduction of M2M communication, the intercell cooperative link selection algorithm is used to optimize its resilience. The effectiveness of the algorithm is proven by simulation results.

Yönetsel Roller ve Beceriler Değişebilir mi? Endüstri 4.0 Bağlamında Keşifsel Bir Çalışma

This research aims to determine whether Mintzberg’s (1971;1973) managerial roles and Katz’s (1955) managerial skills have changed today when industry 4.0 has been discussed. The subject of research was questioned with a qualitative approach by using the snowball sampling method using the deep interview technique and evaluated through content analysis. It was found that some of the Mintzberg’s roles have lost importance and some become more important. Also, leadership, motivation, taking initiative, reliability, self-confidence, self-management, good time management, technical expertise, customer, quality and human-orientedness, teamwork, flexibility, digital adaptation, organizing, risk-taking, creativity, imagination, openness to experience, curiosity, empathy, problem-solving, strategic thinking ability, lifelong learning, being a researcher, decision making, modeling, programming, digital literacy, digital vision, devotional, interpersonal communication, M2M communication, cultural awareness, IT technology skills, using big data, interdisciplinary work, network technology, data-network security, business process management and cooperation skills become more important with industry 4.0.

SDR-Based High-Definition Video Transmission for Biomedical Engineering

Background: Software-Defined Radio (SDR) frameworks from cellular telephone base stations, e.g., Multiservice Distributed Access System (MDAS) and small cells, employ extensively integrated RF agile transceivers. The Internet of Medical Things (IoMT) is the collection of medical devices and applications that connect to healthcare IT systems through online computer networks. Medical devices equipped with Wi-Fi allow M2M communication, which is the backbone of IoMT and associated devices linked to cloud platforms containing stored data to be analyzed. Examples of IoMT include remote patient monitoring of people with chronic or long-term conditions, tracking patient medication orders and the location of patients admitted to hospitals, and patients' wearables to send info to caregivers. Infusion pumps connected to dashboards and hospital beds rigged with sensors measuring patients' vital signs are medical devices that can be converted to or deployed as IoMT technology.
 Methods: This work proposes an SDR architecture to allow wireless High-Definition (HD) video broadcast for biomedical applications. This text examines a Wideband Wireless Video (WWV) signal chain implementation using the transceivers, the data transmitted volume, the matching occupied RF bandwidth, the communication distance, the transmitter’s power, and the implementation of the PHY layer as Orthogonal Frequency Division Multiplexing (OFDM) with test results to evade RF interference.
 Results: As the IoMT grows, the amount of possible IoMT uses increases. Many mobile devices employ Near Field Communication (NFC) Radio Frequency Identification (RFID) tags allowing them to share data with IT systems. RFID tags in medical equipment and supplies allow hospital staff can remain aware of the quantities they have in stock. The practice of using IoMT devices to observe patients in their homes remotely is also known as telemedicine. This kind of treatment spares patients from traveling to healthcare facilities whenever they have a medical question or change in their condition.
 Conclusion: An SDR-based HD biomedical video transmission is proposed, with its benefits and disadvantages for biomedical WWV are discussed. The security of IoMT sensitive data is a developing concern for healthcare providers.

Spatial Group Based Access Class Barring for Massive Access in M2M Communications

In this letter, a novel spatial group based access class barring (ACB) scheme is proposed for machine-to-machine (M2M) random access system with timing advance (TA) assisted machine-type devices (MTDs) identification and preamble reuse. Specifically, multiple ACB factors are assigned for groups to provide precise access control, and an optimization problem of determining the optimal ACB factors which maximize the throughput is formulated. To reduce the computational complexity, the optimal problem is further simplified to get a suboptimal solution. The performance advantages of the proposed scheme are verified by simulations.

A location-aware power control mechanism for interference mitigation in M2M communications over cellular networks

Machine-to-Machine (M2M) communication is considered as a promising technology in fifth-generation (5G) cellular networks to reduce the power consumption and improve energy efficiency. To achieve these benefits, identification of unknown machine location is crucial for mitigating interference. Therefore, this paper proposes a location-aware communication mode selection based power control mechanism for reducing interference in M2M communications over cellular networks. The proposed mechanism depends on the threshold distance while communicating among M2M pair. Consequently, user equipment (UE) selects the proper communication mode in the proposed mechanism. Resource allocation between the M2M UEs (MUEs) and cellular UEs (CUEs) that share the resources in both orthogonal and non-orthogonal ways are analyzed for different modes. A water filling algorithm and Lagrange decomposition scheme based power optimization process are adopted for allocating the proper optimal transmit power to each UE in the proposed mechanism. Simulation results are compared with the non-orthogonal and orthogonal resource sharing scheme based proposed mechanism which shows that the orthogonal resource sharing scheme provides better system performance in the proposed network.

A Distance Based Communication Mode Selection Mechanism for M2M Communications Over Cellular Networks

The implementation of machine-to-machine (M2M) communications in fifth-generation (5G) cellular networks can facilitate with several benefits like enhancement of bandwidth utilization, accommodating large number of users and decreasing traffic load on evolved node B (eNB). Integration of location information of unknown machine in communication mode selection mechanism is the key feature of this research. In this paper, a distance based communication mode selection mechanism using non-orthogonal resource sharing scheme is adopted in the proposed system model. Under the proposed mechanism, the expressions of throughput and RBs utilization policy are derived, which are the key parameters to evaluate the performance in the proposed network. Depending on the mode selection condition, such as threshold distance and threshold SINR between M2M users and regular cellular users, a UE can automatically choose its communication mode in the network. It is supposed that selection of mode before data transfer can improve the system performance. On the other hand, designing of efficient distance assisted proposed resource blocks (RBs) utilization policy reduces the traffic load on the eNB. Extensive simulations are carried out for evaluating the performance of the proposed mechanisms. The system performance is compared with various changeable parameters, such as throughput, mode selection threshold SINR, threshold distance and RBs. Besides, the proposed mechanism provides better network performance as well as reduces the traffic load in the proposed network.

Distributive Throughput Optimization for Massive Random Access of M2M Communications in LTE Networks

Machine-to-machine (M2M) communications, which aims to enable autonomous communication between machine devices with minimum human intervention, have experienced remarkable growth over the past few years. In massive M2M communications, random access (RA) collision is one of the critical problems at the network entry stage. To alleviate the channel contention during the network access stage, most existing RA solutions for M2M communications need the base station (BS) to determine backoff parameters, whose optimal values are hard to obtain and would also incur substantial signaling overhead, especially in dense scenarios. To address this issue, a distributive approach is highly desirable. In this paper, a new method for distributive estimation of optimal backoff parameters is proposed. Specifically, each machine type device (MTD) only needs to observe their own successful and total transmissions of access requests during an estimation interval, after which each MTD can obtain an estimation of the optimal backoff parameters according to an explicit expression of the observed statistics. It is found that the estimation interval determines the performance of the proposed scheme. When the number of MTDs in the network does not change or varies slowly, the network throughput can be maximized if the estimation interval is chosen properly. Compared to existing centralized methods, the proposed method can achieve similar performance with much lower signaling overhead. The proposed scheme can be applied for both homogeneous and heterogeneous scenarios and provide a practical access design method for M2M communications.

Resource Optimization for Delay-Tolerant Data in Blockchain-Enabled IoT With Edge Computing: A Deep Reinforcement Learning Approach

Recently, the development of the Internet of Things (IoT) provides plenty of opportunities and challenges in various fields. As an essential part of IoT, machine-to-machine (M2M) communications open a novel way that the machine-type communication devices (MTCDs) are connected and communicated without any human intervention. Meanwhile, delay-tolerant data play an important role in M2M communications-based IoT, and it puts more emphasis on powerful data caching, computing, and processing, as well as the security and stability of data transmission. To meet these requirements in M2M communications networks, in this article, we introduce some promising technologies, such as edge computing and blockchain, and propose a joint optimization framework about caching, computation, and security for delay-tolerant data in M2M communications networks based on dueling deep $Q$ -network (DQN). According to the dynamic decision process by DQN, the optimal selection and decision of caching servers, computing servers, and blockchain systems can be made to achieve maximum system rewards, which includes higher efficiency of data processing, lower network costs, and better security of data interaction. Extensive simulation results with different system parameters show that our proposed framework can effectively improve the system performance for blockchain-enabled M2M communications compared to the existing schemes.

MQTT protocol employing IOT based home safety system with ABE encryption

This project aims towards the usage of MQTT (Message queueing telemetry transport) protocol in IoT (Internet of things) along with adopting a feasible means of encrypting the message transfers in applications. The lightweight nature of MQTT protocol makes possible the transfer of information speedily and hence, has now being used in applications related to IoT, WSN (Wireless sensor networks), and M2M (Machine to machine) communications. Here, MQTT is deployed between ESP-8266 Wi-Fi SoCs namely- NodeMCU ESP-8266 12E and ESP-01 8266 Wi-Fi modules. Both communicate using the MQTT protocol using the internet via Wi-Fi. The ESP-8266 Wi-Fi SoCs have completely revolutionized approach towards IoT because of numerous advantages. This project also includes the usage of 2 sensors namely- PIR (Passive InfraRed) motion detector sensors and an MQ-5 gas sensor which sense human presence and some gases respectively. These sensors read the environment around them for the required information, systems encrypt that information and subsequently, transmit the data over the internet to the MQTT broker stationed at the cloud. This encrypted data is then sent to a central node- NodeMCU ESP-8266 12E which decrypts it and then alerts the user about any mishappening, through the Blynk app.

Multi-protocol bridge generation for M2M communication using MQTT

MQTT (Message Queuing Telemetry Transport) is known as a quasi-standard for IoT application communication between IoT devices and OPC UA (Open Platform Communication Unified Architecture) is the de facto standard that enables M2M communication in modern industry 4.0. But there are also industrial machines that still use RESTful (Representational State Transfer) APIs as their only communication interface. Integrating machines with these three protocols into automated manufacturing processes and enact a machine to machine communication between them can be challenging. This paper demonstrates how a M2M communication supporting HTTP, MQTT and OPC UA can be implemented using MQTT as the communication protocol. Furthermore, the goal is to create a model for each bridge that can be used to create interface mappings from MQTT to HTTP or from MQTT to OPC UA. This model can then easily be used to generate MQTT clients that bridge the different protocols and enable the M2M communication between machines to share their information.

UAV-Assisted Data Transmission in Blockchain-Enabled M2M Communications with Mobile Edge Computing

Recently, the development of the internet of Things (ioT) provides plenty of opportunities and challenges in various fields. As an essential part of ioT, machine-to-machine (M2M) communications open a novel way that machine-type communication devices (MTCDs) are connected and communicated without any human intervention. However, when ioT infrastructures are destroyed, network services will be disrupted. Then it is difficult for the MTCDs located in remote areas to restore communication by themselves immediately. To cope with these problems, in this article, we introduce some promising technologies such as unmanned aerial vehicles (UAV), blockchain and mobile edge computing (MEC) to ensure data transmission, security and reliability in damaged M2M communications networks. Meanwhile, we propose a joint optimization framework to maximize both data computation capacity and throughput of blockchain systems, and formulate it as a Markov decision process (MDP). in order to solve the dynamic and complicated optimization problem, dueling deep Q-network (DQN) is adopted, so that the optimal selection and decision can be made to achieve maximum system rewards. Simulation results with different system parameters show that our proposed framework can improve the system performance effectively compared to the existing schemes. Finally, open research issues and challenges are discussed for UAV-assisted M2M communications.

Optimal Resource Allocation in Cellular Networks With H2H/M2M Coexistence

Machine-to-Machine (M2M) communications plays a key role in the evolution of the Internet of Things (IoT). Cellular networks are one of the main technologies to support the deployment of M2M communications. However, the characteristics and Quality-of-Service (QoS) requirements of M2M traffic are different from those of conventional Human-to-Human (H2H) traffic, that makes radio resource allocation a complex task. In this paper, a two-phase optimal resource allocation algorithm is proposed for H2H/M2M coexistence. The first phase performs joint power-resource allocation in order to satisfy the QoS requirements of H2H traffic while considering the delay constraints of delay-sensitive M2M traffic. Then, the second phase focuses on meeting the QoS requirements of M2M traffic. Simulation results are presented which show that the proposed algorithm is able to balance the demands of M2M and H2H traffic, meet their diverse QoS requirements, and ensure fairness for delay-tolerant M2M traffic.

An Efficient Secure Authentication and Key Establishment Scheme for M2M Communication in 6LoWPAN in Unattended Scenarios

Machine-to-machine (M2M) is an important part of Internet of Things (IoT), and is used to describe those technologies applied in wireless communication automatically between mechanics or electronics instruments. With the rapid development and wide application of the Internet of Things, IETF is assigned to design IPv6 over low power wireless personal area network (6LoWPAN). The address of IPv6 is indefinite, which means it can satisfy addressing requirements for M2M. The 6LoWPAN standard has clarified important issues in M2M, but communication security has not been effectively resolved. In this article, we analyzed the existing security protocol for M2M communication in 6LoWPAN. The analysis result shows that the protocol has the defect of data leakage after the node is captured. In addition, the EAKES6Lo protocol is also vulnerable to sinkhole attacks and plaintext-chosen attacks. Based on the above analysis, an M2M communication mutual authentication protocol based on 6LoWPAN in unattended operation is proposed. The protocol establishes a reasonable secret key distribution mechanism and designs an anti-capture attack detection method for unattended nodes to resist attacks, such as replay attacks, sinkhole attacks, plaintext-chosen attacks, and physical capture attacks. Finally, the security of the protocol is proved by BAN.

Energy‐efficient resource allocation for lifetime maximization in M2M networks

SummaryMachine‐to‐machine (M2M) communications is one of the major enabling technologies for the realization of the Internet of Things (IoT). Most machine‐type communication devices (MTCDs) are battery powered, and the battery lifetime of these devices significantly affects the overall performance of the network and the quality of service (QoS) of the M2M applications. This paper proposes a lifetime‐aware resource allocation algorithm as a convex optimization problem for M2M communications in the uplink of a single carrier frequency division multiple access (SC‐FDMA)‐based heterogeneous network. A K‐means clustering is introduced to reduce energy consumption in the network and mitigate interference from MTCDs in neighbouring clusters. The maximum number of clusters is determined using the elbow method. The lifetime maximization problem is formulated as a joint power and resource block maximization problem, which is then solved using Lagrangian dual method. Finally, numerical simulations in MATLAB are performed to evaluate the performance of the proposed algorithm, and the results are compared to existing heuristic algorithm and inbuilt MATLAB optimal algorithm. The simulation results show that the proposed algorithm outperforms the heuristic algorithm and closely model the optimal algorithm with an acceptable level of complexity. The proposed algorithm offers significant improvements in the energy efficiency and network lifetime, as well as a faster convergence and lower computational complexity.

Multi-packet reception dynamic frame-slotted ALOHA for IoT: Design and analysis

Machine-to-Machine(M2M) Data Collection networks form an integral part of the internet of things wherein a Data Collector (DC) collects data from a large number of nodes. M2M communication protocols should not only be efficient, but they should also be easy to implement. In this regard, Frame Slotted aloha based Medium Access Control protocols have gained popularity for these networks. In the current paper, we propose and analyze the Dynamic Frame Slotted Aloha(DFSA) algorithm for an M2M system with DC having a multi-packet reception (MPR) capability. We develop a stochastic model for the proposed MPR-DFSA algorithm. Based on the Karp-Upfal-Widgerson inequality, we derive asymptotic expressions and bounds for (a) expected number of nodes contending in a given iteration of the algorithm and (b) expectation of the number of iterations the MPR DFSA algorithm takes to finish. Further per-slot throughput and transmission delay of the packet of the MPR-DFSA algorithm have been derived. The analysis is validated through simulation. We compared the proposed MPR DFSA protocol with random access protocols of LTE and Narrowband IoT standards. Finally, we evaluate the performance of MPR DFSA protocol under real-world IoT network scenarios.

A NOVEL TECHNOLOGY FOR MACHINE TO MACHINE COMMUNICATION USING ETHEREUM SMART CONTRACTS

In the emerging world of IoT applications, machines are going to be at the endpoints of the Internet engaging in complex Machine to Machine (M2M) communications. Be it a personal assistant (softbot)making an appointment with a doctor or an autonomous car filling fuel or charging at a refueling station, in the future, it is going to be M2M communications without human intervention. In such a scenario, robust and secure technology is essential to record every M2M transactions. This paper makes use of blockchain, a distributed ledger technology for intelligent transportation systems. It is proposed that blockchain networks such as Ethereum have the foundations to record and satisfy the transaction that has happened between the machines. A permissioned Ethereum blockchain – the smart contract –is used for recording each every transaction that come off between the car and electric station. An algorithm is proposed to recharge the autonomous electric vehicles as a case study.