M2M Services Research Articles

Performance Analysis of an IoT-Based Personal Vocal Assistant for Cruise Ships Over Satellite Networks

According to data traffic forecast reported in Cisco (2018), the volume of data transported by Internet in 2021 will exceed the threshold of 3.0 ZB per year, generated by roughly 30 billions of devices. SATCOM’s capability to bring Internet connectivity in parts of the world that until few years ago was impossible to reach (e.g., in the middle of the ocean), the use of satellite platforms for M2M services has become more and more widespread, with an unprecedented increase over the last five years (see Herrero and De Gaudenzi, 2012 and Scalise <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> , 2013) and expected further diffusion in the near future. One of the most interesting applications, enabled by the Internet of Things (IoT), that has attracted significant attention in the M2M field is the personal vocal assistant (PVA). It is a software agent that can perform tasks or services for an individual based on commands or questions given through voice instructions. The main contribution of this article is a performance analysis, both theoretical and simulated, of satellite networks for PVA services over cruise ships. Namely, a PVA must provide feedback to the user in a short amount of time to guarantee a high Quality of Experience (QoE) Zhang <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">et al.</i> , 2013. For this analysis, we tested different satellite providers and we come to a conclusion regarding their feasibility as a reference network for the PVS employment on a cruise ship. Future studies will investigate the proposed scenario by broadening the performance analysis through actual measurements over a real-world satellite channel to practically demonstrate the validity of our approach.

Network architectures and protocols of M2M communications

The issues of building the architecture of M2M networks and managing M2M services using the capabilities of the IMS platform are considered Introduction. M2M (Machine to Machine) is a complex of technologies that provide automatic interaction between devices (things) without human intervention. The Internet of Things is not a single technology, but a whole system of technological solutions. It is a global network infrastructure, which consists of computer networks of physical objects, the traditional IP Internet, and various devices connecting these networks.

Managing Security Risks in Wireless Web Services

Over the last twenty years, the Internet has become highly interactive and is not merely a static repository of websites, which allows its users to interact proactively. The functions and tasks of the Internet have evolved during this twenty-year period, such that it is no longer a rudimentary collection of websites. The Internet empowers individual users to explore the Internet in an exponentially greater capacity than in years past. In this study, we will consider the issues like security and trust issues in IoT and local cloud interfaces. Additionally, the security, requirements of M2M services and security solutions for the internet are analyzed, and their ineffectiveness is discussed.

Brief Paper: Secret Key and Tag Generation for IIoT Systems Based on Edge Computing

Industry 4.0 is continuous automation by applying the latest smart technologies to traditional manufacturing industries. It means that large-scale M2M (Machine-to-Machine) communication and IoT (Internet of Things) technologies are well integrated to build efficient production systems by analyzing and diagnosing various issues without human intervention. Edge computing is widely used for M2M services that handle real-time interactions between devices at industrial machinery tool sites. Here, secure data transmission is required while interacting. Thus, this paper focused on a method of creating and maintaining secret key and security tag used for message authentication between end-devices and edge-device.

Identity Authentication with Association Behavior Sequence in Machine-to-Machine Mobile Terminals

With the rapid development of machine-to-machine (M2M) mobile smart terminals, M2M services can be used in a wide range of industries, including such as tele-medicine, remote meter reading and public security. Since different industries and enterprise users have different requirements for M2M specific applications, the security identity authentication of M2M mobile terminals is particularly worthy of attention. Existing methods can effectively solve the unsustainable problem of one-time verification, however they cannot address the dynamic relevance characteristics of user behavior sufficiently. Thus, the accuracy of user identity authentication needs to be further improved. In this paper, we propose a terminal identity authentication technology based on user association behavior analysis. In order to identify the abnormal login during each behavior process of authenticated user, we take largest coincident part of the user behavior sequence and short coincide into consideration. In addition, we propose Behavior Common Subsequence Sequence Similarity Algorithm based on the traditional sequence pattern of Behavior Common Subsequence(BCS). The experimental results demonstrate that the proposed method can effectively improve the accuracy of user’s behavioral sequence, and prove the uniqueness of different sequences on the other hand.

A blockchain-based authentication scheme for the machine-to-machine communication of a cyber physical system

Today, the manner in which we communicate has greatly advanced. The technology is not just about machines, but people with technology together. Machine-to-machine (M2M) communication is unavoidable in the Internet of things. However, at the same time, there are more attacks against the M2M system. Therefore, a reliable and secure authentication mechanism is required. Blockchain technology is decentralized and highly secure while being tamper-proof. This protects M2M service providers by eliminating the single point of failures. This paper proposes a blockchain-based authentication scheme that uses a practical Byzantine fault tolerance (pBFT) consensus mechanism for M2M security in cyber physical systems. By implementing a blockchain to an M2M system, it provides an ID for devices on the blockchain. Simulation results have shown that the data on the chain cannot be altered. A pBFT consensus algorithm also ensures that the blockchain network is able to come to a consensus with faults.

Design of a Secure Password-Based Authentication Scheme for M2M Networks in IoT Enabled Cyber-Physical Systems

The Internet of Things (IoT) forms a foundation for cyber-physical systems. We propose an efficient and secure authentication scheme for machine-to-machine (M2M) networks in IoT enabled cyber-physical systems. Smart objects and smart devices over CPS are capable of capturing a variety of multimedia contents; interact with each other and also with the physical world in a fully automatic manner without human interference. The proposed scheme allows any pair of entities in an M2M network to mutually authenticate each other and agree on a session key for communicating data in a secure and efficient way. The authentication process does not incorporate the M2M service provider, and hence eliminates the burden of managing the authentication of massive scale devices at the edge of the network. The burden of the authentication process is offloaded and distributed on the gateways under the authority of this M2M service provider. The proposed scheme requires the mobile user to hold only one secret key provided by the M2M service provider, by which, he can roam randomly in the M2M network and authenticate to any of the gateways in the domain. Then, this authenticated gateway allows the mobile user to authenticate with any sensor node in the domain. In the proposed scheme, the authentication process does not rely on any public key cryptographic operations. Authentication is achieved using very few hash invocations and symmetric key encryptions. Therefore, the scheme is suitable for environmental sensors which are limited in resources (computation, storage, and energy). We analyze the security of the proposed scheme using BAN logic, which is widely accepted as a framework for the assessment of authentication protocols and also using ProVerif. We assess the efficiency of the proposed scheme and compare with some recently proposed schemes.

A Q-learning approach for machine-type communication random access in LTE-Advanced

Due to the wide proliferation of the 3GPP long term evolution (LTE) and LTE-Advanced systems as the air interface for 4th generation (4G) wireless systems and beyond, telecommunication operators became more interested in using the LTE infrastructure to meet the projected surge in demand for machine-to-machine (M2M) and IoT communications. As a result, the LTE-Advanced system must evolve to provide these services as an overlay over the original network that is originally designed for human-to-human (H2H) communication. In this setup, M2M communication devices share the same random access channel (RACH) with the H2H communication devices. Since M2M communication is expected to be massive, consequently the RACH is a new bottleneck in the LTE-A system. This triggered the need to enhance the operation of the RACH to meet the needs to support the low power and low data rates of M2M devices. The current standardized scheme to request access to the system is known to suffer from congestion and overloading in the presence of a huge number of devices. Accordingly, recent research pointed to the need of designing more efficient ways to manage the random access channel in such setups. Most of previous works focused on solving the congestion problem in RACH in the presence of M2M solely, but not with the existence of both M2M and H2H services. In this work we propose a new random access channel scheme based on Q-learning approach to reduce the congestion problem. The scheme adaptively divides the available preambles between both M2M and H2H devices in a way that provides an acceptable service for the H2H devices and maximizes the number of active M2M devices. The adaptation is done based on current demand levels from both the H2H and M2M devices and the observed service levels. The results indicate that the proposed approach provides high random access channel success probability for both M2M and H2H devices even with the huge number of M2M devices.

A policy-aware Service Oriented Architecture for secure machine-to-machine communications

Breakthrough recent advancements in the field of machine-to-machine (M2M) communications impose the necessity to improve the service delivery by enforcing appropriate security rules. Due to the large number of the connected devices, the criticality of the M2M applications (e.g. patient monitoring and operation of critical infrastructures), and the network stability weaknesses, we need to consider and analyse the security aspects and establish a flexible policy-aware Service Oriented Architecture (SOA) competent to deal with these emerging challenges. This paper presents the existing reference models and proposes a novel Secure M2M Architecture (SeMMA) based on ETSI's M2M communication functional architecture enhanced with policy-based management capabilities and SOA capabilities. We explore the policy-based management aspects to improve the security of the M2M components and services and to mitigate the security concerns that arise by evaluating different scenarios. It is shown that incorporating an adaptive policy enforcement of the suitable security controls enables enhanced security capabilities, increased agility, and better service levels in the field of M2M communications.

Access to Device Reachability Data as a Component of Horizontal M2M Service Platform

The variety of Machine-to-Machine (M2M) applications based on very heterogeneous forms of platforms, technology, and data models has resulted in vertical solutions where interoperability is very limited. In order to develop horizontal platforms across different business domains, networks and devices, it is necessary to outline generic capabilities. Service Capabilities provide data mediation functions that may be shared by different applications through application programming interfaces. The paper presents an approach to design RESTful Web Services for access to location and presence status information of M2M devices. The Device Reachability Service Capability provides access to device location and allows device presence information to be registered and obtained. Web Service operations are identified by analysis on typical use cases. M2M device reachability information is modelled as REST resources organized in a tree structure. Web Service performance characteristics are evaluated by simulation.

Efficient and Improved Navigation Application for Smart Devices in IoT Environment

Smart cities are not merely the infusion of technology into a city’s infrastructure, but also require citizens interacting with their urban environment in a smart and informed manner. Transportation is key aspect of smart cities, where new route-planning applications provide as connected Car applications. For example, On-Board Human-Machine Interface (HMI) Apps, smartphone apps, API development, OBD-II, and SDL. Moreover, by using proprietary mobile apps, it is possible to get the GPS coordinates of a car, trace its route, open its doors, start its engine, and turn on its auxiliary devices. In addition, to study the usage of ICT to enhance quality and performance of urban services, reduce costs and resource consumption, and engage more effectively and actively with its citizens. The IoT is enabled by the latest developments in RFID, smart sensors, communication technologies, and Internet protocols. The basic premise is to have smart sensors collaborate directly without human involvement to deliver a new class of applications. The current revolution in Internet, mobile, and machine-to-machine (M2M) technologies can be seen as the first phase of the IoT. In the coming years, the IoT is expected to bridge diverse technologies to enable new applications by connecting physical objects together in support of intelligent decision making. This paper presents an overview of technical details that pertain to the IoT enabling technologies and applications. Compared to other survey papers in the field, our objective is to provide a more thorough summary of the most relevant application issues to enable researchers and application developers to get up to speed quickly on how ICT provide new route-planning application using IoT. We also provide an overview of some of the key IoT and M2M challenges presented in the recent literature and provide a summary of related research work. Moreover, we explore the relation between the IoT and M2M technologies. Also, present the need for better horizontal integration among IoT services. Finally, we present detailed service use-cases to illustrate how the different solutions presented in the paper fit together to deliver desired IoT &amp; M2M services. Since more devices are connected to the Internet every day and for various purposes, this will generate increasing amounts of data that will need to be crunched. New and better analytics systems will have to be developed, not to mention cloud storage space to deal with all the data.

Analysis of a Hybrid Priority Scheme for Multiclass M2M Communications Over LTE-A Networks

Machine-to-machine (M2M) communication is one of the promising technologies to provide smart and efficient services for the advanced long term evolution (LTE-A) networks. Therefore, the mobile network operators find huge potential by enabling M2M communication in LTE-A systems. However, number of M2M devices over LTE-A network require additional transmission resources due to heterogeneous requirement that generates a major issue of allocating the available resources between the primary service of human-to-human (H2H) communications and multiple M2M services. This paper proposes a hybrid preemptive/non-preemptive resume priority scheme that is able to handle the heterogeneity requirements of M2M services while incorporating to LTE networks. In the proposed model, the relations between H2H and M2M are preemptive, whereas M2M and M2M are non-preemptive. In addition, we classify the M2M traffic into a number of classes based on the delay sensitivity of each traffic services. The analytical model is developed to evaluate the delay performance of the proposed scheme. Moreover, the comparison based on simulation results is conducted between the proposed scheme and two existing state-of-the-art resource allocation schemes. Based on the numerical results, the proposed scheme performed better in terms of extended transmission time reduction.

A Review of Wireless and Satellite-Based M2M/IoT Services in Support of Smart Grids

The Smart Grid (SG) is an evolution of the electricity network that dynamically integrates the activities and energy control of power consumers, power generators, distribution systems, and devices connected to the grid (e.g., substations, transformers, and so on). The goal of the SG is to economically and efficiently deliver a sustainable, reliable, and secure electricity supply. Machine-to-Machine (M2M) technology is designed for automated data exchange between devices, and thus has applicability to SGs. With M2M technology, organizations track and manage assets; inventories; transportation fleets; oil and gas pipelines; mines; wide-spread infrastructure; natural phenomena such as weather conditions, crop production, forestry condition, and water flows; and, as noted, SGs. Wireless communication is a staple of M2M. These wireless technologies range from unlicensed local connectivity, to licensed 3G/4G/5G cellular, to Low Earth Orbit (LEO) satellites. All of these technologies are relevant to the SG. Utilities have started to gradually support M2M and Supervisory Control And Data Acquisition (SCADA) systems over satellite links. This article focuses on wireless and satellite-based M2M services, as applicable to the Smart Grid, including the use of Internet of Things (IoT), particularly for the transmission and distribution (TD some comparisons to wireline solutions are also discussed.

Measurement-Based Signaling Management Strategies for Cellular IoT

In the future, all devices that benefit from an Internet connection will be connected. Internet of Things technologies are key enablers of this vision by moving beyond basic connectivity machine-to-machine (M2M) communications brings to more intelligent interconnection of physical things on a massive scale. This anticipated growth is expected to challenge the planning and operation of cellular networks due to new diverse traffic models and high signaling loads. In this paper, we conduct a detailed experimental study using state-of-the-art drive testing equipment in order to measure, quantify, and analyze the signaling overhead of two classes of M2M services that resemble smart metering and vehicular applications. Two practical signaling reduction techniques are proposed and analyzed, with focus on aggregation as an efficient approach to overcome the resulting surge in signaling load. We complement the experimental results with an analytical evaluation to quantify the tradeoffs between M2M data transmission delay and the level of aggregation. Moreover, we present a novel case study to assess the potential negative impact of M2M signaling traffic on network planning and operation in 4G cellular networks.

Exploiting the Capture Effect to Enhance RACH Performance in Cellular-Based M2M Communications.

Cellular-based machine-to-machine (M2M) communication is expected to facilitate services for the Internet of Things (IoT). However, because cellular networks are designed for human users, they have some limitations. Random access channel (RACH) congestion caused by massive access from M2M devices is one of the biggest factors hindering cellular-based M2M services because the RACH congestion causes random access (RA) throughput degradation and connection failures to the devices. In this paper, we show the possibility exploiting the capture effects, which have been known to have a positive impact on the wireless network system, on RA procedure for improving the RA performance of M2M devices. For this purpose, we analyze an RA procedure using a capture model. Through this analysis, we examine the effects of capture on RA performance and propose an Msg3 power-ramping (Msg3 PR) scheme to increase the capture probability (thereby increasing the RA success probability) even when severe RACH congestion problem occurs. The proposed analysis models are validated using simulations. The results show that the proposed scheme, with proper parameters, further improves the RA throughput and reduces the connection failure probability, by slightly increasing the energy consumption. Finally, we demonstrate the effects of coexistence with other RA-related schemes through simulation results.

기계 간 통신 서비스에 따라 자원 효율을 최대화하는 LTE 시스템 변수 최적화

기계 간 통신 서비스에 따라 자원 효율을 최대화하는 LTE 시스템 변수 최적화

An Approach to Self-Configuration of M2M Services

Abstract The increased number of connected devices and Machine-to-Machine (M2M) applications becomes business and technical challenge for network operators. The complexity of connectivity challenge yields for appropriate connectivity management solutions. The explosion of M2M services may result in undesired service interaction. Despite of the considerable progress in service interaction management, there is a lack of knowledge on the kind of interaction in real M2M communication systems. In this paper, a method for service orchestration between M2M applications which add value to basic device connectivity management is proposed. The automatic resolving of service interaction using policies allows service self-configuration and provisioning of adaptive service continuity to end users.

사물지능통신(M2M)을 위한 하이브리드 스펙트럼 센싱 시스템

본 논문에서는 M2M 서비스를 위한 클러스터 기반의 혼합 스펙트럼 센싱 시스템에 대하여 연구한다. 클러스터 내에서, 주 노드의 전송반경 이내의 부 노드들은 국부 스펙트럼 센싱을 통한 경판정 방법을 사용하여 주 노드의 존재 유무를 판단하며, 그 이외의 부 노드들과 무선 채널 환경이 좋지 않은 부 노드들은 협력 스펙트럼 센싱을 수행하여 얻은 값들을 연판정 방법을 통해 주사용자의 존재를 판단한다. 레일리 페이딩 채널하에서, 제안된 혼합 스펙트럼 센싱 시스템에서, 부 노드들의 수에 따른 성능을 기존 시스템과 분석한다. 협력 센싱을 수행하는 사용자의 수를 2, 3, 4로 증가함에 따라 클러스터 오류확률은 SNR이 -10[dB]에서 각각 0.5608, 0.5252, 0.4001으로 감소됨을 알 수 있었다. 제안된 시스템은 연판정-연판정, 연판정-경판정 방법을 사용하는 기존 시스템 보다 적은 오버헤드 트래픽을 사용하므로 주파수 이용 측면에서도 효과적임을 알 수 있었다. This paper presents cluster based hybrid spectrum sensing system for M2M services. For each cluster, secondary nodes within the transmission radius of the primary node use hard decision method through local spectrum sensing to determine whether the primary node exists. And the other secondary nodes and the secondary nodes having poor radio channel conditions judge the existence of the primary node through the soft decision method of the values obtained by performing the cooperative spectrum sensing. In the proposed hybrid spectrum sensing system, the performance according to the number of secondary nodes is analyzed with the conventional system over Rayleigh fading channel. As the number of cooperative sensing users increased to 2, 3 and 4, the cluster error probability decreased to 0.5608, 0.5252 and 0.4001 at SNR of -10[dB] respectively. Since the proposed system uses less overhead traffic, it is found that it is more effective in terms of frequency usage than the conventional system using soft decision-soft decision and soft decision-hard decision methods.

Internet of Things (IoT) with Cloud Computing and Machine-to-Machine (M2M) Communication

The Internet of Things (IoT) is a new revolution of the Internet. Objects make themselves recognizable and they obtain intelligence by making or enabling context related decisions. They can communicate information about themselves. They can access information that has been aggregated by other things, or they can be components of complex services. The three important factors propelling the IoT forward are Sensing Nodes, Embedded Processing and Communication. This transformation is accompanied with the emergence of cloud computing capabilities supported by an increase in storage capacity and high end processing and the Machine-to-Machine (M2M) communication for data transport with security. By introducing cloud computing technology, we can make a full call to the storage resource pool and computing resource pool in the cloud computing architecture, and provide high reliability for IoT cloud storage service and efficient cloud computing services to users. The service layer for M2M type of communication will provide a framework for the integration of the different communication technologies deployed in the field of IoT. This M2M service layer will provide the needed services like data transport, security, devices management and device discovery in a harmonized manner across a multitude of vertical domains to the application layer. In this paper, a brief introduction of IoT is given and the IoT with cloud storage and M2M communication is explained. The main issues of IoT related with storage, requirement of high end devices, security, privacy, data transport can be solved by the combination of IoT with cloud computing and M2M communication. This will also benefit the IoT in its ease of use in day-to-day life and believe to be future in this area which is getting ready for its revolution.

Performance of Quantized Random Beamforming in Delay-Tolerant Machine-Type Communication

Machine-to-machine (M2M) communication represents a new paradigm for mobile cellular networks, where a massive number of low-cost devices request the transfer of small amounts of data without human intervention. One option to tackle this problem is obtained by combining random beamforming (RBF) with opportunistic scheduling. RBF can be used to induce larger channel fluctuations, and opportunistic scheduling can be used to select M2M devices when their overall channel quality is good. Traditional RBF does not fulfill M2M requirements, because overall channel quality needs to be tracked continuously. In order to tackle this limitation, a novel codebook-based RBF architecture that identifies in advance the time instants in which overall channel quality should be reported, within a coherence time window, is proposed. This opportunistic feedback mechanism reduces signaling overhead and enables energy saving at M2M devices. A simplified methodology is presented to evaluate the system mean data rate, using for this purpose closed form formulas derived from SNR distribution approximations. Results reveal that the performance loss that is experienced for introducing the proposed modifications to traditional RBF scheme is negligible. The concepts analyzed in this paper provide useful insights, and show that codebook-based RBF with simplified opportunistic scheduling algorithms is an excellent combination to provide wide-area M2M services with low-cost devices and limited signaling overhead.