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The machine economy (ME) is an emergent phenomenon that combines multiple emerging digital technologies, such as Internet of Things (IoT), artificial intelligence (AI), or blockchain, enabling economically autonomous acting machines. We investigate this phenomenon by combining a literature review and a qualitative interview study across different industries to derive propositions about the ME. Finally, we develop a five-layer model of the ME from our propositions that helps academia and practice explore this emerging phenomenon further. Our results indicate that the ME builds on several emerging digital technologies and becomes increasingly relevant for practice and academia. [ABSTRACT FROM AUTHOR]

In future wireless communication, a large number of devices equipped with several different types of sensors will require access networks with diverse quality-of-service constraints. In cellular network evolution, the long term evolution advanced (LTE-A) networks has standardized Machine-to-Machine (M2M) features. Such M2M technology can provide a promising infrastructure for Internet of things (IoT) sensing applications, which usually require real-time data reporting. However, LTE-A is not designed for directly supporting such low-data-rate devices with optimized energy efficiency since it depends on core technologies of LTE that are originally designed for high-data-rate services. This paper investigate the maximum energy efficient data packets M2M transmission with uplink channels in LTE-A network. We formulate it into a joint problem of Modulation-and-Coding Scheme (MCS) assignment, resource allocation and power control, which can be expressed as a non-deterministic polynomial hard (NP-hard) mixed-integer linear fractional programming problem. Then we propose a global optimization scheme with Charnes-Cooper transformation and Glover linearization. The numerical experiment results show that with limited resource blocks, our algorithm can maintain low data packets dropping ratios while achieving optimal energy efficiency for a large number of M2M nodes, comparing with other typical counterparts. [ABSTRACT FROM AUTHOR]

The rapid development of technology has brought about a revolution in healthcare stimulating a wide range of smart and autonomous applications in homes, clinics, surgeries and hospitals. Smart healthcare opens the opportunity for a qualitative advance in the relations between healthcare providers and end-users for the provision of healthcare such as enabling doctors to diagnose remotely while optimizing the accuracy of the diagnosis and maximizing the benefits of treatment by enabling close patient monitoring. This paper presents a comprehensive review of non-invasive vital data acquisition and the Internet of Things in healthcare informatics and thus reports the challenges in healthcare informatics and suggests future work that would lead to solutions to address the open challenges in IoT and non-invasive vital data acquisition. In particular, the conducted review has revealed that there has been a daunting challenge in the development of multi-frequency vital IoT systems, and addressing this issue will help enable the vital IoT node to be reachable by the broker in multiple area ranges. Furthermore, the utilization of multi-camera systems has proven its high potential to increase the accuracy of vital data acquisition, but the implementation of such systems has not been fully developed with unfilled gaps to be bridged. Moreover, the application of deep learning to the real-time analysis of vital data on the node/edge side will enable optimal, instant offline decision making. Finally, the synergistic integration of reliable power management and energy harvesting systems into non-invasive data acquisition has been omitted so far, and the successful implementation of such systems will lead to a smart, robust, sustainable and self-powered healthcare system. [ABSTRACT FROM AUTHOR]

Machine-to-machine (M2M) communication devices communicate and exchange information with each other in an independent manner to perform necessary tasks. The machine communicates with another machine over a wireless network. Wireless communication opens up the environment to huge vulnerabilities, making it very easy for hackers to gain access to sensitive information and carry out malicious actions. This paper proposes an M2M communication system through the internet in Tele-Robotics and provides network performance security. Tele-robotic systems are designed for surgery, treatment and diagnostics to be conducted across short or long distances while utilizing wireless communication networks. The systems also provide a low delay and secure communication system for the tele-robotics community and data security. The system can perform tasks autonomously and intelligently, minimizing the burden on medical staff and improving the quality and system performance of patient care. In the medical field, surgeons and patients are located at different places and connected through public networks. So the design of a medical sensor node network with LEACH protocol for secure and reliable communication ensures through the attack and without attack performance. Finally, the simulation results show low delay and reliable secure network transmission.

To meet the increased requirement of machine-to-machine (M2M) communication, the potential to support massive access with sporadic traffic in uplink of two typical methods, one is the collision avoidance (CA) method at the user side, and the other is the collision resolution (CR) method at the base station (BS) side, is explored under grant-free protocol in this paper. A comprehensive study from MAC layer is conducted under the proposed distributed queue model, which describes the queue behavior of each device and the interaction between devices under grant-free protocol. The upper bounds of the throughput and the success probability of CA method are derived and the closed forms of the throughput and the success probability of a typical CR method, known as power domain multiple access (PDMA), are derived. The performance is further analyzed besides delay and stability. Through simulations, we validate that there is a hopeful upper bound for CA method, and the performance of PDMA can be flexibly improved with variable power level, which has a similar effect with channel extension. On the other hand, we note that grant-free protocol is suitable for access when the input traffic is below a critical threshold, otherwise packets would be blocked at the queue and the delay would increase infinitely.

The Media Access Control (MAC) serves as an imperative part of wireless communication networks which enables efficient provisioning of communication resources for device interconnectivity and ensures Quality of Service (QoS). The emergence of Large-Scale Internet of Things (LS-IoT) networks is characterised by a multi-domain distributed wireless communication network that provides end-to-end connectivity for a multitude of active heterogeneous Machine-to-Machine (M2M) devices. The nature of LS-IoT networks requires robust and scalable MAC protocols to manage concurrent, dynamic and massive media access and resource allocation. Several reviews have been conducted on MAC protocols with a handful of them focused on LS-IoT networks or massive M2M networks. In this paper, the characterisation of LS-IoT networks and the MAC component are extensively discussed delineating the impact of LS-IoT on the MAC. Emerging research issues on the MAC for LS-IoT networks including high collision probability, high control overheads, spectrum constraints, timing constraints, hardware constraints, energy consumption and hidden terminals are discussed. Some recently proposed solutions in literature for enhancing the MAC in LS-IoT networks are discussed under LS-IoT specific MAC protocol enhancement classifications. The contributions and drawbacks of the recent solutions in literature are discussed and summarised. The Future direction that is oriented towards the use of virtualisation within the framework of Network Function Virtualisation (NFV) and Software-Defined Networking (SDN) approaches is proposed. This is aimed at providing a dynamic distributed multidimensional MAC resource scaling approach for LS-IoT access network devices to ensure a robust and effective MAC for massive M2M devices in LS-IoT networks.

RPL, the standard IPv6 routing protocol for low-power and lossy networks in the emerging Internet of things (IoT), is designed mainly for efficient many-to-one data collection scenarios where the majority of the traffic flows from embedded devices to a gateway. Although RPL does support root-to-node downwards routing and peer-to-peer (P2P) communication, its P2P performance is inefficient and unsatisfactory due to excessively high churn and bottlenecks in the P2P path. However, P2P routing is important for machine-to-machine communication where nodes in IoT applications communicate with one another and control devices beyond simply collecting data. In this work, we propose a neighbor-graph-based RPL (NG-RPL) that significantly improves P2P routing performance. By including additional routing information when a packet passes through the root node for the first time in a P2P communication, NG-RPL finds efficient P2P routes opportunistically, when available, without significant overhead. We implement NG-RPL in Contiki-NG and evaluate its performance through extensive Cooja simulations. Results show that NG-RPL reduces routing churn, which improves packet reception ratio, round-trip time, and energy usage of P2P communication compared to standard RPL.

The rapid development of technology has brought about a revolution in healthcare stimulating a wide range of smart and autonomous applications in homes, clinics, surgeries and hospitals. Smart healthcare opens the opportunity for a qualitative advance in the relations between healthcare providers and end-users for the provision of healthcare such as enabling doctors to diagnose remotely while optimizing the accuracy of the diagnosis and maximizing the benefits of treatment by enabling close patient monitoring. This paper presents a comprehensive review of non-invasive vital data acquisition and the Internet of Things in healthcare informatics and thus reports the challenges in healthcare informatics and suggests future work that would lead to solutions to address the open challenges in IoT and non-invasive vital data acquisition. In particular, the conducted review has revealed that there has been a daunting challenge in the development of multi-frequency vital IoT systems, and addressing this issue will help enable the vital IoT node to be reachable by the broker in multiple area ranges. Furthermore, the utilization of multi-camera systems has proven its high potential to increase the accuracy of vital data acquisition, but the implementation of such systems has not been fully developed with unfilled gaps to be bridged. Moreover, the application of deep learning to the real-time analysis of vital data on the node/edge side will enable optimal, instant offline decision making. Finally, the synergistic integration of reliable power management and energy harvesting systems into non-invasive data acquisition has been omitted so far, and the successful implementation of such systems will lead to a smart, robust, sustainable and self-powered healthcare system.

Machine-to-machine (M2M) communication devices communicate and exchange information with each other in an independent manner to perform necessary tasks. The machine communicates with another machine over a wireless network. Wireless communication opens up the environment to huge vulnerabilities, making it very easy for hackers to gain access to sensitive information and carry out malicious actions. This paper proposes an M2M communication system through the internet in Tele-Robotics and provides network performance security. Tele-robotic systems are designed for surgery, treatment and diagnostics to be conducted across short or long distances while utilizing wireless communication networks. The systems also provide a low delay and secure communication system for the tele-robotics community and data security. The system can perform tasks autonomously and intelligently, minimizing the burden on medical staff and improving the quality and system performance of patient care. In the medical field, surgeons and patients are located at different places and connected through public networks. So the design of a medical sensor node network with LEACH protocol for secure and reliable communication ensures through the attack and without attack performance. Finally, the simulation results show low delay and reliable secure network transmission. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) and millimeter-wave (mmWave) communication are two important technologies considered for the fifth generation (5G) of mobile networks. In this paper, we propose a machine-to-machine (M2M) communication underlaying heterogeneous network (HetNet) with mmWave-NOMA transmission, where small cell users (SCUs) and machine type communication (MTC) devices share the same resource block (RB) to increase the network capacity. We formulate an optimization problem to select efficient users and allocate transmission powers to SCUs and MTC devices. The object of optimization is to maximize the energy efficiency (EE) subject to the minimum spectral efficiency (SE) requirements and maximum transmission powers. We present a low computational complexity sub-optimum solution based on the non-cooperative game. An iterative algorithm with fast convergence speed and a reduced complexity search-based algorithm are respectively presented to solve the power control and user selection problems. The comparison between the proposed solution and optimum solution for different number of transmit antennas indicate that there is a small gap between SEs and EEs of the proposed and optimum solutions. Further, the results of user selection scheme demonstrate that the location of strong user affects the performance. We also derive analytical expressions for the outage probability which confirm Monte Carlo simulations. [ABSTRACT FROM AUTHOR]

Abstract Machine-to-Machine (M2M) communication technologies enable autonomous networking among devices without human intervention. Such autonomous control is of paramount importance for several deployments of the Internet of Things (IoT), including smart manufacturing applications, healthcare systems and home automation just to name a few. As a result, several M2M technologies are nowadays available on the market as either proprietary solutions or the effort of standardization initiatives, each targeted for a specific class of IoT applications and characterized by unique features in terms of achievable performance, frequency in use and supported network topologies. In this paper, we aim to organize the existing M2M approaches and technologies into a consistent framework that provides an in-depth vision of the main trends, future directions and open issues. We provide three main contributions in this survey. First, we identify the main use cases and requirements of M2M scenarios and we introduce a multi-layer taxonomy for M2M solutions, taking into account both deployment types and PHY/MAC characteristics. Second, in light of such characteristics, we provide an in-depth review of the existing M2M wireless technologies, considering both proprietary and open/standardized solutions for proximity-based, short-range and large-scale networks. Finally, we perform a critical comparison of the surveyed solutions over different M2M use cases and requirements, and we identify the research directions and open issues that still have to be addressed. [ABSTRACT FROM AUTHOR]

The emerging paradigm of Machine to Machine (M2M)-driven Internet of Things (IoT), where physical objects are not disconnected from the virtual world but aim at collectively provide contextual services, calls for enhanced and more energy-efficient resource management approaches. In this paper, the problem is addressed through a joint interest, physical and energy-aware clustering and resource management framework, capitalizing on the wireless powered communication (WPC) technique. Within the proposed framework the numerous M2M devices initially form different clusters based on the low complexity Chinese Restaurant Process (CRP), properly adapted to account for interest, physical and energy related factors. Following that, a cluster-head is selected among the members of each cluster. The proposed approach enables the devices of a cluster with the support of the cluster-head to harvest and store energy in a stable manner through Radio Frequency (RF) signals adopting the WPC paradigm, thus prolonging the operation of the overall M2M network. Each M2M device is associated with a generic utility function, which appropriately represents its degree of satisfaction in relation to the consumed transmission power. Based on the distributed nature of the M2M network, a maximization problem of each device's utility function is formulated as a non-cooperative game and its unique Nash equilibrium point is determined, in terms of devices’ optimal transmission powers. Considering the devices’ equilibrium transmission powers, the optimal charging transmission powers of the cluster-heads are derived. The performance of the proposed approach is evaluated via modeling and simulation and under various topologies and scenarios, and its operational efficiency and effectiveness is demonstrated. [ABSTRACT FROM AUTHOR]

A new scheme to resolve the intra-cell pilot collision for machine-to-machine (M2M) communication in crowded massive multiple-input multiple-output (MIMO) systems is proposed. The proposed scheme permits those failed user equipments (UEs), judged by a strongest-user collision resolution (SUCR) protocol, to contend for the idle pilots, i.e., the pilots that are not selected by any UE in the initial step. This scheme is called as SUCR combined idle pilots access (SUCR-IPA). To analyze the performance of the SUCR-IPA scheme, we develop a simple method to compute the access success probability of the UEs in each random access slot. The simulation results coincide well with the analysis. It is also shown that, compared with the SUCR protocol, the proposed SUCR-IPA scheme increases the throughput of the system significantly, and thus decreases the number of access attempts dramatically. [ABSTRACT FROM PUBLISHER]

In this paper, we propose an early preamble collision detection (e-PACD) scheme at the first step of random access (RA) procedure based on tagged preambles (PAs), which consist of both PA and tag Zadoff–Chu sequences using different root numbers, respectively. The proposed e-PACD scheme enables faster PA collision detection and notification, compared with the conventional RA scheme. Accordingly, it can reduce the RA delay and remove resource wastes which occur at the third step of the conventional RA procedure. The reduced RA delay achieved by the proposed e-PACD scheme can contribute to an ultralow latency requirement in fifth-generation (5G) cellular networks. In addition, the proposed e-PACD scheme enables the eNodeB to monitor the number of RA-attempting nodes (RA load) on each physical RA channel slot. The PACD probability and the RA load monitoring accuracy are mathematically analyzed, and the RA performance enhancement of the proposed scheme is evaluated in terms of RA success probability, average RA delay, and RA resource efficiency, compared with the conventional RA scheme. [ABSTRACT FROM PUBLISHER]

Providing diverse and strict quality-of-service (QoS) guarantees is one of the most important requirements in machine-to-machine (M2M) communications, which is particularly need for appropriate resource allocation for a large number of M2M devices. To efficiently allocate resource blocks (RBs) for M2M devices while satisfying QoS requirements, we propose group-based M2M communications, in which M2M devices are clustered based on their wireless transmission protocols, their QoS characteristics, and their requirements. To perform joint RB and power allocation in SC-FDMA-based LTE-A networks, we formulate a sum-throughput maximization problem, while respecting all the constraints associated with SC-FDMA scheme, as well as QoS requirements in M2M devices. The constraints in uplink SC-FDMA air interface in LTE-A networks complicate the resource allocation problem. We solve the resource allocation problem by first transforming it into a binary integer programming problem and then formulate a dual problem using the Lagrange duality theory. Numerical results show that the proposed algorithm outperforms traditional Greedy algorithm in terms of throughput maximization while satisfying QoS requirements, and its performance is close to the optimal design. [ABSTRACT FROM PUBLISHER]

Wireless power transmission (WPT) is an emerging technology that is gaining increased visibility in recent years. Efficient WPT circuits, systems and strategies can address a large group of applications spanning from batteryless systems, battery-free sensors, passive RF identification, near-field communications, and many others. WPT is a fundamental enabling technology of the Internet of Things concept, as well as machine-to-machine communications, since it minimizes the use of batteries and eliminates wired power connections. WPT technology brings together RF and dc circuit and system designers with different backgrounds on circuit design, novel materials and applications, and regulatory issues, forming a cross disciplinary team in order to achieve an efficient transmission of power over the air interface. This paper aims to present WPT technology in an integrated way, addressing state-of-the-art and challenges, and to discuss future R&D perspectives summarizing recent activities in Europe. [ABSTRACT FROM AUTHOR]

The recent deployment of Cyber-Physical Systems (CPS) has emerged as a promising approach to provide extensive interaction between computational and physical worlds. For a large-scale distributed CPS comprising of numerous machines, sharing radio resource efficiently with the existing wireless networks while maintaining sufficient quality of service (QoS) for machine-to-machine (M2M) communications becomes an essential and challenging requirement. By clustering CPS machines as a swarm with the cluster head managing radio resources inside the swarm, spectrum sharing among numerous machines can be achieved in a distributed and scalable fashion. Specifically, we apply the recent innovation, cognitive radio, and a special mode in cognitive radio, interweave coexistence, to leverage machines to collect radio resource usage information for autonomous and interference-free radio resource management in the CPS. To reduce the communication overheads of channel sensing feedbacking from machines, we apply compressive sensing to construct a spectrum map indicating the radio resource availability on any given locations within the CPS coverage. Such spectrum map resource management (SMRM) only utilizes a small portion of machines to perform channel sensing but enables distributed cluster-based spectrum sharing in an efficient way. Through the concept of effective capacity, the SMRM controls available resources to guarantee the QoS for communications of CPS. By evaluating the performance of the proposed SMRM in the most promising realization of CPS based on LTE-Advanced machine-type communications coexisting with LTE-Advanced Macrocells to utilize identical spectrum, the simulation results show effective QoS guarantees of CPS by SMRM in the realistic environments. [ABSTRACT FROM AUTHOR]

The Constrained Application Protocol (CoAP) is a transfer protocol for constrained nodes and networks, such as those that will form the Internet of Things. Much like its older and heavier cousin HTTP, CoAP uses the REST architectural style. Based on UDP and unencumbered by historical baggage, however, CoAP aims to achieve its modest goals with considerably less complexity. [ABSTRACT FROM AUTHOR]