A Survey of Traffic Issues in Machine-to-Machine Communications Over LTE

Timely message delivery is a key enabler for Internet of Things (IoT) and cyber-physical systems to support wide range of context-dependent applications. Conventional time-related metrics (e.g. delay and jitter) fails to characterize the timeliness of the system update. Age of information (AoI) is a time-evolving metric that accounts for the packet inter-arrival and waiting times to assess the freshness of information. In the foreseen large-scale IoT networks, mutual interference imposes a delicate relation between traffic generation patterns and transmission delays. To this end, we provide a spatiotemporal framework that captures the peak AoI (PAoI) for large scale IoT uplink network under time-triggered (TT) and event triggered (ET) traffic. Tools from stochastic geometry and queueing theory are utilized to account for the macroscopic and microscopic network scales. Simulations are conducted to validate the proposed mathematical framework and assess the effect of traffic load on PAoI. The results unveil a counter-intuitive superiority of the ET traffic over the TT in terms of PAoI, which is due to the involved temporal interference correlations. Insights regarding the network stability frontiers and the location-dependent performance are presented. Key design recommendations regarding the traffic load and decoding thresholds are highlighted.

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“…. (6) Using the intensity function in (6), the transmission success probability in the TT traffic model is defined as…”

Section: Across Different Time Slots Within the Same Cycle T By An Apmentioning

confidence: 99%

A Spatiotemporal Model for Peak AoI in Uplink IoT Networks: Time Versus Event-Triggered Traffic

Emara

ElSawy

Bauch

2020

IEEE Internet Things J.

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“…Cellular communication technologies defined by 3GPP [20], 4G machine-to-machine communications [21] or Machine Type Communications (MTC) [22] are still emerging. For instance, in [23], the authors analyze the potential of 5G cellular systems for being a key driver in a global IoT, considering both the technological and standardization aspects.…”

Section: Related Workmentioning

confidence: 99%

Home Automation System Based on Intelligent Transducer Enablers

Suárez-Albela

Fraga‐Lamas

Fernández‐Caramés

et al. 2016

Sensors

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This paper presents a novel home automation system named HASITE (Home Automation System based on Intelligent Transducer Enablers), which has been specifically designed to identify and configure transducers easily and quickly. These features are especially useful in situations where many transducers are deployed, since their setup becomes a cumbersome task that consumes a significant amount of time and human resources. HASITE simplifies the deployment of a home automation system by using wireless networks and both self-configuration and self-registration protocols. Thanks to the application of these three elements, HASITE is able to add new transducers by just powering them up. According to the tests performed in different realistic scenarios, a transducer is ready to be used in less than 13 s. Moreover, all HASITE functionalities can be accessed through an API, which also allows for the integration of third-party systems. As an example, an Android application based on the API is presented. Remote users can use it to interact with transducers by just using a regular smartphone or a tablet.

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“…simultaneous access attempts from many machines reacting to the same events), while HTC (Human Type Communication) is uncoordinated one. The QoS requirements of MTC are different in terms of security, reliability and latency [3].…”

Section: Introductionmentioning

confidence: 99%

Fixed Rate Statistical QoS Provisioning for Markovian Sources in Machine Type Communication

Qasmi

Shehab

Alves

2019

2019 16th International Symposium on Wireless Communication Systems (ISWCS)

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In this paper, we study the trade-off between reliability and latency in machine type communication (MTC), which consists of single transmitter and receiver in the presence of Rayleigh fading channel. We assume that the transmitter does not know the channel conditions, therefore it would be transmitting information over a fixed rate. The fixed rate transmission is modeled as a two-state continuous-time Markov process, where the optimum transmission rate is obtained. Moreover, we conduct a performance analysis for different arrival traffic originated from MTC device via effective rate transmission. We consider that the arrival traffic is modeled as a Markovian process namely Discrete-Time Markov process, Fluid Markov process, and Markov Modulated Poisson process, under delay violation constraints. Using effective bandwidth and effective capacity theories, we evaluate the trade-off between reliability-latency and identify QoS (Quality of Service) requirement, and derive lower and upper bounds for the effective capacity subject to channel memory decay rate limits.

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A Survey of Traffic Issues in Machine-to-Machine Communications Over LTE

Cited by 137 publications

References 71 publications

A Spatiotemporal Model for Peak AoI in Uplink IoT Networks: Time Versus Event-Triggered Traffic

A Spatiotemporal Model for Peak AoI in Uplink IoT Networks: Time Versus Event-Triggered Traffic

Home Automation System Based on Intelligent Transducer Enablers

Fixed Rate Statistical QoS Provisioning for Markovian Sources in Machine Type Communication

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