Impact of Machine-to-Machine Traffic on LTE Data Traffic Performance

Yasir Mehmood; Thomas  Potsch; Safdar Nawaz Khan Marwat; Farhan Ahmad; Carmelita Goerg; Imran Rashid

doi:10.1007/978-3-319-23512-7_25

Impact of Machine-to-Machine Traffic on LTE Data Traffic Performance

Yasir Mehmood, Thomas Potsch, Safdar Nawaz Khan Marwat, Farhan Ahmad, Carmelita Goerg, Imran Rashid

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

3 Citations (Scopus)

Abstract

Machine-to-machine (M2M) communication is an emerging paradigm in which trillions of intelligent devices are expected to communicate without or with small human intervention. The increasing M2M devices have severe impact on long-term evolution (LTE) data traffics. Moreover, the behavior of M2M traffic also differs from traditional mobile traffic. In future, logistics and transportations are considered to be the main M2M application areas. These applications disparately demand more efficient M2M traffic modeling to reduce end-to-end (E2E) delay between various interconnected machines. This paper investigates several traffic models and highlights the impact of M2M traffic in logistics and transportation on LTE data traffic. We evaluate the overall LTE network performance in terms of E2E delays for file transfer, voice, and video users.

Original language	English
Title of host publication	Dynamics in Logistics
Subtitle of host publication	Proceedings of the 4th International Conference LDIC, 2014 Bremen, Germany
Publisher	Springer Verlag
Pages	259-269
Number of pages	11
ISBN (Electronic)	978-3-319-23512-7
ISBN (Print)	978-3-319-23511-0
DOIs	https://doi.org/10.1007/978-3-319-23512-7_25
Publication status	Published - 22 Dec 2015
Externally published	Yes

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10.1007/978-3-319-23512-7_25

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Impact of Machine-to-Machine Traffic on LTE Data Traffic Performance. / Mehmood, Yasir; Potsch, Thomas ; Khan Marwat, Safdar Nawaz et al.
Dynamics in Logistics: Proceedings of the 4th International Conference LDIC, 2014 Bremen, Germany. Springer Verlag, 2015. p. 259-269.

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

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AU - Mehmood, Yasir

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AU - Goerg, Carmelita

AU - Rashid, Imran

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N2 - Machine-to-machine (M2M) communication is an emerging paradigm in which trillions of intelligent devices are expected to communicate without or with small human intervention. The increasing M2M devices have severe impact on long-term evolution (LTE) data traffics. Moreover, the behavior of M2M traffic also differs from traditional mobile traffic. In future, logistics and transportations are considered to be the main M2M application areas. These applications disparately demand more efficient M2M traffic modeling to reduce end-to-end (E2E) delay between various interconnected machines. This paper investigates several traffic models and highlights the impact of M2M traffic in logistics and transportation on LTE data traffic. We evaluate the overall LTE network performance in terms of E2E delays for file transfer, voice, and video users.

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Impact of Machine-to-Machine Traffic on LTE Data Traffic Performance

Abstract

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