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

Yasir Mehmood, Thomas Pötsch, Safdar Nawaz Khan Marwat, Farhan Ahmad, Carmelita Görg, Imran Rashid

Research output: Chapter in Book/Report/Conference proceedingChapter

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 languageEnglish (US)
Title of host publicationLecture Notes in Logistics
PublisherSpringer Science and Business Media B.V.
Pages259-269
Number of pages11
DOIs
StatePublished - 2016

Publication series

NameLecture Notes in Logistics
ISSN (Print)2194-8917
ISSN (Electronic)2194-8925

Keywords

  • LTE
  • LTE data traffic
  • M2M
  • Traffic modeling

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Mechanical Engineering

Fingerprint Dive into the research topics of 'Impact of Machine-to-Machine Traffic on LTE Data Traffic Performance'. Together they form a unique fingerprint.

Cite this