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

Autor:	Yasir Mehmood, Carmelita Görg, Thomas Pötsch, Imran Rashid, Farhan Ahmad, Safdar Nawaz Khan Marwat
Rok vydání:	2015
Předmět:	Data traffic Mobile traffic Machine to machine Application areas Computer science business.industry ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS File transfer Network performance business Traffic generation model Computer network
Zdroj:	Dynamics in Logistics ISBN: 9783319235110 LDIC
DOI:	10.1007/978-3-319-23512-7_25
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::db205366035193a607a30820025cd7c5 https://doi.org/10.1007/978-3-319-23512-7_25 Zobrazit plný text záznamu