The recent developments in the Internet of Things related technologies have caused a shift towards smart applications such as smart cities, smart homes, smart education systems, e-health, and online applications to run businesses. These, in turn, have introduced significant additional loads to the existing network infrastructures. In addition, these applications use big data and require relatively short response times. In this paper, we are introducing a new scheduling and routing approach to enhance the end user experience, and utilize the network resources by providing improved transmission speed for the big data applications. The approach considers the source and destination requirements in terms of data size, expected delay, link load, and link capacity. Extensive simulations are performed, and the results obtained show the efficiency of our approach against other competitive approaches in terms of in-network delay, network throughput, and dropped packets.

Network Experience Scheduling and Routing Approach for Big Data Transmission in the Internet of Things

Mostarda, Leonardo;
2019

Abstract

The recent developments in the Internet of Things related technologies have caused a shift towards smart applications such as smart cities, smart homes, smart education systems, e-health, and online applications to run businesses. These, in turn, have introduced significant additional loads to the existing network infrastructures. In addition, these applications use big data and require relatively short response times. In this paper, we are introducing a new scheduling and routing approach to enhance the end user experience, and utilize the network resources by providing improved transmission speed for the big data applications. The approach considers the source and destination requirements in terms of data size, expected delay, link load, and link capacity. Extensive simulations are performed, and the results obtained show the efficiency of our approach against other competitive approaches in terms of in-network delay, network throughput, and dropped packets.
2019
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11391/1569088
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 32
  • ???jsp.display-item.citation.isi??? 25
social impact