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http://hdl.handle.net/10609/112466
Title: Delay and energy consumption analysis of frame slotted ALOHA variants for massive data collection in internet-of-things scenarios
Author: Vázquez Gallego, Francisco
Tuset Peiró, Pere  
Alonso Zarate, Luis
Alonso Zarate, Jesús
Others: Centre Tecnològic de Telecomunicacions de Catalunya
Universitat Politècnica de Catalunya
Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3)
Keywords: massive communication
data collection
medium access control
frame slotted ALOHA
delay
energy consumption
internet of things
Issue Date: 1-Jan-2020
Publisher: Applied Sciences
Citation: Vázquez-Gallego, F., Tuset-Peiró, P., Alonso, L. & Alonso-Zarate, J. (2020). Delay and Energy Consumption Analysis of Frame Slotted ALOHA variants for Massive Data Collection in Internet-of-Things Scenarios. Applied Sciences, 10(1), 1-16. doi: 10.3390/app10010327
Project identifier: info:eu-repo/grantAgreement/SGR-60-2017
info:eu-repo/grantAgreement/SGR-891-2017
info:eu-repo/grantAgreement/TEC2017-87456-P
info:eu-repo/grantAgreement/RTI2018-095438-A-I00
Also see: https://doi.org/10.3390/app10010327
Abstract: This paper models and evaluates three FSA-based (Frame Slotted ALOHA) MAC (Medium Access Control) protocols, namely, FSA-ACK (FSA with ACKnowledgements), FSA-FBP (FSA with FeedBack Packets) and DFSA (Dynamic FSA). The protocols are modeled using an AMC (Absorbing Markov Chain), which allows to derive analytic expressions for the average packet delay, as well as the energy consumption of both the network coordinator and the end-devices. The results, based on computer simulations, show that the analytic model is accurate and outline the benefits of DFSA. In terms of delay, DFSA provides a reduction of 17% (FSA-FBP) and 32% (FSA-ACK), whereas in terms of energy consumption DFSA provides savings of 23% (FSA-FBP) and 28% (FSA-ACK) for the coordinator and savings of 50% (FSA-FBP) and 24% (FSA-ACK) for end-devices. Finally, the paper provides insights on how to configure each FSA variant depending on the network parameters, i.e., depending on the number of end-devices, to minimize delay and energy expenditure. This is specially interesting for massive data collection in IoT (Internet-of-Things) scenarios, which typically rely on FSA-based protocols and where the operation has to be optimized to support a large number of devices with stringent energy consumption requirements.
Language: English
URI: http://hdl.handle.net/10609/112466
ISSN: 2076-3417MIAR
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