An Analytical Model Based on Population Processes to Characterize Data Dissemination in 5G Opportunistic Networks
Author(s) -
Enrique Hernandez-Orallo,
Marina Murillo-Arcila,
Juan-Carlos Cano,
Carlos T. Calafate,
J. Alberto Conejero,
Pietro Manzoni
Publication year - 2018
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2017.2779748
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
The scarcity of bandwidth due to the explosive growth of mobile devices in 5G makes the offloading messaging workload to Wi-Fi devices that use opportunistic connections, a very promising solution. Communications in mobile opportunistic networks take place upon the establishment of ephemeral contacts among mobile nodes using direct communication. In this paper, we propose an analytical model based on population processes to evaluate data dissemination considering several parameters, such as user density, contact rate, and the number of fixed nodes. From this model, we obtain closed-form expressions for determining the diffusion time, the network coverage, and the waiting time. Newer 5G wireless technologies, such as WiGig, can offer multi-gigabit speeds, low latency, and security-protected connectivity between nearby devices. We therefore focus our work on the impact of high-speed and short-range wireless communications technologies for data dissemination in mobile opportunistic networks. Moreover, we test whether the coexistence with a fixed infrastructure can improve content dissemination, and thus justify its additional cost. Our results show that, when user density is high, the diffusion is mainly performed through the opportunistic contacts between mobile nodes, and that the diffusion coverage is close to 100%. Moreover, the diffusion is fast enough to dynamically update the information among all the participating members, so users do not need to get closer to fixed spots for receiving updated information.
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