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Scientific Article details

Title Collecting Sensed Data with Opportunistic Networks: The Case of Contact Information Overhead
ID_Doc 41342
Authors Amah, TE; Kamat, M; Bakar, K; Abd Rahman, SO; Mohammed, MH; Abali, AM; Moreira, W; Oliveira, A
Title Collecting Sensed Data with Opportunistic Networks: The Case of Contact Information Overhead
Year 2017
Published Information, 8, 3
DOI 10.3390/info8030108
Abstract The rising human population in urban environments drives the mission towards smart cities, which envisions a wide deployment of sensors in order to improve the quality of living. In this regard, opportunistic networks (OppNets) present an economical means of collecting delay tolerant data from sensors to their respective gateways for providing various Smart City services. Due to the distributed nature of the network, encounter-based routing protocols achieve acceptable throughput by requiring nodes to exchange and update contact information on an encounter basis. Unfortunately, sufficient insight into the associated overhead is lacking in the literature. Hence, we contribute by modelling contact information overhead and investigating its impact on OppNet routing, particularly in terms of data exchange success and energy consumption on portable handheld devices. Our findings reveal that the expected contact information overhead in Smart City scenarios significantly reduces data exchange success and increases energy consumption on portable handheld devices, thereby threatening the feasibility of the technology. We address this issue by proposing an algorithm that can be incorporated into encounter-based routing protocols to reduce contact information overhead without compromising throughput. Simulation results show that our proposed algorithm reduces the average contact information overhead, increases throughput and reduces average energy consumption.
Author Keywords opportunistic networks; delay tolerant data; sensed data collection; routing; wireless sensors; Smart City; Internet of things; smartphones
Index Keywords Index Keywords
Document Type Other
Open Access Open Access
Source Emerging Sources Citation Index (ESCI)
EID WOS:000418508900038
WoS Category Computer Science, Information Systems
Research Area Computer Science
PDF https://www.mdpi.com/2078-2489/8/3/108/pdf?version=1504617074
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