The Impact of Message Replication on the Performance of Opportunistic Networks for Sensed Data Collection

Information

Muhammad Hafiz Mohammed¹  Aliyu M. Abali¹  Tekenate E. Amah¹  Kamalrulnizam Abu Bakar¹  Maznah Kamat¹  Syed Othmawi Abd Rahman¹  Waldir Moreira²  Antonio Oliveira-Jr³ 

[1] Department of Computer Science, Faculty of Computing, Universiti Teknologi Malaysia, Skudai 81310, Johor, Malaysia;Fraunhofer-AICOS, Porto 4200-135, Portugal;Institute of Informatics, Federal University of Goiás, Goiânia 74690-900, GO, Brazil;

关键词: opportunistic networks;    delay tolerant data;    sensed data collection;    routing;    wireless sensors;    smart city;    Internet of Things;    smartphones;   

DOI  :  10.3390/info8040143

来源: DOAJ

【 摘 要 】

Opportunistic networks (OppNets) provide a scalable solution for collecting delay‑tolerant data from sensors for their respective gateways. Portable handheld user devices contribute significantly to the scalability of OppNets since their number increases according to user population and they closely follow human movement patterns. Hence, OppNets for sensed data collection are characterised by high node population and degrees of spatial locality inherent to user movement. We study the impact of these characteristics on the performance of existing OppNet message replication techniques. Our findings reveal that the existing replication techniques are not specifically designed to cope with these characteristics. This raises concerns regarding excessive message transmission overhead and throughput degradations due to resource constraints and technological limitations associated with portable handheld user devices. Based on concepts derived from the study, we suggest design guidelines to augment existing message replication techniques. We also follow our design guidelines to propose a message replication technique, namely Locality Aware Replication (LARep). Simulation results show that LARep achieves better network performance under high node population and degrees of spatial locality as compared with existing techniques.

【 授权许可】

Unknown