Pregled bibliografske jedinice broj: 928908
Edge computing architecture for mobile crowdsensing
Edge computing architecture for mobile crowdsensing // IEEE Access, 6 (2018), 1; 10662-10674 doi:10.1109/ACCESS.2018.2799707 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 928908 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Edge computing architecture for mobile crowdsensing
Autori
Marjanović, Martina ; Antonić, Aleksandar ; Podnar Žarko, Ivana ;
Izvornik
IEEE Access (2169-3536) 6
(2018), 1;
10662-10674
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
mobile crowdsensing ; mobile edge computing ; MCS functional architecture ; MEC reference architecture
Sažetak
Mobile crowdsensing (MCS) is a human-driven Internet of Things (IoT) service empowering citizens to observe phenomena of individual, community, or even societal value by sharing sensor data about their environment {; ; ; \color{; ; ; red}; ; ; while on the move}; ; ; . Typical MCS service implementations utilize cloud-based centralized architecture which consumes a lot of computational resources and generates significant network traffic, {; ; ; \color{; ; ; red}; ; ; both in mobile networks and towards cloud-based MCS services. Mobile Edge Computing (MEC) is a natural choice to distribute MCS solutions by moving computation to network edge, since a MEC-based architecture enables significant performance improvements due to partitioning of problem space based on location, where real-time data processing and aggregation is performed close to data sources. This in turn reduces the associated traffic in mobile core and will facilitate MCS deployments of massive scale. This paper proposes an edge computing architecture adequate for massive scale MCS services by placing key MCS features within the reference MEC architecture. In addition to improved performance, the proposed architecture decreases privacy threats and permits citizens to control the flow of contributed sensor data. It is adequate for both data analytics and real-time MCS scenarios, in line with the 5G vision to integrate a huge number of devices and enable innovative applications requiring low network latency. Our analysis of service overhead introduced by distributed architecture and service reconfiguration at network edge performed on real user traces shows that this overhead is controllable and small compared to the aforementioned benefits.}; ; ; When enhanced by interoperability concepts, the proposed architecture creates an environment for the establishment of an MCS marketplace for bartering and trading of both raw sensor data and aggregated/processed information.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika, Računarstvo
POVEZANOST RADA
Projekti:
HRZZ-IP-2013-11-8065 - Komunikacije usmjerene čovjeku u pametnim mrežama (HUTS) (Matijašević, Maja, HRZZ ) ( CroRIS)
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus