prikaz prve stranice dokumenta Energy-efficient mobile crowd sensing in the internet of things domain
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doctoral thesis
Energy-efficient mobile crowd sensing in the internet of things domain
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. urn:nbn:hr:168:897786
Marjanović, Martina
University of Zagreb
Faculty of Electrical Engineering and Computing
Department of Telecommunications

Institutional repository: FER Repository

Cite this document

Marjanović, M. (2018). Energy-efficient mobile crowd sensing in the internet of things domain (Doctoral thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:897786

Marjanović, Martina. "Energy-efficient mobile crowd sensing in the internet of things domain." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:897786

Marjanović, Martina. "Energy-efficient mobile crowd sensing in the internet of things domain." Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2018. https://urn.nsk.hr/urn:nbn:hr:168:897786

Marjanović, M. (2018). 'Energy-efficient mobile crowd sensing in the internet of things domain', Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 23 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:897786

Marjanović M. Energy-efficient mobile crowd sensing in the internet of things domain [Doctoral thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2018 [cited 2024 November 23] Available at: https://urn.nsk.hr/urn:nbn:hr:168:897786

M. Marjanović, "Energy-efficient mobile crowd sensing in the internet of things domain", Doctoral thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2018. Available at: https://urn.nsk.hr/urn:nbn:hr:168:897786

Metadata
TitleEnergy-efficient mobile crowd sensing in the internet of things domain
Title (croatian)Energetski učinkovito skupno opažanje okoline pokretnim uređajima u području interneta stvari
AuthorMartina Marjanović
MentorIvana Podnar Žarko (mentor)
Committee memberIvana Podnar Žarko (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
(Department of Telecommunications)
Zagreb
Defense date and country2018, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Universal decimal classification
(UDC)		654 - Telecommunication and telecontrol
Abstract
Mobile Crowd Sensing (MCS) is a new paradigm that empowers ordinary citizens to collectively sense the environment by using their mobile devices and share data of common interest. Since MCS applications can cause significant energy consumption and quickly drain user's battery, it is vital to achieve energy-efficient sensing and data transmission from mobile devices to the cloud so that valuable data is collected when it is indeed required by an MCS service. In this thesis we first provide a comprehensive overview of existing MCS applications, identify their unique features and define a functional MCS architecture which is mapped to existing IoT reference architectures. Then, we propose a mathematical model for MCS that describes the basic crowd sensing interactions. The proposed model is used to define the algorithms for energy-efficient data acquisition in both centralized and decentralized MCS systems. In particular, we present a centralized MCS ecosystem which utilizes a quality-driven sensor management function to continuously select the k-best workers for a predefined sensing task in the area of interest. The algorithm is designed to obviate redundant worker activity and consequently reduce overall system energy consumption. Our results show that by using the proposed algorithm the overall energy consumption for an MCS task can be significantly reduced if compared to a baseline approach which acquires all generated sensor data. Next, we propose a hierarchical MCS ecosystem which assumes the usage of edge computing resources to decentralize MCS services and improve their performance. The proposed architecture allows users to autonomously decide when to contribute data to the edge MCS service by using a Bloom filter structure. Finally, we extensively evaluate the proposed decentralized algorithm by using a real data set containing crowd sensed data. Our analysis shows that a Bloom filter structure is indeed applicable for MCS and its usage can greatly reduce energy consumption in decentralized MCS environment.
Abstract (croatian)
Skupno opažanje okoline pokretnim uređajima (engl. Mobile Crowd Sensing, MCS) je nova paradigma koja omogućava običnim građanima da zajednički prikupljaju i dijele podatke o svojoj okolini koristeći pokretne uređaje. Budući da takve aplikacije mogu uzrokovati značajnu potrošnju energije i brzo isprazniti baterije na pokretnim uređajima i senzorima, potrebno je postići energetski-učinkovito prikupljanje i prijenos podataka s pokretnih uređaja do poslužitelja u računalnom oblaku kako bi se prikupili samo oni podaci koji mogu donijeti dodatnu vrijednost za krajnjeg korisnika. U ovom radu dan je sveobuhvatan pregled postojećih usluga u području skupnog opažanja okoline, identificirane su njihove jedinstvene značajke i definirana je generička funkcijska arhitektura koja je potom preslikana na relevantne referentne arhitekture u području Interneta stvari. Potom je predložen formalni model za MCS koji koristi notaciju teorije skupova u definicijama i opisu svojstava sustava. Predloženi model koristi se za definiranje algoritama za energetski-učinkovito prikupljanje podataka u centraliziranim i decentraliziranim sustavima za skupno opažanje okoline. Prvo je predstavljen algoritam pogodan za centralizirane sustave gdje koordinator smješten u računalnom oblaku upravlja cjelokupnim procesom prikupljanja podataka kontinuirano odabirući k-najboljih korisnika koji mogu izvršiti zadatak u nekom području. Algoritam je dizajniran kako bi minimizirao redundantne aktivnosti mjernih čvorova i smanjio ukupnu potrošnju energije u sustavu. Rezultati pokazuju da se korištenjem predloženog algoritma može značajno smanjiti ukupna potrošnja energije u usporedbi s rješenjem temeljnom na periodičkom prikupljanju podataka. Zatim je predstavljen algoritam pogodan za distribuirane sustave za skupno opažanje okoline u pokretu koji koriste računalne resurse na rubu mreže kako bi se decentralizirale usluge za MCS i poboljšala njihova izvedba. Predloženi algoritam omogućuje korisnicima da autonomno i informirano odlučuju kada će prikupljati i prenositi podatke koristeći strukturu podataka Bloom filtra. Naposljetku je dana iscrpna evaluacija predloženog rješenja na stvarnom skupu podataka. Rezultati pokazuju da je Bloom filter doista primjenjiv za MCS te da njegova upotreba može uvelike smanjiti potrošnju energije u decentraliziranom okruženju.
Keywords
Keywords (croatian)
Languageenglish
URN:NBNurn:nbn:hr:168:897786
Study programmeTitle: Electrical Engineering and Computing
Study programme type: university
Study level: postgraduate
Academic / professional title: Doktor znanosti elektrotehnike i računarstva (Doktor znanosti elektrotehnike i računarstva)
Type of resourceText
Extent159 str. ; 30 cm.
File originBorn digital
Access conditionsClosed access
Terms of useLicence In copyright icon
Created on2019-04-03 14:55:46