Enabling Internet of Things Applications: An End-to-end Approach

Thumbnail Image

Files

isbn9789526039268.pdf (5.61 MB)
Errata_kortoci_pranvera_DD_88_2020_publication_P4.pdf (108.59 KB)

URL

Journal Title

Journal ISSN

Volume Title

School of Science | Doctoral thesis (article-based) | Defence date: 2020-06-10
Unless otherwise stated, all rights belong to the author. You may download, display and print this publication for Your own personal use. Commercial use is prohibited.

Authors

Date

2020

Department

Tietotekniikan laitos
Department of Computer Science

Major/Subject

Mcode

Degree programme

Language

en

Pages

91 + app. 58

Series

Aalto University publication series DOCTORAL DISSERTATIONS, 88/2020

Abstract

There is a massive amount of smart objects around us that interact with each other through Internet-based communication standards, forming the so-called Internet of Things (IoT). The scope of the IoT is quite wide and the related applications have diverse requirements in terms of security, data quality, and reliability. We consider different aspects of the IoT: taking an IoT device securely into use, establishing communication with an application server, and collecting as well as transmitting sensory data to remote data storage facilities (e.g., servers in the cloud). In fact, the IoT ecosystem and its immense device-generated data have given rise to several computing paradigms (e.g., cloud, edge, and fog) with different potential and means of sustaining the ever-growing IoT. This dissertation addresses the requirements of a secure and dependable IoT by taking an end-to-end approach. First, it proposes a light-weight mechanism for the initial configuration of network and security parameters to ensure secure bootstrapping of IoT devices. We specifically target a secure as well as a user-friendly IoT: in fact, our solution requires neither human intervention nor physical access to the device, and it incurs low power expenditure. Second, this dissertation addresses challenges in data collection due to the constrained resources available on IoT devices and limited availability of wireless bandwidth. To this end, we consider people- and agent-based data collection with different types of mobility (e.g., uncontrolled, semi-controlled, and fully-controlled). In particular, we leverage the fog computing paradigm and propose a protocol to offload data opportunistically from IoT end-devices to mobile gateways with unknown and uncontrolled mobility. Moreover, we investigate the impact of incentive mechanisms to ensure user participation in the collection of sensory data. To this end, we leverage the mobile edge computing paradigm and design a smart incentive mechanism for participatory crowdsourcing systems that increases the amount of collected data and maximizes the social welfare of the system. Additionally, we propose a communication protocol for ubiquitous wireless devices to disseminate data to mobile agents with fully-controlled mobility to assist search and rescue teams during disaster scenarios. We characterize the impact of our proposed protocol in extending the battery life of the devices and thus increasing the chances of assisting the survivors. Finally, this dissertation presents a light-weight data reduction mechanism that operates at gateways and edge tiers, supporting data-intensive IoT applications. Specifically, it performs filtering and fusion on time series data, thereby reducing the amount of data transmitted to a remote data center while retaining a high recovery accuracy with respect to the original data stream.

Description

The public defense on 10th June 2020 at 12:00 will be available via remote technology. Link: https://aalto.zoom.us/j/67819394930 Zoom Quick Guide: https://www.aalto.fi/en/services/zoom-quick-guide Electronic online display version of the doctoral thesis is available by email by request from aaltodoc-diss@aalto.fi

Supervising professor

Di Francesco, Mario, Prof., Aalto University, Department of Computer Science, Finland

Keywords

internet of things, data collection protocols, cloud and fog computing

Other note

Parts

  • [Publication 1]: Mohit Sethi, Pranvera Kortoçi, Mario Di Francesco, Tuomas Aura. Secure and Low-Power Authentication for Resource-Constrained Devices. In Proceedings of the 5th International Conference on the Internet of Things (IoT 2015), Seoul, pp. 30-36.
    DOI: 10.1109/IOT.2015.7356545 View at publisher
  • [Publication 2]: Pranvera Kortoçi, Liang Zheng, Carlee Joe-Wong, Mario Di Francesco, Mung Chiang. Fog-based Data Offloading in Urban IoT Scenarios. In Proceedings of the 38th International Conference on Computer Communications (INFOCOM 2019), Paris, pp. 784-792.
    Full text in Acris/Aaltodoc: http://urn.fi/URN:NBN:fi:aalto-201907304523
    DOI: 10.1109/INFOCOM.2019.8737503 View at publisher
  • [Publication 3]: Pranvera Kortoçi, Abbas Mehrabi, Carlee Joe-Wong, Mario Di Francesco. Location-aware Quality Data Collection with Mobile Crowdsourcing for Time-sensitive IoT Applications. Submitted, 2020
  • [Publication 4]: Farouk Mezghani, Pranvera Kortoçi, Nathalie Mitton, Mario Di Francesco. A Multi-tier Communication Scheme for Drone-assisted Disaster Recovery Scenarios. In IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2019), Istanbul, pages 1-7.
    DOI: 10.1109/PIMRC.2019.8904140 View at publisher
  • [Publication 5]: Liang Feng, Pranvera Kortoçi, Yong Liu. A Multi-tier Data Reduction Mechanism for IoT Sensors. In Proceedings of the 7th International Conference on the Internet of Things (IoT 2017), Linz, pages 1-8.
    DOI: 10.1145/3131542.3131557 View at publisher
  • [Errata file]: Errata of P. 4

Citation

Permanent link to this item

https://urn.fi/URN:ISBN:978-952-60-3926-8

Collections

[diss] Perustieteiden korkeakoulu / SCI