Research @ NEXTCON is funded by
QUALCOMM Inc. Â (through Wireless Internet of Things Lab at Clarkson)
NEXTCON Lab. has been founded by Dr. Burak Kantarci at Clarkson University. Main Research Areas are Internet of Things (IoT), cloud computing, mobile social networks, secure and trustworthy computing and communications, vehicular ad hoc network, vehicular clouds, smart cities, and smart connected health systems. NEXTCON is a member of the Wireless Internet of Things Lab at Clarkson.
NEXTCON Lab is looking for highly motivated graduate and undergraduate students whose research interests match with the research areas of the lab. Clarkson undergraduates are always welcome to discuss internship opportunities at NEXTCON lab with Dr. Kantarci. If you are interested in pursuing research in NEXTCON Lab., send an email to burak.kantarci@uOttawa.ca along with your research interests and your resume with your references.
This research builds on Dr. Kantarci`s research on cloud-centric IoT and sensing as a service, and the NSF CRII grant with the research project entitled "CRII:SaTC: Energy efficient participatory data collection and Context-Aware Incentives for Trustworthy Crowdsensing via Mobile Social Networks".
In a crowdsensing system, energy efficient data collection is a primary concern for mobile sensing service providers (i.e., mobile users offering sensing as a service via built-in sensors on their mobile devices) in order to maximize battery life whereas trustworthiness is a primary concern for the end users. The proposed research will simultaneously address energy-efficient data collection and context-aware incentives to both minimize power consumption and maximize data trustworthiness. Furthermore, this research will propose new user-driven crowdsensing business models where smart phone users compete with each other for compensation based on the usefulness and trustworthiness of their sensing data. The ultimate societal impacts of the research are new crowdsensing applications in the areas of public safety, disaster management and community engagement that will be enabled by improved energy-efficient data collection, increased crowdsending trustworthiness through context aware sensing, and new crowdsensing business models that will incentivize more users to offer their mobile device built-in sensors as a service.
The proposed research will extend the ongoing efforts on trustworthy crowdsensing to address energy efficient data collection and new context-aware user incentive strategies to improve data trustworthiness. In order to address energy efficient data collection, coalitional game theory-based algorithms will be proposed while trustworthiness of the aggregated system will be addressed by defining new trustworthiness functions and context analysis of mobile social networks of the sensing data providers. These methodologies will be validated through comparison to benchmark optimization models. Statistical and collaborative trust scores will be used to introduce new trustworthiness and reputation functions for sensing service providers. The new trustworthiness and reputation functions will mitigate the impact of adversaries including the Sybils who aim at misinformation and manipulation. An emphasis will be placed on compatibility with emerging mobile social network (MSN) models and their associated spatio-temporal context analyses. The research will be completed by building a framework which combines the merits of energy efficient data collection and context-aware user incentives.
M. Pouryazdan, B. Kantarci, T. Soyata and H. Song, "Anchor-Assisted and Vote-based Trustworthiness Assurance in Smart City Crowdsensing" IEEE Access special issue on Smart Cities, 2016.
B. Kantarci, C. D. Pearsall, K. G. Carr, "SONATA: Social Network-Assisted Trustworthiness Assurance in Smart City Crowdsensing," IGI Global International Journal of Distributed Systems and Technologies, Special Issue on Advances in Clouds for Smart Cities, 2015 (accepted).
B. Kantarci, P. M. Glasser, L. Foschini, "Crowdsensing with social network-aided collaborative trust scores," in Proc. IEEE Global Communications Conference (GLOBECOM), San Diego, CA, USA, Dec. 2015 (accepted).
A. Murturi, B. Kantarci, S. Oktug, "A Reference Model for Crowdsourcing as a Service," in Proc. IEEE Intl. Conference on Cloud Networking (CLOUDNET), Niagara Falls, ON, Canada, Oct. 2015 (accepted).
B. Kantarci, H. T. Mouftah, "Sensing as a Service in Cloud-Centric Internet of Things Architecture," to appear in Enabling Real-Time Mobile Cloud Computing through Emerging Technologies, edited by T. Soyata, IGI Global, Hershey, PA, 2015.
B. Kantarci, H. T. Mouftah, "Trustworthy Sensing for Public Safety in Cloud-Centric Internet of Things," IEEE Internet of Things Journal, vol. 1, issue 4, pp. 360-368, August 2014.
B. Kantarci, H. T. Mouftah, "Sensing Services in Cloud-Centric Internet of Things: A Survey, taxonomy and challenges, " IEEE International Conference on Communications (ICC) Workshop on Cloud Computing Systems, Networks and Applications, London, UK, June 2015 (accepted).
B. Kantarci, H. T. Mouftah, "Trustworthy Crowdsourcing via Mobile Social Networks," IEEE GLOBECOM, Austin, TX, Dec. 2014
B. Kantarci, H. T. Mouftah, "Mobility-aware Trustworthy Crowdsourcing in Cloud-Centric Internet of Things," IEEE Intl. Symposium on Computers and Communications (ISCC), Madeira,Portgual, June 2014
B. Kantarci, H. T. Mouftah, "Reputation-based Sensing-as-a-Service for Crowd Management Over the Cloud," IEEE International Conference on Communications (ICC), Sydney, Australia, June 2014.
Behaviometrics/Internet of Biometric Things (IoBT):
This research builds on Dr. Kantarci`s collaborative research project with co-PIs Dr. Melike Erol-Kantarci and Dr. Stephanie Schuckers., and it is funded through NSF I/UCRC Center for Identification Technology and Reseach (CITeR) in 2015-2016 with the research project entitled "Context-aware anomaly detection in Internet of Biometric Things (IoBT)".
B. Kantarci, M. Erol-Kantarci, S. Schuckers, "Towards secure cloud-centric Internet of Biometric Things, " in Proc. IEEE Intl. Conference on Cloud Networking (CLOUDNET), Niagara Falls, ON, Canada, Oct. 2015.
Cloud computing enables users to receive Infrastructure/ Platform/Software as a Service (XaaS) via a shared pool of resources based on the pay-as-you-go fashion. Data centers, as the hosts of physical servers, play the key role in the delivery of cloud services. Therefore, interconnection of data centers over a backbone network is one of the major challenges affecting the performance of the cloud system, as well as the operational expenditures of the service providers. We research the design methods for operational cost-efficient design of a cloud backbone through demand profile-based network virtualization where the data centers are located at the core nodes of a transport network. Addressing energy-efficiency in a cloud backbone helps reducing the operational expenditure (Opex) of the network and data center operators. Another factor which affects the Opex of the operators is the downtime of cloud services which can be denoted by resiliency, availability and/or reliability. Therefore, we aim at designing methods which aim at cutting the electric bills of the operators, and which reduce the downtime penalties of the operators. Furthermore, the approaches that jointly consider these challenges and overcome the related challenges are studied, as well.
B. Kantarci, H. T. Mouftah, "Resilient Design of a Cloud System over an Optical Transport Network," IEEE Network, vol 29/5, pp. 80-87, Jul/Aug. 2015.
H. T. Mouftah and B. Kantarci, "Communication Infrastructures for Cloud Computing", IGI Global, Hershey, Pennsylvania, USA, September 2013, DOI: 10.4018/978-1-4666-4522-6, ISBN13: 9781466645226.
B. Kantarci, H. T. Mouftah, "Inter-Data Center Network Dimensioning under Time-of-Use Pricing," IEEE Transactions on Cloud Computing, 2014 (accepted)
B. Kantarci, L. Foschini, A. Corradi, H. T. Mouftah, "Design of Energy-Efficient Cloud Systems via Network and Resource Virtualization," Wiley-International Journal of Network Management, SI on Management and Security technologies for Cloud Computing, doi: 10.1002/nem.1838, August 2013.
B. Kantarci, H. T. Mouftah, "Designing an Energy-Efficient Cloud Network," IEEE/OSA Journal of Optical Communications and Networking, vol. 4/11, pp. B101-B113, Nov. 2012.
B. Kantarci and H. T. Mouftah, "Inter-data center networks with minimum operational costs," to appear in Cloud Services, Networking, and Management, edited by N. Fonseca and R. Boutaba, Wiley-IEEE Press, ISBN: 978-1-118-84594-3, April 2015.
B. Kantarci and H. T. Mouftah, "Energy-efficiency in Cloud Data Centers," in "Communication Infrastructures for Cloud Computing," edited by H. T. Mouftah and B. Kantarci, IGI Global, Hershey, PA, pp. 241-263, Sep. 2013
B. Kantarci and H. T. Mouftah, "Energy-efficient Design of a Cloud Computing Backbone," in "Communication Infrastructures for Cloud Computing," edited by H. T. Mouftah and B. Kantarci, IGI Global, Hershey, PA, pp. 283-305, Sep. 2013.
Secure and Trustworthy Computing and Communications in Cloud and IoT systems
Internet of Things (IoT) concept provides a number of opportunities to improve our daily lives while also creating a potential risk of increasing the vulnerability of personal information to security and privacy breaches. Data collected
from IoT is usually offloaded to the Cloud which may further leave data prone to a variety of attacks if security and privacy issues are not handled properly. Anomaly detection has been one of the widely adopted security measures in wired and wireless networks. However, it is not straight forward to apply most of the anomaly detection techniques to IoT and cloud. One of the main challenges is deriving outlier features from the vast volume of data pumped from IoT to the cloud. Other challenges include the large number of sources generating data, heterogenous connectivity and traffic patterns of IoT devices, cloud services being offered at geographically remote places and causing IoT data to be stored in different countries with different legislations. This research identifies the challenges and opportunities in anomaly detection for IoT and cloud. It introduces the prominent features and application fields of IoT and Cloud, then demonstrates security and privacy risks to personal information and finally focuses on solutions.
M. Aloqaily, B. Kantarci, H. T. Mouftah, "A Generalized Framework for Quality of Experience (QoE)-based Provisioning in a Vehicular Cloud," in Proc. IEEE International Conference on Ubiquitous Wireless Broadband (ICUWB), Montreal, QC, Canada, October 2015 (accepted).
I. Butun, B. Kantarci, M. Erol-Kantarci, "Anomaly detection and privacy preservation in cloud-centric Internet of Things," IEEE International Conference on Communications (ICC) Workshop on Security and Privacy for Internet of Things and Cyber-Physical Systems, London, UK, June 2015.
M. Aloqaily, B. Kantarci, H. T. Mouftah, "On the impact of Quality of Experience (QoE) in a vehicular cloud with various providers," 11th Intl. Conference HONET-PfE, Charlotte, NC, Dec. 2014
M. Aloqaily, B. Kantarci, H. T. Mouftah, "Provisioning Delay Effect of Partaking a Trusted Third Party in a Vehicular Cloud," Global Information Infrastructure and Networking Symposium (GIIS), Montreal, QC, Canada, Sep. 2014.