Current research

New: I am looking for creative, energetic, and hard-working BS, MS, and PhD students with interests in the Internet of Things, edge computing, mobile systems, and wireless and mobile networking to join my lab at Duke University. PhD students can be admitted to start as soon as January 2019. Please e-mail me your CV, your transcripts, and a brief note about your research interests at mariaag /at/

My work is in the cross-disciplinary area currently known as the Internet of Things (IoT). The long-term vision of my work is taking the IoT to the point where intelligent, reliable, adaptive pervasive IoT deployments can be created near-automatically beginning-to-end, from hardware form factor generation to communication support to cloud infrastructure specifications. The current focus of my work is on enabling the next generation of interactivity, cognition, and deployment automation in the Internet of Things with fog and edge computing. I am also interested in new IoT node form factors, particularly for smart city-oriented and human-centered IoT deployments.

Intelligence on the edge: I am excited about the opportunities  associated with bringing advanced intelligence close to the end users with edge and fog computing. However, it is far from trivial to adapt both training and inference algorithms to the constraints of edge systems, and to figure out how to best exploit the advantages of both edge nodes and cloud components of the overall IoT systems. We are currently exploring multiple directions in adapting different machine learning algorithms to collaborative edge/fog conditions. This research will enable the next level of interactivity and cognition in Internet of Things deployments, while also reducing network loads and energy consumption associated with machine learning algorithms.

Related publications:

  • P. Naghizadeh, M. Gorlatova, A. S. Lan, M. Chiang, submitted to IEEE Conference on Decision and Control (IEEE CDC’18), Mar. 2018.
  • Y. Ruan, L. Zheng, M. Gorlatova, M. Chiang, C. Joe-Wong, The Economics of Fog Computing: Pricing Tradeoffs for Distributed Data Analytics, Fognet and Fogonomics, Wiley, in print, 2018 (invited book chapter).
  • T. Chang, L. Zheng, M. Gorlatova, C. Gitau, C.-Y. Huang, M. Chiang, Demo: Decomposing Data Analytics in Fog Networks, in Proc. ACM SenSys’17, Delft, Netherlands, Nov. 2017. [Demo abstract PDF] [Video of the demo]

Aiding Internet of Things communications and control with smart gateways: Currently, many elements of communications, networking, and control in the Internet of Things are statically pre-configured. We are exploring how smart gateways can aid in automatic protocol selection, bandwidth allocation, functionality placement, automatic management of network resource reservations, and other adaptive on-demand behavior in IoT systems. Among other techniques, we are examining the applications of reinforcement learning in these contexts. This research will lead to increased capabilities and reduced energy consumption in the IoT systems, and will enable supporting the combination of ultra-low-latency and high-bandwidth communications that are required in modern practical IoT deployments.

Related publications:

  • H. Inaltekin, M. Gorlatova, M. Chiang, Virtualized Control over Fog: Interplay between Reliability and Latency, submitted to IEEE Internet of Things Journal, Feb. 2018.
  • X. Zhang, Y. Im, Y. Sun, M. Gorlatova, S. Ha, M. Chiang, C. Joe-Wong, submitted to IEEE Conference on Network Protocols (IEEE ICNP’18), May 2018.
  • S. Ahn, M. Gorlatova, P. Naghizadeh, M. Chiang, P. Mittal, Adaptive Fog-based Output Security for Augmented Reality, to appear in ACM SIGCOMM VR/AR Network Workshop, Budapest, Hungary, Aug. 2018. [Paper PDF]

Enabling practical augmented reality with edge computing: Current augmented reality deployments have multiple limitations that need to be overcome for augmented reality to become a practical pervasive technology. These limitations include high energy consumption, limited multi-user experiences, and general lack of robustness and intelligence. We are currently exploring a range of approaches for improving augmented reality experiences with edge computing, including making the experiences more adaptive, more secure, and enabling advanced communication and networking support for them.

Related publications:

  • S. Ahn, M. Gorlatova, P. Naghizadeh, M. Chiang, P. Mittal, Adaptive Fog-based Output Security for Augmented Reality, to appear in ACM SIGCOMM VR/AR Network Workshop, Budapest, Hungary, Aug. 2018. [Paper PDF]

IoT applications: The vast majority of my research applies across a broad range of applications and use cases. I am particularly interested in smart city-oriented and human-centered IoT deployments. In smart cities, the challenges associated with collaborative intelligence at scale are particularly pronounced. In human-centered IoT deployments, such as deployments focused on fitness, wellness, and medical applications, intelligence-on-the-edge is on the cusp of enabling in-context real-time performance analysis, activity suggestions, and behavior modification recommendations. Furthermore, both smart city and human-centered IoT applications call for new IoT node form factors and novel approaches to energy and communication resource management in the IoT.

Broader impacts: In an applied field like the Internet of Things, it is particularly important to share scientific findings with broad technical and non-technical communities. I place emphasis on making code, data, and experimental how-to guides widely available, and on developing long-term industry collaborations for sharing wide-reaching research-relevant and industry-relevant insights in joint presentations and publications. I have advised IoT startups in the fitness and wellness space; I am also particularly excited about developing opportunities for seamless transfer of research to industry-wide deployments, such as contributing edge computing-related developments to the EdgeX Foundry open source project.

Related work:

Previous research: My Ph.D. research focused on developing energy harvesting active networked tags for ubiquitous networking of commonplace objects in the Internet of Things [Dissertation PDF]. More information about this work: EnHants, energy harvesting.  My M.Sc. research and key elements of my industry research focused on security and privacy in wireless and mobile networks. [All publications]