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Scaling Down the Energy Cost of Connecting Everday Objects to the Internet

09 Jun
Wednesday, 06/09/2021 10:00am to 12:00pm
Zoom Meeting
PhD Thesis Defense
Zoom link: https://www.google.com/url?q=https://zoom.us/j/91038083039?pwd%3DcWlTYjFZa1kzcGo3VUppN1BuNDgxZz09&sa=D&source=calendar&usd=2&usg=AOvVaw19tbcEYKDYO3ZQ4ytPM4hR     Abstract: The emergence of the newest generation of wireless networking, 5G, has opened the door to a lot of novel applications for industries as well as individuals that have been infeasible so far with the existing networks. Among those, the idea of connecting everything to the network (internet of things, IoT) is the one with probably the biggest market potential in various spaces. Based on the dramatic improvements in 5G's network quality metrics such as throughput (up to Gbps) and latency (<1ms), IoT promises new opportunities for better analytics and control of thousands of objects and sensors in the environments using cloud computing, AI and machine learning technologies etc., which is essential for enabling the proposed industrial (e.g. smart manufacturing) and end consumer (e.g. smart homes, healthcare) applications.

From a practicality perspective, however, there are several other factors than the quality of wireless networks which also determine the feasibility of the internet of things for industries and households. Most importantly, given the number of connected nodes (tens to thousands) the cost of deployment as well as maintenance becomes super crucial. But the most widely known options for connecting the objects, i.e. duty-cycled commodity radios such as Bluetooth LE and Zigbee, introduce a lot of problems and limitations in terms of price (~$10 a piece), and maintenance (need battery replacement every few days or weeks).

The main argument of this thesis is that if the existing commodity are replaced with new, energy-optimized radios, the cost of deployment will be reduced (from several dollars to few cents per node) as well as the maintenance will be much more doable as the nodes can last on their small energy budgets for very long times. To this end, passive radio technologies seem the best fit.  Passive tags, such as backscatter RFID tags, are already being widely used for identification purposes (for example, in EPCGen2 RF identification systems). In those systems, a bigger device RFID reader is responsible for providing the RF carrier signal for the tag, thereby dramatically reducing the energy requirement of the tag for sending or receiving their data to three to four orders of magnitude less than commodity radios such as BLE or ZigBee. However, since the standard RFID systems are limited in their capabilities and hard to deploy and coexist with commodity networks such as WiFi, adopting passive radio technologies in industrial and household wireless networks for their energy benefits is a highly non-trivial effort.  The main focus of this thesis is to find innovative approaches for fusing passive radios together with existing infrastructure and consumer devices such as cellphones, WiFi routers etc without introducing too much change in them while being able to hugely scale down the power consumption of wireless communication.

The main contributions of this thesis are:  (1) Radio polymorphism (Morpho), a novel approach for ultra low power radio design based on combining active and passive radios, in order to enable robust and pervasive streaming and cloud offloading. (2) xSHIFT, enabling battery-free backscatter tags that can directly communicate with commodity radios without any additional infrastructure. (3) MIXIQ, a new ultra low power receiver design that leverages the available devices nearby for converting a simple envelope detector to a high-range, high-throughput receiver. The proposed contributions have all been successfully prototyped using off-the-shelf components and show promising performance. 

Advisor: Deepak Ganesan