Enhancing Data Security and Energy Efficiency on Battery-Free Programmable Platform via Adaptive Scheduling

Embedded devices constantly face two challenges in data security and energy efficiency. These devices are limited in processing such secure functions, as well as maintaining enough energy for the device to function properly. One example involves the healthcare industry, where some patients may requi...

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Bibliographic Details
Main Author: Copello, Claudio Gustavo
Format: Others
Published: OpenSIUC 2016
Subjects:
Online Access:https://opensiuc.lib.siu.edu/theses/2038
https://opensiuc.lib.siu.edu/cgi/viewcontent.cgi?article=3052&context=theses
Description
Summary:Embedded devices constantly face two challenges in data security and energy efficiency. These devices are limited in processing such secure functions, as well as maintaining enough energy for the device to function properly. One example involves the healthcare industry, where some patients may require an Implantable Cardioverter Defibrillator (ICD) in their hearts to measure the heartbeat rate, while powered by a battery. The heartbeat rate is sent wirelessly, and the ICD can receive a jolt of electricity when the heartbeat rate reaches an abnormal value. Transmitting data alone, however, yields potential security risks when sending plain data. Work has shown that an attacker could intercept the heartbeat rate of the ICD, and intentionally send jolts of electricity. Also, replacing the battery on an ICD involves quite a painful process for the patient. A battery-less device that can receive energy wirelessly is much more convenient, but also poses a challenge where power loss may occur under long distances due to a limited supply of energy. In this paper, we design an adaptive light-weight scheduling mechanism that enhances data security, as well as improving energy efficiency on a device with such constraints. We will then prototype this scheduler on a Wireless Identification and Sensing Platform (WISP) device, which includes these constraints. Our results will then demonstrate the capabilities of such adaptive scheduling under various distances.