Constant Time, Fixed Memory, Zero False Negative Error Logging for Low Power Wearable Devices
Title | Constant Time, Fixed Memory, Zero False Negative Error Logging for Low Power Wearable Devices |
Publication Type | Conference Paper |
Year of Publication | 2017 |
Authors | Doolan, S., Hoseiny, N., Hosein, N., Bhagwandin, D. |
Conference Name | 2017 IEEE Conference on Wireless Sensors (ICWiSe) |
Keywords | Body Sensors, Caching Algorithm, Conferences, constant insertion time, constant memory, constant time, embedded devices, Error Logging, error logging algorithm, false positive error rate, firmware, firmware faults, fixed memory, hashing, Human Behavior, Internet of Things, IoT systems, low power wearable devices, privacy, pubcrawl, reliability, resilience, Resiliency, run-time error logging, Scalability, security, Sensor systems, traditional error logging algorithms, wearable computers, wearable devices, Wearable sensors, wearables security, Wireless communication, Wireless sensor networks, wireless wearable embedded devices, zero false negative error |
Abstract | Wireless wearable embedded devices dominate the Internet of Things (IoT) due to their ability to provide useful information about the body and its local environment. The constrained resources of low power processors, however, pose a significant challenge to run-time error logging and hence, product reliability. Error logs classify error type and often system state following the occurrence of an error. Traditional error logging algorithms attempt to balance storage and accuracy by selectively overwriting past log entries. Since a specific combination of firmware faults may result in system instability, preserving all error occurrences becomes increasingly beneficial as IOT systems become more complex. In this paper, a novel hash-based error logging algorithm is presented which has both constant insertion time and constant memory while also exhibiting no false negatives and an acceptable false positive error rate. Both theoretical analysis and simulations are used to compare the performance of the hash-based and traditional approaches. |
URL | https://ieeexplore.ieee.org/document/8267156/ |
DOI | 10.1109/ICWISE.2017.8267156 |
Citation Key | doolan_constant_2017 |
- traditional error logging algorithms
- pubcrawl
- Reliability
- resilience
- Resiliency
- run-time error logging
- Scalability
- security
- Sensor Systems
- privacy
- wearable computers
- Wearable devices
- Wearable sensors
- wearables security
- Wireless communication
- wireless sensor networks
- wireless wearable embedded devices
- zero false negative error
- false positive error rate
- Caching Algorithm
- Conferences
- constant insertion time
- constant memory
- constant time
- embedded devices
- Error Logging
- error logging algorithm
- Body Sensors
- firmware
- firmware faults
- fixed memory
- hashing
- Human behavior
- Internet of Things
- IoT systems
- low power wearable devices