Internet of Things Session Management Over LTE—Balancing Signal Load, Power, and Delay
| Autor: | Yuan-Yao Shih, Yuan-Yao Lou, Xiaoli Wang, Mung Chiang, Ming-Jye Sheng |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Computer Networks and Communications
business.industry Network packet Computer science Real-time computing 020206 networking & telecommunications 02 engineering and technology Radio Resource Control Synchronization Computer Science Applications Hardware and Architecture Signal Processing Scalability Telecommunications link 0202 electrical engineering electronic engineering information engineering Discontinuous reception 020201 artificial intelligence & image processing Algorithm design Session (computer science) business Information Systems Computer network |
| Zdroj: | IEEE Internet of Things Journal. 3:339-353 |
| ISSN: | 2372-2541 |
| DOI: | 10.1109/jiot.2015.2497230 |
| Popis: | To efficiently support and manage massive number of Internet of Things (IoT) short and bursty sessions, current long-term evolution (LTE) system needs to reduce signal load generated by IoT session setup/synchronization, while balancing the system performance, such as UE power consumption and delays to time-sensitive traffic. In LTE, radio resource control (RRC) and discontinuous reception (DRX) affect power consumption, signal load, and delay. We provide a session management methodology suitable for IoT traffic over LTE. Our analysis starts with a Markov chain analysis of the impact of DRX parameters. This is followed by an optimal uplink scheduler design and an IoT-aware adaptive DRX algorithm at the client, both of which modulate the tradeoff among signal load, delay, and power consumption. Scalability is also considered by providing a high-priority clustering-based adaptive DRX algorithm at eNB. Simulation results show that for packets with 0.1 s delay, our scheduler outperforms “Tx now” (and “Wait Till Deadline”) by 50% (and 30%) in power saving and by 60% (and 15%) in signal saving. With knowledge of the traffic pattern, IoT-aware adaptive DRX can further reduce signal load by 25%, especially for delay-sensitive traffic. |
| Databáze: | OpenAIRE |
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