برنامه ریزی انتقال انعطاف پذیر در زمان واقعی برای شبکه های بی سیم با کارهای غیر قطعی

Wireless Sensor Networks (WSNs) are increasingly used in industrial applications such as the Internet-of-Things, Smart City technologies and critical infrastructure monitoring. Industrial WSNs often operate in a cluster or star configuration. To ensure real-time and predictable performance, link access is typically managed using time-slotted superframe methods. These methods generally use static and potentially inefficient slot assignments. In this paper, we propose to dynamically readjust time slot lengths as a technique to minimize overall energy consumption. Our approach combines real-time performance guarantees with energy conservation methods through a set of dynamic modulation based adaptive packet transmission scheduling algorithms that are designed to reclaim unused slot times. To support our reclaiming method in a wireless environment we introduce a novel low-power listening technique called reverse-low-power listening (RLPL) as part of an overall Hybrid Low-Power Listening (HLPL) protocol. We evaluate our algorithms using Castalia simulator against an oracle-based approach, and show that our dynamic slot reclaiming approach, coupled with HLPL, can introduce substantial power savings without sacrificing real-time support which may be a new approach towards improving industrial wireless standards.