Deadline-Aware Scheduling With Adaptive Network Coding for Real-Time Traffic

Abstract

We study deadline-aware scheduling with adaptive network coding (NC) for real-time traffic over a single-hop wireless network. To meet hard deadlines of real-time traffic, the block size for NC is adapted based on the remaining time to the deadline so as to strike a balance between maximizing the throughput and minimizing the risk that the entire block of coded packets may not be decodable by the deadline. This sequential block size adaptation problem is then cast as a finite-horizon Markov decision process. One interesting finding is that the optimal block size and its corresponding action space monotonically decrease as the deadline approaches, and that the optimal block size is bounded by the "greedy" block size. These unique structures make it possible to significantly narrow down the search space of dynamic programming, building on which we develop a monotonicity-based backward induction algorithm (MBIA) that can find the optimal block size in polynomial time. Furthermore, a joint real-time scheduling and channel learning scheme with adaptive NC is developed to adapt to channel dynamics in a mobile network environment. Then, we generalize the analysis to multiple flows with hard deadlines and long-term delivery ratio constraints. We devise a low-complexity online scheduling algorithm integrated with the MBIA, and then establish its asymptotical utility optimality. The analysis and simulation results are corroborated by high-fidelity wireless emulation tests, where actual radio transmissions over emulated channels are performed to demonstrate the feasibility of the MBIA in finding the optimal block size in real time.

TDMH: a communication stack for real-time wireless mesh networks

“…Other approaches try to cope with the limitations of CSMA, by using Quality of Service (QoS) [15] to prioritize real-time traffic, or jamming the channel first to stop non realtime traffic and then transmitting, a technique referred to as bandjacking [28]. The work by Yang et al [27] proposes a custom PHY layer that adapts the network coding at runtime to meet soft deadlines, while active drop queues [18] have been introduced to support bursty soft real-time application, such as multimedia traffic. Industrial wireless protocols for factory automations also exist.…”

Investigating an Adaptive Network Coding Control Protocol for Multihop-Multipath Networks for Network Reconfigurability

“…The work in [7] studies adaptive network coding (NC) for real-time traffic over a single-hop wireless network. In their study, the block size for NC is adapted based on the remaining time to the deadline .It generalized the analysis to multiple flows with hard deadlines and long-term delivery ratio constraints.…”

DeepNP: Deep Learning-Based Noise Prediction for Ultra-Reliable Low-Latency Communications

“…In the presence of delayed feedback, the works [3]- [5] proposed codes to reduce the streaming delay over an erasure channel. For coded blocks, [6] proposed an adaptive solution, where the sender can choose the size of the next block and the number of packets information in the block for deadline-aware applications. The recently proposed adaptive and causal random linear network coding (AC-RLNC) scheme, applied to single-path, multi-path, and multihop networks [10]- [12], implements joint scheduling-coding in a manner that is both causal and adaptive.…”