Network packet

Multipath TCP

Network congestion

Multipath propagation

Real-time computing

Scheduling (production processes)

Transmission delay

Economics

Computer science

Burst switching

Packet loss

Distributed computing

Computer network

Routing protocol

Network scheduler

Link-state routing protocol

Multipath routing

Operations management

Path (computing)

Channel (broadcasting)

IEEE Journal on Selected Areas in Communications

Multipath transport protocols utilize multiple network paths (e.g., WiFi and cellular) to achieve improved performance and reliability, compared with their single-path counterparts. The scheduler of a multipath transport protocol determines how to distribute the data packets onto different paths. However, state-of-the-art multipath schedulers face the challenge when dealing with heterogeneous paths with dynamic path characteristics (i.e., packet loss, fluctuation of delay). In this paper, we propose Peekaboo, a novel learning-based multipath scheduler that is aware of the dynamic characteristics of the heterogeneous paths. Peekaboo is able to learn scheduling decisions to adopt over time based on the current path characteristics and dynamicity levels - from both deterministic and stochastic perspectives. We implement Peekaboo in Multipath QUIC (MPQUIC) and compare it with state-of-the-art multipath schedulers for a wide range of dynamic heterogeneous environments, upon both emulated and real networks. Our results show that Peekaboo outperforms the other schedulers by up to 31.2% in emulated networks and up to 36.3% in real network scenarios.

Peekaboo: Learning-Based Multipath Scheduling for Dynamic Heterogeneous Environments