Work

Mixer

Year: 2018

Type: conference-paper

Abstract: Many-to-all communication is a prerequisite for many applications and network services, including distributed control and data replication. However, current solutions do not meet the scalability and latency requirements of emerging applications. This paper presents Mixer, a many-to-all broadcast primitive for dynamic wireless mesh networks. Mixer integrates random linear network coding (RLNC) with synchronous transmissions and approaches the order-optimal scaling in the number of messages to be exchanged. To achieve an efficient operation in real networks, we design Mixer in response to the theory of RLNC and the characteristics of physical-layer capture. Our experiments demonstrate, for example, that Mixer outperforms the state of the art by up to 3.8x and provides a reliability greater than 99.99 % even at a node moving speed of 60 km/h.

Source: ACM Conference on Embedded Networked Sensor Systems (SenSys)

DOI: 10.1145/3274783.3274849

Authors: Carsten Herrmann, Fabian Mager, Marco Zimmerling

Institution: Technische Universität Dresden

Language: English

Topic: Cooperative Communication and Network Coding

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: bronze

Funder: Deutsche Forschungsgemeinschaft

Awards: G1055339152, G1324889792, G6015671976