Pushing the Limits of Transmission Concurrency for Low Power Wireless Networks

Author:

Liu Daibo1ORCID,Cao Zhichao2ORCID,Hou Mengshu3,Rong Huigui1,Jiang Hongbo1

Affiliation:

1. Hunan University, Changsha, Hunan Province, P.R. China

2. Michigan State University, East Lansing, MI, USA

3. University of Electronic Science and Technology of China, Chengdu, Sichuan, P.R. China

Abstract

Concurrent transmission (CT) has been widely adopted to optimize the throughput of various data transmissions in wireless networks, such as bulk data dissemination and high-rate data collection. In CT, besides the possible data frame collision at receivers, we observe that acknowledgment frame (ACK) collision at senders can also significantly diminish concurrency opportunities. In this article, to avoid the potential ACK collision in CT, we propose ALIGNER which develops a new transmission pattern to coordinate concurrent senders in a distributed manner. The key idea is to align the silent periods of concurrent transmitters. To achieve this goal, we align the end of data frames concurrently transmitted by several senders. Therefore, the potentially arriving ACKs can avoid a collision with ongoing data transmissions because the concurrent senders are in a listening state to wait for receivers’ ACKs for a short and fixed period. ALIGNER can be applied for both deterministic and opportunistic forwarding protocols. It optionally uses a random back-off and slotted ACK mechanism to avoid a potential collision among simultaneously arrived ACKs in opportunistic forwarding. In addition, ALIGNER adopts a tailor-made metrics to analyze the throughput benefit of concurrent transmission for both deterministic and opportunistic data collection protocols. We have implemented ALIGNER in TinyOS and conducted extensive experiments on a real testbed. Experimental results show that ALIGNER can significantly increase the concurrency opportunities in both deterministic (up to 105%) and opportunistic (up to 89.7%) forwarding compared with the state-of-the-art CT methods.

Funder

Fundamental Research Funds for the Central Universities

Hunan Provincial Natural Science Foundation of China

NSFC

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications

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