Name
Abstract | ||
|---|---|---|
AbstractConcurrent 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. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1145/3406834 | ACM Transactions on Sensor Networks |
Keywords | DocType | Volume |
Internet of Things, duty cycled networks, transmission concurrency | Journal | 16 |
Issue | ISSN | Citations |
4 | 1550-4859 | 2 |
PageRank | References | Authors |
0.36 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daibo Liu | 1 | 2 | 2.39 |
| Zhichao Cao | 2 | 172 | 23.04 |
| Mengshu Hou | 3 | 2 | 1.37 |
| Huigui Rong | 4 | 2 | 0.70 |
| Hongbo Jiang | 5 | 58 | 12.99 |