Name
Title | ||
|---|---|---|
Token-Scheduled High Throughput Data Collection With Topology Adaptability In Wireless Sensor Network |
Abstract | ||
|---|---|---|
This paper presents a data gathering protocol for wireless sensor network applications that require high throughput and topology adaptability under the premises of uniform traffic and energy-rich environments. Insofar as high throughput is concerned, TDMA is more suitable than CSMA. However, traditional TDMA protocols require complex scheduling of transmission time slots. The scheduling burden is the primary barrier to topology adaptability. Under the premises of uniform traffic and energy-rich environments, this paper proposes a token-scheduled multi-channel TDMA protocol named TKN-TWN to ease the scheduling burden while exploiting the advantages of TDMA. TKN-TWN uses multiple tokens to arbitrate data transmission. Due to the simplified scheduling based on tokens, TKN-TWN is able to provide adaptability for topology changes. The contention-free TDMA and multi-channel communication afford TKN-TWN the leverage to sustain high throughput based on pipelined packet forwarding. TKN-TWN further associates the ownership of tokens with transmission slot assignment toward throughput optimization. We implement TKN-TWN on Tmote Sky with TinyOS 2.1.1 operating system. Experimental results in a deployed network consisting of 32 sensor nodes show that TKN-TWN is robust to network changes caused by occasional node failures. Evaluation also shows that TKN-TWN is able to provide throughput of 9.7 KByte/s. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1587/transcom.E97.B.1656 | IEICE TRANSACTIONS ON COMMUNICATIONS |
Keywords | Field | DocType |
wireless sensor networks, TDMA, token, multi-channel, scheduling | Wireless network,Key distribution in wireless sensor networks,Computer science,Computer network,Wireless WAN,Real-time computing,Maximum throughput scheduling,Throughput,Mobile wireless sensor network,Wi-Fi array,Wireless sensor network,Distributed computing | Journal |
Volume | Issue | ISSN |
E97B | 8 | 0916-8516 |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jinzhi Liu | 1 | 4 | 1.52 |
| Makoto Suzuki | 2 | 67 | 14.19 |
| Doo hwan Lee | 3 | 24 | 9.17 |
| Hiroyuki Morikawa | 4 | 432 | 69.52 |