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| Content Provider | ACM Digital Library |
|---|---|
| Author | Hassan, Mahbub Chou, Chun Tung Adesina, Adesoji A. Zarepour, Eisa |
| Abstract | Chemical reactors are designed to efficiently produce high-value chemical products but at the same time they also produce low-value by-products. The selectivity of a chemical process refers to the proportion of high-value product produced. A nano sensor network (NSN) monitoring the chemical process at the molecule level could help improving the selectivity by preventing the reactions that lead to low value by-products. Therefore, a central requirement to achieve high selectivity by NSN is reliable communication. A challenge to realising reliable communication within a chemical reactor is its time-varying chemical composition, which in turn creates a time-varying radio channel and noise. The sensor nodes therefore need to adjust their transmission power according to the chemical composition while maintaining a low overall power budget. We show that this problem can be modelled as a Markov Decision Process (MDP). However, the MDP solution requires the sensors to know the composition of the reactor at each time instance, which is prohibitive. We therefore derive off-line time-based policies that these sensors can use. We illustrate our work by using an important chemical process for fuel production and demonstrate the performance of our proposed off-line policies against the optimal MDP policy. |
| Starting Page | 1 |
| Ending Page | 9 |
| Page Count | 9 |
| File Format | |
| ISBN | 9781450329798 |
| DOI | 10.1145/2619955.2619973 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2014-05-06 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Content Type | Text |
| Resource Type | Article |
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