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https://hdl.handle.net/10356/86877
Title: | ART: Adaptive fRequency-Temporal Co-Existing of ZigBee and WiFi | Authors: | Li, Feng Luo, Jun Shi, Gaotao He, Ying |
Keywords: | Continuous Frequency Allocation ZigBee |
Issue Date: | 2016 | Source: | Li, F., Luo, J., Shi, G., & He, Y. (2017). ART: Adaptive fRequency-Temporal Co-Existing of ZigBee and WiFi. IEEE Transactions on Mobile Computing, 16(3), 662-674. | Series/Report no.: | IEEE Transactions on Mobile Computing | Abstract: | Recent large-scale deployments of wireless sensor networks have posed a high demand on network throughput, forcing all (discrete) orthogonal ZigBee channels to be exploited to enhance transmission parallelism. However, the interference from widely deployed WiFi networks has severely jeopardized the usability of these discrete ZigBee channels, while the existing CSMA-based ZigBee MAC is too conservative to utilize each channel temporally. In this paper, we propose ART (Adaptive fRequency-Temporal co-existing) as a framework consisting of two components: FAVOR (FrequencyAllocation for Versatile Occupancy of spectRum) and P-CSMA (Probabilistic CSMA), to improve the co-existence between ZigBee and WiFi in both frequency and temporal perspectives. On one hand, FAVOR allocates continuous (center) frequencies to nodes/links in a near-optimal manner, by innovatively converting the problem into a spatial tessellation problem in a unified frequency-spatial space. This allows ART to fully exploit the “frequency white space” left out by WiFi. On the other hand, ART employs P-CSMA to opportunistically tune the use of CSMA for leveraging the “temporal white space” of WiFi interference, according to real-time assessment of transmission quality. We implement ART in MicaZ platforms, and our extensive experiments strongly demonstrate the efficacy of ART in enhancing both throughput and transmission quality. | URI: | https://hdl.handle.net/10356/86877 http://hdl.handle.net/10220/44200 |
ISSN: | 1536-1233 | DOI: | 10.1109/TMC.2016.2573303 | Schools: | School of Computer Science and Engineering | Rights: | © 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/TMC.2016.2573303]. | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Journal Articles |
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