July 2012, 2012:219,
Open Access This content is freely available online to anyone, anywhere at any time.
Date: 17 Jul 2012
Analysis of superframe adjustment and beacon transmission for IEEE 802.15.4 cluster tree networks
Wireless sensor networks based on the IEEE 802.15.4 standard are able to achieve low-power transmissions in the low-rate and short-distance wireless personal area network (PAN). A cluster tree network consists of several clusters; each cluster has a coordinator, known as cluster coordinator, and several device nodes. In the cluster tree topology of IEEE 802.15.4, a PAN coordinator periodically transmits beacon frames to its coordinator nodes as well as a coordinator node periodically transmit beacon frames to their device nodes. The main challenge in the cluster tree network is the collisions between beacons or even between beacon and data frames, which degrades the network performance. In order to decrease collisions, this article proposes the superframe adjustment and beacon transmission scheme (SABTS) by assigning the accurate values of beacon order and superframe order for the PAN coordinator, cluster coordinators, and device nodes, and deciding the precise time for the beacon transmission of PAN and coordinator nodes. A Markov chain model for the cluster tree network is developed with taking into account packet retransmission, acknowledgement, and defer transmission. Both analytical and simulation results show that SABTS performs better than IEEE 802.15.4 standard in terms of the probability of successful transmission, network goodput, and energy consumption.
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- Analysis of superframe adjustment and beacon transmission for IEEE 802.15.4 cluster tree networks
- Open Access
- Available under Open Access This content is freely available online to anyone, anywhere at any time.
EURASIP Journal on Wireless Communications and Networking
- Online Date
- July 2012
- Online ISSN
- Springer International Publishing AG
- Additional Links
- Wireless sensor network
- IEEE 802.15.4
- Personal area network
- Cluster tree topology
- Markov chain
- Industry Sectors