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Cited by 309

The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.

PEDAMACS: power efficient and delay aware medium access protocol for sensor networks

Ergen, S.C., Varaiya, P.·2006·IEEE Transactions on Mobile Computing

Abstract

PEDAMACS is a Time Division Multiple Access (TDMA) scheme that extends the common single hop TDMA to a multihop sensor network, using a high-powered access point to synchronize the nodes and to schedule their transmissions and receptions. The protocol first enables the access point to gather topology (connectivity) information. A scheduling algorithm then determines when each node should transmit and receive data, and the access point announces the transmission schedule to the other nodes. The performance of PEDAMACS is compared to existing protocols based on simulations in TOSSIM, a simulation environment for TinyOS, the operating system for the Berkeley sensor nodes. For the traffic application we consider, the PEDAMACS network provides a lifetime of several years compared to several months and days based on random access schemes with and without sleep cycles, respectively, making sensor network technology economically viable.

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Metadata

Authors
Ergen, S. C., & Varaiya, P.
Venue
IEEE Transactions on Mobile Computing
Published
2006-07
Volume
5
Issue
7
Pages
920-930
ISSN
1536-1233 (ISSN-L)
OpenAlex
W2129185512
Cited by
309
References
15
FWCI
34.18
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: PEDAMACS: power efficient and delay aware medium access protocol for sensor networks. https://app.cochat.ai/papers/10.1109/tmc.2006.100
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Ergen, S. C., & Varaiya, P. (2006). PEDAMACS: power efficient and delay aware medium access protocol for sensor networks. IEEE Transactions on Mobile Computing. https://doi.org/10.1109/tmc.2006.100

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.