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Cited by 225

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A Calculus Approach to Energy-Efficient Data Transmission With Quality-of-Service Constraints

Open access
Zafer, M.A., Modiano, E.·2009·IEEE/ACM Transactions on Networking

Abstract

Transmission rate adaptation in wireless devices provides a unique opportunity to trade off data service rate with energy consumption. In this paper, we study optimal rate control to minimize transmission energy expenditure subject to strict deadline or other quality-of-service (QoS) constraints. Specifically, the system consists of a wireless transmitter with controllable transmission rate and with strict QoS constraints on data transmission. The goal is to obtain a rate-control policy that minimizes the total transmission energy expenditure while ensuring that the QoS constraints are met. Using a novel formulation based on cumulative curves methodology, we obtain the optimal transmission policy and show that it has a simple and appealing graphical visualization. Utilizing the optimal ldquoofflinerdquo results, we then develop an online transmission policy for an arbitrary stream of packet arrivals and deadline constraints, and show, via simulations, that it is significantly more energy-efficient than a simple head-of-line drain policy. Finally, we generalize the optimal policy results to the case of time-varying power-rate functions.

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Metadata

Authors
Zafer, M. A., & Modiano, E.
Venue
IEEE/ACM Transactions on Networking
Published
2009-06
Volume
17
Issue
3
Pages
898-911
ISSN
  • 1063-6692 (ISSN-L)
  • 1558-2566
OpenAlex
W2160706299
Cited by
225
References
0
FWCI
13.20
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: A Calculus Approach to Energy-Efficient Data Transmission With Quality-of-Service Constraints. https://app.cochat.ai/papers/10.1109/tnet.2009.2020831
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Zafer, M. A., & Modiano, E. (2009). A Calculus Approach to Energy-Efficient Data Transmission With Quality-of-Service Constraints. IEEE/ACM Transactions on Networking. https://doi.org/10.1109/tnet.2009.2020831

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