STAC: Simultaneous Transmitting and Air Computing in Wireless Data Center Networks
August 24, 2015 Β· Declared Dead Β· π 2015 IEEE/CIC International Conference on Communications in China (ICCC)
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Shengli Zhang, Xiugang Wu, Ayfer Ozgur
arXiv ID
1508.05935
Category
cs.NI: Networking & Internet
Cross-listed
cs.IT
Citations
15
Venue
2015 IEEE/CIC International Conference on Communications in China (ICCC)
Last Checked
4 months ago
Abstract
The data center network (DCN), wired or wireless, features large amounts of Many-to-One (M2O) sessions. Each M2O session is currently operated based on Point-to-Point (P2P) communications and Store-and-Forward (SAF) relays, and is generally followed by certain further computation at the destination. %typically a weighted summation of the received digits. Different from this separate P2P/SAF-based-transmission and computation strategy, this paper proposes STAC, a novel physical layer scheme that achieves Simultaneous Transmission and Air Computation in wireless DCNs. In particular, STAC takes advantage of the superposition nature of electromagnetic (EM) waves, and allows multiple transmitters to transmit in the same time slot with appropriately chosen parameters, such that the received superimposed signal can be directly transformed to the needed summation at the receiver. Exploiting the static channel environment and compact space in DCN, we propose an enhanced Software Defined Network (SDN) architecture to enable STAC, where wired connections are established to provide the wireless transceivers external reference signals. Theoretical analysis and simulation show that with STAC used, both the bandwidth and energy efficiencies can be improved severalfold.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Networking & Internet
R.I.P.
π»
Ghosted
π
π
The Cartographer
Federated Learning in Mobile Edge Networks: A Comprehensive Survey
π
π
The Cartographer
A Survey of Indoor Localization Systems and Technologies
R.I.P.
π»
Ghosted
Survey of Important Issues in UAV Communication Networks
π
π
The Cartographer
Network Function Virtualization: State-of-the-art and Research Challenges
π
π
The Cartographer
Applications of Deep Reinforcement Learning in Communications and Networking: A Survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted