Coded Computing for Master-Aided Distributed Computing Systems

Chen, Haoning; Wu, Youlong

doi:10.1109/itw46852.2021.9457580

Cited by 6 publications

(2 citation statements)

References 9 publications

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“…The placement delivery array (PDA) was applied to reduce the number of sub-files and output functions of the CDC scheme [12]. Chen et al studied a central server-aided MapReduce system and proposed an optimal scheme that achieves the minimum communication load [13]. Heterogeneous distributed computing systems with different storage sizes and computing capabilities were studied in [16]- [18].…”

Section: Introductionmentioning

confidence: 99%

Coded Wireless Distributed Computing via Interference Alignment

Yuan

2022

2022 IEEE International Symposium on Information Theory (ISIT)

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Distributed computing frameworks such as MapReduce and Spark are often used to process large-scale data computing jobs. In wireless scenarios, exchanging data among distributed nodes would seriously suffer from the communication bottleneck due to limited communication resources such as bandwidth and power. To address this problem, we propose a coded parallel computing (CPC) scheme for distributed computing systems where distributed nodes exchange information over a half-duplex wireless interference network. The CPC scheme achieves the multicast gain by utilizing coded computing to multicast coded symbols intended to multiple receiver nodes and the cooperative transmission gain by allowing multiple transmitter nodes to jointly deliver messages via interference alignment. To measure communication performance, we apply the widely used latency-oriented metric: normalized delivery time (NDT). It is shown that CPC can significantly reduce the NDT by jointly exploiting the parallel transmission and coded multicasting opportunities. Surprisingly, when 𝐾 tends to infinity and the computation load is fixed, CPC approaches zero NDT while all state-of-the-art schemes achieve positive values of NDT. Finally, we establish an information-theoretic lower bound for the NDT-computation load trade-off over half-duplex network, and prove our scheme achieves the minimum NDT within a multiplicative gap of 3, i.e., our scheme is order optimal.

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Section: Introductionmentioning

confidence: 99%

Coded Wireless Distributed Computing via Interference Alignment

Yuan

2022

2022 IEEE International Symposium on Information Theory (ISIT)

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“…However, the achievable scheme has only been validated in a small network that consists just three computing nodes. In the work of [178], the authors consider a master-aided edge computing network by incorporating the master in the completing the computation tasks. This proposed scheme reduces communication time and achieves an optimal tradeoff between the overall communication time, computation load and master's storage capacity.…”

Section: Edge Computingmentioning

confidence: 99%