A New Interference-Alignment Scheme for Wireless MapReduce
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2022
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| _version_ | 1866929233139335168 |
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| author | Bi, Yue Wigger, Michèle Wu, Yue |
| author_facet | Bi, Yue Wigger, Michèle Wu, Yue |
| contents | We consider a full-duplex wireless Distributed Computing (DC) system under the MapReduce framework. New upper and lower bounds on the optimal tradeoff between Normalized Delivery Time (NDT) and computation load are presented. The upper bound strictly improves over the previous reported upper bounds and is based on a novel interference alignment (IA) scheme tailored to the interference cancellation capabilities of MapReduce nodes. The lower bound is proved through information-theoretic converse arguments. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2210_06621 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | A New Interference-Alignment Scheme for Wireless MapReduce Bi, Yue Wigger, Michèle Wu, Yue Information Theory Distributed, Parallel, and Cluster Computing We consider a full-duplex wireless Distributed Computing (DC) system under the MapReduce framework. New upper and lower bounds on the optimal tradeoff between Normalized Delivery Time (NDT) and computation load are presented. The upper bound strictly improves over the previous reported upper bounds and is based on a novel interference alignment (IA) scheme tailored to the interference cancellation capabilities of MapReduce nodes. The lower bound is proved through information-theoretic converse arguments. |
| title | A New Interference-Alignment Scheme for Wireless MapReduce |
| topic | Information Theory Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2210.06621 |