A Data and Service placement strategy for edge networks
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Updated
Dec 22, 2023 - Python
A Data and Service placement strategy for edge networks
The ecoHMEM framework is a user-level framework that performs automatic object-level placement on heterogeneous memory systems such as DRAM and Persistent Memory.
A research simulation framework for optimizing data placement across edge servers to minimize total access time. Provides configurable bandwidth models and performance metrics for edge computing research.
Proof-of-concept demonstrating Apache Kafka rack-aware topic placement across distributed datacenters using Docker Compose, KRaft mode, and Strimzi on Kubernetes
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