Using Message-Passing DCOP Algorithms to Solve Energy-Efficient Smart Environment Configuration Problems
Authors: Pierre Rust, Gauthier Picard, Fano Ramparany
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We illustrate our approach through a running example, and evaluate the performances of the implemented protocols on a simulated realistic environment. |
| Researcher Affiliation | Collaboration | Pierre Rust Orange Labs pierre.rust@orange.com Gauthier Picard MINES Saint Etienne, CNRS Lab Hubert Curien UMR 5516 picard@emse.fr Fano Ramparany Orange Labs fano.ramparany@orange.com |
| Pseudocode | No | The paper describes algorithms like DPOP and Max-Sum conceptually but does not provide pseudocode or structured algorithm blocks. |
| Open Source Code | No | The paper does not provide any statement or link indicating that its source code is open or publicly available. |
| Open Datasets | No | We implement and evaluate DPOP and Max-Sum on randomly generated instances. ... For each problem size (same number of rules, models and actuators), 30 instances are generated and solved. The paper uses synthetically generated instances for its experiments, not a publicly available dataset with concrete access information. |
| Dataset Splits | No | The paper mentions generating instances and solving them but does not specify any train/validation/test splits, percentages, or sample counts for reproducibility. |
| Hardware Specification | No | The paper describes the limited capabilities of smart devices in their simulated environment ('microcontrollers with just a few KBytes of RAM', 'low power network with limited throughput'), but it does not specify the actual hardware used to run the simulations or experiments themselves. |
| Software Dependencies | No | The paper mentions implementing DPOP and Max-Sum but does not specify any software names with version numbers (e.g., programming languages, libraries, or simulation platforms used for the experiments). |
| Experiment Setup | No | The paper describes the characteristics of the randomly generated problem instances (e.g., '10 actuators, 5 rules and a growing number of models'), but it does not provide specific experimental setup details such as hyperparameters for the DCOP algorithms or simulation environment settings. |