Decentralized Radio Resource Allocation for Single-Network and Multi-Homing Services in Cooperative Heterogeneous Wireless Access Medium
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This paper studies radio resource allocation for mobile terminals (MTs) in a heterogeneous wireless access medium. Unlike the existing solutions in literature, we consider the simultaneous presence of both single-network and multi-homing services in the networking environment. In single-network services, an MT is assigned to the best wireless access network available at its location. On the other hand, in multi-homing services, an MT utilizes all available wireless access networks simultaneously. The objective of the radio resource allocation is of twofold: to determine the optimal assignment of MTs with single-network service to the available wireless access networks, and to find the corresponding optimal bandwidth allocation to the MTs with single-network and multi-homing services. We develop a sub-optimal decentralized implementation of the radio resource allocation, which relies on network cooperation to perform the allocation in a dynamic environment in an efficient manner. The MT plays an active role in the resource allocation operation, whether by selecting the best available wireless network for single-network services or by determining the required bandwidth share from each available network for multi-homing services. Simulation results are presented to demonstrate the performance of the proposed algorithm.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it