.png){kind=icon}
Return
Category Attribute-Oriented Heterogeneous Resource Allocation and Task Offloading for SAGIN Edge Computing
.png){kind=icon}
OA
AI
DOI：10.3390/jsan14040081.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Space-Air-Ground Integrated Network (SAGIN), which is considered a network architecture with great development potential, exhibits significant cross-domain collaboration characteristics at present. However, most of the existing works ignore the matching and adaptability of differential tasks and heterogeneous resources, resulting in significantly inefficient task execution and undesirable network performance. As a consequence, we formulate a category attribute-oriented resource allocation and task offloading optimization problem with the aim of minimizing the overall scheduling cost. We first introduce a task–resource matching matrix to facilitate optimal task offloading policies with computation resources. In addition, virtual queues are constructed to take the impacts of randomized task arrival into account. To solve the optimization objective which jointly considers bandwidth allocation, transmission power control and task offloading decision effectively, we proposed a deep reinforcement learning (DRL) algorithm framework considering type matching. Simulation experiments demonstrate the effectiveness of our proposed algorithm as well as superior performance compared to others.
Keywords:
Space-Air-Ground Integrated Network
type matching
task offloading
resource allocation
reinforcement learning
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
4.2
Papers:
619
Citations:
1.6K
Organization
Cited Papers
Dynamic Computation Offloading and Server Deployment for UAV-Enabled Multi-Access Edge Computing
PREAI
ShareSaveShareSave
ShareSaveShareSaveShareSaveShareSaveSpace-air-ground integrated network (SAGIN) for 6G: Requirements, architecture and challenges.png)
CHINA COMMUNICATIONS
CHINA COMMUNICATIONSIF3.1
PREAI
ShareSaveShareSave
View more