.png){kind=icon}
Return
RAMOS: A Resource-Aware Multi-Objective System for Edge Computing
.png){kind=icon}
PRE
AI
DOI：10.1109/TMC.2020.2984134.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Mobile and IoT devices are becoming increasingly capable computing platforms that are often underutilized. In this paper, we propose RAMOS, a system that leverages the idle compute cycles in a group of heterogeneous mobile and IoT devices that can be clustered to form an edge FemtoCloud. At the heart of this system, we formulate a multi-objective, resource-aware task assignment and scheduling problem. The scheduler runs in two main modes; latency-minimization and energy-efficiency. Under the latency-minimization mode, it strives to maximize the computational throughput of the constructed FemtoCloud while maintaining the energy consumption below an operator specified threshold. Under the energy-efficient mode, it minimizes the total energy consumed in the FemtoCloud while meeting defined tasks deadlines. Due to the NP-Completeness of this scheduling problem, we design a set of heuristics to solve it. We implement a prototype of our system and use it to evaluate its performance and efficiency. Our results demonstrate the system's ability to meet different scheduling objectives while adhering to pre-specified time and energy constraints. Compared to other schedulers, RAMOS achieves 10 to 40 percent completion time improvement under latency minimization mode and up to 30 percent more energy-efficiency under the energy-efficient mode.
Keywords:
Task analysis
Processor scheduling
Energy consumption
Schedules
Performance evaluation
Systems architecture
Batteries
Edge computing
FemtoCloud
internet of things
IoT cloud
mobile cloud
mobile computing
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
9.2
Papers:
5.8K
Citations:
1.8W
Organization
View more organizations
Cited Papers
ShareSave
ShareSaveShareSaveHighly Efficient and Recyclable g-C3N4/CuO Hybrid Nanocomposite Towards Enhanced Visible-Light Photocatalytic Performance.png)
Nano
NanoIF0
PREAI
ShareSaveShareSaveShareSaveShareSave View more