Search alternatives:
resource optimization » resource utilization (Expand Search), resource utilisation (Expand Search), resource limitations (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
task resource » a resource (Expand Search)
binary task » binary mask (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
resource optimization » resource utilization (Expand Search), resource utilisation (Expand Search), resource limitations (Expand Search)
wolf optimization » whale optimization (Expand Search), swarm optimization (Expand Search), _ optimization (Expand Search)
task resource » a resource (Expand Search)
binary task » binary mask (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
-
1
-
2
CDF of task latency, approximated as the inverse of the achieved computation rate.
Published 2025Subjects: -
3
-
4
Comparisons of computation rate performance for different offloading algorithms.for N = 10, 20, 30.
Published 2025Subjects: -
5
Comparison of total time consumed for different offloading algorithms.for N = 10, 20, 30.
Published 2025Subjects: -
6
-
7
-
8
-
9
-
10
-
11
-
12
The evolution of the Wireless Power Transfer (WPT) time fraction β over simulation frames.
Published 2025Subjects: -
13
-
14
-
15
-
16
The flowchart of the proposed algorithm.
Published 2024“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
-
17
Summary of literature review.
Published 2024“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
-
18
Topic description.
Published 2024“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
-
19
Notations along with their descriptions.
Published 2024“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”
-
20
Detail of the topics extracted from DUC2002.
Published 2024“…To overcome this limitation, recent advancements have introduced multi-objective evolutionary algorithms for ATS. This study proposes an enhancement to the performance of ATS through the utilization of an improved version of the Binary Multi-Objective Grey Wolf Optimizer (BMOGWO), incorporating mutation. …”