Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Dynamic Scheduling for Over-the-Air Federated Edge Learning with Energy
  Constraints   Machine learning and wireless communication technologies are jointly
facilitating an intelligent edge, where federated edge learning (FEEL) is a
promising training framework. As wireless devices involved in FEEL are resource
limited in terms of communication bandwidth, computing power and battery
capacity, it is important to carefully schedule them to optimize the training
performance. In this work, we consider an over-the-air FEEL system with analog
gradient aggregation, and propose an energy-aware dynamic device scheduling
algorithm to optimize the training performance under energy constraints of
devices, where both communication energy for gradient aggregation and
computation energy for local training are included. The consideration of
computation energy makes dynamic scheduling challenging, as devices are
scheduled before local training, but the communication energy for over-the-air
aggregation depends on the l2-norm of local gradient, which is known after
local training. We thus incorporate estimation methods into scheduling to
predict the gradient norm. Taking the estimation error into account, we
characterize the performance gap between the proposed algorithm and its offline
counterpart. Experimental results show that, under a highly unbalanced local
data distribution, the proposed algorithm can increase the accuracy by 4.9% on
CIFAR-10 dataset compared with the myopic benchmark, while satisfying the
energy constraints.

8
The categories of this paper are: hep-ex
19
The categories of this paper are: eess
3
The categories of this paper are: physics
22
The categories of this paper are: chao-dyn
12
The categories of this paper are: nucl-th
35
The categories of this paper are: mtrl-th
28
The categories of this paper are: alg-geom
23
The categories of this paper are: solv-int
18
The categories of this paper are: econ
16
The categories of this paper are: stat
0
The categories of this paper are: hep-ph
27
The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an
25
The categories of this paper are: patt-sol
9
The categories of this paper are: nlin
30
The categories of this paper are: q-alg