Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Exploiting Moving Intelligence: Delay-Optimized Computation Offloading
  in Vehicular Fog Networks   Future vehicles will have rich computing resources to support autonomous
driving and be connected by wireless technologies. Vehicular fog networks
(VeFN) have thus emerged to enable computing resource sharing via computation
task offloading, providing wide range of fog applications. However, the high
mobility of vehicles makes it hard to guarantee the delay that accounts for
both communication and computation throughout the whole task offloading
procedure. In this article, we first review the state-of-the-art of task
offloading in VeFN, and argue that mobility is not only an obstacle for timely
computing in VeFN, but can also benefit the delay performance. We then identify
machine learning and coded computing as key enabling technologies to address
and exploit mobility in VeFN. Case studies are provided to illustrate how to
adapt learning algorithms to fit for the dynamic environment in VeFN, and how
to exploit the mobility with opportunistic computation offloading and task
replication.

21
The categories of this paper are: adap-org
8
The categories of this paper are: hep-ex
22
The categories of this paper are: chao-dyn
0
The categories of this paper are: hep-ph
10
The categories of this paper are: q-bio
5
The categories of this paper are: gr-qc
16
The categories of this paper are: stat
27
The categories of this paper are: comp-gas
36
The categories of this paper are: cmp-lg
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
7
The categories of this paper are: hep-th
17
The categories of this paper are: q-fin
18
The categories of this paper are: econ
35
The categories of this paper are: mtrl-th
13
The categories of this paper are: quant-ph