Energy-efficient optimized computing offloading method for vehicular edge computing network and system thereof

Patent metadata

Field	Value
Publication number	US-11445400-B2
Application number	US-202017437120-A
Country	US
Kind code	B2
Filing date	Aug 4, 2020
Priority date	Jul 15, 2020
Publication date	Sep 13, 2022
Grant date	Sep 13, 2022

Abstract

The present disclosure relates to an energy-efficient optimized computing offloading method for a vehicular edge computing network and a system thereof; the method comprises: calculating the energy efficiency cost EEC of local computing; calculating the energy efficiency cost EEC of mobile edge computing; determining an optimal offloading decision based on the energy efficiency cost of local computing and the energy efficiency cost of mobile edge computing; determining an optimal CPU frequency and an optimal transmit power of the vehicle based on the optimal offloading decision; and determining the optimal offloading time of the vehicle based on the optimal CPU frequency and the optimal transmit power of the vehicle. The method of the present disclosure can improve the computing offloading efficiency.

First claim

What is claimed is:

1. An energy-efficient optimized computing offloading method for a vehicular edge computing network, comprising:
calculating an energy efficiency cost EEC of local computing, wherein the calculating comprises:
calculating a local computing latency;
determining an energy consumption of local computing based on the local computing latency; and
determining an energy efficiency cost EEC of local computing based on the energy consumption and the local computing latency;

calculating an energy efficiency cost EEC of mobile edge computing, wherein the calculating comprises:
calculating a distance between a vehicle n and a base station BS;
determining a channel gain between the vehicle n and the base station based on the distance;
determining a real-time transmission rate from the vehicle n to the base station based on the channel gain;
determining a task offloading time based on the real-time transmission rate;
calculating a computing time of an MEC server;
determining a total latency of mobile edge computing based on the task offloading time and the computing time of the MEC server;
calculating an energy consumption of mobile edge computing; and
determining the energy efficiency cost EEC of mobile edge computing based on the energy consumption of mobile edge computing and the total latency of mobile edge computing;

determining an optimal offloading decision based on the energy efficiency cost of local computing and the energy efficiency cost of mobile edge computing, wherein the determining adopts the following formula:

a
n
*

=

{

1
,

if
⁢

Cost
n
o

<

Cost
n
l

&

⁢

T
n
o

<

c
n

0
,

otherwise

where a* n represents the optimal offloading decision,

c
n

=
△

R
max
2

-

D
2

-

x
n

v
n

 represents a maximum communication time between the vehicle and the base station, R max represents a maximum communication coverage of the base station BS, D represents a vertical distance between the base station and a road, x n represents an initial position of the vehicle n on the road, v n represents a moving speed of the vehicle

n
,

Cost
n
l

=
△

Z
n
l

+

λ
n

⁢

L
n

⁢

C
n

f
n
l

 represents a computing cost of local computing,

Cost
n
o

=
△

Z
n
o

+

λ
n

(

t
n
ot

+

L
n

⁢

C
n

f
MEC

)

 represents a computing cost of mobile edge computing, λ n represents a Lagrange multiplier corresponding to the latency constraint (1−a n )T n l +a n T n o ≤T n,max , a n represents a decision variable, T n,max represents a maximum tolerable latency, L n represents a data size of a task R n , C n represents the computational complexity of the task R n , f n l represents a computing speed of the vehicle n, T n l represents the local computing latency, T n o represents the total latency of mobile edge computing, Z n o represents the energy efficiency cost EEC of mobile edge computing, and Z n l represents the energy efficiency cost EEC of local computing;

Assignees

• Univ Nantong

Inventors

• Zhang Guoan
• Gu Xiaohui
• Jin Li
• Gu Jinyuan
• Ji Chen
• Ji Yancheng
• Duan Wei

Classifications

• H04W52/343

  taking into account loading or congestion level · CPC title

• H04W52/283

  Power depending on the position of the mobile · CPC title

• H04W52/146

  Uplink power control · CPC title

• H04W52/0287

  changing the clock frequency of a controller in the equipment · CPC title

• H04W4/44

  for communication between vehicles and infrastructures, e.g. vehicle-to-cloud [V2C] or vehicle-to-home [V2H] · CPC title