An efficient task offloading scheme in vehicular edge computing

Vehicular edge computing (VEC) is a promising paradigm to offload resource-intensive tasks at the network edge. Owing to time-sensitive and computation-intensive vehicular applications and high mobility scenarios, cost-efficient task offloading in the vehicular environment is still a challenging pro...

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Vydané v:Journal of cloud computing : advances, systems and applications Ročník 9; číslo 1; s. 1 - 14
Hlavní autori: Raza, Salman, Liu, Wei, Ahmed, Manzoor, Anwar, Muhammad Rizwan, Mirza, Muhammad Ayzed, Sun, Qibo, Wang, Shangguang
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 02.06.2020
Springer Nature B.V
SpringerOpen
Predmet:
Algorithms
Communication
Computation offloading
Computer Communication Networks
Computer Science
Computer simulation
Computer System Implementation
Computer Systems Organization and Communication Networks
Edge computing
Information Systems Applications (incl.Internet)
Mobile edge computing
Mobility
Software Engineering/Programming and Operating Systems
Special Purpose and Application-Based Systems
Task offloading
Vehicular edge computing
Vehicular networks
Vehicular edge computing
Mobility
Vehicular networks
Task offloading
Mobile edge computing
ISSN:2192-113X, 2192-113X
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Popis
Shrnutí:Vehicular edge computing (VEC) is a promising paradigm to offload resource-intensive tasks at the network edge. Owing to time-sensitive and computation-intensive vehicular applications and high mobility scenarios, cost-efficient task offloading in the vehicular environment is still a challenging problem. In this paper, we study the partial task offloading problem in vehicular edge computing in an urban scenario. Where the vehicle computes some part of a task locally, and offload the remaining task to a nearby vehicle and to VEC server subject to the maximum tolerable delay and vehicle’s stay time. To make it cost-efficient, including the cost of the required communication and computing resources, we consider to fully exploit the vehicular available resources. We estimate the transmission rates for the vehicle to vehicle and vehicle to infrastructure communication based on practical assumptions. Moreover, we present a mobility-aware partial task offloading algorithm, taking into account the task allocation ratio among the three parts given by the communication environment conditions. Simulation results validate the efficient performance of the proposed scheme that not only enhances the exploitation of vehicular computation resources but also minimizes the overall system cost in comparison to baseline schemes.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2192-113X
2192-113X
DOI:10.1186/s13677-020-00175-w