An Opportunistic Vehicle-Based Task Assignment for IoT offloading

dc.contributor.authorSarieddine, Khaled
dc.contributor.authorArtail, Hassan Ali
dc.contributor.authorSafa, Haidar
dc.contributor.departmentDepartment of Electrical and Computer Engineering
dc.contributor.departmentDepartment of Computer Science
dc.contributor.facultyMaroun Semaan Faculty of Engineering and Architecture (MSFEA)
dc.contributor.facultyFaculty of Arts and Sciences (FAS)
dc.contributor.institutionAmerican University of Beirut
dc.date.accessioned2025-01-24T11:30:52Z
dc.date.available2025-01-24T11:30:52Z
dc.date.issued2022
dc.description.abstractIoT is one of the most prolific origins of data that is collected from sensory inputs. IoT devices are characterized by low computational power, thus motivating the computation offloading scheme, a promising technique that mitigates energy performance issues in limited power devices. Instead of offloading to fog or cloud, a new research track is emerging where devices unload their computational needs to vehicles roaming around, and this particular type of offloading is called vehicular fog offloading. In this paper, we propose the use of vehicles as Mobile Computing Nodes (MCNs) roaming around within an area to offer computational services to IoT devices. Assigning tasks to an appropriate MCN by an IoT device that wishes to offload specific communication tasks to it will be formulated based on the quality of the communication channel and on the time needed to offload the computation request. Specifically, the vehicle which will serve as an MCN must be within the range of the requesting fixed IoT device and offer suitable SINR and the estimated duration of connection values, while taking into consideration its mobility. Another challenge would be delivering the results back to the IoT device or another party, knowing that the vehicles will not be stationary. The performance results show that the proposed system represents a promising solution by offering computation offloading services and delivering the results within acceptable times, regardless of where the vehicle might be when it wants to return the results. © 2022 Elsevier B.V.
dc.identifier.doihttps://doi.org/10.1016/j.comnet.2022.109038
dc.identifier.eid2-s2.0-85130605559
dc.identifier.urihttp://hdl.handle.net/10938/27497
dc.language.isoen
dc.publisherElsevier B.V.
dc.relation.ispartofComputer Networks
dc.sourceScopus
dc.subjectEstimated duration of connection
dc.subjectMcn
dc.subjectMobile computing clouds
dc.subjectMobile computing node
dc.subjectSinr
dc.subjectMobile computing
dc.subjectSignal interference
dc.subjectSpurious signal noise
dc.subjectVehicle performance
dc.subjectComputation offloading
dc.subjectComputing nodes
dc.subjectMobile-computing
dc.subjectSensory input
dc.subjectTasks assignments
dc.subjectInternet of things
dc.titleAn Opportunistic Vehicle-Based Task Assignment for IoT offloading
dc.typeArticle

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
2022-1649.pdf
Size:
2.71 MB
Format:
Adobe Portable Document Format