A Task Offloading Scheme for WAVE Vehicular Clouds and 5G Mobile Edge Computing

Souza, Alisson Barbosa de; Rego, Paulo A. L.; Rocha, Paulo H. G.; Carneiro, Tiago; Souza, José Neuman de

doi:10.1109/globecom42002.2020.9348130

Cited by 9 publications

(6 citation statements)

References 13 publications

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“…Then, we compared the performance of BCV with other four algorithms: FIFO (First In, First Out -used to show the behavior of choosing servers at random) [Souza et al 2021], HVC (Hybrid Vehicular edge Cloud -an of the main and most cited state-of-the-art solutions) [Feng et al 2018], GCF (Greedy for CPU Free) [Souza et al 2020b] and GTT (Greedy Task by Task) [Souza et al 2021]. The performances of the different algorithms were evaluated with a massive amount of experiments according to the two main metrics of this thesis: tasks by occurrence type and reduction in execution time.…”

Section: Discussionmentioning

confidence: 99%

A Context-Oriented Framework and Decision Algorithms for Computation Offloading in Vehicular Edge Computing

Souza

Rego

Souza

2022

Anais Estendidos Do XL Simpósio Brasileiro De Redes De Computadores E Sistemas Distribuídos (SBRC Estendido 2022)

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Some increasingly popular vehicular applications have critical time requirements. As vehicles still do not have enough computation power, they cannot satisfy these demands satisfactorily. One option to deal with this problem is to enable vehicles to transfer computational tasks to cooperating devices through the offloading technique. However, performing this technique in vehicular scenarios is challenging due to the fast movement of network nodes and the frequent disconnections. Thus, we propose a context-oriented framework and decision algorithms to reduce the execution time of vehicular applications reliably through computation offloading in vehicular edge computing systems. Experimental results show that our solutions can significantly improve the execution time of vehicular applications.

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Section: Discussionmentioning

confidence: 99%

A Context-Oriented Framework and Decision Algorithms for Computation Offloading in Vehicular Edge Computing

Souza

Rego

Souza

2022

Anais Estendidos Do XL Simpósio Brasileiro De Redes De Computadores E Sistemas Distribuídos (SBRC Estendido 2022)

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“…In our previous work [33], we proposed a scheme that applies computation offloading to edge servers, via 5G/V2I, and vehicles, via WAVE/V2V. However, the scheme does not use information about CPU capacity and known routes of 185 vehicles.…”

Section: Related Workmentioning

confidence: 99%

“…We compared the proposed decision algorithm (GTT) with four other algorithms: FIFO (First In, First Out), HVC (Hybrid Vehicular edge Cloud) [32], MDO (Multi-Decision based Offloading) [19], and GCF (Greedy for CPU Free) [33]. All algorithms used the failure recovery mechanism described in Section 4.2.4 and were tested under the same scenarios and conditions.…”

Section: Comparison With Other Algorithmsmentioning

confidence: 99%

A context-oriented framework for computation offloading in vehicular edge computing using WAVE and 5G networks

Souza

Rego

Carneiro

et al. 2021

Vehicular Communications

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“…In traditional V2N scenarios, tasks are exclusively offloaded to base stations, leading to the underutilization of available computational resources in other vehicles on the road [1,2] . Many scenarios describe base station computational capacity as an infinitely large cloud server, which is inconsistent with real-world requirements.…”

Section: Introductionmentioning

confidence: 99%