Multi-objective computation offloading for Internet of Vehicles in cloud-edge computing

Xu, Xiaolong; Gu, Renhao; Dai, Fei; Qi, Lianyong; Wan, Shaohua

doi:10.1007/s11276-019-02127-y

Cited by 65 publications

(28 citation statements)

References 43 publications

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“…In [13], researchers develop a computational offloading scheme for internet of vehicles (IoV) applications. Their work utilizes a genetic algorithm to optimize the offloading of compute tasks to edge servers.…”

Section: Other Related Workmentioning

confidence: 99%

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Energy Aware Routing with Computational Offloading for Wireless Sensor Networks

Barker¹,

Swany²

2020

Computer Science &Amp; Information Technology (CS &Amp; IT)

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Wireless sensor networks (WSN) are characterized by a network of small, battery powered devices, operating remotely with no pre-existing infrastructure. The unique structure of WSN allow for novel approaches to data reduction and energy preservation. This paper presents a modification to the existing Q-routing protocol by providing an alternate action of performing sensor data reduction in place thereby reducing energy consumption, bandwidth usage, and message transmission time. The algorithm is further modified to include an energy factor which increases the cost of forwarding as energy reserves deplete. This encourages the network to conserve energy in favor of network preservation when energy reserves are low. Our experimental results show that this approach can, in periods of high network traffic, simultaneously reduce bandwidth, conserve energy, and maintain low message transition times.

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Section: Other Related Workmentioning

confidence: 99%

“…Our work retains elements of energy efficiency, computational offloading, and congestion management to build a novel approach to routing based off of the Q-routing algorithm from [9] and is detailed in section 3. Other approaches have examined similar aspects, such as in [13] and [14].…”

Section: Other Related Workmentioning

confidence: 99%

Energy Aware Routing with Computational Offloading for Wireless Sensor Networks

Barker¹,

Swany²

2020

Computer Science &Amp; Information Technology (CS &Amp; IT)

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“…Xu et al [19] proposed a genetic algorithm‐based multi‐objective function to reduce the energy consumption, shorten the computing task processing time, and decrease load imbalance. Furthermore, SAW and MCDM are used to evaluate the efficiency and effectiveness of the solution.…”

Section: Related Workmentioning

confidence: 99%

Best fit power weighted difference method for fog node selection in smart cities

et al. 2020

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“…When the load of MEC server is unstable, it will affect the server performance and even lead to server failure. On the other hand, the energy consumed in the operation process is also one of the measurement criteria [3]. Therefore, when allocating resources, it is necessary to optimize the load and energy consumption of a large number of deployed MEC servers to reduce the cost of edge equipment [4].…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Optimized Immune Algorithm For Computing Offloading Problem In Edge Computing Scenes of Internet of Vehicles

Zhu

Cai

Sun

et al. 2021

Preprint

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With the development of 5G technology, the Internet of Vehicles (IoV) has also received worldwide attention. IoV edge computing achieves the goal of low latency by offloading tasks to the Mobile Edge Computing Server (MECS). However, it is still a challenge to reduce the computing delay of mobile terminal devices while ensuring the low energy consumption and load balancing of servers. In order to solve this problem, the system model, delay model, load balancing model, energy consumption model and objective optimization model are established in this paper. A computational unloading scheme based on multi-objective immune optimization algorithm is proposed. Finally, this scheme is compared with the reference scheme and the literature scheme. Simulation experiments show that the proposed scheme can effectively reduce the average unload delay of users, optimize the workload between servers, and effectively reduce energy consumption. Its performance is better than the schemes in the literature.

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Multi-objective computation offloading for Internet of Vehicles in cloud-edge computing

Cited by 65 publications

References 43 publications

Energy Aware Routing with Computational Offloading for Wireless Sensor Networks

Energy Aware Routing with Computational Offloading for Wireless Sensor Networks

Best fit power weighted difference method for fog node selection in smart cities

Multi-Objective Optimized Immune Algorithm For Computing Offloading Problem In Edge Computing Scenes of Internet of Vehicles

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