scholarly journals SDN-Enabled 3C Resource Integration in Green Internet of Electrical Vehicles

2021 ◽  
Author(s):  
Handi Chen ◽  
Xiaojie Wang ◽  
Zhaolong Ning ◽  
Lei Guo
Keyword(s):  
Quality Of Service ◽  
Renewable Energy ◽  
Real World ◽  
Migration Policy ◽  
Imitation Learning ◽  
The Internet ◽  
Electrical Vehicles ◽  
Resource Policy ◽  
Computational Resources

With the advocacy of green renewable energy, Electric Vehicles (EVs) have gradually become the mainstream in the automobile market. Due to the finite edge resources of the Internet of EVs, this paper integrates idle communication, caching and computational resources of EVs to enrich the available resources for vehicular task migration. Considering the limited capacity and resources of EVs, a distributed lightweight imitation learning-based efficient Task cOoperative migration Policy Integrating 3C resource policy, named TOPIC, is proposed to maximize the obtained quality of service. The experimental results based on the real-world traffic dataset of Hangzhou (China) demonstrate the QoS obtained based on the expert policy and agent policy of TOPIC is about 3 times higher than other representative policies.

scholarly journals A Robust Service Selection Method Based on Uncertain QoS

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Yanping Chen ◽  
Lu Jiang ◽  
Jianke Zhang ◽  
Xiaoxiao Dong
Keyword(s):  
Quality Of Service ◽  
Real World ◽  
Model Experiment ◽  
Service Providers ◽  
Service Selection ◽  
Selection Method ◽  
The Internet ◽  
Aggregation Functions ◽  
Uncertain Qos

Nowadays, the number of Web services on the Internet is quickly increasing. Meanwhile, different service providers offer numerous services with the similar functions. Quality of Service (QoS) has become an important factor used to select the most appropriate service for users. The most prominent QoS-based service selection models only take the certain attributes into account, which is an ideal assumption. In the real world, there are a large number of uncertain factors. In particular, at the runtime, QoS may become very poor or unacceptable. In order to solve the problem, a global service selection model based on uncertain QoS was proposed, including the corresponding normalization and aggregation functions, and then a robust optimization model adopted to transform the model. Experiment results show that the proposed method can effectively select services with high robustness and optimality.

scholarly journals Curriculum Learning for Natural Answer Generation

2018 ◽  
Author(s):  
Cao Liu ◽  
Shizhu He ◽  
Kang Liu ◽  
Jun Zhao
Keyword(s):  
Full Advantage ◽  
Real World ◽  
Large Scale ◽  
Question Answering ◽  
Generative Models ◽  
The Internet ◽  
Basic Model ◽  
The Arts ◽  
Learning Data

By reason of being able to obtain natural language responses, natural answers are more favored in real-world Question Answering (QA) systems. Generative models learn to automatically generate natural answers from large-scale question answer pairs (QA-pairs). However, they are suffering from the uncontrollable and uneven quality of QA-pairs crawled from the Internet. To address this problem, we propose a curriculum learning based framework for natural answer generation (CL-NAG), which is able to take full advantage of the valuable learning data from a noisy and uneven-quality corpus. Specifically, we employ two practical measures to automatically measure the quality (complexity) of QA-pairs. Based on the measurements, CL-NAG firstly utilizes simple and low-quality QA-pairs to learn a basic model, and then gradually learns to produce better answers with richer contents and more complete syntaxes based on more complex and higher-quality QA-pairs. In this way, all valuable information in the noisy and uneven-quality corpus could be fully exploited. Experiments demonstrate that CL-NAG outperforms the state-of-the-arts, which increases 6.8% and 8.7% in the accuracy for simple and complex questions, respectively.

Architectures, Protocols and Quality of Service for the Internet of the Future

1999 ◽  
Vol 10 (2) ◽  
pp. 107-109
Author(s):  
Matteo D'Ambrosio ◽  
Guest Editor ◽  
Mohammed Atiquzzaman ◽  
Guest Editor
Keyword(s):  
Quality Of Service ◽  
The Internet ◽  
The Future
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