Dynamic Scheduling Policy for Patient Flow in a Smart Environment

CHEN Xiao; DING Jie; Nigel Thomas

doi:10.1049/cje.2017.01.003

Volume 26 Issue 3

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CHEN Xiao, DING Jie, Nigel Thomas, “Dynamic Scheduling Policy for Patient Flow in a Smart Environment,” Chinese Journal of Electronics, vol. 26, no. 3, pp. 530-536, 2017, doi: 10.1049/cje.2017.01.003

Citation:

CHEN Xiao, DING Jie, Nigel Thomas, “Dynamic Scheduling Policy for Patient Flow in a Smart Environment,” Chinese Journal of Electronics, vol. 26, no. 3, pp. 530-536, 2017, doi: 10.1049/cje.2017.01.003

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Dynamic Scheduling Policy for Patient Flow in a Smart Environment

doi: 10.1049/cje.2017.01.003

1.
School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang 212013, China;
2.
State Key Laboratory of Software Development Environment, Beihang University, Beijing 100191, China;
3.
School of Information Engineering, Yangzhou University, Yangzhou 225009, China;
4.
School of Computing Science, Newcastle University, Newcastle Upon Tyne NE1 7RU, UK

Funds: This work is supported by the Natural Science Foundation of Jiangsu (No.BK20160543), the National Natural Science Foundation of China (No.61472343, No.U1405255), and the State Key Laboratory Program (No.BM20082061507).

Received Date: 2015-09-07
Rev Recd Date: 2016-01-15
Publish Date: 2017-05-10

Abstract

Abstract

Given the popularity of smart environment in a hospital involving the participation of a large group of patients, scheduling of patients towards their desired destination is still being a challenging issue. With the development of Internet of Things (IoT), smart environments are increasingly being deployed in various public scenarios and in particular, hospitals are an important target environment for smart environments. This paper models a dynamic scheduling policy based on a patient flow scenario in order to solve the queuing issue and facilitate people's experience. The dynamic scheduling policy aims to forward incoming patients to dissolve jams especially at the peaks by giving accurate predication of appointment time. The main modelling technique is a formal method-Performance evaluation process algebra (PEPA). The findings show that the dynamic scheduling policy is able to efficiently improve the patient flow.
- Dynamic scheduling,
- Patient flow,
- Smart environment,
- Formal method,
- Performance evaluation process algebra (PEPA)

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References(14)

References

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