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Dynamic scheduling algorithm for LTE uplink with smart‐metering traffic
Author(s) -
Amarasekara Bhagya,
Ranaweera Chathurika,
Evans Rob,
Nirmalathas Ampalavanapillai
Publication year - 2017
Publication title -
transactions on emerging telecommunications technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.366
H-Index - 47
ISSN - 2161-3915
DOI - 10.1002/ett.3163
Subject(s) - computer science , quality of service , computer network , network packet , metering mode , scheduling (production processes) , telecommunications link , base station , cellular network , real time computing , cellular traffic , engineering , mechanical engineering , operations management
Long‐term evolution (LTE) is a promising last mile access candidate technology for the smart‐metering communication architecture. However, when the mobile LTE network is used to support smart meters (SMs), the quality‐of‐service (QoS) requirements of the smart‐metering traffic as well as all the other typical mobile network traffic need to be ensured. This becomes problematic when the network users generate diverse traffic types that have different QoS requirements. Therefore, in this paper, we propose a dynamic bandwidth scheduling algorithm to ensure the required QoS of various traffic types arising from both SMs and mobile users. Our proposed dynamic bandwidth allocation algorithm integrates two schedulers that are designed for periodic and emergency SM traffic situations that have different SM traffic intensities and QoS requirements. Designing of two schedulers provides the advantages of leveraging the particular traffic characteristics of these two diverse operational situations and achieving the maximum use of resources to ensure QoS requirements. In addition, to alleviate potential problems created by simultaneous emergency SM traffic, we also propose a method that deploys a random delay for SM packet transmissions. We analyse the delay and packet drop ratio of diverse traffic types when both the LTE base station scheduler and the SMs deploy our proposed methods under either periodic or emergency SM traffic conditions in the smart grid. Our results show that our proposed mechanisms are capable of satisfying the QoS requirements of both mobile users and SMs under diverse traffic conditions.