Predicting the energy consumption in software defined wireless sensor networks: a probabilistic Markov model approach
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ORIGINAL RESEARCH
Predicting the energy consumption in software defined wireless sensor networks: a probabilistic Markov model approach Atefeh Rahimifar1 · Yousef Seifi Kavian1 · Hooman Kaabi1 · Mohammad Soroosh1 Received: 18 January 2019 / Accepted: 3 October 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract The smart world is connecting all universe more than ever thought possible, benefiting from the significant advances of the Internet of Things (IoT) applications using wireless sensor networks (WSN) as the core technology. A challenging issue in the IoT paradigm is the heterogeneity in different parts of the network. The network developers need to use resources belonging to different platforms for their applications, and the software defined network (SDN) approach is a mainly considered solution. In this paper, a software defined wireless sensor network (SDWSN) with an energy predictor model (SDWSN-EPM) based on the Markov probabilistic model is proposed to reduce the energy consumption and the network latency. The energy consumption rate (ECR) of the sensor nodes is modeled using the Markov model and the states of the sensor nodes. The ECR is used by the SDN controller to predict the residual energy level of the nodes and consequently, the energy consumption of the network. The cumulative distribution functions (CDF) of the delay, power consumption, and the network lifetime in both SDWSN and SDWSN-EPM schemes are compared. The results confirm that the SDWSN-EPM model significantly improves the performance of the sensor networks. Keywords Software defined wireless sensor networks · Energy consumption prediction · Markov model · Performance evaluation · Internet of things
1 Introduction The Internet of Things (IoT) is rapidly taking over the world. Smart healthcare, smart grid, smart cities, smart homes, smart vehicles, smart underwater networks, and intelligent transportation are some examples of the IoT applications which are making significant development in our daily life (Ma and Li 2020; Yamauchi et al. 2020; Menon et al. 2020). Wireless sensor network (WSN) is an inseparable part of the IoT that collect and transfer information. Moreover, with advancements in IoT, wireless devices can be integrated into existing wired systems, making it a heterogeneous network, where different mediums, protocols, and software parts may coexist in the same network (Cecílio et al. 2017). Therefore, creating a seamless interaction between heterogeneous networks is a significant challenges of the IoT.
* Yousef Seifi Kavian [email protected] 1
Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran
In recent years a new achievement has been proposed to solve IoT problems such as management difficulty, heterogeneity, and low flexibility of networks (Anadiotis et al. 2016, 2018). This approach, which applies wireless sensor nodes based on the SDN paradigm and OpenFlow (McKeown et al. 2008), is called software defined wireless sensor network (SDWSN). The SDWSN separates the
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