TY - JOUR
T1 - Energy-Efficient Topology Control Mechanism for IoT-Oriented Software-Defined WSNs
AU - Ding, Zhaoming
AU - Shen, Lianfeng
AU - Chen, Hongyang
AU - Yan, Feng
AU - Ansari, Nirwan
N1 - Funding Information:
This work was supported in part by the Specialized Development Foundation for the Achievement Transformation of Jiangsu Province under Grant BA2019025; in part by the National Natural Science Foundation of China under Grant 61601122; in part by the National Natural Science Foundation of China under Grant 62271452; in part by the Changzhou Key Laboratory of 5G + Industrial Internet Fusion Application under Grant CM20223015; in part by the Changzhou Sci&Tech Program under Grant CJ20220068; and in part by the Research Fund of Jiangsu University of Technology under Grant KYY22006.
Publisher Copyright:
IEEE
PY - 2023
Y1 - 2023
N2 - In time-varying software-defined wireless sensor networks (SDWSNs) for Internet-of-Things (IoT) applications, the topology may change due to the interference or abnormal events, thus leading to network performance degradation. In this paper, an energy-efficient topology control (TC) mechanism applied for IoT-oriented SDWSNs is proposed to maximize the network energy efficiency (EE) during the dynamic topology maintenance. First, a hierarchical SDWSN architecture consisting of the cluster-based sensing network and the programmable relay network is presented. Second, two TC algorithms based on the link EE are proposed to apply in the cluster and relay sub-networks of SDWSN, respectively. In the cluster sub-network, the proposed distributed TC algorithm enables the link interference mitigation by employing power control and rate allocation in each cluster. In the relay sub-network, the proposed centralized TC algorithm first utilizes a specified model to construct the original topology. During the dynamic topology maintenance, the proposed centralized TC algorithm is realized by the value-iteration learning method based on a Markov decision process (MDP) model, upon which the state-transition probability (STP) of the relay sub-network is obtained, where the relay-network state is composed of the link, the queue, and the residual energy ratio states for all nodes in the relay sub-network. Finally, simulation results show that both two TC algorithms can improve the corresponding sub-network EE of time-varying SDWSN.
AB - In time-varying software-defined wireless sensor networks (SDWSNs) for Internet-of-Things (IoT) applications, the topology may change due to the interference or abnormal events, thus leading to network performance degradation. In this paper, an energy-efficient topology control (TC) mechanism applied for IoT-oriented SDWSNs is proposed to maximize the network energy efficiency (EE) during the dynamic topology maintenance. First, a hierarchical SDWSN architecture consisting of the cluster-based sensing network and the programmable relay network is presented. Second, two TC algorithms based on the link EE are proposed to apply in the cluster and relay sub-networks of SDWSN, respectively. In the cluster sub-network, the proposed distributed TC algorithm enables the link interference mitigation by employing power control and rate allocation in each cluster. In the relay sub-network, the proposed centralized TC algorithm first utilizes a specified model to construct the original topology. During the dynamic topology maintenance, the proposed centralized TC algorithm is realized by the value-iteration learning method based on a Markov decision process (MDP) model, upon which the state-transition probability (STP) of the relay sub-network is obtained, where the relay-network state is composed of the link, the queue, and the residual energy ratio states for all nodes in the relay sub-network. Finally, simulation results show that both two TC algorithms can improve the corresponding sub-network EE of time-varying SDWSN.
KW - Energy efficiency
KW - Heuristic algorithms
KW - Internet of Things
KW - Markov decision process
KW - Network topology
KW - Real-time systems
KW - Relays
KW - Topology
KW - Wireless sensor networks
KW - internet of things
KW - software-defined wireless sensor networks
KW - topology control
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U2 - 10.1109/JIOT.2023.3260802
DO - 10.1109/JIOT.2023.3260802
M3 - Article
AN - SCOPUS:85151532253
SN - 2327-4662
SP - 1
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
ER -