TY - JOUR
T1 - QoS-Predicted Energy Efficient Routing for Information-Centric Smart Grid
T2 - A Network Calculus Approach
AU - Wang, Kuan
AU - Li, Jianhua
AU - Wu, Jun
AU - Li, Gaolei
N1 - Funding Information:
This work was supported by the National Natural Science Foundation of China under Grants 61571300 and 61431008.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/9/17
Y1 - 2018/9/17
N2 - As the proportion of information content in the power grid increased, information-centric smart grid (iCenS) has drawn much attention in recent years. By introducing features of information-centric networking on decentralization, multi-path transmission, and in-network caching to distributed power systems, the iCenS enabled more efficient demand response, disruption tolerant, and mobility support. However, due to the strict quality of services (QoSs) requirement of power grid and a large number of resource-limited infrastructures existed in iCenS, it still faces the following challenges. First, multi-path addressing will cause redundant packets and the transmission of duplicate packet consumes the node energy which may lead to link failure; the delayed transaction of key component information like tele-protection will induce electricity accidents. Second, it is hard to model the traffic of iCenS without introducing extra computing burden because of its interest-driven feature and constantly updated forwarding information base. we propose a QoS-predicted energy efficient routing (QPER) scheme for iCenS, which leverage on the network calculus. Upon collecting the real-time state information of the iCenS nodes, the QPER rapidly predicts the QoS boundary and energy consumption of each link for upcoming traffic flows by establishing the service curve and arrival curve. The simulation results validate that our method is superior to traditional multicast routing algorithm in terms of delay, energy consumption, packet loss, and others. Simultaneously, providing various routing methods for different service information can ensure the stability and minimize the security risks.
AB - As the proportion of information content in the power grid increased, information-centric smart grid (iCenS) has drawn much attention in recent years. By introducing features of information-centric networking on decentralization, multi-path transmission, and in-network caching to distributed power systems, the iCenS enabled more efficient demand response, disruption tolerant, and mobility support. However, due to the strict quality of services (QoSs) requirement of power grid and a large number of resource-limited infrastructures existed in iCenS, it still faces the following challenges. First, multi-path addressing will cause redundant packets and the transmission of duplicate packet consumes the node energy which may lead to link failure; the delayed transaction of key component information like tele-protection will induce electricity accidents. Second, it is hard to model the traffic of iCenS without introducing extra computing burden because of its interest-driven feature and constantly updated forwarding information base. we propose a QoS-predicted energy efficient routing (QPER) scheme for iCenS, which leverage on the network calculus. Upon collecting the real-time state information of the iCenS nodes, the QPER rapidly predicts the QoS boundary and energy consumption of each link for upcoming traffic flows by establishing the service curve and arrival curve. The simulation results validate that our method is superior to traditional multicast routing algorithm in terms of delay, energy consumption, packet loss, and others. Simultaneously, providing various routing methods for different service information can ensure the stability and minimize the security risks.
KW - Smart grids
KW - energy efficiency
KW - information-centric networking
KW - network calculus
KW - quality of service
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U2 - 10.1109/ACCESS.2018.2870929
DO - 10.1109/ACCESS.2018.2870929
M3 - Article
AN - SCOPUS:85053613630
SN - 2169-3536
VL - 6
SP - 52867
EP - 52876
JO - IEEE Access
JF - IEEE Access
M1 - 8467331
ER -