Context Aware Traffic Scheduling Algorithm for Power Distribution Smart Grid Network

The emergence of smart grid poses technical challenges to the power distribution network because of the increasing data traffic resulting from diverse data applications. Traffic scheduling algorithms manage these heterogeneous applications by applying different priorities to each traffic type based on its quality of service (QoS). However, QoS alone cannot accurately capture complex situations wherein packets with low priority occasionally need to be served first based on their context, resulting in a suboptimal solution. This paper proposes a context aware traffic scheduling (CATSchA) algorithm to schedule the traffic such that it could adapt to varying power network conditions. The power distribution network traffic is characterized based on heterogeneous traffic demands, and then mapped into weighted quality classes. The CATSchA algorithm is implemented in a packet switched network using NS-3 simulator, and the traffic demand is fulfilled based on the algorithm’s context awareness. Compared with traditional traffic scheduling algorithms, the proposed algorithm lowers the delay while maintaining the throughput and link efficiency.

[1]  Chen Tian,et al.  Joint Optimization on Bandwidth Allocation and Route Selection in QoE-Aware Traffic Engineering , 2019, IEEE Access.

[2]  Faouzi Kamoun,et al.  IP/MPLS networks with hardened pipes: service concepts, traffic engineering and design considerations , 2019, J. Ambient Intell. Humaniz. Comput..

[3]  H. T. Mouftah,et al.  Delay Critical Smart Grid Applications and Adaptive QoS Provisioning , 2015, IEEE Access.

[4]  Hamid Reza Pourreza,et al.  Multi-class routing protocol using virtualization and SDN-enabled architecture for smart grid , 2018, Peer-to-Peer Netw. Appl..

[5]  Shanlin Yang,et al.  Big data driven smart energy management: From big data to big insights , 2016 .

[6]  Waqar Mahmood,et al.  Energy efficient context aware traffic scheduling for IoT applications , 2017, Ad Hoc Networks.

[7]  Mohammad Hossein Yaghmaee Moghaddam,et al.  SDN-Based Quality of Service Networking for Wide Area Measurement System , 2020, IEEE Transactions on Industrial Informatics.

[8]  H. T. Mouftah,et al.  Quality-of-service-aware fiber wireless sensor network gateway design for the smart grid , 2013, 2013 IEEE International Conference on Communications Workshops (ICC).

[9]  Carlos Samitier,et al.  Utility Communication Networks and Services , 2017 .

[10]  Xu Li,et al.  A reliable QoS-aware routing scheme for neighbor area network in smart grid , 2016, Peer Peer Netw. Appl..

[11]  Itziar Angulo,et al.  Smart Grid Applications for a Practical Implementation of IP over Narrowband Power Line Communications , 2017 .

[12]  Mohammad Hossein Yaghmaee,et al.  QUALITY OF SERVICE GUARANTEE IN SMART GRID INFRASTRUCTURE COMMUNICATION USING TRAFFIC CLASSIFICATION , 2013 .

[13]  A. K. M. Baki Continuous Monitoring of Smart Grid Devices Through Multi Protocol Label Switching , 2014, IEEE Transactions on Smart Grid.

[14]  Saifur Rahman,et al.  Communication network requirements for major smart grid applications in HAN, NAN and WAN , 2014, Comput. Networks.

[15]  H. T. Mouftah,et al.  Smart grid monitoring with service differentiation via EPON and wireless sensor network convergence , 2014, Opt. Switch. Netw..

[16]  Byrav Ramamurthy,et al.  Dynamic provisioning in virtualized Cloud infrastructure in IP/MPLS-over-WDM networks , 2017, 2017 International Conference on Computing, Networking and Communications (ICNC).

[17]  Gaochao Xu,et al.  SDN-Based Data Center Networking With Collaboration of Multipath TCP and Segment Routing , 2017, IEEE Access.

[18]  Ian F. Akyildiz,et al.  Channel-aware routing and priority-aware multi-channel scheduling for WSN-based smart grid applications , 2016, J. Netw. Comput. Appl..