A QoS-aware Data Aggregation Strategy for Resource constrained IoT-enabled AMI Network in Smart Grid

Emerging Internet of Things (IoT) technologies and applications have enabled the Smart Grid Utility control center to connect, monitor, exchange data between smart appliances, meters (SMs), concentrators (DCs) server (CCS) over Internet. In particular, DC receives different Advanced Metering Infrastructure (AMI) from multiple SMs for processing, queuing, aggregation, forwarding onward towards CCS things networking. However, DCs are expensive component AMI network. Recently, used as relay-devices accomplish a cost-effective network infrastructure avoid placement bottleneck problem. recourse constrained (limited CPU, RAM, storage, capacity) intelligent devices which faces numerous communication challenges during outage conditions summer peak hours where bulk amount with traffic rates latency exchanged center. Therefore, an efficient aggregation at is required deal high volume in order optimize constrained-resources this article, we propose hybrid strategy implemented on aggregator-head (AH) clustering topology performs Interval Meter Reading (IMR) application data. AH induction greatly reduce workload cluster-heads (CHs), efficiently utilizes constrained-resource cost effective-manner. The proposed evaluated existing approaches using CloudSim simulation tool. Experimental results obtained compared show effectiveness such that limited resources optimized, CH minimized, QoS maintained.