# An Energy Efficient Routing Approach for Cloud-Assisted Green Industrial IoT Networks
Even though the life of the battery of any device is not endless, however, reducing the energy consumption for prolonging the lifetime of the network is an important aspect of routing optimization in the network. In resource-constrained networks, most of the energy consumption on a node occurs due to the transmission and reception, because the rest of the time, generally nodes are in sleeping or inactive state. While RPL is considered as a default routing protocol for IoT, it constructs the routing topology based on a different node and link metrics and constraints. The route selection in RPL is based on either a link quality metric or hop count, which results in an inefficient route selection in terms of energy efficiency because nodes are unaware of any energy resources. Furthermore, a single metric based topology construction approach in RPL makes the network imbalance and creates energy hotspots, particularly near to the root node. The best route selection is performed in such a manner to minimize a path cost based on specific metrics in the objective function (OF). Therefore, the routing decision in RPL is mainly made based on a single parameter, such as reliability, or delay. As a result, the selection of only one parameter in the routing decision inevitably suppress other. For example, if the only delay is considered, the nodes cannot experience high energy consumption, and vice versa. For this reason, metrics that represent multiple of these parameters need to consider in the OF to fulfill IIoT requirements, which is one of the goals of this paper. Many existing studies have presented a different version of RPL energy optimization, but the duty cycling aspect has ignored mostly. According to the evaluation in [18], the default implemented version of RPL cannot encounter the QoS requirements of modern IoT concepts, such as resource efficiency, network lifetime, and network reliability. In order to enlarge network lifetime, efficient resource utilization of nodes is an important concern particularly for resource-constrained networks. Besides, for efficient data delivery in IoT applications such as emergency monitoring, the forwarding node should be aware of nodes' sleep and awake states. Based on this understanding, in this paper, we propose a resource aware and reliable OF (RAROF) based on RPL specification to enable the IIoT system more reliable and energy-efficient. For efficient data delivery, RAROF builds an optimum path by exploiting the information regarding the duty cycle, link quality, and energy condition of the node through which a node sends the data packets. Our contribution in this paper can be summarized as follows:  
* This paper enhances the routing approach in RPL for the IIoT system with different data flows. For this, RAROF selects the reliable path focusing on the node resources. Unlike default path selection, we consider different routing metric that represents the node as well as link characteristics. Besides, these routing metrics are aimed to respond to the requirement of the IIoT applications. * A new routing metric named node vulnerability index (NVI) is proposed, which includes the duty cycle information, link quality, energy profile of a node during the path selection process for network life improvement. * We aim to put forward a simple conceptual cloud-assisted emergency monitoring system architecture for RPL based IIoT application. The composite architecture specifies the application of RPL by focusing on reforming industrial operations through cutting-edge technologies. * We propose a simple multi-queueing approach to deal with the diverse data traffic generated from the IoT application. In this perspective, the queuing model is responsible for employing the prioritization of each packet according to the traffic sensitivity. * We analyze the effectiveness of our proposed approach in different aspects by conducting extensive simulation tests through the Cooja simulator.