# Energy and Delay Aware Data Aggregation in Routing Protocol for Internet of Things
## 2 Related Works  
In this section, we discuss energy-aware data aggregation techniques in RPL to increase the packet delivery ratio, decrease the delay, and improve the lifetime of the network in IoT. [PERSON] et al. [20] proposed an enhanced data aggregation method for IoT. It proposed a distributed method to balance the child node and reduce the congestion among the nodes in the network. Also, a learning automata-based dynamic data aggregation technique is proposedto aggregate the data in RPL (LA-RPL). Each node has a learning automaton to perform the data aggregation and transmission from one node to another node. The simulation has been done using a Contiki Cooja simulator. The LA-RPL's performance is compared to RPL, BD-RPL, m-RPL, and A-RPL. However, LA-RPL causes congestion, as it doesn't consider the trickle timer. [PERSON] and [PERSON] [21] proposed a data aggregation based RPL (A-RPL) protocol for IoT. In IoT, the routing protocol changes its path frequently due to its resource-constrained nature. It proposed a dynamic method to reconstruct the DODAG quickly, which finds a suitable objective function among the number of objective functions. In this dynamic method, the sink node collects the aggregated data from the downstream nodes. A-RPL selects the parent node based on the environmental changes and control overhead in the network. The performance of A-RPL is compared with RPL and A-RPL. A-RPL provides substantial packet delivery consistency and increases the lifespan of the network. However, it causes congestion in a particular situation, as it does not consider the dynamic trickle timer. [PERSON] et al. [22] proposed a reliable group communication protocol (RECOUP) for IoT. RPL is a network routing protocol for IoT. However, it lacks reliability, scalability, and security. So, it proposed a reliable group communication (RECOUP) protocol, which performs cluster-based multicast routing. The performance of RECOUP improves the packet delivery ratio by 25% and decrease the delay by 100 ms. Thus, it extends the network lifetime. However, it takes more energy consumption, as it checks each data packet in each node. [PERSON] et al. [23] proposed content-centric routing in RPL (CCR-RPL) for IoT. Nowadays, IoT can be used in various applications. However, the routing protocol faces difficulty while collecting the data present in the dense network. To avoid this issue, it proposed a content-centric routing protocol for IoT. It identifies the content via the routing path. Then, the data aggregation process is carried out in the intermediate node from the source to the destination. The simulation has been conducted in COOJA and TeloSB. The performance of CCR-RPL is compared to RPL. The CCR-RPL achieves better performance in terms of latency, energy efficiency, and reliability in both the scenarios. However, it creates congestion due to dynamic network conditions. [PERSON] et al. [24] suggested a parent cluster RPL (C-RPL) for IoT. C-RPL uses the opportunistic forwarding scheme for synchronization and selects the optimal parent cluster set to reduce the latency between source and destination. While transferring the data, the priority-based scheduling scheme is incorporated in RPL. The simulation has been conducted in NS3. C-RPL performance is compared to RPL and ORPL performance. It achieves not able performance by means of reliability and by avoiding the packet retransmission. However, C-RPL packet loss occurs, as it takes more time to select the cluster parent. [PERSON] et al. [25] proposed a fuzzy-based data fusion technique for IoT (FLWP). FLWP is proposed to maximize the lifespan of the network. The operations of FLWP is as follows: first, it performs data fusion using fuzzy logic. Later, it predicts the optimal route based on the data fusion value. The performance of FLWP is compared with the AODV routing protocol. It provides superior performance to the AODV protocol. However, it takes a longer time to predict the parent node. [PERSON] et al. [26] proposed cooperative interaction in multiple RPL.