Load-Balancing in Multi-Sink IoT Networks

Abstract

Embedded items (things) are items that are connected to the Internet and have access to global services and people. Wireless Sensor Networks (WSNs) are increasingly becoming the Internet of Things' core network. Moreover, WSNs must support numerous applications concurrently and process vast volumes of data as IoT becomes more integrated into daily life. Thus, using the WSN multi-sink is crucial. Wireless Sensor Networks with multiple sinks are prone to congestion in sink nodes, lowering the efficiency of data collection and processing. The majority of Internet of Things (IoT) applications use the RPL routing protocol, which is offered by Internet Engineering Task Force (IETF). RPL considers IoT deployment requirements across many applications to be highly interoperable and versatile. Nonetheless, several issues still need to be resolved, particularly in large-scale networks. Congestion is one of the problems with RPL, which leads to packet losses at the sink, as a result of the memory overflow incident. This paper introduces Multi sink Load-Balancing Algorithm (MSLBA) that proposed to resolve the congestion issue across several sinks. The suggested approach effectively balances load across sinks by dynamically updating RPL in accordance with DAG Size (DS), Hope Count (HC), and Node Rank (NR). As a result, RPL is able to appropriately spread the load among the sinks. In terms of Packet Delivery Ratio (PDR), MSLBA greatly outperformed the standard RPL algorithm. Throughput, and Delay. The PDR was improved by 9%, while the throughput and latency were improved by 8.5% and 68%, respectively.

Keywords

• Internet of Things (IoT), Wireless Sensor Network (WSN), Multi-Sink WSN, Load-Balancing