The size of the IoT network is expanding due to advancements in the IoT field, leading to increased interest in the multi-sink mechanism. The IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) is a representative IoT protocol that focuses on the Low-Power and Lossy Networks. However, research on comparing multi-sink strategies within the RPL network is limited. Therefore, this project aims to compare three common strategies: multiple-DODAG in one instance, virtual root, and multiple-instance. Using these strategies, we design and implement RPL networks and conduct simulations in various scenarios. Five different topologies are utilized in the experiments, considering different packet loss rates. Performance evaluation of each strategy is conducted using the Cooja simulator and Contiki-NG system, with a focus on the number of RPL control packets, Packet Delivery Ratio (PDR), and energy consumption. The results indicate that both the virtual root and multiple-DODAG strategies perform well with low packet loss, while the virtual root strategy outperforms the multiple-DODAG strategy with high packet loss. Additionally, the virtual root strategy incurs slightly higher energy costs than the multiple-DODAG strategy. Furthermore, the multiple-instance strategy demonstrates poor performance in most scenarios, except for the packet delivery ratio under high packet loss conditions. Besides the analysis, potential areas for future research on the RPL’s multi-sink mechanism are finally identified. / Storleken på IoT-nätverket expanderar på grund av framsteg inom IoT-området, vilket leder till ökat intresse för multi-sink-mekanismen. IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL) är ett representativt IoT-protokoll som fokuserar på Nät med låg effekt och förluster. Forskningen om jämförelse av multi-sink-strategier inom RPL-nätverket är dock begränsad. Därför syftar detta projekt till att jämföra tre vanliga strategier: multiple - DODAG i en instans, virtuell rot och multi-instans. Med hjälp av dessa strategier designar och implementerar vi RPL-nätverk och genomför simuleringar i olika scenarier. Fem olika topologier används i experimenten, med olika packet loss rate. Prestationsutvärdering av varje strategi utförs med hjälp av Cooja-simulatorn och Contiki-NG-systemet, med fokus på antalet RPL control packets, Packet Delivery Ratio (PDR) och energiförbrukning. Resultaten indikerar att både virtuell rot och multiple-DODAG strategier fungerar bra vid låg datapaketförlust, medan den virtuella rotstrategin överträffar multiple-DODAG strategin vid hög datapaketförlust. Dessutom medför den virtuella rotstrategin något högre energikostnader än flera DODAG-strategin. Dessutom visar multi-instans-strategin dålig prestanda i de flesta scenarier, förutom när det gäller datapaketleveransförhållandet under höga datapaketförlustförhållanden. Utöver analysen identifieras slutligen potentiella områden för framtida forskning om RPL-protokollets multi-sink-mekanism.

The use of Internet of Things systems has increased to meet the need for smart systems in various fields, such as smart homes, intelligent industries, medical systems, agriculture, and the military. IoT networks are expanding daily to include hundreds and thousands of IoT devices, which transmit information through other linked devices to reach the network sink or gateway. The information follows different routes to the network sink. Finding an ideal routing solution is a big challenge due to several factors, such as power, computation, storage, and memory limitation for IoT devices. In 2011, A new standardized routing protocol for low-power and lossy networks was released by the Internet Engineering task force (IETF). The IETF adopted a distance vector routing algorithm for the RPL protocol. RPL protocol utilizes the objective functions (OFs) to select the path depending on diffident metrics.These OFs with different metrics must be evaluated and tested to develop the best routing solution.This project aims to test the performance of standardized RPL objective functions in a simulation environment. Afterwards, a new objective function with a new metric will be implemented and tested in the same environmental conditions. The performance results of the standard objective functions and the newly implemented objective function will be analyzed and compared to evaluate whether the standard objective functions or the new objective function is better as a routing solution for the IoT devices network.