Energy‐efficient routing in low power and lossy networks with concurrent overlapping RPL instances

Abstract

The popularity of the Internet of Things (IoT) has cut across different fields in the information and communication technology domain. Such a remarkable surge in popularity has indeed marked its stamp in the number of IoT applications getting developed. These applications rely on a solid backing in the low power and lossy networks (LLNs), which is a crucial IoT‐enabling technology. This results in more than one application being performed on top of the same network. Such a scenario is mentioned by the Internet Engineering Task Force, in its description regarding the IPv6 routing protocol for LLNs (RPL), as multiple active routing instances sharing an LLN. The issue becomes more interesting when these instances have overlapping sets of nodes. This article presents a novel objective function (OF) named Multi‐OF that enables the creation of an energy‐efficient RPL instance in an LLN with concurrent overlapping instances. The optimization achieved by Multi‐OF can be attributed to the inclusion of a novel metric named packet energy correlation index (PECI) along with expected transmission count. The correlation provided by PECI gives an estimate regarding the ability of a node, in terms of the available residual energy, to handle the packets waiting in its queue (ie, packet buffer). The efficiency of the proposed OF has been justified through simulations conducted using Contiki‐COOJA, the results of which show improvements in terms of power consumption of nodes, packet delivery ratio, number of preferred parent changes per node, packet overhead, end‐to‐end delay, and jitter.

Dynamic-RPL: Enhancing RPL-Based IoT Networks with Effective Support of Dynamic Topology Management

“…Moreover, there have been practical considerations towards introducing specific OF designs for effective routing in multi-instance and multi-DODAG setups. Examples are QAD-OF [17], OFQS [18], Multi-OF [26], and MEHOF [27]. These OFs provide RPL networks with the ability to apply different routing optimization objectives for complex RPL setups in a managed and flexible manner.…”