NAmbOA: A Hybrid Metaheuristic for Energy-Prioritized Multi-Objective Route Optimization in RPL-Based 6LoWPAN IoT Networks

Abstract

Energy consumption remains a major concern in RPL-based 6LoWPAN networks, where constrained devices operate with limited battery, processing, and communication resources. This paper presents an energy-prioritized six-objective routing framework that jointly considers Average Energy Consumption (AEC), Convergence Time (CT), Packet Overhead (PoH), Packet Delivery Ratio (PDR), Average Path Length (APL), and End-to-End Delay (EED) over DODAG-compatible routes. For the primary source-level experiment, every route in the complete candidate set (K ≤ 5) is evaluated and the minimum-fitness route is selected exactly; no metaheuristic advantage is claimed for this small discrete problem. The NAmbOA hybrid search, combining NiOA-inspired diversification and CAOA-inspired leader-guided intensification, is evaluated separately in a coupled network-wide parent-selection problem. On 200-node controlled instances, the energy-priority formulation reduces mean AEC by 23.35% relative to an ETX-minimizing/MRHOF-like reference, with modest differences in the reported overhead, delay, and delivery endpoints. Across 30 paired network-wide instances, NAmbOA obtains lower final fitness than the NiOA-inspired and CAOA-inspired component-only variants, while no significant convergence-speed advantage is observed. The results support an energy-centered routing trade-off and a network-wide hybrid-search contribution under the stated simulator assumptions; they do not constitute validation of a full standards-compliant RPL implementation.

Keywords: Energy efficiency; routing reliability; packet delivery; path selection; convergence behavior; objective function.

Received Date: June 19, 2026

Accepted Date: July 10, 2026

Published Date: August 01, 2026

Available Online at: https://www.ijsrisjournal.com/index.php/ojsfiles/article/view/922