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access icon free DCRL-RPL: Dual context-based routing and load balancing in RPL for IoT networks

© The Institution of Engineering and Technology
Received 28/01/2020, Accepted 30/03/2020, Revised 18/03/2020, Published 06/04/2020

Routing Protocol for Low power lossy network (RPL) is emerged to evade the energy issues in the Internet of Things (IoT) network. Although, RPL noticeably satisfies the requirement of the IoT network, still there exist certain open issues to resolve. This paper addresses the problem of routing overhead, packet losses and load imbalance in RPL based IoT network. These downsides are solved using the proposed Dual Context-based Routing and Load Balancing in RPL based Network (DCRL-RPL). Primarily, we implement the grid construction where the network area is split into a different level of the unequal grid. The ranking based Grid Selection process is executed to select the optimal grid head node in each grid. The grid head node in the network schedules its member node using the Reputation based Scheduling method. The elected grid head classifies the data received from its member using Adam Deep Neural Network (ADNN) to provide better routing performance. Here, the sensitive and non-sensitive data are considered as context for objective function selection. At last, the efficacy of the DCRL-RPL is analyzed using the Network Simulator 3.26 (NS3) tool. From comprehensive validation results, we show that DCRL-RPL acquires better results.

Inspec keywords: routing protocols; resource allocation; neural nets; directed graphs; telecommunication power management; Internet of Things; optimisation; telecommunication scheduling

Other keywords: dual context-oriented objective function; Network Simulator 3.26 tool; destination-oriented directed acyclic graph; nonsensitive data transmission; Adam deep neural network; network lifetime; reputation-based scheduling method; low power lossy network routing protocol; load balancing; RPL-based IoT network; dual context-based routing; adaptive trickle algorithm; Internet of Things network; ranking-based grid selection process; optimisation-based objective function selection; MOORA objective function; DCRL-RPL

Subjects: Computer communications; Combinatorial mathematics; Computer networks and techniques; Neural computing techniques; Algebra, set theory, and graph theory; Telecommunication systems (energy utilisation); Combinatorial mathematics; Protocols; Optimisation techniques; Optimisation techniques; Communication network design, planning and routing

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