An Energy‐Efficient Multipath Routing Protocol for Secure Video‐Packet Transmission Across MANETs Using a Blockchain Framework

Abstract

ABSTRACT Appropriate routing strategies are necessary for mobile ad hoc networks (MANETs) in order to facilitate effective data transfer. In order to counter the prevailing problems, the correct routing schemes will need to be selected as the default configurations are used. In this paper, a special optimal link state routing (OLSR) protocol is proposed to incorporate a deep learning methodology to facilitate efficient video streaming in MANETs. This study presents a new improved variant of the OLSR protocol, which is specially tailored to achieve efficient video streaming in MANETs. It is a radical approach that combines a deep‐learning model with blockchain technology to overcome security and reliability issues. It starts with the gathering of video content that is available publicly. In order to detect black‐hole nodes, a special twin‐attention‐based Elman spiking neural network model is applied. The reliability of the neighboring nodes is then measured by means of trust values. The pufferfish optimization algorithm, or the accuracy‐aware energy‐efficient multipath routing algorithm (AEMRAP), which takes into account node‐ and link‐stability degrees, is used in making routing decisions. Interplanetary file system (IPFS) technology is used to store the data on blockchain and increase its security. The authentication of the blockchain architecture is conducted via the delegated proof‐of‐stake (DPoS) method that also delivers an extra protection of MANETs against unauthorized access. The study demonstrates superior performance in securing and optimizing video transmission, confirming that the extended OLSR protocol is highly effective for MANET video streaming applications. The proposed model exceeds the current approaches with a throughput of 2100 Kbps, an average end latency of 20.2 s, and a packet‐delivery ratio of 92.3%.