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An improved congestion-controlled routing protocol for IoT applications in extreme environments

- Adil, Muhammad, Usman, Muhammad, Jan, Mian, Abulkasim, Hussein, Farouk, Ahmed, Jin, Zhanpeng

  • Authors: Adil, Muhammad , Usman, Muhammad , Jan, Mian , Abulkasim, Hussein , Farouk, Ahmed , Jin, Zhanpeng
  • Date: 2024
  • Type: Text , Journal article
  • Relation: IEEE Internet of Things Journal Vol. 11, no. 3 (2024), p. 3757-3767
  • Full Text: false
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  • Description: The Internet of Things (IoT) has shown its presence in applications that require monitoring extreme environments, such as wildfires, military operations, and coastal areas, among others. In these applications, the IoT nodes are deployed in hazardous terrains where humanistic access is hard or not possible. Hence, to ensure reliable data transmission in these applications, novel routing protocols need to be designed due to the multihop nature of communication possessed by the deployed nodes. Currently, most of the routing protocols utilized by IoT nodes follow traditional approaches, which creates congestion and contention in the network. As a result, the network performance is degraded in terms of various communication metrics. To address this problem and improve the communication statistics in extreme environments, we propose a deep- Q -learning-enable-destination-sequenced distance-vector (DQL-DSDV) framework. DQL-DSDV focuses on selecting the next hop during communication. Initially, the DSDV protocol updates routing information for connected nodes. This information is subsequently utilized by the deep- Q -learning (DQL) algorithm to compute the next hop count. This computation is based on reward functions, known as Q-values, which are conceptualized as the distance between connected nodes by taking into account the traffic flow. These distinguishing operational features of DQL and DSDV ensure that DQL-DSDV minimizes the packet lost ratio, congestion, end-to-end delay, and communication cost with improved Quality of Service (QoS). During simulations, we observed significant improvement in these performance metrics, in the presence of the existing schemes. Despite that, we checked the computation complexity of the proposed approach with existing protocols, which demonstrated noteworthy outcomes just like the other metrics. © 2014 IEEE.

Performance evaluation of high definition video streaming over mobile ad hoc networks

- Usman, Muhammad, Jan, Mian, He, Xiangjian, Alam, Muhammad

  • Authors: Usman, Muhammad , Jan, Mian , He, Xiangjian , Alam, Muhammad
  • Date: 2018
  • Type: Text , Journal article
  • Relation: Signal processing Vol. 148, no. (2018), p. 303-313
  • Full Text: false
  • Reviewed:
  • Description: A unique combinational approach of QoS and QoE for multimedia traffic in MANETs is proposed in this paper.•A feedback-based multi-path transmission strategy is adopted to minimize the data loss during HD video streaming.•An EC technique based on multi-threading-based parallel processing is used to recover the lost video frames.•We use multiple objective evaluation metrics to test the performance of the EC technique on recovered video frames.•Subjective analysis is combined with objective evaluation using subjective scores and statistical analysis to maintain QoE. Video Service Providers (VSPs) can collect and analyze an enormous amount of multimedia data from various cloud storage centers using real-time big data systems for supporting various online customers. The infrastructure-less nature of Mobile Ad Hoc Networks (MANETs) makes the video streaming a challenging task for VSPs. High packet-loss probability in MANETs can create a notable distortion in the received video quality. In this paper, High Definition (HD) videos are streamed over MANETs. First, a transmission model is designed followed by a distortion model to estimate network distortions, such as packet-loss rate and end-to-end delay. Based on the proposed models, a video streaming framework is designed to efficiently utilize the available bandwidth in MANETs, minimize the network distortions, and improve Quality of Service (QoS). Later, an Error Concealment (EC) technique is used to conceal the lost/dropped video frames to improve the Quality of Experience (QoE). Experimental results show that our proposed video streaming framework outperforms the state-of-the-art routing protocols designed for MANETs, such as Destination-Sequenced Distance Vector (DSDV) and Optimized Link Sate Routing (OLSR) protocols. In the end, both subjective and objective evaluations are performed to evaluate the perceptual quality of the concealed video data.
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