DIEER: Delay-Intolerant Energy-Efficient Routing with Sink Mobility in Underwater Wireless Sensor Networks

Abstract

Underwater Wireless Sensor Networks (UWSNs) are an enabling technology for many applications in commercial, military, and scientific domains. In some emergency response applications of UWSN, data dissemination is more important, therefore these applications are handled differently as compared to energy-focused approaches, which is only possible when propagation delay is minimized and packet delivery at surface sinks is assured. Packet delivery underwater is a serious concern because of harsh underwater environments and the dense deployment of nodes, which causes collisions and packet loss. Resultantly, re-transmission causes energy loss and increases end-to-end delay ( D E 2 E ). In this work, we devise a framework for the joint optimization of sink mobility, hold and forward mechanisms, adoptive depth threshold ( d t h ) and data aggregation with pattern matching for reducing nodal propagation delay, maximizing throughput, improving network lifetime, and minimizing energy consumption. To evaluate our technique, we simulate the three-dimensional (3-D) underwater network environment with mobile sink and dense deployments of sensor nodes with varying communication radii. We carry out scalability analysis of the proposed framework in terms of network lifetime, throughput, and packet drop. We also compare our framework to existing techniques, i.e., Mobicast and iAMCTD protocols. We note that adapting varying d t h based on node density in a range of network deployment scenarios results in a reduced number of re-transmissions, good energy conservation, and enhanced throughput. Furthermore, results from extensive simulations show that our proposed framework achieves better performance over existing approaches for real-time delay-intolerant applications.

Research and Development of Delay-Sensitive Routing Tensor Model in IoT Core Networks

“…Based on the analysis of existing solutions for QoS routing in IoT and WSN [ 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ], the classification of the main types of solutions to ensure the Quality of Service level in telecommunication networks that support and maintain them has been performed ( Table 1 ).…”

“…Additionally, all considered solutions can be divided into two broad categories: heuristic and optimization [ 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 ]. The most promising is precisely the optimization approach, which, when solving QoS routing problems, is aimed at optimal network resources.…”

“…However, the QoS routing solutions in IoT and WSN revealed that delay requirements must always be fulfilled [ 31 , 32 , 33 , 34 , 35 ]. At the same time, the solutions based on the softwarized network management and QoS routing in IoT and WSN aimed at considering all the needed QoS indicators, namely, delay, loss, and bandwidth.…”

“…A common feature of the vast majority of promising theoretical solutions to QoS routing problems is their formulation in optimization form [ 16 , 17 , 18 , 19 , 20 , 21 , 22 , 31 , 33 , 35 , 36 , 37 , 38 , 39 , 40 ], which helps increase the efficiency of using a valuable network resource for the practical implementation of these solutions. Depending on the aspect and detail of the consideration of the routing task and the completeness of external and internal factors concerning the network, optimization problems can belong to a variety of classes and types.…”

ROBINA: Rotational Orbit-Based Inter-Node Adjustment for Acoustic Routing Path in the Internet of Underwater Things (IoUTs)

“…The dead nodes are those nodes that are not able to deliver the data to sonobuoys. For quick data delivery, many routing and flooding schemes use the shortest path and routing tables, angle-based flooding, the three-hop reliability model, watchman-based flooding, depth and location-based routing, pressure, and cluster/subnet-based approaches [ 5 , 6 , 7 , 8 ]. As nodes around the sonobuoys suffer, and the entire traffic load can die early, we propose the internodes adjustment mechanism for providing an alternative route by following the greedy forwarding approach to recover the data from the dead nodes.…”