Implantation modified deep echo state neural networks and improve harmony clustering algorithm for optimal and energy efficient path in mobile sink

Wireless network sensors based on the mobile sink are regarded to be a common network and used in various fields in the last few years, they are thought to be easy to use, but contain the problem of energy loss and are affected by an energy hole problem, as it depends on batteries. This paper proposes a solution to this problem by using an innovative objective function for a consistent distributing of cluster heads, the enhanced harmony search based routing protocols based on energy equilibrated node clustering protocol. In order to route the data packet among the sink and cluster heads, an enhanced modified deep echo state neural network is suggested. The efficiency of a projected integrated clustering and routing protocol has been investigated at 500 nodes, and the 96 per cent success data for the proposed algorithm is given using the average energy consumption, send and receive packaged and optimum numbers of CH

A Hybrid Algorithm for Reliable and Energy-efficient Data Gathering in Wireless Sensor Networks

Reliability and energy efficiency are two important requirements of the data gathering process in wireless sensor networks. Accordingly, we propose a novel data gathering algorithm which meets these requirements. The proposed scheme categorizes the sensed data into valuable and normal data and handles each type of data based on its demands. The main requirement of valuable data is reliability. Thus, the adopted strategy to gather this type of data is to send several copies of data packets toward the sink. The rise of energy exhaustion in this scheme is tolerable. This is due to that, the valuable data is generated at a low rate. On the other hand, our main concern in gathering normal data is energy efficiency. As most of the sensed data is normal, an energy-efficient approach to gather normal data results in considerable energy conserving. Thus, we exploit clustering technique for normal data gathering. We also propose a lightweight intrusion detection system to detect malicious nodes. Simulation results and theoretical analysis confirm that our proposed algorithm provides reliability and energy efficiency at an acceptable level

Coverage Protocols for Wireless Sensor Networks: Review and Future Directions

The coverage problem in wireless sensor networks (WSNs) can be generally defined as a measure of how effectively a network field is monitored by its sensor nodes. This problem has attracted a lot of interest over the years and as a result, many coverage protocols were proposed. In this survey, we first propose a taxonomy for classifying coverage protocols in WSNs. Then, we classify the coverage protocols into three categories (i.e. coverage aware deployment protocols, sleep scheduling protocols for flat networks, and cluster-based sleep scheduling protocols) based on the network stage where the coverage is optimized. For each category, relevant protocols are thoroughly reviewed and classified based on the adopted coverage techniques. Finally, we discuss open issues (and recommend future directions to resolve them) associated with the design of realistic coverage protocols. Issues such as realistic sensing models, realistic energy consumption models, realistic connectivity models and sensor localization are covered

A Survey on Underwater Acoustic Sensor Network Routing Protocols

Underwater acoustic sensor networks (UASNs) have become more and more important in ocean exploration applications, such as ocean monitoring, pollution detection, ocean resource management, underwater device maintenance, etc. In underwater acoustic sensor networks, since the routing protocol guarantees reliable and effective data transmission from the source node to the destination node, routing protocol design is an attractive topic for researchers. There are many routing algorithms have been proposed in recent years. To present the current state of development of UASN routing protocols, we review herein the UASN routing protocol designs reported in recent years. In this paper, all the routing protocols have been classified into different groups according to their characteristics and routing algorithms, such as the non-cross-layer design routing protocol, the traditional cross-layer design routing protocol, and the intelligent algorithm based routing protocol. This is also the first paper that introduces intelligent algorithm-based UASN routing protocols. In addition, in this paper, we investigate the development trends of UASN routing protocols, which can provide researchers with clear and direct insights for further research

Enhancing graph-routing algorithm for industrial wireless sensor networks

Industrial Wireless Sensor Networks (IWSNs) are gaining increasing traction, especially in domains such as the Industrial Internet of Things (IIoT), and the Fourth Industrial Revolution (Industry 4.0). Devised for industrial automation, they have stringent requirements regarding data packet delivery, energy consumption balance, and End-to-End Transmission (E2ET) time. Achieving effective communication is critical to the fulfilment of these requirements and is significantly facilitated by the implementation of graph-routing – the main routing method in the Wireless Highway Addressable Remote Transducer (WirelessHART), which is the global standard of IWSNs. However, graph-routing in IWSN creates a hotspot challenge resulting from unbalanced energy consumption. This issue stems from the typical configuration of WirelessHART paths, which transfers data packets from sensor nodes through mesh topology to a central system called the Network Manager (NM), which is connected to a network gateway. Therefore, the overall aim of this research is to improve the performance of IWSNs by implementing a graph-routing algorithm with unequal clustering and optimisation techniques. In the first part of this thesis, a basic graph-routing algorithm based on unequal clustering topologies is examined with the aim of helping to balance energy consumption, maximise data packet delivery, and reduce the number of hops in the network. To maintain network stability, the creation of static clusters is proposed using the WirelessHART Density-controlled Divide-and-Rule (WDDR) topology. Graph-routing can then be built between Cluster Heads (CHs), which are selected according to the maximum residual energy rate between the sensor nodes in each static cluster. Simulation results indicate that graph-routing with the WDDR topology and probabilistic unequal clustering outperforms mesh topology, even as the network density increased, despite isolated nodes found in the WDDR topology. The second part of this thesis focuses on using the Covariance-Matrix Adaptation Evolution Strategy (CMA-ES) algorithm. This addresses the three IWSN requirements that form the focus of this research, by proposing three single-objective graph-routing paths: minimum distance (PODis), maximum residual energy (POEng), and minimum end-to-end transmission time (POE2E). The research also adapts the CMA-ES to balance multiple objectives, resulting in the Best Path of Graph-Routing with a CMA-ES (BPGR-ES). Simulation results show that the BPGR-ES effectively balances IWSN requirements, but single-objective paths of graph-routing does not achieve balanced energy consumption with mesh topology, resulting in a significant reduction in the efficiency of the network. Therefore, the third part of this thesis focuses on an Improvement of the WDDR (IWDDR) topology to avoid isolated nodes in the static cluster approaches. The IWDDR topology is used to evaluate the performance of the single-objective graph-routing paths (PODis, POEng, and POE2E). The results show that in IWDDR topology, single-objective graph-routing paths result in more balanced energy consumption

5G wireless network support using umanned aerial vehicles for rural and low-Income areas

>Magister Scientiae - MScThe fifth-generation mobile network (5G) is a new global wireless standard that enables state-of-the-art mobile networks with enhanced cellular broadband services that support a diversity of devices. Even with the current worldwide advanced state of broadband connectivity, most rural and low-income settings lack minimum Internet connectivity because there are no economic incentives from telecommunication providers to deploy wireless communication systems in these areas. Using a team of Unmanned Aerial Vehicles (UAVs) to extend or solely supply the 5G coverage is a great opportunity for these zones to benefit from the advantages promised by this new communication technology. However, the deployment and applications of innovative technology in rural locations need extensive research