Hierarchical Routing with Optimal Clustering Using Fuzzy Approach for Network Lifetime Enhancement in Wireless Sensor Networks

Abstract

Wireless sensor network (WSN) is one of the major emerging fields in real-time scenarios due to the features of sensors. Sensors are used in remote areas because of their usability. Energy is the major issue to be addressed in sensor networks. This energy affects the entire network lifetime. To resolve the energy issues of WSN, clustering and proper routing are the two major procedures that have to be focused on. In this paper, hierarchical routing with optimal clustering using a fuzzy system (HROCF) is proposed for network lifetime enhancement in WSNs. This proposed scheme uses two phases: selection of a cluster leader with a fuzzy inference system and the hierarchical routing strategy are implemented for routing to consume the energy of the sensors resourcefully. During the first phase, a proper cluster leader can be nominated through the fuzzy inputs, namely: residual energy, cost, and position. In the second phase, hierarchical routing can communicate the information from the lower region to the sink node through the cluster leaders in higher regions. These two phases help to prolong the lifetime. The simulation analysis demonstrates that the HROCF scheme reduces the overall energy spent in the network and supports an increase in the lifespan in terms of more alive sensors compared to the existing schemes.

A Fuzzy Logic Based Cluster Head Election Technique for Energy Consumption Reduction in Wireless Sensor Networks

“…This model minimizes the number of control packets transferred, as clustering is not done in each round. A hierarchical routing protocol is proposed in [21] that uses a fuzzy-based clustering technique to reduce energy consumption in WSNs. Residual energy, communication cost, and position of nodes are the inputs to the FIS, which generates an output of the best node to act as a cluster leader.…”

“…The energy consumption is significantly reduced when compared to the cited research, and the network lifetime of the nodes is increased. These fuzzy-based algorithms reviewed in [17]- [21] achieve improved network lifetime and energy consumption performance due to the optimal CH selection. The use of fuzzy logic at the first instance of CH appointment instead of applying a probabilistic approach can be attributed to this improvement.…”

“…The LND shows the point at which all nodes in the network are dead, and no data transmission occurs after that point. A comparison of the studies cited in the related works [14]- [26] shows that the authors in [21] achieved the best results in terms of network lifetime and energy consumption based on fuzzy logic. On this basis, the simulation results of the proposed model are compared with those of the HROCF model developed in [21].…”

“…The bar graph in figure 15 shows the different points at which there was the first node death (FND), 50% node deaths, also referred to as half nodes dead (HND), and when the last node (LND) in the network died. The comparison is made between [17], [21], [24]. The FND signifies the point at which network stability is affected.…”

Review of Modern Approaches to 3D Digitization of Tangible Cultural Heritage

“…Such a comprehensive approach is essential to ensure that the digitization of tangible heritage retains its intrinsic value and can contribute to the global preservation of cultural heritage. [13,14,15,16,17,18] Adherence to ethical principles is key to ensuring that the digitization process respects the legal frameworks, sensitivities, and authentic preservation of historical artifacts. For example, when digitizing objects with cult or religious significance, care must be taken to respect these values and not to forget to consider the potential impacts of publicly sharing digital models not only in the local community but perhaps also abroad.…”