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This paper proposes a quantitative evaluation algorithm based on a comprehensive analysis of material's shape, texture, color, style, and other characteristics using indoor wireless networking design and cloud data to improve the application effectiveness of ecological environment materials. It also adopts a data-driven method to quantitatively evaluate the application effectiveness of ecological environment materials using indoor wireless network design based on preliminary feature information. Specifically, this work reconstructs the feature space of ecological environment materials by extracting dimensionality features related to the quantitative evaluation, and analyzes the mutual information features of big data fusion. Moreover, a quantitative regression analysis and statistical model construction is used to evaluate the application effectiveness by using preliminary feature information as a constraint condition. In addition, this study employs the spatial effect element feature analysis method to quantitatively analyze and rigorously test the application effectiveness assessment. The empirical results show that the proposed quantitative evaluation algorithm has good accuracy and high reliability, which can effectively improve the application quality of ecological environment materials in indoor wireless network design. [ABSTRACT FROM AUTHOR]

In the multi hop communication of wireless sensor networks, relay stations are used to realize remote transmission. In order to avoid the air data repeating collision problem and multi-path retransmission problem of wireless signals sent by relay nodes, this paper proposes a relaying algorithm using dual buffer pool. The node buffer pool is added in the node to store the package source identifier and packet count pairs, the package buffer pool is added to the package to store paths in transmission. First, after the package is received from radio, the node compares the pairs of the SID and Count in the node buffer pool with the pairs of the package source identifier and package count in the package. If there are pairs, the package is discarded, otherwise the package source identifier and package count are added into the node buffer pool. Next step, if the node identifier is equal to the destination byte DID in package, the package will be processed in the node and terminated transmission, otherwise the package will be continued to process. Then the node compares the node identifier with the package buffer pool bytes. If there is the node identifier in the package pool, the package will be discarded, otherwise the relay node stores its own node identifier into the packet buffer pool to create a new package and transmit forwards. The algorithm is implemented on CC2530 chip and relaying experiments of wireless sensor network are carried out. The results show that the algorithm can achieve relay forwarding and avoid duplicating forwarding data collision and avoid multipaths duplicate forwarding. [ABSTRACT FROM AUTHOR]

Nodes localization has been a critical subject in wireless sensor network (WSN) field. As far as existing localization algorithms are concerned, distance vector hop (DV-Hop) has the advantages of no extra hardware and implementation simplicity, however its localization accuracy cannot meet some specific requirements. In order to enhance the accuracy of WSN nodes localization, a DV-Hop based localization algorithm based on nodes negotiation and multi communication radii (NNMCR DV-Hop) is proposed in this paper. Firstly, the hop counts between WSN nodes is modified from an integer to a decimal by changing communication radius of anchor nodes through nodes negotiation. By refining the hop counts, the accuracy of the estimated distance from the unknown to the anchor nodes is improved. Secondly, the calculation of the average hop size of the anchor node is abstracted into a combinatorial optimization problem which is solved by using binary particle swarm optimization (BPSO) to improve the accuracy of the estimated distance which is between the anchor and the unknown node. Finally, when calculating the coordinates of unknown nodes, only the anchor nodes with smaller hop counts are selected to participate in the calculation. Simulation experiments show that compared with the original DV-Hop as well as other improved algorithms based on DV-Hop, NNMCR DV-Hop greatly improves the localization accuracy of unknown nodes without additional hardware. [ABSTRACT FROM AUTHOR]

Wireless powered communication network (WPCN) is a promising technique to resolve the power constraint issue faced by wireless nodes at the same time it also provides green and a safer solution. This paper studies, mutual sharing between WPCN and simultaneous wireless information and power transfer model where optimal resource allocation occurs between licensed/bandwidth group and an unlicensed/power group to enhance the system performance. The main aim of this paper is to maximize system weighted sum rate and minimize power consumption during transmission by optimal time allocation and energy beamforming vector allocation. These multiobjective combinatorial problems are solved using joint metaheuristic particle swarm optimization-cuckoo search algorithm to provide an optimal solution. The results are compared using a conventional mathematical optimization algorithm to set as a baseline for performance parameters. The obtained results demonstrate that the efficient joint metaheuristic approach provides a significant gain in the system performance and also offers a computationally less complex approach for solving a complicated non-convex multiobjective problem of wireless powered network. [ABSTRACT FROM AUTHOR]

Cognitive Radio Wireless Sensor Networks (CRWSNs) promise optimized spectrum utilization but face challenges in sustaining energy balance, particularly due to the emergence of “hot spots.” In CRWSNs, Cluster Heads (CHs) closer to the sink experience higher traffic as compared to those farther away, primarily due to their role in data collaboration and relaying to the sink. This leads to early depletion of their energy reserves and potentially causing the network to partition creating hot spots or energy holes. Effective clustering algorithms are needed to mitigate these hot spots. The main objective of the paper is to propose a novel clustering scheme titled “Unequal Clustering Energy Hole Avoidance (UCEHA) algorithm” to address hot spot issues in CRWSNs. UCEHA partitions the network into clusters based on sink proximity, selecting CHs considering node energy, communication channels, neighbors, and sink distance. An enhanced spectrum-aware AODV mechanism facilitates efficient data routing. To test and validate the proposed methodology, extensive experimentations were conducted and the results demonstrate UCEHA’s superiority over existing methods, exhibiting reduced energy consumption (average 19%), improved network load balance (average 26%), increased network lifetime (average 40%), and enhanced throughput (average 8%). These results highlight the effectiveness of UCEHA algorithm in addressing energy imbalance and hot spot issues in CRWSNs, ultimately leading to enhanced network performance and longevity. [ABSTRACT FROM AUTHOR]