An assessment of vegetation cover of Mysuru City, Karnataka State, India, using deep convolutional neural networks

Mahendra, H. N.; Mallikarjunaswamy, S; Subramoniam, Suresh

doi:10.1007/s10661-023-11140-w

Cited by 23 publications

(12 citation statements)

References 44 publications

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“…The unique challenges posed by 5G LTE, such as higher susceptibility to interference, signal fading, and the demands of supporting high data rates with minimal latency, necessitate a nuanced approach to error correction. This gap underscores the need for an in-depth investigation into the types of errors that predominantly affect 5G LTE and the effectiveness of existing error-correcting codes in this specific context [13][14][15].…”

Section: Research Gapmentioning

confidence: 99%

Enhancing 5G LTE Communications: A Novel LDPC Decoder for Next-Generation Systems

Venkatesh,

Mallikarjunaiah,

Srikantaswamy

et al. 2024

IDA

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The advent of fifth-generation (5G) long-term evolution (LTE) technology represents a critical leap forward in telecommunications, enabling unprecedented high-speed data transfer essential for today's digital society. Despite the advantages, the transition introduces significant challenges, including elevated bit error rate (BER), diminished signal-to-noise ratio (SNR), and the risk of jitter, undermining network reliability and efficiency. In response, a novel low-density parity check (LDPC) decoder optimized for 5G LTE applications has been developed. This decoder is tailored to significantly reduce BER and improve SNR, thereby enhancing the performance and reliability of 5G communications networks. Its design accommodates advanced switching and parallel processing capabilities, crucial for handling complex data flows inherent in contemporary telecommunications systems. A distinctive feature of this decoder is its dynamic adaptability in adjusting message sizes and code rates, coupled with the augmentation of throughput via reconfigurable switching operations. These innovations allow for a versatile approach to optimizing 5G networks. Comparative analyses demonstrate the decoder's superior performance relative to the quasi-cyclic low-density check code (QCLDC) method, evidencing marked improvements in communication quality and system efficiency. The introduction of this LDPC decoder thus marks a significant contribution to the evolution of 5G networks, offering a robust solution to the pressing challenges faced by next-generation communication systems and establishing a new standard for high-speed wireless connectivity.

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Section: Research Gapmentioning

confidence: 99%

Enhancing 5G LTE Communications: A Novel LDPC Decoder for Next-Generation Systems

Venkatesh,

Mallikarjunaiah,

Srikantaswamy

et al. 2024

IDA

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“…It lets work happen at the edge while also letting the cloud talk to the edge. LB is an important part of fog networks because it keeps some FNs from being idle or overloaded [25]. Figure 4 shows the data flow structure of LB and FC task offloading.…”

Section: Graph Repartitioning-based Dynamic Lb (Dlb)mentioning

confidence: 99%

“…So, one of the problems in the fog environment is how to best assign jobs to FNs. For a scheduling algorithm to work well, it should lower costs and energy use while also taking into account how different FNs are and how committed people are to getting things done on time [82][83][84][85][86][87][88][89][90][91][92]. This study gives a thorough taxonomy to help us understand the research problems better and points out important problems with previous work.…”

Section: Fc Task Schedulingmentioning

confidence: 99%

A Comparative Review of Internet of Things Model Workload Distribution Techniques in Fog Computing Networks

Puttaswamy,

Murthy,

Degha

2024

IDA

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In the realm of fog computing (FC), a vast array of intelligent devices collaborates within an intricate network, a synergy that, while promising, has not been without its challenges. These challenges, including data loss, difficulties in workload distribution, a lack of parallel processing capabilities, and security vulnerabilities, have necessitated the exploration and deployment of a variety of solutions. Among these, software-defined networks (SDN), double-Q learning algorithms, service function chains (SFC), virtual network functions (VNF) stand out as significant. An exhaustive survey has been conducted to explore workload distribution methodologies within Internet of Things (IoT) architectures in FC networks. This investigation is anchored in a parameter-centric analysis, aiming to enhance the efficiency of data transmission across such networks. It delves into the architectural framework, pivotal pathways, and applications, aiming to identify bottlenecks and forge the most effective communication channels for IoT devices under substantial workload conditions. The findings of this research are anticipated to guide the selection of superior simulation tools, validate datasets, and refine strategies for data propagation. This, in turn, is expected to facilitate optimal power consumption and enhance outcomes in data transmission and propagation across multiple dimensions. The rigorous exploration detailed herein not only illuminates the complexities of workload distribution in FC networks but also charts a course towards more resilient and efficient IoT ecosystems.

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“…It mostly looks into how data gets sent from a cluster head to a sink node and how routing works between cluster heads. For WMSNs, the TPGF (Two-Phase Greedy Forwarding) method [7] looks for the almost shortest routing paths between nodes that don't connect to each other and get around holes. TPGF offers multi-path transmission by frequently running the algorithm to find more on-demand routing paths that don't connect to the same node.…”

Section: Figure 1 Fundamental Block Diagram Of Wireless Sensor Networ...mentioning

confidence: 99%

Efficient Geographic Routing for High-Speed Data in Wireless Multimedia Sensor Networks

Pandith,

Ramaswamy,

Srikantaswamy

et al. 2023

JESA

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In recent eras, a large amount of data has been transferred through wireless networks in fifth-generation communication using a two-phase geography greedy forwarding (TPGF) routing algorithm with reconfigurable routing metrics represented by RrTPGF in random duty-cycled wireless multilevel multimedia sensor networks (WMSNs). The proposed method reduces the sleep delay in geographic routing networks. the systematically forwarded node in the geographic routing network to identify the significant neighboring nodes. The proposed algorithm is efficient in identifying the geographical distance of the neighboring node and identifying the sleeping delay of the nodes during the communication process. The proposed algorithm efficiently differentiates the worked node from the unworked node on the basis that it identifies the optimal single routing path with a low sleeping delay time at geographic routing. As per the simulation result, the performance of the proposed method shows better results as compared to the conventional methods when considering the scenario size of 750mm × 450mm and 250 nodes with respect to the average delay of the proposed method, which is reduced to 0.6%, and the average hop counts, which are reduced to 0.56% as compared to the conventional method.

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An assessment of vegetation cover of Mysuru City, Karnataka State, India, using deep convolutional neural networks

Cited by 23 publications

References 44 publications

Enhancing 5G LTE Communications: A Novel LDPC Decoder for Next-Generation Systems

Enhancing 5G LTE Communications: A Novel LDPC Decoder for Next-Generation Systems

A Comparative Review of Internet of Things Model Workload Distribution Techniques in Fog Computing Networks

Efficient Geographic Routing for High-Speed Data in Wireless Multimedia Sensor Networks

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