Technical Study on 5G Using Soft Computing Methods

Divakaran, J.; Malipatil, Somashekhar; Zaid, Tareeq; Pushpalatha, M.; Patil, Vilaskumar; Arvind, C.; Titus, T. Joby; Srihari, K.; Vignesh, M; Gadgay, Baswaraj; Sundramurthy, Venkatesa Prabhu

doi:10.1155/2022/1570604

Cited by 28 publications

(24 citation statements)

References 29 publications

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“…e energy consumption, the response time, and the two other parameters are used to explain the QoS methodology of the entire network services [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27].…”

Section: Literature Reviewmentioning

confidence: 99%

QoS Analysis for Cloud-Based IoT Data Using Multicriteria-Based Optimization Approach

Loganathan

Chitra²,

Sivasankari³

et al. 2022

Computational Intelligence and Neuroscience

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This work explains why and how QoS modeling has been used within a multicriteria optimization approach. The parameters and metrics defined are intended to provide a broader and, at the same time, more precise analysis of the issues highlighted in the work dedicated to placement algorithms in the cloud. In order to find the optimal solution to a placement problem which is impractical in polynomial time, as in more particular cases, meta-heuristics more or less approaching the optimal solution are used in order to obtain a satisfactory solution. First, a model by a genetic algorithm is proposed. This genetic algorithm dedicated to the problem of placing virtual machines in the cloud has been implemented in two different versions. The former only considers elementary services, while the latter uses compound services. These two versions of the genetic algorithm are presented, and also, two greedy algorithms, round-robin and best-fit sorted, were used in order to allow a comparison with the genetic algorithm. The characteristics of these two algorithms are presented.

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Section: Literature Reviewmentioning

confidence: 99%

QoS Analysis for Cloud-Based IoT Data Using Multicriteria-Based Optimization Approach

Loganathan

Chitra²,

Sivasankari³

et al. 2022

Computational Intelligence and Neuroscience

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“…The multipath routing process must not recover the link failure. This minimizes the network lifetime and detection efficiency and improves the communication overhead [22][23][24][25][26][27][28][29][30][31][32][33][34].…”

Section: Overview Of Proposed Schemementioning

confidence: 99%

Energy Auditing and Broken Path Identification for Routing in Large-Scale Mobile Networks Using Machine Learning

Venu

Revanesh

Supriya³

et al. 2022

Wireless Communications and Mobile Computing

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In mobile computing, all nodes are movable nodes, which causes many problems for transmitting data packets in a sequence manner; since the mobile nodes are connected with each other, during movement, nodes make the connection fail or damaged. This kind of link damage is caused by nodes that travel out of range from the network limit and also affect the packet success rate. This reduces the network lifetime and detection efficiency and increases the communication overhead. Every mobile node in mobile computing is an unstable node, causing numerous problems for broadcasting data packets in a series method. When the mobile nodes are connected to each other, relay nodes cause the link to break or else sustain damage. This type of connection failure is brought on by nodes that leave the network’s permitted range, which also lowers the packet success rate. The link failure cannot be recovered by the multipath routing algorithm. As a result, the communication overhead is increased while the network lifetime and detection effectiveness are reduced. Then, the novel energy routing (NER) method that has been proposed is employed to support the energetic routing path across the middle nodes. It is challenging to locate the failed channels and carry on with the successful packet transfer. The master node selection algorithm is intended to identify the best relaying node, fault-free packet transmission process among the network structure’s relaying nodes. The master node is efficiently chosen in this manner. The master node, also known as the energy-based important node, is employed in the mobile network to carry out error-free packet transmission procedures. The other nodes are lower energy nodes that do not participate in packet forwarding, and this algorithm only detects the higher energy successful nodes. This lengthens the network’s lifespan, improves detection effectiveness, and lowers communication overhead. The energy-based heavy node is also known as the master node, which is used to perform a problem-free communication process in the mobile network. This algorithm only accepts the higher energy successful node; the remaining nodes are lower energy nodes which do not perform the communication process. This increases the network lifetime and detection efficiency and reduces the communication overhead. The performance metrics for the proposed system is evaluated by end to end delay, communication overhead, throughput, detection efficiency, network lifetime, and packet drop rate.

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“…Due to the anomalous changes in node energy levels, mobile nodes offer unreliable communication among themselves. It is so challenging to control such node actions that target node fails to gather packets [29][30][31][32][33][34][35][36][37][38].…”

Section: Motivationmentioning

confidence: 99%

Lightweight Pattern Matching Method for DNA Sequencing in Internet of Medical Things

Rexie

Raimond

Murugaaboopathy

et al. 2022

Computational Intelligence and Neuroscience

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An area of medical science, that is, gaining prominence, is DNA sequencing. Genetic mutations responsible for the disease have been detected using DNA sequencing. The research is focusing on pattern identification methodologies for dealing with DNA-sequencing problems relating to various applications. A few examples of such problems are alignment and assembly of short reads from next generation sequencing (NGS), comparing DNA sequences, and determining the frequency of a pattern in a sequence. The approximate matching of DNA sequences is also well suited for many applications equivalent to the exact matching of the sequence since the DNA sequences are often subject to mutation. Consequently, recognizing pattern similarity becomes necessary. Furthermore, it can also be used in virtually every application that calls for pattern matching, for example, spell-checking, spam filtering, and search engines. According to the traditional approach, finding a similar pattern in the case where the sequence length is ls and the pattern length is lp occurs in O (ls ∗ lp). This heavy processing is caused by comparing every character of the sequence repeatedly with the pattern. The research intended to reduce the time complexity of the pattern matching by introducing an approach named “optimized pattern similarity identification” (OPSI). This methodology constructs a table, entitled “shift beyond for avoiding redundant comparison” (SBARC), to bypass the characters in the texts that are already compared with the pattern. The table pertains to the information about the character distance to be skipped in the matching. OPSI discovers at most spots of similar patterns occur in the sequence (by ignoring è mismatches). The experiment resulted in the time complexity identified as O (ls. è). In comparison to the size of the pattern, the allowed number of mismatches will be much smaller. Aspects such as scalability, generalizability, and performance of the OPSI algorithm are discussed. In comparison with the hamming distance-based approximate pattern matching algorithm, the proposed algorithm is found to be 69% more efficient.

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Technical Study on 5G Using Soft Computing Methods

Cited by 28 publications

References 29 publications

QoS Analysis for Cloud-Based IoT Data Using Multicriteria-Based Optimization Approach

QoS Analysis for Cloud-Based IoT Data Using Multicriteria-Based Optimization Approach

Energy Auditing and Broken Path Identification for Routing in Large-Scale Mobile Networks Using Machine Learning

Lightweight Pattern Matching Method for DNA Sequencing in Internet of Medical Things

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