Public Auditing Scheme for Integrity Verification in Distributed Cloud Storage System

Mahalakshmi, K.; Kousalya, K.; Shekhar, Himanshu; Thomas, Aby K.; Bhagyalakshmi, L.; Suman, Sanjay Kumar; Chandragandhi, S.; Bachanna, Prashant; Srihari, K.; Sundramurthy, Venkatesa Prabhu

doi:10.1155/2021/8533995

Cited by 39 publications

(24 citation statements)

References 20 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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“…Since the maximum distance path is chosen for forwarding, data packets make maximum cost or resource utilization. It improves energy usage and packet drop level [22][23][24][25][26][27][28][29][30][31][32][33].…”

Section: Overview Of the Proposed Schemementioning

confidence: 99%

Stable Route Selection for Adaptive Packet Transmission in 5G-Based Mobile Communications

Jegadeesan¹,

Beno²,

Manikandan³

et al. 2022

Wireless Communications and Mobile Computing

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In mobile nodes in the network, they are unstable, so single-path communication does not provide sufficient results. In the alternative single path, communication is very difficult to handle the heavy load. The poor connectivity among the mobile node makes the uncertainty of packet loss; the path link is not measured in this network. The communication cost is also focused to achieve valid packet transmission. Because the high distance path selected for packet transmission causes a high cost for communication. It increases energy consumption and packet loss rate. So, the proposed dispersed path selection for communication (DPAC) method is constructed to obtain the best minimum distance routing path, this path operates with the help of queue variation that handled the data packet’s maintenance, and the time slot exceeds its limit. Packets are kept waiting, to increase the packet broadcasting efficiency. The multipath jamming detection algorithm is constructed to provide link-based path packet overload detection scheme to identify the packet overload. Also, separate the path based on its characteristics, to control overload. It reduces energy consumption and packet loss rate.

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Public Auditing Scheme for Integrity Verification in Distributed Cloud Storage System

Cited by 39 publications

References 20 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

Stable Route Selection for Adaptive Packet Transmission in 5G-Based Mobile Communications

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