Cooperative Routing for Improving the Lifetime of Wireless Ad-Hoc Networks

Agriculture has a key role in the overall economic development of the country. Climate change, irregular rainfall, changes in the nutrient content of the soil, and other environmental changes are seen as a severe problem in crop yield prediction. Using deep learning (DL) models that incorporate multiple factors can be viewed as an essential strategy for attaining accurate and effective solutions to this issue. The crop yield can be predicted using yield data obtained from a historical source that includes information about the weather, soil nutrient content, soil type, the season in which the crop was grown, and its yield. In order to train the model and achieve high accuracy, a large set of data including multiple factors would be required. This research aims to forecast the yield of a certain crop using long short-term memory (LSTM) time series analysis and the information currently available. The data used to construct the models was obtained from a reputable source and contains correct numbers. Before growing a crop that has been sown on a piece of agricultural land, the yield prediction utilizing advanced methodologies can assist farmers predict the yield of a specific crop.

Section: Related Workmentioning

confidence: 99%

Prediction on field crops yield based on analysis of deep learning model

Iniyan

Jebakumar

Rajendran

et al. 2023

“…The process applies a broadcast encryption technique based on anonymous identification to the data access control system in a cloud storage server [24]. However, because the key data is not updated immediately, it may cause a bottleneck in the rekeying system or security corruption [25]. The sender is permitted by the proposed approach to prevent some people from reading the ciphertexts.…”

Section: Communication Cost (Cc)mentioning

confidence: 99%

“…However, there are many of the access control authorization obligations as could reasonably be expected to the Cloud while limiting the data introduction chances due to conspiring users and cloud [24]. The design that underpins various ways to deal with secure information collection in cloud [25].…”

mentioning

confidence: 99%

Flexible and secure continues data transmission among multiple users in cloud environment

Elumalai

Dinakaran

2023

Cloud computing is an internet based computing where the sharable information, software and resources are provided based on demand devices. Where, the rapid development and pervasive growth of unavoidable sending of message advances, there are expanding requests of adaptable cryptographic natives to protected group data transactions and computing platforms in cloud. Group key agreement (GKA) protocol enables a group to share a standard encryption key across an open network so that only members of the group may decode the ciphertexts encoded using the secret encryption key that has been released. However, a sender cannot deny any specific member from decryptions the ciphertexts in cloud. However, before sending a message to a group, a user must join the group and follow the GKA protocol to provide the intended members access to a secret key. To find a better solution for the above-mentioned issues, flexible and secure continues data transmission (FSCDT) algorithm is proposed to offer dynamic and secure data transfer broadcasting without full trust of key authority in unreliable cloud environment. It provides compete security proof, outlines the requirements of the aggregatability of the secret attribute based FSCDT building block. Based on experimental evaluations, FSCDT algorithm minimizes encryption time, decryption time and communication cost.

“…objective to enhance the lifetime and minimize the route detection cost. This approach using the fresher encounter algorithm to improve energy-efficiency and solves the node dead issues [26]. Multipath delay commutator fast fourier transform has been proposed for enhancing the throughput and speed [27].…”

Section: Introductionmentioning

confidence: 99%

Bi-directional trust management system in fog computing using logistic regression

Priyadarshini

Malarvizhi²

2023

<span lang="EN-US">Fog computing is a decentralised computing infrastructure that brings data, storage, computation, and communication resources closer to end users by extending typical cloud computing services to the network edge. A fog node can serve another fog node based on their processing power allowing fog-to-fog interaction. Fog nodes, being independent must be trusted for delegation because they collect sensitive data and share with other discrete fog nodes, where standard cryptographic solutions are ineffective against the internal attacks tossed by rogue fog node. This paper proposes a Bi-directional trust management system for secure transactions and fog-to-fog collaboration to address this problem in a fog environment, which allows a service requester to assess a service provider’s trustworthiness and the service provider to assess the service requester's level of trust before beginning a connection. This trust management system works based on the recommendation system, which is estimated using logistic regression by fog service provider and subjective logic by fog service requester for the establishment of secured connection between them. Using quality of security parameters, the proposed work yields the result of decision making between the fog service requester and fog service provider.</span>