Efficient Handoff Detection for Computation Offloading using Machine Learning and Bio-Inspired Optimization Techniques in Mobile Edge Computing DOI

Vaishali Joshi,

Kishor Patil

2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT), Год журнала: 2024, Номер 34, С. 100 - 104

Опубликована: Апрель 6, 2024

With the rise of smartphones and Internet Things (IoT), more calculations are being performed on mobile devices, which rapidly depletes their power reserves. To save battery device offloading tasks to cloud is one solutions but, delay-sensitive applications, such as virtual gaming, augmented reality, etc., negatively affected by solution task a centralized cloud. For maximum efficiency in both consumption latency, it desirable locate resources at Edge Network. Quality Experience (QoE) if mobility end user not addressed. Handoff detection crucial for resolving issues edge computing. In this work, we offer machine learning bio-inspired optimization-based method detecting handoffs.

Язык: Английский

Secure Cloud Data Access: Unifying Quantum Key Distribution and Attribute-Based Encryption for Enhanced Data Protection DOI
Ashutosh Kumar, Garima Verma

SN Computer Science, Год журнала: 2023, Номер 4(6)

Опубликована: Окт. 16, 2023

Язык: Английский

Процитировано

1

Aplicação da tecnologia blockchain na gestão de dados dos prontuários eletrônicos de pacientes: revisão integrativa da literatura DOI Creative Commons
Isaque Benevides Castro Carvalho, Gustavo Wanderley Lopes Azevedo, Márcia Maria Pereira Rendeiro

и другие.

Revista Sustinere, Год журнала: 2023, Номер 11(2), С. 584 - 607

Опубликована: Дек. 23, 2023

A gestão em saúde atualmente enfrenta desafios na forma como os dados dos pacientes são armazenados prontuários. O sistema centralizado dificulta o acesso a suas informações confidenciais, prejudicando controle sobre seus próprios registros de saúde. Muitas vezes, desconhecem completamente as anotações feitas Esta pesquisa tem objetivo identificar estudos aplicação da tecnologia blockchain área saúde, buscando soluções para melhorar armazenamento e aos revisão integrativa foi realizada 2022, consultando publicações nas bases eletrônicos MEDLINE, Web of Science Scopus, resultando 18.728 encontrados. Após critérios exclusão, inclusão qualidade, foram utilizados nesta 83 relevantes. Embora número aplicações esteja constante crescimento, algumas limitações ainda precisam ser superadas. Existem que não encontraram adequadas. Apesar do potencial interesse blockchain, seu impacto no prontuários está fase documentação, atendimento clínico mais desenvolvidas. maioria com base se encontra estágio conceitos iniciais e, alguns casos, operam usuários restritas. No entanto, acreditamos futuro elimina intermediários, um imenso exercer efeito positivo significativo

Процитировано

1

Secure Virtual Machine Migration and Host Overload Detection Using Modified Pelican Optimization with Variable Load Mean Function DOI

S. Parthasarathy

Journal of Circuits Systems and Computers, Год журнала: 2024, Номер 33(14)

Опубликована: Март 15, 2024

Low-resource utilization and high-energy consumption have become progressively protuberant issues in cloud data centers. Virtual Machine (VM) migration is the key objective to resolve this issue. Moreover, extreme VM might empower Service-Level Agreement (SLA) violations. Few works are considered for optimizing throughput energy consumption. An efficient must consider different parameters like network communication overhead, resource utilization, quality of service which a multi-objective Hence, paper, Modified Pelican Optimization-based Variable Load Mean Function (MPO-VLMF)-based host overload detection presented security enhancement developed. The main motive study achieve enhancement. To obtain detection, variable load mean function In function, weight parameter selected by considering Optimization (MPO). Levy flight (LF) enhancing updating process (PO). enhance system, Digital Signature-based Encryption (DSE) Based on proposed approach, obtained. technique implemented evaluated performance measures. It compared with conventional approaches justify system.

Язык: Английский

Процитировано

0

Evaluation of Secure Methods for Migrating Virtual Machines to the Cloud DOI
Harmeet Kaur, Shubham Gargrish

Опубликована: Фев. 9, 2024

Cloud services are becoming more popular due to their numerous benefits, such as low cost, dependability, and user-friendliness. Data security protocols have been created in response the increasing demand. It is critical for cloud computing ensure that data can only be accessed by authorized users. To safeguard cloud-based platforms, ML-dependent solutions employed, even though cryptographic procedures still principal means of guaranteeing security. Any information technology infrastructure might benefit significantly from artificial intelligence's capacity assess real-time while providing threat information. When migrating VMs, it crucial keep consideration. Conducting an analysis methods used during VM migration primary goal this work. Beyond that, we covered various ML In addition, certain properties accuracy, security, computational speed, time savings, throughput, so on compare with algorithms inference gathering. Apart comparative based approaches has done metrics like authentication process, delay, throughput CIA triad We could enhance through integrating cryptography procedures.

Язык: Английский

Процитировано

0

Efficient Handoff Detection for Computation Offloading using Machine Learning and Bio-Inspired Optimization Techniques in Mobile Edge Computing DOI

Vaishali Joshi,

Kishor Patil

2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT), Год журнала: 2024, Номер 34, С. 100 - 104

Опубликована: Апрель 6, 2024

With the rise of smartphones and Internet Things (IoT), more calculations are being performed on mobile devices, which rapidly depletes their power reserves. To save battery device offloading tasks to cloud is one solutions but, delay-sensitive applications, such as virtual gaming, augmented reality, etc., negatively affected by solution task a centralized cloud. For maximum efficiency in both consumption latency, it desirable locate resources at Edge Network. Quality Experience (QoE) if mobility end user not addressed. Handoff detection crucial for resolving issues edge computing. In this work, we offer machine learning bio-inspired optimization-based method detecting handoffs.

Язык: Английский

Процитировано

0