Membrane computing inspired protocol to enhance security in cloud network

2018 ◽  
Vol 75 (4) ◽  
pp. 2181-2192
Author(s):  
K. Maharajan ◽  
B. Paramasivan
Keyword(s):  
Membrane Computing ◽  
Cloud Network

Allocation of Virtual Machines to the Cloud Network Using the Barking-Deer Approach

2020 ◽  
Author(s):  
Himadri Biswas ◽  
Sudipta Sahana ◽  
Priyajit Sen ◽  
Debabrata Sarddar
Keyword(s):  
Virtual Machines ◽  
Cloud Network

scholarly journals Computation offloading through mobile vehicles in IoT-edge-cloud network

2020 ◽  
Vol 2020 (1) ◽  
Author(s):  
Jun Long ◽  
Yueyi Luo ◽  
Xiaoyu Zhu ◽  
Entao Luo ◽  
Mingfeng Huang
Keyword(s):  
Reinforcement Learning ◽  
Energy Consumption ◽  
Low Cost ◽  
Computation Offloading ◽  
Mobile Edge Computing ◽  
Challenging Problem ◽  
Learning Technique ◽  
Cloud Network ◽  
The City ◽  
Task Offloading

AbstractWith the developing of Internet of Things (IoT) and mobile edge computing (MEC), more and more sensing devices are widely deployed in the smart city. These sensing devices generate various kinds of tasks, which need to be sent to cloud to process. Usually, the sensing devices do not equip with wireless modules, because it is neither economical nor energy saving. Thus, it is a challenging problem to find a way to offload tasks for sensing devices. However, many vehicles are moving around the city, which can communicate with sensing devices in an effective and low-cost way. In this paper, we propose a computation offloading scheme through mobile vehicles in IoT-edge-cloud network. The sensing devices generate tasks and transmit the tasks to vehicles, then the vehicles decide to compute the tasks in the local vehicle, MEC server or cloud center. The computation offloading decision is made based on the utility function of the energy consumption and transmission delay, and the deep reinforcement learning technique is adopted to make decisions. Our proposed method can make full use of the existing infrastructures to implement the task offloading of sensing devices, the experimental results show that our proposed solution can achieve the maximum reward and decrease delay.

scholarly journals The NECOS Approach to End-to-End Cloud-Network Slicing as a Service

2021 ◽  
Vol 59 (3) ◽  
pp. 91-97
Author(s):  
Stuart Clayman ◽  
Augusto Neto ◽  
Fabio Verdi ◽  
Sand Correa ◽  
Silvio Sampaio ◽  
...  
Keyword(s):  
Network Slicing ◽  
End To End ◽  
Cloud Network

Cost-efficient mobility offloading and task scheduling for microservices IoVT applications in container-based fog cloud network

2021 ◽  
Author(s):  
Abdullah Lakhan ◽  
Muhammad Suleman Memon ◽  
Qurat-ul-ain Mastoi ◽  
Mohamed Elhoseny ◽  
Mazin Abed Mohammed ◽  
...  
Keyword(s):  
Task Scheduling ◽  
Cost Efficient ◽  
Cloud Network ◽  
And Task

Improving cloud network security using the Tree-Rule firewall

2014 ◽  
Vol 30 ◽  
pp. 116-126 ◽  
Author(s):  
Xiangjian He ◽  
Thawatchai Chomsiri ◽  
Priyadarsi Nanda ◽  
Zhiyuan Tan
Keyword(s):  
Network Security ◽  
Cloud Network

scholarly journals Simulation challenges in membrane computing

2020 ◽  
Vol 2 (4) ◽  
pp. 392-402
Author(s):  
Luis Valencia-Cabrera ◽  
Ignacio Pérez-Hurtado ◽  
Miguel Á. Martínez-del-Amor
Keyword(s):  
Membrane Computing
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