scholarly journals Fog-based Spider Web Algorithm to Overcome Latency in Cloud Computing

2020 ◽  
pp. 1781-1790
Author(s):  
ABDUL RASHID DAR ◽  
D Ravindran ◽  
Shahidul Islam
Keyword(s):  
Cloud Computing ◽  
Web Applications ◽  
Virtual Machines ◽  
Fog Computing ◽  
Network Reduction ◽  
Spider Web ◽  
Network Bandwidth ◽  
Computing Services ◽  
Cloud Computing Services ◽  
Cloud Users

The cloud-users are getting impatient by experiencing the delays in loading the content of the web applications over the internet, which is usually caused by the complex latency while accessing the cloud datacenters distant from the cloud-users. It is becoming a catastrophic situation in availing the services and applications over the cloud-centric network. In cloud, workload is distributed across the multiple layers which also increases the latency. Time-sensitive Internet of Things (IoT) applications and services, usually in a cloud platform, are running over various virtual machines (VM’s) and possess high complexities while interacting. They face difficulties in the consolidations of the various applications containing heterogenetic workloads. Fog computing takes the cloud computing services to the edge-network, where computation, communication and storage are within the proximity to the end-user’s edge devices. Thus, it utilizes the maximum network bandwidth, enriches the mobility, and lowers the latency. It is a futuristic, convenient and more reliable platform to overcome the cloud computing issues. In this manuscript, we propose a Fog-based Spider Web Algorithm (FSWA), a heuristic approach which reduces the delays time (DT) and enhances the response time (RT) during the workflow among the various edge nodes across the fog network. The main purpose is to trace and locate the nearest f-node for computation and to reduce the latency across the various nodes in a network. Reduction of latency will enhance the quality of service (QoS) parameters, smooth resource distribution, and services availability. Latency can be an important factor for resource optimization issues in distributed computing environments. In comparison to the cloud computing, the latency in fog computing is much improved.

Cloud-Based Platforms and Infrastructures

2017 ◽  
pp. 47-90
Author(s):  
Marcus Tanque
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Cloud Service ◽  
Resource Provisioning ◽  
Virtual Networks ◽  
Network Resources ◽  
Computing Services ◽  
Service Models ◽  
Cloud Computing Services ◽  
Shared Network

Cloud computing consists of three fundamental service models: infrastructure-as-a-service, platform-as-a service and software-as-a-service. The technology “cloud computing” comprises four deployment models: public cloud, private cloud, hybrid cloud and community cloud. This chapter describes the six cloud service and deployment models, the association each of these services and models have with physical/virtual networks. Cloud service models are designed to power storage platforms, infrastructure solutions, provisioning and virtualization. Cloud computing services are developed to support shared network resources, provisioned between physical and virtual networks. These solutions are offered to organizations and consumers as utilities, to support dynamic, static, network and database provisioning processes. Vendors offer these resources to support day-to-day resource provisioning amid physical and virtual machines.

An Energy-efficient Virtual Machine Placement Algorithm based Service Level Agreement in Cloud Computing Environments

2017 ◽  
Vol 2 (6) ◽  
pp. 1-6
Author(s):  
Arash Mazidi ◽  
Elham Damghanijazi ◽  
Sajad Tofighy
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Service Level ◽  
Model Management ◽  
Time Data ◽  
Computing Services ◽  
Cloud Computing Services ◽  
Placement Algorithm ◽  
Leading Enterprises

The cloud computing has given services to the users throughout the world during recent years. The cloud computing services have been founded according to ‘As-Pay-You-Go’ model and some leading enterprises give these services. The giving these cloud-computing services has been developed every day and these requirements necessitate for more infrastructures and Internet providers (IPs). The nodes of data centers consume a lot of energy in cloud structure and disseminate noticeable amount of carbon dioxide into the environment. We define a framework and structure for cloud environment of efficient energy in the present paper. We examine the present problems and challenges based on this structure and then present and model management algorithms and source allocation in cloud computing environment in order to manage energy in addition to considering Service Level Agreement. The proposed algorithm has been implemented by cloudsim simulator where the obtained results from simulation of real-time data indicate that the proposed method is superior to previous techniques in terms of energy consumption and observance of Service Level Agreement. Similarly, number of live migration of virtual machines and quantity of transferred data has been improved.

Cloud-Based Platforms and Infrastructures

2019 ◽  
pp. 84-126
Author(s):  
Marcus Tanque
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Cloud Service ◽  
Resource Provisioning ◽  
Virtual Networks ◽  
Network Resources ◽  
Computing Services ◽  
Service Models ◽  
Cloud Computing Services ◽  
Shared Network

Cloud computing consists of three fundamental service models: infrastructure-as-a-service, platform-as-a service and software-as-a-service. The technology “cloud computing” comprises four deployment models: public cloud, private cloud, hybrid cloud and community cloud. This chapter describes the six cloud service and deployment models, the association each of these services and models have with physical/virtual networks. Cloud service models are designed to power storage platforms, infrastructure solutions, provisioning and virtualization. Cloud computing services are developed to support shared network resources, provisioned between physical and virtual networks. These solutions are offered to organizations and consumers as utilities, to support dynamic, static, network and database provisioning processes. Vendors offer these resources to support day-to-day resource provisioning amid physical and virtual machines.

scholarly journals Processing Optimization of Typed Resources with Synchronized Storage and Computation Adaptation in Fog Computing

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Zhengyang Song ◽  
Yucong Duan ◽  
Shixiang Wan ◽  
Xiaobing Sun ◽  
Quan Zou ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Fog Computing ◽  
Network Resources ◽  
Network Bandwidth ◽  
Computing Services ◽  
Processing Cost ◽  
Processing Optimization ◽  
Optimization Mechanism ◽  
And Storage ◽  
The Internet Of Things

Wide application of the Internet of Things (IoT) system has been increasingly demanding more hardware facilities for processing various resources including data, information, and knowledge. With the rapid growth of generated resource quantity, it is difficult to adapt to this situation by using traditional cloud computing models. Fog computing enables storage and computing services to perform at the edge of the network to extend cloud computing. However, there are some problems such as restricted computation, limited storage, and expensive network bandwidth in Fog computing applications. It is a challenge to balance the distribution of network resources. We propose a processing optimization mechanism of typed resources with synchronized storage and computation adaptation in Fog computing. In this mechanism, we process typed resources in a wireless-network-based three-tier architecture consisting of Data Graph, Information Graph, and Knowledge Graph. The proposed mechanism aims to minimize processing cost over network, computation, and storage while maximizing the performance of processing in a business value driven manner. Simulation results show that the proposed approach improves the ratio of performance over user investment. Meanwhile, conversions between resource types deliver support for dynamically allocating network resources.

Trustworthy Framework for Insider Attack Prevention and Detection

2019 ◽  
pp. 62-82
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Cloud Service ◽  
Virtual Machine Monitor ◽  
Computing Architecture ◽  
Insider Attack ◽  
Computing Services ◽  
Least Privilege ◽  
Security Properties ◽  
Cloud Computing Services

This chapter introduces a trustworthy cloud computing architecture that uses the security properties offered by a virtual machine monitor that enforces the principle of least privilege. These security properties are a strong building block to provide trustworthy cloud computing services to cloud consumers. This chapter briefly explained about a proposed system to prevent insider attacks in cloud environment from cloud consumer and cloud service provider perspectives. The proposed framework is initiating how virtual machines are providing the most reliable security materials of the cloud computing architecture. For cloud consumers, the proposed architecture allocates the well-built security materials of the reliable cloud computing services.

The Establishment of Information Management Security under Cloud Computing Environment

2015 ◽  
Vol 713-715 ◽  
pp. 2405-2408 ◽  
Author(s):  
Tao Li
Keyword(s):  
Cloud Computing ◽  
Development Process ◽  
Market Potential ◽  
Computing Environment ◽  
Security Risks ◽  
Cloud Computing Environment ◽  
Network Bandwidth ◽  
Computing Services ◽  
New Information ◽  
Cloud Computing Services

Cloud computing is Internet-based computing model which can share new information resources through virtualization, it can be dynamically according to the user needs to provide computing, storage, network bandwidth, software and other resources and it has great market potential and become the focus of the current IT giants construction of the project. However, just as other new things, there are flaws and loopholes need to continuously improve and enhance the development process in the future of cloud computing. In this paper, the development process of computing services of cloud security incidents is discussed and we analyzes the potential security risks of cloud computing services, security building and then put forward the ideas of security management development under cloud computing environment.

scholarly journals Resource Utilization Scheme of Idle Virtual Machines for Multiple Large-Scale Jobs Based on OpenStack

2019 ◽  
Vol 9 (20) ◽  
pp. 4327
Author(s):  
Jueun Jeon ◽  
Jong Hyuk Park ◽  
Young-Sik Jeong
Keyword(s):  
Cloud Computing ◽  
Resource Utilization ◽  
Virtual Machine ◽  
Large Scale ◽  
Virtual Machines ◽  
Engineering Application ◽  
Computing Services ◽  
Cloud Computing Services ◽  
Scientific Technical ◽  
Utilization Scheme

Cloud computing services that provide computing resources to users through the Internet also provide computing resources in a virtual machine form based on virtualization techniques. In general, supercomputing and grid computing have mainly been used to process large-scale jobs occurring in scientific, technical, and engineering application domains. However, services that process large-scale jobs in parallel using idle virtual machines are not provided in cloud computing at present. Generally, users do not use virtual machines anymore, or they do not use them for a long period of time, because existing cloud computing assigns all of the use rights of virtual machines to users, resulting in the low use of computing resources. This study proposes a scheme to process large-scale jobs in parallel, using idle virtual machines and increasing the resource utilization of idle virtual machines. Idle virtual machines are basically identified through specific determination criteria out of virtual machines created using OpenStack, and then they are used in computing services. This is called the idle virtual machine–resource utilization (IVM–ReU), which is proposed in this study.

Sign in / Sign up

Export Citation Format

Share Document