scholarly journals Toward a Unified Framework for the Heterogeneous Cloud Utilizing Bytecode Containers

2021 ◽  
Author(s):  
David Andrew Lloyd Tenty
Keyword(s):  
Cloud Computing ◽  
Resource Utilization ◽  
Heterogeneous Systems ◽  
Public Cloud ◽  
Unified Framework ◽  
The Public ◽  
Cloud Environments ◽  
Heterogeneous Cloud ◽  
Systems Framework ◽  
Computing Landscape

As we approach the limits of Moore’s law the Cloud computing landscape is becoming ever more heterogeneous in order to extract more performance from available resources. Meanwhile, the container-based cloud is of growing importance as a lightweight way to deploy applications. A unified heterogeneous systems framework for use with container-based applications in the heterogeneous cloud is required. We present a bytecode-based framework and it’s implementation called Man O’ War, which allows for the creation of novel, portable LLVM bitcode-based containers for use in the heterogeneous cloud. Containers in Man O’ War enabled systems can be efficiently specialized for the available hardware within the Cloud and expand the frontiers for optimization in heterogeneous cloud environments. We demonstrate that a framework utilizing portable bytecode-based containers eases optimizations such as heterogeneous scaling which have the potential to improve resource utilization and significantly lower costs for users of the public cloud.

scholarly journals Toward a Unified Framework for the Heterogeneous Cloud Utilizing Bytecode Containers

2021 ◽  
Author(s):  
David Andrew Lloyd Tenty
Keyword(s):  
Cloud Computing ◽  
Resource Utilization ◽  
Heterogeneous Systems ◽  
Public Cloud ◽  
Unified Framework ◽  
The Public ◽  
Cloud Environments ◽  
Heterogeneous Cloud ◽  
Systems Framework ◽  
Computing Landscape

As we approach the limits of Moore’s law the Cloud computing landscape is becoming ever more heterogeneous in order to extract more performance from available resources. Meanwhile, the container-based cloud is of growing importance as a lightweight way to deploy applications. A unified heterogeneous systems framework for use with container-based applications in the heterogeneous cloud is required. We present a bytecode-based framework and it’s implementation called Man O’ War, which allows for the creation of novel, portable LLVM bitcode-based containers for use in the heterogeneous cloud. Containers in Man O’ War enabled systems can be efficiently specialized for the available hardware within the Cloud and expand the frontiers for optimization in heterogeneous cloud environments. We demonstrate that a framework utilizing portable bytecode-based containers eases optimizations such as heterogeneous scaling which have the potential to improve resource utilization and significantly lower costs for users of the public cloud.

A Review on Load Balancing Model Using Best Partition Technique

2017 ◽  
Vol 7 (8) ◽  
pp. 284
Author(s):  
M. Chaitanya ◽  
K. Durga Charan
Keyword(s):  
Cloud Computing ◽  
Fault Tolerance ◽  
Load Balancing ◽  
Load Balance ◽  
Large Impact ◽  
Cloud Environment ◽  
Public Cloud ◽  
The Public ◽  
Partition Technique ◽  
Textual Content

Load balancing makes cloud computing greater knowledgeable and could increase client pleasure. At reward cloud computing is among the all most systems which offer garage of expertise in very lowers charge and available all the time over the net. However, it has extra vital hassle like security, load administration and fault tolerance. Load balancing inside the cloud computing surroundings has a large impact at the presentation. The set of regulations relates the sport idea to the load balancing manner to amplify the abilties in the public cloud environment. This textual content pronounces an extended load balance mannequin for the majority cloud concentrated on the cloud segregating proposal with a swap mechanism to select specific strategies for great occasions.

scholarly journals A Conceptual Model for Cloud Computing Adoption by SMEs in Australia

2016 ◽  
pp. 307-334 ◽  
Author(s):  
Ishan Senarathna ◽  
Matthew Warren ◽  
William Yeoh ◽  
Scott Salzman
Keyword(s):  
Cloud Computing ◽  
Conceptual Model ◽  
Business Service ◽  
Perceived Benefits ◽  
Public Cloud ◽  
Total Cost ◽  
The Public ◽  
Software Applications ◽  
On Demand ◽  
Cloud Computing Adoption

Cloud Computing is an increasingly important worldwide development in business service provision. The business benefits of Cloud Computing usage include reduced IT overhead costs, greater flexibility of services, reduced TCO (Total Cost of Ownership), on-demand services, and improved productivity. As a result, Small and Medium-Sized Enterprises (SMEs) are increasingly adopting Cloud Computing technology because of these perceived benefits. The most economical deployment model in Cloud Computing is called the Public Cloud, which is especially suitable for SMEs because it provides almost immediate access to hardware resources and reduces their need to purchase an array of advanced hardware and software applications. The changes experienced in Cloud Computing adoption over the past decade are unprecedented and have raised important issues with regard to privacy, security, trust, and reliability. This chapter presents a conceptual model for Cloud Computing adoption by SMEs in Australia.

Software Design for Passing Sarbanes-Oxley in Cloud Computing

2014 ◽  
pp. 1659-1674
Author(s):  
Solomon Lasluisa ◽  
Ivan Rodero ◽  
Manish Parashar
Keyword(s):  
Cloud Computing ◽  
Implementation Process ◽  
Legal Issues ◽  
General Analysis ◽  
Legal Regulations ◽  
Public Cloud ◽  
The Public ◽  
Sarbanes Oxley ◽  
Legal Constraint ◽  
Specific Analysis

The purpose of this chapter is to identify and analyze the challenges of creating new software in the public cloud due to legal regulations. Specifically, this chapter explores how the Sarbanes-Oxley Act (SOX) will indirectly affect the development and implementation process of cloud computing applications in terms of software engineering and actual legality of said software solutions. The goal of this chapter is twofold - to bring attention to the need for specific analysis of legal issues in public clouds (as opposed to general analysis), and to illustrate the need for cloud developers to address legal constraint while creating their platforms, in order to increase their viability in the corporate environment.

Software Design for Passing Sarbanes-Oxley in Cloud Computing

2012 ◽  
pp. 27-42
Author(s):  
Solomon Lasluisa ◽  
Ivan Rodero ◽  
Manish Parashar
Keyword(s):  
Cloud Computing ◽  
Implementation Process ◽  
Legal Issues ◽  
General Analysis ◽  
Legal Regulations ◽  
Public Cloud ◽  
The Public ◽  
Sarbanes Oxley ◽  
Legal Constraint ◽  
Specific Analysis

The purpose of this chapter is to identify and analyze the challenges of creating new software in the public cloud due to legal regulations. Specifically, this chapter explores how the Sarbanes-Oxley Act (SOX) will indirectly affect the development and implementation process of cloud computing applications in terms of software engineering and actual legality of said software solutions. The goal of this chapter is twofold - to bring attention to the need for specific analysis of legal issues in public clouds (as opposed to general analysis), and to illustrate the need for cloud developers to address legal constraint while creating their platforms, in order to increase their viability in the corporate environment.

scholarly journals Employing Vertical Elasticity for Efficient Big Data Processing in Container-Based Cloud Environments

2021 ◽  
Vol 11 (13) ◽  
pp. 6200
Author(s):  
Jin-young Choi ◽  
Minkyoung Cho ◽  
Jik-Soo Kim
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Processing ◽  
Data Storage ◽  
Resource Utilization ◽  
System Throughput ◽  
Big Data Processing ◽  
Cloud Environments ◽  
Utilization Scheme ◽  
Adaptive Resource

Recently, “Big Data” platform technologies have become crucial for distributed processing of diverse unstructured or semi-structured data as the amount of data generated increases rapidly. In order to effectively manage these Big Data, Cloud Computing has been playing an important role by providing scalable data storage and computing resources for competitive and economical Big Data processing. Accordingly, server virtualization technologies that are the cornerstone of Cloud Computing have attracted a lot of research interests. However, conventional hypervisor-based virtualization can cause performance degradation problems due to its heavily loaded guest operating systems and rigid resource allocations. On the other hand, container-based virtualization technology can provide the same level of service faster with a lightweight capacity by effectively eliminating the guest OS layers. In addition, container-based virtualization enables efficient cloud resource management by dynamically adjusting the allocated computing resources (e.g., CPU and memory) during the runtime through “Vertical Elasticity”. In this paper, we present our practice and experience of employing an adaptive resource utilization scheme for Big Data workloads in container-based cloud environments by leveraging the vertical elasticity of Docker, a representative container-based virtualization technique. We perform extensive experiments running several Big Data workloads on representative Big Data platforms: Apache Hadoop and Spark. During the workload executions, our adaptive resource utilization scheme periodically monitors the resource usage patterns of running containers and dynamically adjusts allocated computing resources that could result in substantial improvements in the overall system throughput.

A Survey

2018 ◽  
pp. 181-191
Author(s):  
Srishti Sharma ◽  
Yogita Gigras
Keyword(s):  
Cloud Computing ◽  
Security Threats ◽  
Public Cloud ◽  
Security Measures ◽  
Unauthorized Access ◽  
Cloud Data ◽  
The Public ◽  
Fast Pace

The cloud computing field is an emerging field and continuously growing at a fast pace. The data stored on the public cloud is not safe as the attackers can hack or gain unauthorized access to the data and can modify its contents to harm the organizations and the users as well. They pose security threats and risks at various levels. These threats need to be removed and security actions need to be taken at right time to protect the cloud data and resources from being misused by the attackers. Some of the security measures are summarized in order to protect the data.

A Survey on Database Performance in Virtualized Cloud Environments

2012 ◽  
Vol 8 (3) ◽  
pp. 1-26 ◽  
Author(s):  
Todor Ivanov ◽  
Ilia Petrov ◽  
Alejandro Buchmann
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Resource Utilization ◽  
Database Systems ◽  
High Availability ◽  
Feed Processing ◽  
Computing Platform ◽  
Efficient Resource ◽  
Cloud Environments ◽  
Column Stores

Cloud Computing emerged as a major paradigm over the years. Major challenges it poses to computer science are related to latency, scale, and reliability issues. It leverages strong economical aspects and provides sound answers to questions like energy consumption, high availability, elasticity, or efficient computing resource utilization. Many Cloud Computing platform and solution providers resort to virtualization as key underlying technology. Properties like isolation, multi-virtual machine parallelism, load balancing, efficient resource utilization, and dynamic pre-allocation besides economic factors make it attractive. It not only legitimates the spread of several types of data stores supporting a variety of data modes, but also inherently requires different types of load: (i) analytical; (ii) Transactional/Update-intensive; and (iii) mixed real-time feed processing. The authors survey how database systems can best leverage virtualization properties in cloud scenarios. The authors show that read mostly database systems and especially column stores profit from virtualization in analytical and search scenarios. Secondly, cloud analytics virtualized database systems are efficient in transactional scenarios such as Cloud CRM virtualized database systems lag. The authors also explore how the nature of mixed cloud loads can be best reflected by virtualization properties like load balancing, migration, and high availability.

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