scholarly journals An Architecture of IoT Service Delegation and Resource Allocation Based on Collaboration between Fog and Cloud Computing

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Aymen Abdullah Alsaffar ◽  
Hung Phuoc Pham ◽  
Choong-Seon Hong ◽  
Eui-Nam Huh ◽  
Mohammad Aazam
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Big Data ◽  
Fog Computing ◽  
Decision Rules ◽  
Service Level Agreement ◽  
Data Distribution ◽  
Service Level ◽  
Memory Storage ◽  
Smart Devices

Despite the wide utilization of cloud computing (e.g., services, applications, and resources), some of the services, applications, and smart devices are not able to fully benefit from this attractive cloud computing paradigm due to the following issues: (1) smart devices might be lacking in their capacity (e.g., processing, memory, storage, battery, and resource allocation), (2) they might be lacking in their network resources, and (3) the high network latency to centralized server in cloud might not be efficient for delay-sensitive application, services, and resource allocations requests. Fog computing is promising paradigm that can extend cloud resources to edge of network, solving the abovementioned issue. As a result, in this work, we propose an architecture of IoT service delegation and resource allocation based on collaboration between fog and cloud computing. We provide new algorithm that is decision rules of linearized decision tree based on three conditions (services size, completion time, and VMs capacity) for managing and delegating user request in order to balance workload. Moreover, we propose algorithm to allocate resources to meet service level agreement (SLA) and quality of services (QoS) as well as optimizing big data distribution in fog and cloud computing. Our simulation result shows that our proposed approach can efficiently balance workload, improve resource allocation efficiently, optimize big data distribution, and show better performance than other existing methods.

Distance Aware VM allocation process to minimize energy consumption in cloud computing

2019 ◽  
Vol 12 ◽  
Author(s):  
Gurpreet Singh ◽  
Manish Mahajan ◽  
Rajni Mohana
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Research Work ◽  
Service Level Agreement ◽  
Service Level ◽  
Physical Machine ◽  
Allocation Process

BACKGROUND: Cloud computing is considered as an on-demand service resource with the applications towards data center on pay per user basis. For allocating the resources appropriately for the satisfaction of user needs, an effective and reliable resource allocation method is required. Because of the enhanced user demand, the allocation of resources has now considered as a complex and challenging task when a physical machine is overloaded, Virtual Machines share its load by utilizing the physical machine resources. Previous studies lack in energy consumption and time management while keeping the Virtual Machine at the different server in turned on state. AIM AND OBJECTIVE: The main aim of this research work is to propose an effective resource allocation scheme for allocating the Virtual Machine from an ad hoc sub server with Virtual Machines. EXECUTION MODEL: The execution of the research has been carried out into two sections, initially, the location of Virtual Machines and Physical Machine with the server has been taken place and subsequently, the cross-validation of allocation is addressed. For the sorting of Virtual Machines, Modified Best Fit Decreasing algorithm is used and Multi-Machine Job Scheduling is used while the placement process of jobs to an appropriate host. Artificial Neural Network as a classifier, has allocated jobs to the hosts. Measures, viz. Service Level Agreement violation and energy consumption are considered and fruitful results have been obtained with a 37.7 of reduction in energy consumption and 15% improvement in Service Level Agreement violation.

Resource Allocation Policies in Cloud Computing Environment

2017 ◽  
pp. 115-132 ◽  
Author(s):  
Suvendu Chandan Nayak ◽  
Sasmita Parida ◽  
Chitaranjan Tripathy ◽  
Prasant Kumar Pattnaik
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Resource Utilization ◽  
Service Level Agreement ◽  
Service Level ◽  
Computing Environment ◽  
Cloud Computing Environment ◽  
On Demand ◽  
Different Types ◽  
Cloud Datacenter

The basic concept of cloud computing is based on “Pay per Use”. The user can use the remote resources on demand for computing on payment basis. The on-demand resources of the user are provided according to a Service Level Agreement (SLA). In real time, the tasks are associated with a time constraint for which they are called deadline based tasks. The huge number of deadline based task coming to a cloud datacenter should be scheduled. The scheduling of this task with an efficient algorithm provides better resource utilization without violating SLA. In this chapter, we discussed the backfilling algorithm and its different types. Moreover, the backfilling algorithm was proposed for scheduling tasks in parallel. Whenever the application environment is changed the performance of the backfilling algorithm is changed. The chapter aims implementation of different types of backfilling algorithms. Finally, the reader can be able to get some idea about the different backfilling scheduling algorithms that are used for scheduling deadline based task in cloud computing environment at the end.

scholarly journals Resource Allocation Techniques in Cloud Computing: A Review and Future Directions

2020 ◽  
Vol 26 (6) ◽  
pp. 40-51
Author(s):  
Muhammad Faraz Manzoor ◽  
Adnan Abid ◽  
Muhammad Shoaib Farooq ◽  
Naeem A. Azam ◽  
Uzma Farooq
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Literature Review ◽  
Service Providers ◽  
Service Level Agreement ◽  
Service Level ◽  
Process Data ◽  
Future Directions ◽  
Computing Model ◽  
Structured Literature Review

Cloud computing has become a very important computing model to process data and execute computationally concentrated applications in pay-per-use method. Resource allocation is a process in which the resources are allocated to consumers by cloud providers based on their flexible requirements. As the data is expanding every day, allocating resources efficiently according to the consumer demand has also become very important, keeping Service Level Agreement (SLA) between service providers and consumers in prospect. This task of resource allocation becomes more challenging due to finite available resources and increasing consumer demands. Therefore, many unique models and techniques have been proposed to allocate resources efficiently. In the light of the uniqueness of the models and techniques, the main aim of the resource allocation is to limit the overhead/expenses associated with it. This research aims to present a comprehensive, structured literature review on different aspects of resource allocation in cloud computing, including strategic, target resources, optimization, scheduling and power. More than 50 articles, between year 2007 and 2019, related to resource allocation in cloud computing have been shortlisted through a structured mechanism and they are reviewed under clearly defined objectives. It presents a topical taxonomy of resource allocation dimensions, and articles under each category are discussed and analysed. Lastly, salient future directions in this area are discussed.

On the Conceptualization of Elastic Service Evaluation in Cloud Computing

2021 ◽  
pp. 1587-1601
Author(s):  
Danqing Feng ◽  
Zhibo Wu ◽  
Zhan Zhang ◽  
Jinwei Fu
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Service Level Agreement ◽  
Service Level ◽  
Service Evaluation ◽  
Resource Optimization ◽  
Resource Allocations ◽  
Allocation Strategy ◽  
Resource Allocation Strategy ◽  
Different Dimensions

Cloud computing is becoming an urgent technology in the enterprises. One key characteristic in the cloud computing is the elasticity. Then, it is urgent for the users how to rank the renting services reasonably. Considering the main features of the elasticity, this article gives classification on resource optimization. However, one of the major challenges is how to optimize resource allocation in an elastic manner. Due to the special pay-as-you-go manner, resource optimizing strategies are associated with the goal of minimizing the costs on the premise of service-level-agreement (SLA). Another challenge of resource optimizing strategies is to how to dynamically respond to the application demands. In this paper, the authors sketch the elastic definition more clearly. Secondly, different dimensions are described on elastic resource allocations. Thirdly, it is important to seek out the proper resource allocation strategy. Finally, the challenges and conclusions are discussed in this article.

On the Conceptualization of Elastic Service Evaluation in Cloud Computing

2019 ◽  
Vol 12 (1) ◽  
pp. 36-48 ◽  
Author(s):  
Danqing Feng ◽  
Zhibo Wu ◽  
Zhan Zhang ◽  
Jinwei Fu
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Service Level Agreement ◽  
Service Level ◽  
Service Evaluation ◽  
Resource Optimization ◽  
Resource Allocations ◽  
Allocation Strategy ◽  
Resource Allocation Strategy ◽  
Different Dimensions

Cloud computing is becoming an urgent technology in the enterprises. One key characteristic in the cloud computing is the elasticity. Then, it is urgent for the users how to rank the renting services reasonably. Considering the main features of the elasticity, this article gives classification on resource optimization. However, one of the major challenges is how to optimize resource allocation in an elastic manner. Due to the special pay-as-you-go manner, resource optimizing strategies are associated with the goal of minimizing the costs on the premise of service-level-agreement (SLA). Another challenge of resource optimizing strategies is to how to dynamically respond to the application demands. In this paper, the authors sketch the elastic definition more clearly. Secondly, different dimensions are described on elastic resource allocations. Thirdly, it is important to seek out the proper resource allocation strategy. Finally, the challenges and conclusions are discussed in this article.

scholarly journals Multicriteria Resource Brokering in Cloud Computing for Streaming Service

2015 ◽  
Vol 2015 ◽  
pp. 1-15
Author(s):  
Chih-Lun Chou ◽  
Gwo-Jiun Horng ◽  
Chieh-Ling Huang ◽  
Wei-Chun Hsieh
Keyword(s):  
Resource Allocation ◽  
Cloud Computing ◽  
Programming Model ◽  
Service Level Agreement ◽  
Multicriteria Decision Making ◽  
Service Level ◽  
Resource Brokering ◽  
Goal Programming Model ◽  
Service Oriented ◽  
Streaming Service

By leveraging cloud computing such as Infrastructure as a Service (IaaS), the outsourcing of computing resources used to support operations, including servers, storage, and networking components, is quite beneficial for various providers of Internet application. With this increasing trend, resource allocation that both assures QoS via Service Level Agreement (SLA) and avoids overprovisioning in order to reduce cost becomes a crucial priority and challenge in the design and operation of complex service-based platforms such as streaming service. On the other hand, providers of IaaS also concern their profit performance and energy consumption while offering these virtualized resources. In this paper, considering both service-oriented and infrastructure-oriented criteria, we regard this resource allocation problem as Multicriteria Decision Making problem and propose an effective trade-off approach based on goal programming model. To validate its effectiveness, a cloud architecture for streaming application is addressed and extensive analysis is performed for related criteria. The results of numerical simulations show that the proposed approach strikes a balance between these conflicting criteria commendably and achieves high cost efficiency.

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