scholarly journals Prediction of CPU Utilization in Cloud Environment during Seasonal Trend

2021 ◽  
Vol 9 (12) ◽  
pp. 08-11
Author(s):  
Smitha Krishnan ◽  
Dr B.G Prasanthi
Keyword(s):  
Service Level ◽  
End User ◽  
Workload Prediction ◽  
Computing Services ◽  
Previous Algorithm ◽  
Storage Technologies ◽  
Accuracy Of Prediction ◽  
And Storage ◽  
Data Centres

Today, the most recent paradigm to emerge is that of Cloud computing, which promises reliable services delivered to the end-user through next-generation data centres which are built on virtualized compute and storage technologies Consumer will be able to access desired service from a “Cloud” anytime anywhere in the world on the bases of demand. Computing services need to be highly reliable, scalable, easy accessible and autonomic to support ever-present access, dynamic discovery and computability, consumers indicate the required service level through Quality of Service (QoS) parameters, according to Service Level Agreements (SLAs) A suitable mdel for the prediction is being developed. Here Genetic Algorithm is chosen in combination with stastical model to do the workload prediction .It is expected to give better result by producing less error rate and more accuracy of prediction compared to the previous algorithm.

scholarly journals A Proposal for End-to-End QoS Provisioning in Software-Defined Networks

2017 ◽  
Vol 7 (4) ◽  
pp. 2261 ◽  
Author(s):  
Francesco Lucrezia ◽  
Guido Marchetto ◽  
Fulvio Risso ◽  
Michele Santuari ◽  
Matteo Gerola
Keyword(s):  
Smart Grids ◽  
Service Level ◽  
End User ◽  
Delay Bound ◽  
Qos Guarantee ◽  
End To End Delay ◽  
Network Controller ◽  
Edge Network ◽  
End To End

This paper describes a framework application for the control plane of a network infrastructure; the objective is to feature end-user applications with the capability of requesting at any time a customised end-to-end Quality-of-Service profile in the context of dynamic Service-Level-Agreements. Our solution targets current and future real-time applications that require tight QoS parameters, such as a guaranteed end-to-end delay bound. These applications include, but are not limited to, health-care, mobility, education, manufacturing, smart grids, gaming and much more. We discuss the issues related to the previous Integrated Service and the reason why the RSVP protocol for guaranteed QoS did not take off. Then we present a new signaling and resource reservation framework based on the cutting-edge network controller ONOS.  Moreover, the presented system foresees the need of considering the edges of the network, where terminal applications are connected to, to be piloted by distinct logically centralised controllers. We discuss a possible inter-domain communication mechanism to achieve the end-to-end QoS guarantee.

Transporting the Cloud

2014 ◽  
pp. 135-156
Author(s):  
Claudio Estevez
Keyword(s):  
Cloud Computing ◽  
Mobile Cloud Computing ◽  
Transport Layer ◽  
Mobile Cloud ◽  
Transport Protocols ◽  
End User ◽  
Advantages And Disadvantages ◽  
Processing Power ◽  
And Storage

Cloud computing is consistently proving to be the dominant architecture of the future, and mobile technology is the catalyst. By having the processing power and storage remotely accessible, the main focus of the terminal is now related to connectivity and user-interface. The success of cloud-based applications greatly depends on the throughput experienced by the end user, which is why transport protocols play a key role in mobile cloud computing. This chapter discusses the main issues encountered in cloud networks that affect connection-oriented transport protocols. These issues include, but are not limited to, large delay connections, bandwidth variations, power consumption, and high segment loss rates. To reduce these adverse effects, a set of proposed solutions are presented; furthermore, the advantages and disadvantages are discussed. Finally, suggestions are made for future mobile cloud computing transport-layer designs that address different aspects of the network, such as transparency, congestion-intensity estimation, and quality-of-service integration.

Optimal Management of Cloud Centers with Different Arrival Modes for Cloud Computing Environment

2012 ◽  
Vol 2 (3) ◽  
pp. 86-97
Author(s):  
Veena Goswami ◽  
Sudhansu Shekhar Patra ◽  
G. B. Mund
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Service Level ◽  
Finite Buffer ◽  
Web Browser ◽  
Computing Paradigm ◽  
Computing Services ◽  
Multi Server

Cloud computing is a new computing paradigm in which information and computing services can be accessed from a Web browser by clients. Understanding of the characteristics of computer service performance has become critical for service applications in cloud computing. For the commercial success of this new computing paradigm, the ability to deliver guaranteed Quality of Services (QoS) is crucial. Based on the Service level agreement, the requests are processed in the cloud centers in different modes. This paper analyzes a finite-buffer multi-server queuing system where client requests have two arrival modes. It is assumed that each arrival mode is serviced by one or more Virtual machines, and both the modes have equal probabilities of receiving service. Various performance measures are obtained and optimal cost policy is presented with numerical results. The genetic algorithm is employed to search the optimal values of various parameters for the system.

Using service-level indices to manage the quality of computing services: A case study

1992 ◽  
Vol 18 (2) ◽  
pp. 139-145 ◽  
Author(s):  
Armin Roeseler ◽  
Anneliese von Mayrhauser
Keyword(s):  
Service Level ◽  
Computing Services

scholarly journals A Cross layer QoS Framework for Heterogeneous IoT Environment

2019 ◽  
Vol 9 (2) ◽  
pp. 1972-1979
Keyword(s):  
Service Level ◽  
Cross Layer ◽  
Service Provisioning ◽  
Critical Research ◽  
Distributed Decision Making ◽  
Cross Domain ◽  
Novel Approach ◽  
Cross Platform ◽  
And Storage

Internet of Things (IoT) is one of the fast growing technological paradigm in terms of architecture, standards, protocols, infrastructure deployment, Quality of Service (QoS), Service Level Agreements (SLAs), service provisioning, cross domain and cross platform implementations. IoT involves the techniques and technologies for sensing, actuation, communication, computation, networking and storage. In such a demanding environment the need for cross layer QoS functionalities are essential to address the issues like resources, mobility, security and energy management. The detailed review of literatures on IoT architectures and QoS implementations is made and it is observed that there is a need for cross layer QoS model in IoT environments and is one of the critical research challenges. A novel approach to address the above challenge(s) in an IoT environment requires an appropriate lathering of functional modules to different layers to meet different QoS requirements. Hence we propose a novel cross layer QoS framework supporting adaptable and distributed decision making in the IoT environment as a cross layer implementation addressing energy optimization and bandwidth efficiency. The results are verified by implementing the proposed framework in realistic IoT systems for verifying QoS parameters like delay, energy and bandwidth.

Requirement Analysis and Identification of Challenges and Issues for RTDBs in Cloud Computing

2012 ◽  
Vol 241-244 ◽  
pp. 3067-3070
Author(s):  
Muhammad Irfan ◽  
Hong Zhu
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Database Systems ◽  
Service Level ◽  
Customer Requirements ◽  
End User ◽  
Data Services ◽  
Requirements Gathering ◽  
Real Time Database

Cloud computing is baseline to invent next generation systems. As computer science is progressing by steps of cloud computing, same as requirements gathering, analysis in cloud computing getting more potential. The cloud computing enables services to fulfill requirements of cloud end-user, according to service level agreements. Data services over cloud also getting more potential especially real-time database systems are more critical to meet customer requirements over cloud. We will elaborate and present detailed analysis about requirements for real-time database systems over cloud, as well identify challenges and issues for RTDBs (real-time database systems) in cloud computing. There is need to ensure quality of service (QoS) as guaranty to meet requirements of RTDBs.

scholarly journals RCD: Rapid Close to Deadline Scheduling for datacenter networks

2018 ◽  
Author(s):  
Mohammad Noormohammadpour ◽  
Cauligi S. Raghavendra ◽  
Sriram Rao ◽  
Asad M. Madni
Keyword(s):  
Service Level ◽  
Multimedia Streaming ◽  
Bulk Storage ◽  
Computing Services ◽  
Link Utilization ◽  
Datacenter Networks ◽  
Cloud Computing Services ◽  
Traffic Allocation ◽  
Deadline Scheduling

Datacenter-based Cloud Computing services provide a flexible, scalable and yet economical infrastructure to host online services such as multimedia streaming, email and bulk storage. Many such services perform geo-replication to provide necessary quality of service and reliability to users resulting in frequent large inter-datacenter transfers. In order to meet tenant service level agreements (SLAs), these transfers have to be completed prior to a deadline. In addition, WAN resources are quite scarce and costly, meaning they should be fully utilized. Several recently proposed schemes, such as B4 [1], TEMPUS [2], and SWAN [3] have focused on improving the utilization of inter-datacenter transfers through centralized scheduling, however, they fail to provide a mechanism to guarantee that admitted requests meet their deadlines. Also, in a recent study, authors propose Amoeba [4], a system that allows tenants to define deadlines and guarantees that the specified deadlines are met, however, to admit new traffic, the proposed system has to modify the allocation of already admitted transfers. In this paper, we propose Rapid Close to Deadline Scheduling (RCD), a close to deadline traffic allocation technique that is fast and efficient. Through simulations, we show that RCD is up to 15 times faster than Amoeba, provides high link utilization along with deadline guarantees, and is able to make quick decisions on whether a new request can be fully satisfied before its deadline.

Design and Implement of Auto-Scaling System Based on Eucalyptus Cloud-Computing Platform

2012 ◽  
Vol 546-547 ◽  
pp. 1433-1438 ◽  
Author(s):  
Wei Wei Wang ◽  
Jing Li ◽  
Yuan Yuan Guo ◽  
Hu Song ◽  
Xin Chun Liu
Keyword(s):  
Cloud Computing ◽  
Service Level ◽  
Network Resources ◽  
Computing Platform ◽  
On Demand ◽  
Computing Services ◽  
Cloud Computing Services ◽  
Auto Scaling ◽  
Demand Service

On-demand service is one of the most important characteristics of cloud computing. Cloud-computing services should dynamically and timely deliver computing resources, storage resources and network resources etc. to consumers according to user needs, and service level should be able to meet quality of service. Users only need to pay on demand; otherwise they have to maintain sufficient resources just in order to meet peak requirements, which can be costly. In this paper, we present the design and implementation of Auto-Scaling system and illustrate its system architecture, components and scaling algorithm. Finally, we test the system and the results show that it can be capable of handling sudden load surges, delivering resources to users on demand, saving cost for users and improving resource utilization.

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