Cloud Federations

2016 ◽  
pp. 1-41 ◽  
Author(s):  
Marcio R. M. Assis ◽  
Luiz Fernando Bittencourt ◽  
Rafael Tolosana-Calasanz ◽  
Craig A. Lee
Keyword(s):  
Cloud Computing ◽  
Scientific Community ◽  
Quality Of Services ◽  
Cloud Federation ◽  
Cloud Providers ◽  
Multiple Clouds ◽  
Lock In

With the maturation of the Cloud Computing, the eyes of the scientific community and specialized commercial institutions have turned to research related to the use of multiple clouds. The main reason for this interest is the limitations that many cloud providers individually face to meet all the inherent characteristics of this paradigm. Therefore, using multiple cloud organizations opens the opportunity for the providers to consume resources with more attractive prices, increase the resilience as well as to monetize their own idle resources. When considering customers, problems as interruption of services, lack of interoperability that lead to lock-in and loss of quality of services due to locality are presented as limiting to the adoption of Cloud Computing. This chapter presents an introduction to conceptual characterization of Cloud Federation. Moreover, it presents the challenges in implementing federation architectures, requirements for the development of this type of organization and the relevant architecture proposals.

About Fully Homomorphic Encryption Improvement Techniques

2019 ◽  
Vol 10 (3) ◽  
pp. 1-20
Author(s):  
Ahmed El-Yahyaoui ◽  
Mohamed Daifr Ech-Cherif El Kettani
Keyword(s):  
Cloud Computing ◽  
Homomorphic Encryption ◽  
Quality Of Services ◽  
End User ◽  
Fully Homomorphic Encryption ◽  
Encrypted Data ◽  
Cloud Server ◽  
Encryption Schemes ◽  
Multiple Clients

Fully homomorphic encryption schemes (FHE) are a type of encryption algorithm dedicated to data security in cloud computing. It allows for performing computations over ciphertext. In addition to this characteristic, a verifiable FHE scheme has the capacity to allow an end user to verify the correctness of the computations done by a cloud server on his encrypted data. Since FHE schemes are known to be greedy in term of processing consumption and slow in terms of runtime execution, it is very useful to look for improvement techniques and tools to improve FHE performance. Parallelizing computations is among the best tools one can use for FHE improvement. Batching is a kind of parallelization of computations when applied to an FHE scheme, it gives it the capacity of encrypting and homomorphically processing a vector of plaintexts as a single ciphertext. This is used in the context of cloud computing to perform a known function on several ciphertexts for multiple clients at the same time. The advantage here is in optimizing resources on the cloud side and improving the quality of services provided by the cloud computing. In this article, the authors will present a detailed survey of different FHE improvement techniques in the literature and apply the batching technique to a promising verifiable FHE (VFHE) recently presented by the authors at the WINCOM17 conference.

scholarly journals Efficient and Optimal Service Component Distribution across Multiple Clouds

2018 ◽  
Vol 6 (3) ◽  
pp. 44 ◽  
Author(s):  
Driss Riane ◽  
Ahmed Ettalbi
Keyword(s):  
Cloud Services ◽  
Main Step ◽  
Service Component ◽  
Component Distribution ◽  
Cloud Broker ◽  
Optimal Service ◽  
Multiple Clouds ◽  
Lock In ◽  
Better Than

<span class="fontstyle0">Cloud computing technology is one of the key considerations for business willing to access to different cloud services over the Internet and to benefit from the diversity of IaaS offers and pricing models. Although several solutions are available in the market, there are still some issues to solve. The main important aspect to address is the user’s request complexity, the vendor lock-in risk and the SLA fulfillment. In this paper, we propose a Multi-Cloud Broker called MCB that allows an efficient and optimal service component distribution among different clouds in flexible and dynamic infrastructure provisioning environment, in order to achieve better Quality of Service and cost efficiency. The request partitioning is the main step of our approach, this step is performed using Gomory-Hu tree based algorithm. Our simulation results show how our algorithm is better than existing partitioning algorithms in terms of running time.</span>

scholarly journals Load Balancing Technique with an Efficient Method

2019 ◽  
Vol 8 (6) ◽  
pp. 1257-1262
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Efficient Method ◽  
Load Balance ◽  
Completion Time ◽  
Scheduling Algorithm ◽  
Quality Of Services ◽  
Huge Number ◽  
Task Scheduling Algorithm

There are a huge number of nodes connected to web computing to offer various types of web services to provide cloud clients. Limited numbers of nodes connected to cloud computing have to execute more than a thousand or a million tasks at the same time. So it is not so simple to execute all tasks at the same particular time. Some nodes execute all tasks, so there is a need to balance all the tasks or loads at a time. Load balance minimizes the completion time and executes all the tasks in a particular way.There is no possibility to keep an equal number of servers in cloud computing to execute an equal number of tasks. Tasks that are to be performed in cloud computing would be more than the connected servers. Limited servers have to perform a great number of tasks.We propose a task scheduling algorithm where few nodes perform the jobs, where jobs are more than the nodes and balance all loads to the available nodes to make the best use of the quality of services with load balancing.

scholarly journals Green Metascheduler Architecture to Provide QoS in Cloud Computing

2015 ◽  
Author(s):  
Osvaldo Adilson De Carvalho Junior ◽  
Sarita Mazzini Bruschi ◽  
Regina Helena Carlucci Santana ◽  
Marcos José Santana
Keyword(s):  
Cloud Computing ◽  
Quality Of Service ◽  
Energy Consumption ◽  
Response Time ◽  
Large Scale ◽  
Quality Of Services ◽  
Average Response ◽  
Average Response Time ◽  
Private Cloud

The aim of this paper is to propose and evaluate GreenMACC (Green Metascheduler Architecture to Provide QoS in Cloud Computing), an extension of the MACC architecture (Metascheduler Architecture to provide QoS in Cloud Computing) which uses greenIT techniques to provide Quality of Service. The paper provides an evaluation of the performance of the policies in the four stages of scheduling focused on energy consumption and average response time. The results presented confirm the consistency of the proposal as it controls energy consumption and the quality of services requested by different users of a large-scale private cloud.

Quality of Services and Optimal Management of Cloud Centers with Different Arrival Modes

2014 ◽  
pp. 185-198
Author(s):  
V. Goswami ◽  
S. S. Patra ◽  
G. B. Mund
Keyword(s):  
Cloud Computing ◽  
Virtual Machines ◽  
Service Level Agreement ◽  
Service Level ◽  
Quality Of Services ◽  
Finite Buffer ◽  
Optimal Management ◽  
It Industry ◽  
Computing Paradigm

In Cloud Computing, the virtualization of IT infrastructure enables consolidation and pooling of IT resources so they are shared over diverse applications to offset the limitation of shrinking resources and growing business needs. Cloud Computing is a way to increase the capacity or add capabilities dynamically without investing in new infrastructure, training new personnel, or licensing new software. It extends Information Technology's existing capabilities. In the last few years, cloud computing has grown from being a promising business concept to one of the fast growing segments of the IT industry. For the commercial success of this new computing paradigm, the ability to deliver guaranteed Quality of Services is crucial. Based on the Service Level Agreement, the requests are processed in the cloud centers in different modes. This chapter deals with Quality of Services and optimal management of cloud centers with different arrival modes. For this purpose, the authors consider a finite-buffer multi-server queuing system where client requests have different arrival modes. It is assumed that each arrival mode is serviced by one or more virtual machines, and different modes have equal probabilities of receiving services. Various performance measures are obtained and optimal cost policy is presented with numerical results. A genetic algorithm is employed to search optimal values of various parameters for the system.

Toward Cloud Federation

2012 ◽  
pp. 1-17 ◽  
Author(s):  
Antonio Celesti ◽  
Francesco Tusa ◽  
Massimo Villari
Keyword(s):  
Cloud Computing ◽  
Scientific Community ◽  
Early Stage ◽  
The Internet ◽  
The World ◽  
Cloud Federation ◽  
The Future ◽  
Future Challenges

Federation in cloud computing is an emerging topic. Currently, all over the world in both academia and industry contexts many operators are picking up the advantages of cloud computing and federation in planning the Internet of the future. Nevertheless, cloud federation is at the early stage, and the scientific community is not fully aware how the federation will impact the cloud computing scenario. In this chapter, the authors try to clarify the ideas and discuss the main future challenges regarding cloud federation.

scholarly journals A Decentralized Virtual Machine Migration Approach of Data Centers for Cloud Computing

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaoying Wang ◽  
Xiaojing Liu ◽  
Lihua Fan ◽  
Xuhan Jia
Keyword(s):  
Cloud Computing ◽  
Virtual Machine ◽  
Large Scale ◽  
Data Centers ◽  
Virtual Machines ◽  
Quality Of Services ◽  
Virtual Machine Migration ◽  
Power Models ◽  
Key Steps

As cloud computing offers services to lots of users worldwide, pervasive applications from customers are hosted by large-scale data centers. Upon such platforms, virtualization technology is employed to multiplex the underlying physical resources. Since the incoming loads of different application vary significantly, it is important and critical to manage the placement and resource allocation schemes of the virtual machines (VMs) in order to guarantee the quality of services. In this paper, we propose a decentralized virtual machine migration approach inside the data centers for cloud computing environments. The system models and power models are defined and described first. Then, we present the key steps of the decentralized mechanism, including the establishment of load vectors, load information collection, VM selection, and destination determination. A two-threshold decentralized migration algorithm is implemented to further save the energy consumption as well as keeping the quality of services. By examining the effect of our approach by performance evaluation experiments, the thresholds and other factors are analyzed and discussed. The results illustrate that the proposed approach can efficiently balance the loads across different physical nodes and also can lead to less power consumption of the entire system holistically.

scholarly journals An Efficient Adaptive Load Balancing Algorithm for Cloud Computing Under Bursty Workloads

2015 ◽  
Vol 5 (3) ◽  
pp. 795-800 ◽  
Author(s):  
S. F. Issawi ◽  
A. Al Halees ◽  
M. Radi
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Quality Of Services ◽  
Average Response ◽  
Average Response Time ◽  
It Industry ◽  
Request Rate ◽  
Wide Range ◽  
Load Balancing Algorithm

Cloud computing is a recent, emerging technology in the IT industry. It is an evolution of previous models such as grid computing. It enables a wide range of users to access a large sharing pool of resources over the internet. In such complex system, there is a tremendous need for an efficient load balancing scheme in order to satisfy peak user demands and provide high quality of services. One of the challenging problems that degrade the performance of a load balancing process is bursty workloads. Although there are a lot of researches proposing different load balancing algorithms, most of them neglect the problem of bursty workloads. Motivated by this problem, this paper proposes a new burstness-aware load balancing algorithm which can adapt to the variation in the request rate by adopting two load balancing algorithms: RR in burst and Random in non-burst state. Fuzzy logic is used in order to assign the received request to a balanced VM. The algorithm has been evaluated and compared with other algorithms using Cloud Analyst simulator.  Results show that the proposed algorithm improves the average response time and average processing time in comparison with other algorithms.

scholarly journals A HYBRID ALGORITHM FOR CLOUD DATA SECURITY USING MD5 AND ABE

2016 ◽  
Vol 3 (3) ◽  
Author(s):  
Umesh Joshi ◽  
Prof. Anurag Jain
Keyword(s):  
Cloud Computing ◽  
Data Security ◽  
Hybrid Algorithm ◽  
Quality Of Services ◽  
Cloud Data ◽  
Computing Model ◽  
Current Scenario ◽  
Cloud Network ◽  
Hashing Function

The evolution of IT technology Cloud computing shows the strength in past year. It takes controls in all three services Saas, Paas and Iaas. But with gradual increment of technology the quality of services also main issues. Services should be accurate up to date and secure. The level of approval for any computing model is calculated by its strength quality and weakness. The current note is focusing on the security of data in Cloud network, it calculate the current scenario and proposed the Hybrid Secure solution. The paper provides the idea implementation to secure the data in cloud. It provides the hybrid secure solution which combine attribute based cryptography with hashing function MD5. It implements the idea on Cloudsim and provides the improved result in tested environment.

scholarly journals W_SR: A QoS Based Ranking Approach for Cloud Computing Service

2014 ◽  
Vol 3 (2) ◽  
pp. 55-62 ◽  
Author(s):  
Arezoo Jahani ◽  
Leyli Mohammad Khanli ◽  
Seyed Naser Razavi
Keyword(s):  
Cloud Computing ◽  
Service Providers ◽  
Cloud Service ◽  
Quality Of Services ◽  
Computing Model ◽  
Cloud Computing Service ◽  
The World ◽  
Service Ranking ◽  
S Application

Cloud computing is a kind of computing model that promise accessing to information resources in request time and subscription basis. In this environment, there are different type of user’s application with different requirements. In addition, there are different cloud Service providers which present spate services with various qualitative traits. Therefore determining the best cloud computing service for users with specific applications is a serious problem. Service ranking system compares the different services based on quality of services (QoS), in order to select the most appropriate service. In this paper, we propose a W_SR (Weight Service Rank) approach for cloud service ranking that uses from QoS features. Comprehensive experiments are conducted employing real-world QoS dataset, including more than 2500 web services over the world. The experimental results show that execution time of our approach is less than other approaches and it is more flexible and scalable than the others with increase in services or users.

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