A secure framework in brokerage of heterogeneous cloud environment for multiple cloud providers

2014 ◽  
Author(s):  
Vikas Pardesi ◽  
Aditya Khamparia ◽  
Narendra Kr Bagde
Keyword(s):  
Cloud Environment ◽  
Cloud Providers ◽  
Heterogeneous Cloud ◽  
Secure Framework

scholarly journals Self-healing trans-cloud applications

Computing ◽  
2021 ◽  
Author(s):  
Antonio Brogi ◽  
Jose Carrasco ◽  
Francisco Durán ◽  
Ernesto Pimentel ◽  
Jacopo Soldani
Keyword(s):  
Open Source ◽  
Cloud Services ◽  
Self Healing ◽  
Controlled Experiments ◽  
Fault Handling ◽  
Extensive Evaluation ◽  
Cloud Providers ◽  
Heterogeneous Cloud ◽  
Cloud Applications ◽  
Unstable States

AbstractTrans-cloud applications consist of multiple interacting components deployed across different cloud providers and at different service layers (IaaS and PaaS). In such complex deployment scenarios, fault handling and recovery need to deal with heterogeneous cloud offerings and to take into account inter-component dependencies. We propose a methodology for self-healing trans-cloud applications from failures occurring in application components or in the cloud services hosting them, both during deployment and while they are being operated. The proposed methodology enables reducing the time application components rely on faulted services, hence residing in “unstable” states where they can suddenly fail in cascade or exhibit erroneous behaviour. We also present an open-source prototype illustrating the feasibility of our proposal, which we have exploited to carry out an extensive evaluation based on controlled experiments and monkey testing.

Research on Energy-Saving Algorithms with Migration Energy Consumption in Heterogeneous Cloud Environment

2014 ◽  
Vol 986-987 ◽  
pp. 1383-1386
Author(s):  
Zhen Xing Yang ◽  
He Guo ◽  
Yu Long Yu ◽  
Yu Xin Wang
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Energy Saving ◽  
Large Scale ◽  
Electrical Energy ◽  
Cloud Environment ◽  
Migration Energy ◽  
Live Migration ◽  
Large Scale Data ◽  
Heterogeneous Cloud

Cloud computing is a new emerging paradigm which delivers an infrastructure, platform and software as services in a pay-as-you-go model. However, with the development of cloud computing, the large-scale data centers consume huge amounts of electrical energy resulting in high operational costs and environment problem. Nevertheless, existing energy-saving algorithms based on live migration don’t consider the migration energy consumption, and most of which are designed for homogeneous cloud environment. In this paper, we take the first step to model energy consumption in heterogeneous cloud environment with migration energy consumption. Based on this energy model, we design energy-saving Best fit decreasing (ESBFD) algorithm and energy-saving first fit decreasing (ESFFD) algorithm. We further provide results of several experiments using traces from PlanetLab in CloudSim. The experiments show that the proposed algorithms can effectively reduce the energy consumption of data center in the heterogeneous cloud environment compared to existing algorithms like NEA, DVFS, ST (Single Threshold) and DT (Double Threshold).

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