scholarly journals H-FFMRA: A Multi Resource Fully Fair Resources Allocation Algorithm in Heterogeneous Cloud Computing

2021 ◽  
Author(s):  
Hamed Hamzeh ◽  
Sofia Meacham ◽  
Kashaf Khan ◽  
Angelos Stefanidis ◽  
Keith Phalp
Keyword(s):  
Cloud Computing ◽  
Resources Allocation ◽  
Allocation Algorithm ◽  
Heterogeneous Cloud

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).

Towards AiP as a Service

2015 ◽  
Vol 7 (2) ◽  
pp. 1-17 ◽  
Author(s):  
Djamel Benmerzoug
Keyword(s):  
Cloud Computing ◽  
Business Processes ◽  
Rapid Development ◽  
Cloud Services ◽  
Agent Based ◽  
Software Artifacts ◽  
Cloud Application ◽  
Business Application ◽  
Agent Interaction ◽  
Heterogeneous Cloud

The challenges that Cloud computing poses to business processes integration, emphasize the need for addressing two major issues: (i) which integration approach should be used allowing an adequate description of interaction aspects of the composed software components ? (ii) how are these interaction descriptions stored and shared to allow other software artifacts to (re)use them ? To address these issues, in this paper the authors propose an Agent Interaction Protocols (AiP)-based approach for reusing and aggregating existing Cloud services to create a new desired business application. The proposed approach facilitates rapid development and provisioning of composite Cloud services by specifying what to compose as an AiP. Furthermore, the authors develop an agent-based architecture that supports flexible scaling of business processes in a virtualized Cloud computing environment. The main goal of the proposed architecture is to address and tackle interoperability challenges at the Cloud application level. It solves the interoperability issues between heterogeneous Cloud services environments by offering a harmonized API. Also, it enables the deployment of applications at public, private or hybrid multi-Cloud environments.

scholarly journals Heterogeneous Cloud Radio Access Networks: Enhanced Time Allocation for Interference Mitigation

2018 ◽  
Vol 2018 ◽  
pp. 1-17
Author(s):  
Imad Al-Samman ◽  
Reham Almesaeed ◽  
Angela Doufexi ◽  
Mark Beach
Keyword(s):  
Cloud Computing ◽  
Resource Sharing ◽  
Interference Mitigation ◽  
Base Station ◽  
Small Cell ◽  
Access Networks ◽  
Cloud Radio Access Networks ◽  
Radio Access Networks ◽  
Radio Access ◽  
Heterogeneous Cloud

Responding to the unprecedented challenges imposed by the 5G technologies, mobile operators have given significant attention to Heterogeneous Cloud Radio Access Networks (H-CRAN) due to their beneficial features of performing optimization, cost effectiveness, and improving spectral and energy efficiency performance. H-CRAN inherits the attractive benefits of Heterogeneous Networks (HetNet) and the cloud computing by facilitating interference mitigation, scalability, and radio resource control. Consequently, H-CRAN is proposed in this article as a cost-effective potential solution to alleviate intertier interference and improve cooperative processing gains in HetNets by employing cloud computing. H-CRAN can provide efficient resource sharing at the spectrum, network, and infrastructure levels. Therefore, this article proposes H-CRAN cooperative interference mitigation method that enhances the time sharing among Radio Remote Heads (RRH) users. The study proposes an enhanced Almost Blank Subframe (ABSF) technique to increase the SINR and throughput of the small-cell (low power base station) and macrocell users. Simulation results show that the proposed Dynamic Programming-Diverse Almost Blank Subframe (ABSF) Pattern (DP-DAP) scheme improved the macro- and small-cell users up to 56% and 35%, respectively, as compared to other state-of-the-art ABSF schemes.

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