Exploring cost-efficient bundling in a multi-cloud environment

Chatzithanasis, Georgios; Filiopoulou, Evangelia; Michalakelis, Christos; Nikolaidou, Maria

doi:10.1016/j.simpat.2021.102338

Cited by 15 publications

(9 citation statements)

References 6 publications

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“…Software components need to be context aware partitioned, so that they are aware of the characteristics of cloud resources where they can be deployed. NFRs optimization (cost, latency, performance), components synchronization, and data consistency are the challenges identified here [61,67,102,103]. Furthermore, the utilization of more than one target deployment resource types requires a cloud agnostic design of software systems [48] and specific programming models and application architectures so that essential characteristics like scalability can be acquired at application level [45].…”

Section: Design and Developmentmentioning

confidence: 99%

Understanding the challenges and novel architectural models of multi-cloud native applications – a systematic literature review

et al. 2023

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The evolution of Cloud Computing into a service utility, along with the pervasive adoption of the IoT paradigm, has promoted a significant growth in the need of computational and storage services. The traditional use of cloud services, focused on the consumption of one provider, is not valid anymore due to different shortcomings being the risk of vendor lock-in a critical. We are assisting to a change of paradigm, from the usage of a single cloud provider to the combination of multiple cloud service types, affecting the way in which applications are designed, developed, deployed and operated over such heterogeneous ecosystems. The result is an effective heterogeneity of architectures, methods, tools, and frameworks, copying with the multi-cloud application concept. The goal of this study is manifold. Firstly, it aims to characterize the multi-cloud concept from the application development perspective by reviewing existing definitions of multi-cloud native applications in the literature. Secondly, we set up the basis for the architectural characterization of these kind of applications. Finally, we highlight several open research issues drawn up from the analysis carried out. To achieve that, we have conducted a systematic literature review (SLR), where, a large set of primary studies published between 2011 and 2021 have been studied and classified. The in-depth analysis has revealed five main research trends for the improvement of the development and operation DevOps lifecycle of “multi-cloud native applications”. The paper finishes with directions for future work and research challenges to be addressed by the software community.

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Section: Design and Developmentmentioning

confidence: 99%

Understanding the challenges and novel architectural models of multi-cloud native applications – a systematic literature review

et al. 2023

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“…The proposed advantages of multi-over single-sourced cloud are manifold [8, p. 6]. Amongst others they comprise reduction of vendor lock-in, cost optimization [11], load balancing and business continuity through partial redundancy, enabling best-of-breed service selection, and even increased security through diversification of data storage and processing [12]. On higher organizational levels it is argued that multi-cloud strategies foster innovation capabilities and agility, e.g., for data analytics [13].…”

Section: Multi-cloud Strategy and Changing It Work Organizationmentioning

confidence: 99%

Planning Distributed Security Operations Centers in Multi-Cloud Landscapes A Systematic Approach, Generalized from A Case Study

Schmidt¹,

Knudsen²,

Niehoff³

et al. 2023

Preprint

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We present a case study on the strategic planning of a security operations center in a typical, modern, mid-size organization. Against the backdrop of the company’s multi-cloud strategy a distributed approach envisioning the involvement of external providers is taken. From a security-centric abstraction of the organizational IT-landscape, a novel strategic planning method for security operation centers is developed with an adaptable relationship matrix as core tool. The method is put to a practical test in modeling different levels of engagement of external providers in the center’s operation. It is shown that concrete output, such as a core statement of work for an external provider, can easily be derived.

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“…(1) for each host in active state acth i ∈ ACTH then do (2) for each VM actv ij ∈ acth i then do (3) if actv ij in idle state then (4) Deallocate actv ij resources to acth i (5) end if loop (6) end for loop (7) end if loop (5) end for loop (6) StatusofVM � 0 (7) for each host in active state acth i ∈ ACTH from acth k to acth 1 then do (8) for each VM actv ij ∈ acth i then do (9) if migration of actv ij to ACTH-acth i then (10) StatusofVM � StatusofVM + 1 (11) migration ij ← Host ID which is being targeted (12) end if loop (13) end for loop (14) if StatusofVM � j − 1 then (15) migrate all VMs using migration ij (16)…”

Section: Computational Intelligence and Neurosciencementioning

confidence: 99%

“…Because of resource restrictions, on-demand workloads are shifted to other data centers on a regular basis. As a result, workload scheduling in a heterogeneous multicloud environment is a hot topic and a challenging undertaking due to the wide variety of cloud resources available [4][5][6][7]. Cloud workloads are planned using VMs, which are assigned based on the amount of tra c and requests.…”

Section: Introductionmentioning

confidence: 99%

An Energy-Efficient Strategy and Secure VM Placement Algorithm in Cloud Computing

Srivastava

Tiwari

Srivastava

et al. 2022

Computational Intelligence and Neuroscience

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One of the important and challenging tasks in cloud computing is to obtain the usefulness of cloud by implementing several specifications for our needs, to meet the present growing demands, and to minimize energy consumption as much as possible and ensure proper utilization of computing resources. An excellent mapping scheme has been derived which maps virtual machines (VMs) to physical machines (PMs), which is also known as virtual machine (VM) placement, and this needs to be implemented. The tremendous diversity of computing resources, tasks, and virtualization processes in the cloud causes the consolidation method to be more complex, tedious, and problematic. An algorithm for reducing energy use and resource allocation is proposed for implementation in this article. This algorithm was developed with the help of a Cloud System Model, which enables mapping between VMs and PMs and among tasks of VMs. The methodology used in this algorithm also supports lowering the number of PMs that are in an active state and optimizes the total time taken to process a set of tasks (also known as makespan time). Using the CloudSim Simulator tool, we evaluated and assessed the energy consumption and makespan time. The results are compiled and then compared graphically with respect to other existing energy-efficient VM placement algorithms.

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Exploring cost-efficient bundling in a multi-cloud environment

Cited by 15 publications

References 6 publications

Understanding the challenges and novel architectural models of multi-cloud native applications – a systematic literature review

Understanding the challenges and novel architectural models of multi-cloud native applications – a systematic literature review

Planning Distributed Security Operations Centers in Multi-Cloud Landscapes A Systematic Approach, Generalized from A Case Study

An Energy-Efficient Strategy and Secure VM Placement Algorithm in Cloud Computing

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