Placement for Intercommunicating Virtual Machines in Autoscaling Cloud Infrastructure
- 1 March 2021
- journal article
- research article
- Published by IGI Global in Journal of Organizational and End User Computing
- Vol. 33 (2), 17-35
- https://doi.org/10.4018/joeuc.20210301.oa2
Abstract
Due to pay-as-you-go style adopted by cloud datacenters (DC), modern day applications having intercommunicating tasks depend on DC for their computing power. Due to unpredictability of rate at which data arrives for immediate processing, application performance depends on autoscaling service of DC. Normal VM placement schemes place these tasks arbitrarily onto different physical machines (PM) leading to unwanted network traffic resulting in poor application performance and increases the DC operating cost. This paper formulates autoscaling and intercommunication aware task placements (AIATP) as an optimization problem, with additional constraints and proposes solution, which uses the placement knowledge of prior tasks of individual applications. When compared with well-known algorithms, CloudsimPlus-based simulation demonstrates that AIATP reduces the resource fragmentation (30%) and increases the resource utilization (18%) leading to minimal number of active PMs. AIATP places 90% tasks of an application together and thus reduces the number of VM migration (39%) while balancing the PMs.Keywords
This publication has 13 references indexed in Scilit:
- Secure integration of IoT and Cloud ComputingFuture Generation Computer Systems, 2018
- Compatibility-based static VM placement minimizing interferenceJournal of Network and Computer Applications, 2017
- Joint affinity aware grouping and virtual machine placementMicroprocessors and Microsystems, 2016
- PLAN: Joint Policy- and Network-Aware VM Management for Cloud Data CentersIEEE Transactions on Parallel and Distributed Systems, 2016
- A Survey on Resource Scheduling in Cloud Computing: Issues and ChallengesJournal of Grid Computing, 2016
- Virtual machine consolidated placement based on multi-objective biogeography-based optimizationFuture Generation Computer Systems, 2016
- Two-Phase Online Virtual Machine Placement in Heterogeneous Cloud Data CenterPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2015
- Resource management for Infrastructure as a Service (IaaS) in cloud computing: A surveyJournal of Network and Computer Applications, 2014
- Energy-aware resource allocation heuristics for efficient management of data centers for Cloud computingFuture Generation Computer Systems, 2012
- Effects of Various Flavonoids on the-Synuclein Fibrillation ProcessParkinson's Disease, 2010