TY - JOUR
T1 - Elastic Load Balancing for Dynamic Virtual Machine Reconfiguration Based on Vertical and Horizontal Scaling
AU - Sotiriadis, Stelios
AU - Bessis, Nik
AU - Amza, Cristiana
AU - Buyya, Rajkumar
PY - 2019/3/1
Y1 - 2019/3/1
N2 - Today, cloud computing applications are rapidly constructed by services belonging to different cloud providers and service owners. This work presents the inter-cloud elasticity framework, which focuses on cloud load balancing based on dynamic virtual machine reconfiguration when variations on load or on user requests volume are observed. We design a dynamic reconfiguration system, called inter-cloud load balancer (ICLB), that allows scaling up or down the virtual resources (thus providing automatized elasticity), by eliminating service downtimes and communication failures. It includes an inter-cloud load balancer for distributing incoming user HTTP traffic across multiple instances of inter-cloud applications and services and we perform dynamic reconfiguration of resources according to the real time requirements. The experimental analysis includes different topologies by showing how real-time traffic variation (using real world workloads) affects resource utilization and by achieving better resource usage in inter-cloud.
AB - Today, cloud computing applications are rapidly constructed by services belonging to different cloud providers and service owners. This work presents the inter-cloud elasticity framework, which focuses on cloud load balancing based on dynamic virtual machine reconfiguration when variations on load or on user requests volume are observed. We design a dynamic reconfiguration system, called inter-cloud load balancer (ICLB), that allows scaling up or down the virtual resources (thus providing automatized elasticity), by eliminating service downtimes and communication failures. It includes an inter-cloud load balancer for distributing incoming user HTTP traffic across multiple instances of inter-cloud applications and services and we perform dynamic reconfiguration of resources according to the real time requirements. The experimental analysis includes different topologies by showing how real-time traffic variation (using real world workloads) affects resource utilization and by achieving better resource usage in inter-cloud.
KW - Cloud computing
KW - cloud elasticity
KW - horizontal scalability
KW - vertical scalability
KW - cloud load balancing
UR - http://www.scopus.com/inward/record.url?scp=85064274344&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85064274344&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/8ba91bd3-f00a-36d7-b49d-21bcbfe4e121/
U2 - 10.1109/TSC.2016.2634024
DO - 10.1109/TSC.2016.2634024
M3 - Article (journal)
SN - 1939-1374
VL - 12
SP - 319
EP - 334
JO - IEEE Transactions on Services Computing
JF - IEEE Transactions on Services Computing
IS - 2
M1 - 7762944
ER -