A comprehensive survey for scheduling techniques in cloud computing
Resource scheduling becomes the prominent issue in cloud computing due to rapid growth
of on demand request and heterogeneous nature of cloud resources. Cloud provides …
of on demand request and heterogeneous nature of cloud resources. Cloud provides …
Elasticity in cloud computing: state of the art and research challenges
Elasticity is a fundamental property in cloud computing that has recently witnessed major
developments. This article reviews both classical and recent elasticity solutions and …
developments. This article reviews both classical and recent elasticity solutions and …
Scheduling Internet of Things requests to minimize latency in hybrid Fog–Cloud computing
Delivering services for Internet of Things (IoT) applications that demand real-time and
predictable latency is a challenge. Several IoT applications require stringent latency …
predictable latency is a challenge. Several IoT applications require stringent latency …
Drl-based deadline-driven advance reservation allocation in eons for cloud–edge computing
The ongoing roll-out of cloud–edge computing and Internet of Things (IoT) has been
simulating the boom of new advance reservation (AR) services, such as bulk-data migration …
simulating the boom of new advance reservation (AR) services, such as bulk-data migration …
Optimized task scheduling for cost-latency trade-off in mobile fog computing using fuzzy analytical hierarchy process
Abstract Mobile Fog Computing (MFC) paradigm can be integrated as a unit called as Multi-
Access Edge Computing (MFC) in a fifth-generation (5G) network. There are extensive …
Access Edge Computing (MFC) in a fifth-generation (5G) network. There are extensive …
Deadline constrained based dynamic load balancing algorithm with elasticity in cloud environment
M Kumar, SC Sharma - Computers & Electrical Engineering, 2018 - Elsevier
The most challenging problem for a cloud service provider is maintaining the quality of
service parameters like reliability, elasticity, kee** the deadline and minimizing the …
service parameters like reliability, elasticity, kee** the deadline and minimizing the …
[HTML][HTML] Solving multi-objective facility location problem using the fuzzy analytical hierarchy process and goal programming: a case study on infectious waste disposal …
N Wichapa, P Khokhajaikiat - Operations Research Perspectives, 2017 - Elsevier
The selection of a suitable location for infectious waste disposal is one of the major
problems in waste management. Determining the location of infectious waste disposal …
problems in waste management. Determining the location of infectious waste disposal …
Application of artificial intelligence in college dance teaching and its performance analysis
Y Wang, G Zheng - … Journal of Emerging Technologies in Learning …, 2020 - learntechlib.org
Artificial intelligence (AI) has not been widely and deeply implemented in dance teaching of
colleges. To solve the problem, this paper identifies the problems with the AI in college …
colleges. To solve the problem, this paper identifies the problems with the AI in college …
Machine learning techniques in optical networks: a systematic map** study
During the last decade, optical networks have become “smart networks”. Software-defined
networks, software-defined optical networks, and elastic optical networks are some …
networks, software-defined optical networks, and elastic optical networks are some …
Analyzing critical success factors for sustainable cloud-based mobile learning (CBML) in crisp and fuzzy environment
Mobile Learning (M-Learning), driven by technological digital advancement, is one of the
essential formats of online learning, providing flexibility to learners. Cloud-based mobile …
essential formats of online learning, providing flexibility to learners. Cloud-based mobile …