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Hybrid Workflow Scheduling on Edge Cloud Computing Systems

Raed Alsurdeh, Rodrigo N. Calheiros, Kenan M. Matawie, Bahman Javadi
2021 IEEE Access  
scheduling technique for hybrid workflows on heterogeneous edge cloud resources.  ...  In this work, we propose an end-to-end hybrid workflow scheduling on an edge cloud system as a two-stage framework.  ...  However, latency is a bottleneck for running stream applications on cloud systems.  ... 
doi:10.1109/access.2021.3116716 fatcat:4n73d2x7cbdepalalfjugesqbu

Scheduling Algorithms for Efficient Execution of Stream Workflow Applications in Multicloud Environments [article]

Mutaz Barika, Saurabh Garg, Andrew Chan, Rodrigo N. Calheiros
2019 arXiv   pre-print
As a consequence, the execution of these applications on cloud environments requires advanced scheduling techniques that adhere to end user's requirements in terms of data processing and deadline for decision  ...  In this paper, we propose two Multicloud scheduling and resource allocation techniques for efficient execution of stream workflow applications on Multicloud environments while adhering to workflow application  ...  Rajkumar Buyya for the insightful comments and suggestions in improving paper quality. This research is supported by an Australian Government Research Training Program (RTP) Scholarship.  ... 
arXiv:1912.08392v1 fatcat:hlvf46sjzbhsvnkf7bvsu6zrwu

Adaptive Scheduling for Efficient Execution of Dynamic Stream Workflows [article]

Mutaz Barika, Saurabh Garg, Rajiv Ranjan
2019 arXiv   pre-print
While for the latter requirement, dynamic scheduling technique not only need to adhere to end user's requirements in terms of data processing and deadline for decision making, and data stream sources location  ...  Therefore, we propose a two-phase adaptive scheduling technique to efficiently schedule dynamic workflow application in Multicloud environment that can respond to changes in the velocity of data at runtime  ...  For scheduling techniques supported with big data application orchestrators, each one of them uses a different scheduling technique to map applications on cloud resources.  ... 
arXiv:1912.08397v1 fatcat:dbs4fokiajeavgz3kbt2hdybiq

Taxonomy and issues for antifragile-based multimedia cloud computing

Syed Fawad Haider, Laraib Abbas, Amjad Ali, Muddesar Iqbal, Imran Raza, Syed Asad Hussain, Doug Young Suh
2016 Journal of Reliable Intelligent Environments  
MCC is proven to be a most dynamic and efficient platform for managing a large amount of multimedia contents with maximum deployment of computing and processing resources at the service provider instead  ...  Cloud computing has become one of the most dynamic and adoptable computing paradigms. Multimedia Cloud Computing (MCC) is one of today's hot research topic.  ...  Therefore, more efficient ways need to be explored to enhance the system overall performance. (11) Workload scheduling: Workload scheduling technique which is mainly based on a greedy algorithm is also  ... 
doi:10.1007/s40860-016-0017-7 fatcat:lhxknk32hff6vkoduzq7meydee

Study of Load Optimization and Performance Issues in Cloud

Madhina D Banu, Aranganathan Aranganathan
2018 Indonesian Journal of Electrical Engineering and Computer Science  
The research study is also planning to find out an effective solution for traffic, data congestion and media streaming issues in a cloud environment.  ...  To optimize the load, the existing load optimization approach is properly utilized federation mechanisms, which offers physical resources based on demand to maintain the cloud application efficiency.  ...  A dynamic Energy-Efficient Migration and Consolidation Algorithm [6] A dynamic energy-efficient migration and consolidation algorithm are developed for replacing the CPU twice threshold methodology to  ... 
doi:10.11591/ijeecs.v11.i3.pp1035-1041 fatcat:il2b7qdsmzfzve5qkhhuxlkdmu

2020 Index IEEE Transactions on Parallel and Distributed Systems Vol. 31

2021 IEEE Transactions on Parallel and Distributed Systems  
., +, TPDS Feb. 2019 445-458 Distributed processing A Holistic Energy-Efficient Real-Time Scheduler for Mixed Stream and Batch Processing Workloads.  ...  ., +, TPDS July 2019 1494-1511 Efficient Operator Placement for Distributed Data Stream Processing Applications.  ... 
doi:10.1109/tpds.2020.3033655 fatcat:cpeatdjlpzhqdersvsk5nmzjkm

Efficient deadline-aware scheduling for the analysis of Big Data streams in public Cloud

Mahmood Mortazavi-Dehkordi, Kamran Zamanifar
2019 Cluster Computing  
Open source distributed stream processing platforms have gained popularity for analyzing streaming Big Data as they provide low latency required for streaming Big Data applications using Cloud resources  ...  This study, therefore, presents BCframework, an efficient deadline-aware scheduling framework used by streaming Big Data analysis applications based on public Cloud resources.  ...  Furthermore, BCframework adapts the algorithm presented in [33] which proposed a deadline and cost aware algorithms for provisioning and scheduling using critical path idea for applications which are  ... 
doi:10.1007/s10586-019-02908-2 fatcat:7g3eufmifrdyfe4kgxum3czknq

Resource Management and Scheduling for Big Data Applications in Cloud Computing Environments [article]

Muhammed Tawfiqul Islam, Rajkumar Buyya
2018 arXiv   pre-print
It will provide an in-depth knowledge on resource management techniques involved while deploying big data processing systems on cloud environment.  ...  It covers the state-of-art practices and researches done in SLA-based resource management with a specific focus on the job scheduling mechanisms.  ...  Cost-efficient Scheduling The monetary cost of running a big data processing cluster in a cloud environment is crucial.  ... 
arXiv:1812.00563v2 fatcat:nidspd4n2vaftdw65pzjiwoxuu

Reactive Monitoring Adaptation for Dynamic Dataflow on Variable Infrastructure

Chethana R M, Megha G S, Gavina C G, Veeranna Kotagi
2020 Zenodo  
Among these according to the user requirements scheduling the resource is very challenging in cloud environment indeed for the low latency over high velocity data streams.  ...  The important and key concept of the clouds is sharing their resources on many different nodes that are making beneficial for any application.  ...  When a client request for efficient resource by sending through cloud server on cloud server on line 3.  ... 
doi:10.5281/zenodo.3749470 fatcat:4vmhiswr5bfibmpcjonpba6uyi

A Cost Effective Scalable Schemefor Dynamic DataService inHeterogeneous Cloud Environment

Drleo John
2020 Figshare  
This paper proposed a new architectural framework to reduce the communication overhead, substantial switching cost and avoid lock-in dependency for the customers who uses the cloud services.  ...  the cloud.  ...  Optimization based algorithm is proposed [16] for efficient task scheduling using particle swarm optimization (PSO) in cloud computing environment.  ... 
doi:10.6084/m9.figshare.11853501.v1 fatcat:vnhhqszy65ec5kghull77a3mka

A Sophisticated Job Scheduling Approach to Minimize the Time Consumption at Computational Cloud

Jyoti Verma, Heena Gulati, Harish Kundra
2014 International Journal of Computer Applications  
This paper focuses on the creation of a sophisticated job scheduling approach consisted of time constrain algorithms and grouping based algorithm.  ...  Although the cloud servers are fast in comparison to the other platforms of servers but still a good scheduling algorithm would enhance the performance of the job execution.  ...  It is a platform that is the basic structure on which the application stands. Through cloud computing web is becoming the platform.  ... 
doi:10.5120/15535-4076 fatcat:35jvdoemcnccro632alamgwhsq

Scheduling Continuous Operators for IoT Edge Analytics

Patient Ntumba, Nikolaos Georgantas, Vassilis Christophides
2021 Proceedings of the 4th International Workshop on Edge Systems, Analytics and Networking  
Then, we propose scheduling algorithms RCS and SOO-CPLEX for placing continuous operators for data stream analytics at the network edge.  ...  Given the limitations of Fog in terms of limited computational resources that can also be shared among multiple analytics with continuous operators over data streams, we introduce a holistic cost model  ...  to the Cloud, this is to ensure that the scheduling algorithm does not alter the semantic of a DSPA application.  ... 
doi:10.1145/3434770.3459738 fatcat:svcs3igsxjanjpzvsjsynwbkki

A spatiotemporal compression based approach for efficient big data processing on Cloud

Chi Yang, Xuyun Zhang, Changmin Zhong, Chang Liu, Jian Pei, Kotagiri Ramamohanarao, Jinjun Chen
2014 Journal of computer and system sciences (Print)  
A novel data driven scheduling is also developed for data processing optimisation.  ...  To tackle the challenges, we propose a novel technique for effectively processing big graph data on Cloud. Specifically, the big data will be compressed with its spatiotemporal features on Cloud.  ...  We aim to prove that under most of applications, our algorithm can achieve efficient big data processing on Cloud without losing acceptable accuracy for most of applications.  ... 
doi:10.1016/j.jcss.2014.04.022 fatcat:yksb3x2gerbchewchyh722nhka

A Review on Scheduling in Cloud Computing

Sujitha A, Gunasekar K
2016 International Journal of UbiComp  
Cloud computing is the requirement based on clients that this computing which provides software, infrastructure and platform as a service as per pay for use norm.  ...  The survey gives an elaborate idea about grid, cloud, workflow scheduling to minimize the energy cost, efficiency and throughput of the system.  ...  Cloud gaming renders an interactive gaming application in the cloud and streams the scenes as a video sequence to the player over Internet.  ... 
doi:10.5121/iju.2016.7302 fatcat:afwp3yravjhbfm3yct5ux2enui

A Survey of Big Data Machine Learning Applications Optimization in Cloud Data Centers and Networks [article]

Sanaa Hamid Mohamed, Taisir E.H. El-Gorashi, Jaafar M.H. Elmirghani
2019 arXiv   pre-print
This survey article reviews the challenges associated with deploying and optimizing big data applications and machine learning algorithms in cloud data centers and networks.  ...  However, the increasing traffic between and within the data centers that migrate, store, and process big data, is becoming a bottleneck that calls for enhanced infrastructures capable of reducing the congestion  ...  The energy efficiency of running a mix of MapReduce and video streaming applications in P2P and community clouds was considered in [125] .  ... 
arXiv:1910.00731v1 fatcat:kvi3br4iwzg3bi7fifpgyly7m4
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