ExaMig Matrix: Process Migration based on Matrix Definition of Selecting Destination in Distributed Exascale Environments

In traditional computing system, load balancer, interim selecting the process, determine the destination computing node based on describing Indicators process status. In distributed Exascale computing system, due to the possibility of occurrence of a dynamic and interactive nature in execution time, it is possible. That the chosen destination computing node affected with dynamic and interactive nature so cannot be considered as a destination in process migration. This paper, by changing management approach in process migration. Consider process as an abstract element on the target computing node and calculates the impact of the factors the parameters affecting the process. Considering the above factors make process migration manager able to create sets of computational node that can be considered as destination computing node. In the event of a dynamic and interactive nature, in each element of the set, the process migration management, consider the effects of the factors affecting the activity of the process management and then re-weighs the computing element which make the above set. Using this mechanism allow the process migration management in case of dynamic and interactive nature occurrence in destination able to decide about changing on global activity execution so it is not necessary to recall load balancer manager in order to choose destination computing node. These subject louds to decrease execution time of process migration activity in distributed Exascale computing system.

[1]  Seo-Young Noh,et al.  A performance analysis of precopy, postcopy and hybrid live VM migration algorithms in scientific cloud computing environment , 2015, 2015 International Conference on High Performance Computing & Simulation (HPCS).

[2]  Manpreet Singh,et al.  An efficient decentralized Load Balancing Algorithm for grid , 2010, 2010 IEEE 2nd International Advance Computing Conference (IACC).

[3]  Ian Foster,et al.  A peer-to-peer approach to resource location in grid environments , 2002 .

[4]  Zhen Li,et al.  Load balancing for cluster systems under heavy-tailed and temporal dependent workloads , 2014, Simul. Model. Pract. Theory.

[5]  Thamarai Selvi Somasundaram,et al.  A distributed cloud resource management framework for High-Performance Computing (HPC) applications , 2017, 2016 Eighth International Conference on Advanced Computing (ICoAC).

[6]  Devendra Thakor,et al.  Performance Measurement and Evaluation of Pluggable to Scheduler Dynamic Load Balancing Algorithm (P2S_DLB) in Distributed Computing Environment , 2018 .

[7]  Mohsen Sharifi,et al.  An Efficient Live Process Migration Approach for High Performance Cluster Computing Systems , 2011 .

[8]  Enda Barrett,et al.  Single system image: A survey , 2016, J. Parallel Distributed Comput..

[9]  Ali Ghaffari,et al.  A Multi-criteria Method for Resource Discovery in Distributed Systems Using Deductive Fuzzy System , 2017, Int. J. Fuzzy Syst..

[10]  R. Sridaran,et al.  Understanding Live Migration Techniques Intended for Resource Interference Minimization in Virtualized Cloud Environment , 2018 .

[11]  Abdelhameed Ibrahim,et al.  Optimization of live virtual machine migration in cloud computing: A survey and future directions , 2018, J. Netw. Comput. Appl..

[12]  Dilawaer Duolikun,et al.  Energy-Aware Migration and Replication of Processes in a Cluster , 2015, 2015 10th International Conference on Broadband and Wireless Computing, Communication and Applications (BWCCA).

[13]  Zhiyi Huang,et al.  Load Balancing in a Cluster Computer , 2006, 2006 Seventh International Conference on Parallel and Distributed Computing, Applications and Technologies (PDCAT'06).

[14]  Javad Akbari Torkestani,et al.  A distributed resource discovery algorithm for P2P grids , 2012, J. Netw. Comput. Appl..

[15]  Antonio Parodi,et al.  Performance of WRF Cloud Resolving Simulations with Data Assimilation on Public Cloud and HPC Environments , 2018, CISIS.

[16]  Nguyen Hong Son,et al.  Load balancing algorithm based on estimating finish time of services in cloud computing , 2016, 2016 18th International Conference on Advanced Communication Technology (ICACT).

[17]  Nima Jafari Navimipour,et al.  A comprehensive study of the resource discovery techniques in Peer-to-Peer networks , 2015, Peer-to-Peer Netw. Appl..

[18]  Kousik Dasgupta,et al.  An Ant-Colony-Based Meta-Heuristic Approach for Load Balancing in Cloud Computing , 2021, Research Anthology on Architectures, Frameworks, and Integration Strategies for Distributed and Cloud Computing.

[19]  Albert Y. Zomaya,et al.  Survey on Grid Resource Allocation Mechanisms , 2014, Journal of Grid Computing.

[20]  Rajkumar Buyya,et al.  A taxonomy and survey of grid resource management systems for distributed computing , 2002, Softw. Pract. Exp..

[21]  Timothy R. Anderson,et al.  Technological Forecasting of Supercomputer Development: The March to Exascale Computing , 2015 .

[22]  A. Nirmal Kumar,et al.  Efficient performance upsurge in live migration with downturn in the migration time and downtime , 2018, Cluster Computing.

[23]  Stefan Lankes,et al.  Application migration in HPC — A driver of the exascale era? , 2016, 2016 International Conference on High Performance Computing & Simulation (HPCS).

[24]  Sanjay Chaudhary,et al.  Improved pre-copy algorithm using statistical prediction and compression model for efficient live memory migration , 2018, Int. J. High Perform. Comput. Netw..

[25]  Soumya Ranjan Jena,et al.  Response Time Minimization of Different Load Balancing Algorithms in Cloud Computing Environment , 2013 .

[26]  José Rodríguez,et al.  Fault tolerance in heterogeneous multi-cluster systems through a task migration mechanism , 2014, 2014 11th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE).

[27]  Yichuan Jiang,et al.  A Survey of Task Allocation and Load Balancing in Distributed Systems , 2016, IEEE Transactions on Parallel and Distributed Systems.

[28]  Ian Foster,et al.  On Fully Decentralized Resource Discovery in Grid Environments , 2001, GRID.

[29]  Chetna Dabas,et al.  Cluster based load balancing in cloud computing , 2015, 2015 Eighth International Conference on Contemporary Computing (IC3).

[30]  Arpita Gopal,et al.  Dynamic Load Balancing Using Periodically Load Collection with Past Experience Policy on Linux Cluster System , 2017 .

[31]  Anthony T. Chronopoulos,et al.  An effective game theoretic static load balancing applied to distributed computing , 2015, Cluster Computing.

[32]  Ehsan Mousavi Khaneghah,et al.  A mathematical multi-dimensional mechanism to improve process migration efficiency in peer-to-peer computing environments , 2018 .

[33]  Mohsen Sharifi,et al.  AMRC: an algebraic model for reconfiguration of high performance cluster computing systems at runtime , 2013, The Journal of Supercomputing.

[34]  Mohsen Sharifi,et al.  A dynamic framework for integrated management of all types of resources in P2P systems , 2010, The Journal of Supercomputing.

[35]  Nima Jafari Navimipour,et al.  Resource discovery in the peer to peer networks using an inverted ant colony optimization algorithm , 2019, Peer Peer Netw. Appl..

[36]  Yu Liu,et al.  DeMS: A hybrid scheme of task scheduling and load balancing in computing clusters , 2017, J. Netw. Comput. Appl..

[37]  Ehsan Mousavi Khaneghah,et al.  Challenges of Process Migration to Support Distributed Exascale Computing Environment , 2018, ICSCA.

[38]  Behrouz Minaei-Bidgoli,et al.  Four-dimensional model for describing the status of peers in peer-to-peer distributed systems , 2013 .

[39]  Aarti Singh,et al.  Autonomous Agent Based Load Balancing Algorithm in Cloud Computing , 2015 .

[40]  Vijayakumar Kadappa,et al.  Adaptive resource discovery models and Resource Selection in grids , 2010, 2010 First International Conference On Parallel, Distributed and Grid Computing (PDGC 2010).

[41]  Tanveer Ahmed,et al.  Analytic Study Of Load Balancing Techniques Using Tool Cloud Analyst. , 2012 .

[42]  Geoffrey G. Xie,et al.  Energy-Efficient Fault-Tolerant Data Storage and Processing in Mobile Cloud , 2015, IEEE Transactions on Cloud Computing.

[43]  Jemal H. Abawajy,et al.  An efficient meta-heuristic algorithm for grid computing , 2013, Journal of Combinatorial Optimization.

[44]  I. Pytharoulis,et al.  The Role of Heat Extinction Depth Concept to Fire Behavior: An Application to WRF-SFIRE Model , 2017 .

[45]  Simon Holmbacka,et al.  A task migration mechanism for distributed many-core operating systems , 2014, The Journal of Supercomputing.

[46]  JiangYichuan.  A Survey of Task Allocation and Load Balancing in Distributed Systems , 2016 .

[47]  Rui L. Aguiar,et al.  Resource discovery for distributed computing systems: A comprehensive survey , 2018, J. Parallel Distributed Comput..