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Escalonamento e Migração de Recursos e Balanceamento de carga

Escalonamento e Migração de Recursos e Balanceamento de carga. Carlos Ferrão Lopes nº M6935 Bruno Simões nº M6082 Celina Alexandre nº M6807 Paulo Cabral nº M6765 Quoc nº M6831. Tecnologias de Cloud e Datacenter Professor Doutor Nuno M. Garcia. 27-04-2015. 1. Overview. 1. Stagger

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Escalonamento e Migração de Recursos e Balanceamento de carga

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  1. Escalonamento e Migração de Recursos e Balanceamento de carga Carlos Ferrão Lopes nº M6935 Bruno Simões nº M6082 Celina Alexandre nº M6807 Paulo Cabral nº M6765 Quoc nº M6831 Tecnologias de Cloud e Datacenter Professor Doutor Nuno M. Garcia 27-04-2015 1

  2. Overview 1. Stagger 2. Migration 3. Load Balancing 27-04-2015 2

  3. Overview 1. Stagger 2. Scheduling Tasks 2.1. Algorithms Hetergeneous Earliest Finish Time (HEFT) 2.2. Algorithms Path Clustering Heuristic (PCH) 2.3 Scheduling algorithms for the comparison study 27-04-2015 3

  4. Overview (Cont.) 3. Scheduling Procedure 3.1. Process Scheduling in Distributed System 27-04-2015 4

  5. What is Scheduling? • A system that uses multi-programming processes compete for processing, as they require dividing the execution time of each. 27-04-2015 5

  6. Scheduling problem • Problem workflow scheduling a set of dependent services: • Order of precedence of services; • Costs of performance of the services; • Communication costs between services; • Resource processing capabilities; • Data transmission capabilities of network connections, which interconnect these resources; 27-04-2015 6

  7. Scheduling algorithm Rating Rating scheduling methods 27-04-2015 7

  8. Scheduling tasks • dependent • independent 27-04-2015 8

  9. Heterogeneous Earliest Finish Time Algorithm (HEFT) • Algorithm Workflow escalation • Using an acyclic digraph (DAG1) for a limited number of heterogeneous computers. • Task scheduling problem is NP-hard 27-04-2015 9 1DAG - Directed acyclic graph

  10. Heterogeneous Earliest Finish Time Algorithm (HEFT) (Cont.) • The HEFT consists of two main phases: • Prioritization phase • Selection phase 27-04-2015 10

  11. Prioritization phase • Each task should be prioritized considering the length of the critical path; • The list of tasks to be performed is then sorted in descending order of the critical path length; • A topological sorting is produced tasks, preserving the precedence constraints of the DAG; 27-04-2015 11

  12. Selection Phase • To select which processor will perform a given task, calculating the earliest time of completion of a given task. With HEFT algorithm, the search for a vacant time slot on a processor P starts from the moment that the processor P becomes vacant. 27-04-2015 12

  13. Path Heuristic Clustering Algorithm (PCH) • Clustering uses the technique to create groups (clusters) tasks; • Groups the ways of the DAG, thus reducing communication costs between tasks; • The tasks of the same cluster are scheduled on the same resource; 27-04-2015 13

  14. Path Heuristic Clustering Algorithm (PCH) (Cont.) • Uses some attributes calculated for each task, estimating the start times (DS = Earliest Start Time) and end (EFT - Estimated Finish Time) of tasks and process; • EST and EFT are calculated using information that is provided by the middleware and the programming model; 27-04-2015 14

  15. Path Heuristic Clustering Algorithm (PCH) (Cont.) Example scheduling using the PCH 27-04-2015 15

  16. Scheduling algorithms for the comparison study • Applications used: • Application Montage1 • Application Epigenomics2 1 is used to generate personalized sky mosaics using multiple points of input images. 2 is used to mapping of epigenetic state of human cells on a large scale genomics. 27-04-2015 16

  17. Analysis Applications Representation of montage application used in the simulation. Representation of epigenomics application used in the simulation. 27-04-2015 17

  18. Architecture • Were also specified two sets: homogeneous and heterogeneous; • Have been implemented in addition to the scheduling algorithms HEFT, CPOP and PCH, a FIFO type of scheduling; 27-04-2015 18

  19. Architecture (Cont.) Architecture 27-04-2015 19

  20. Architecture (Cont.) Computing power table 27-04-2015 20

  21. Experimental Results • Applications to the Montage •   We observed that the FIFO strategy only performs well in homogeneous architecture. •   The PCH algorithm does not perform well in both architectures. •   The algorithms HEFT and CPOP perform well in both architectures with an almost negligible difference. 27-04-2015 21

  22. Analysis Applications Workload simulation result Montage with a set Homogeneous Workload simulation result Montage with a set Heterogeneous 27-04-2015 22 Makespan – The time difference between the beginning and end of a sequence of jobs or tasks

  23. Experimental Results • Applications to Epigenomics •   The PCH algorithm improves performance in this type of application. •   The CPOP algorithm preserves the good performance in both architectures. •   The HEFT algorithm performs well in heterogeneous architecture, but in the homogeneous architecture not. 27-04-2015 23

  24. Analysis Applications Workload simulation result Epigenomics with a set Homogeneous Workload simulation result Epigenomics with a set Heterogeneous 27-04-2015 24 Makespan – The time difference between the beginning and end of a sequence of jobs or tasks

  25. Conclusions • A FIFO strategy is appropriate only in homogeneous architectures. • In heterogeneous architectures it takes a study of both computational resources and tasks. • The HEFT and CPOP algorithms showed good performance and at the same time like in Montage application, while SHP not. • In applications with equipment that prevents the performance in a continuous process, such as montage application, it is not convenient grouping of tasks. 27-04-2015 25

  26. Scheduling Procedure • A multi-programming computer has multiple processes running simultaneously, however, that all processes can not access the CPU at a time and so there is a fair way of implementation of these processes, an algorithm was created to organize tasks. 27-04-2015 26

  27. Process Scheduling in Distributed System • Heterogeneity of the nodes prevents equal distribution; •   In addition to the tasks to be performed it is necessary to: • Processing power; • Unemployment level; •   If you are in possession of information: • Weight of tasks; • Estimated processing time;  27-04-2015 27

  28. Information nodes • Physical characteristics: speed, memory, processor type • Degree of idleness of each node: the processing power is being used; 27-04-2015 28

  29. Measure the level of unemployment • Average waiting time in the run queue • Problem: Priority difference of tasks; •   Generate CPU utilization rate  • Problem: to test specific process from time to time; 27-04-2015 29

  30. Measure the level of unemployment (Cont.) • Problem General: update frequency  • Excessive Update: scheduling algorithm becomes main consumer; • Insufficient Update: wrong choice of a node;  • Algorithms: • Static scheduling; • Scheduling dynamic • Adaptive scheduling; 27-04-2015 30

  31. Scheduling static • Assessment of conditions of the nodes is done once; • Data are used during the entire process; 27-04-2015 31

  32. Dynamic Scheduling • Constant analysis of the nodes characteristics: • Waiting time in the CPU queue: little processing; • CPU Utilization: Small background processes making continuous testing;   27-04-2015 32

  33. Adaptive Scheduling: • Dynamic Scheduling special case; • You can adjust the intensity of CPU consumption: • May fail to perform some tests 27-04-2015 33

  34. Overhead • Distributed memory: high cost in exchange of information between nodes; • Can occur over communications and performance problems: • Nodes are communicating longer than processing; 27-04-2015 34

  35. Algorithms of classification according to the policy • You can sort scheduling algorithms under policies: • Transfer policy: determining a suitable node to receive tasks; • Selection Policy: determine the most appropriate task to be sent to a node; • Location Policy: determine the most appropriate node to receive a given task; • Information Policy: determine storage location of information and frequency of update. 27-04-2015 35

  36. Transfer Policy • Determine a receiver node: node is working below its processing capacity; • Is defined maximum load supported by each node; 27-04-2015 36

  37. Transfer Policy (Cont.) • Problem: donor sends a task to a receiver that immediately becomes a donor: • Task switching is done indefinitely. • Is defined maximum load supported by each node; • Solution: Consider a donor node whose load is less than the limit and will continue to be less than or equal after receiving the task; 27-04-2015 37

  38. Selection Policy • Determine a task to be sent when a node is overloaded or eligible to receive; • In an overloaded node: • Select the task that caused the overload; 27-04-2015 38

  39. Selection Policy (Cont.) • Preemptive scheduling: • A task already running can be transferred to another node; • High transfer costs of the task context (ex .: data in memory); • Usually picks up recently started tasks; • Non-Preemptive Scheduling: • Only tasks that have not yet implemented can be transferred; 27-04-2015 39

  40. Location Policy • Select node to receive a task; • Random method (most commonly used): • Node randomly chooses another node; • Problem: chances of choosing a node in the same situation; • Immediate solution: test if selected node is receiver; • Solution "better": vote between selected nodes. Generates excessive communication. 27-04-2015 40

  41. Information Policy • Corresponds to the exchange of information on their status across multiple nodes: • Local storage: a specific node receives all the status messages of others. • Broadcast: each node sends to others; • Sub-demand: each node has information about you. Information about others only when it becomes donor or recipient. 27-04-2015 41

  42. Scheduling algorithms • Started by the donor: • The node that has a donor in accordance with the transfer policy utilized, looking for a receiver; • Algorithm Random (most common), making the choice of a single receptor twice. • Sub-demand: each node has information about you. Information about others only when it becomes donor or recipient. 27-04-2015 42

  43. Scheduling algorithms (Cont.) • Started by the receiver: • The receiver node calls tasks to process; • Most advantageous approach: unoccupied node has more time to choose a suitable donor; 27-04-2015 43

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