Distributed process and scheduling

Distributed Process

1

Contents

• Distributed process

• Process Management

– Processor allocation

– Process migration

– Threads

13/04/2012 Distributed Systems, B.Tech.IV,

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References:

• Pradeep K. Sinha “Distributed Operation Systems : Concepts and Design” PHI.

• “Process Migration” Dejan S. Milojicic, Fred Douglis, Yves Paindaveine, Richard Wheeler and Songnian Zhou

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Distributed Systems, B.Tech.IV,

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Concept of Process

• Process: An operating system abstraction representing an instance of a running computer program

– Consists of data, stack, register contents, and the state specific to the underlying OS

– Can have one or more threads of control

• Consists of their own stack and register contents, but share a process’s address space and signals.


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Process management

• Conventional OS:

– deals with the mechanisms and policies for sharing the processor of the system among all processes

• Distributed operating system:

– To make best possible use of the processing resources of the entire system by sharing them among all processes


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Process management contd…

• Three concepts to achieve this goal:

– Processor allocation

• Deals with the process of deciding which process should be assigned to which processor

– Process migration

• Deals with the movement of a process from its current location to the processor to which it has been assigned

– Threads

• Deals with fine-grained parallelism for better utilization of the processing capability of the system


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Process Migration

• Process Migration:

– The act of transferring a process between two machines during its execution

– Relocation of a process from its current location (the source node) to another node(the destination node)

• Goals of Process Migration:

– Dynamic load distribution

– Fault resilience

– Improved system administration

– Data access locality


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Process Migration contd…

• Problems with Process Migration:

– Complexity of adding transparent migration

– Lack of compelling commercial argument for OS venders to support process migration


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Process Migration contd… • The flow of execution of a migrating process:


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Source node destination node

Process P1 in

execution

Execution

suspended

Transfer of

control

Execution resumed

Process P1 in

execution

Time

Freezing

Time


• Two types:

– Preemptive process migration

• Process may be migrated during the course of its execution

– Non preemptive process migration

• Process may be migrated before it starts executing on its source node


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• Involves three steps:

– Selection of a process that should be migrated

– Selection of the destination node to which the selected process should be migrated

– Actual transfer of the selected process to the destination node


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Desirable features

• Transperency

– Object class level

– System call and interprocess communication level

• Minimal interference

– Can be done by minimizing freezing time

– Freezing time: a time for which the execution o the process is stopped for transferring its information to the destination node

• Minimal residual dependencies

– Migrated process should not continue to depend on its previous node once it has started executing on new node


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Desirable features contd…

• Effiency

– Time required of migrating a process

– The cost of locating an object

– The cost of supporting remote execution once the process is migrated

• Robustness

– The failure of a node other than the one on which a process is currently running should not affect the execution of that process

• Communication between Coprocesses of a job


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Process migration mechanisms

• Four major subactivities

– Freezing and restarting the process

– Transfer of process’s address space

– Forwarding messages meant for the migrant process

– Handling communication between cooperating processes


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• Mechanisms for freezing and restarting a process

– Immediate and Delayed blocking of the process

• may be blocked immediately or delayed

• if the process is not executing a system call

• if the process is executing a system call but is sleeping at an interruptible priority waiting for a kernel event to occur, it can be immediately blocked from further execution

• -Do- and sleeping at noninterruptible priority waiting for a kernel event to occur, it can not be blocked


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• Fast and Slow I/O operation

– frozen after the completion of all fast I/O operations

– What about slow I/O operations???

• Information about the open files

– No problem for network transparent execution environment

– What about UNIX like systems??? • creation of link

• Reconstruction of file’s path when required

– What about frequently used files like commands???

– What about temporary files?


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Mechanisms for freezing and restarting a process contd… • Reinstating the process on its destination

node

– Creation of a new process

– Process identifier

– What about the process which was blocked while executing a slow system call????


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UPTO THIS FOR MIDSEMESTER EXAM

13/04/2012 Distributed Systems, B. Tech I, SVNIT,

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Process migration mechanisms contd… • Address Space Transfer Mechanisms

– Information to be transferred from source node to destination node: • Process’s state information

• Process’s address space

– Difference between the size of process’s state information and address space

– Possible to transfer the address space without stopping its execution

– Not possible to resume execution until the state information is fully transferred

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Address Space Transfer Mechanisms

• Three methods for address space transfer

– Total Freezing

– Pretransferring

– Transfer on reference


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Address Space Transfer Mechanisms (cont.)

• Total Freezing:

– Execution is stopped while its address space is being transferred

– Simple and easy to implement

– Process is suspended for a long time during migration

– Not suitable for interactive process


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Address Space Transfer Mechanisms(cont.)

• Total Freezing:


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Migration decision

made

Execution

suspended

Transfer of

address space

Execution resumed

Time

Freezing

Time


• Pretransferring (precopying):

– Address space is transferred while the process is still running on the source node

– Initial transfer of the complete address space followed by repeated transfers of the pages modified during previous transfer

– Remaining modified pages are retransferred after the process is frozen for transferring its state information

– Pretransfer operation is executed at a higher priority than all other programs on the source node


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Pretransferring (precopying) (cont.)

– freezing time is reduced

– Total time of migration is increased due to the possibility of redundant page transfers


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Pretransferring(cont.)


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Migration decision

made

Execution

suspended

Transfer of

address space

Execution resumed

Time

Freezing

Time


• Transfer on reference – Based on the assumption that the process tends to use only a

relatively small part of their address space while executing.

– A page of the address space is transferred from its source node to destination node only when referenced

– Demand-driven copy-on-reference approach

– Switching time is very short and independent of the size of the address space

– Not efficient in terms of cost

– Imposes continued load on process’s source node

– Results in failure if source node fails or reboots


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Transfer-on-reference


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Migration decision

made

Execution

suspended

On demand

Transfer of

address space

Execution resumed

Time

Freezing

Time

Process migration mechanisms (cont.)

• Message forwarding mechanisms

– Ensures that all pending, en-route and future messages arrive at the process’s new location

– Classification of the messages to be forwarded:

• Type 1: Messages received at the source node after the process’s execution has been stopped on its source node and process’s execution has not yet been started on its destination node

• Type 2: Message received at the source node after the process’s execution has started on its destination node


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Message forwarding mechanisms contd…

• Type 3: Messages that are to be sent to the migrant process from any other node after it has started executing on the destination node


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Message forwarding mechanisms (cont.)

• Mechanism of Resending the Message

– Messages of type 1 and 2 are returned to the sender as not deliverable or are simply dropped

– Locating a process is required upon the receipt of the nonnegative reply (messages of type 3)

– Drawback: nontransparent to the processes interacting with the migrant process


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• Origin Site Mechanism

– Process identifier has the process’s origin site(or home node) embedded in it

– Each site is responsible for keeping information about the current location of all the processes created on it

– Messages are sent to the origin site first and from there they are forwarded to the current location

– Drawbacks: • not good from reliability point of view

• continuous load on migrant process’s original site


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• Link Traversal mechanism:

– Uses message queue for storing messages of type 1

– Use of link (a forwarding address) for messages of type 2 and 3

– Link has two components: process identifier and last known location of the process

– Migrated process is located by traversing a series of links


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• Link Traversal mechanism:

– Drawbacks:

• poor efficiency

• poor reliability


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• Link Update mechanism:

– Processes communicate via location independent links

– During the transfer phase, the source node sends link update message to all relevant kernels


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Process migration mechanisms (cont.)

• Mechanisms for handling coprocesses

– Communication between a process and its subprocesses

– Two different mechanisms

• Disallowing separation of Coprocesses

• home node or origin site concept


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Mechanisms for handling coprocesses

• Disallowing separation of Coprocesses

– By disallowing the migration of processes that wait for one or more of their children to complete.

– By ensuring that when a parent process migrates, its children processes will be migrated along with it • Concept of logical host

• Process id is structured as {logical host-id, local-index} pair

– Drawback : • Does not allow parallelism within jobs

• Overhead is large when logical host contains several processes

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Mechanisms for handling coprocesses

• home node or origin site concept

– Complete freedom of migrating a process or its subprocesses independently and executing them on different nodes

– Drawback:

• Message traffic and communication cost is significant


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Advantages of process migration • Reducing average response time of processes

• Speeding up individual jobs

– Execute tasks of a job concurrently

– To migrate a job to a node having faster CPU

• Gaining higher throughput

– Using suitable load balancing policy

• Utilizing resources effectively

– Depending on the nature of the process, it can be migrated to the most suitable node

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Advantages of process migration(cont.)

• Reducing network traffic

– Migrate the process closer to the resources it is using most heavily

– To migrate and cluster two or more processes which frequently communicate with each other, on the same node

• improving system reliability

– Migrating critical process to more reliable node

• Improving system security

– A sensitive process may be migrated and run on the secure node


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Distributed Scheduling


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Contents

• Distributed Scheduler

• Motivation

• Issues in load distributing

• Load distributing algorithms

• Load sharing policies


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References:

• Mukesh Singhal, Niranjan Shivaratri. “Advanced concepts in operating systems”. Tata McGraw Hill publication


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Introduction • Need for good resource allocation scheme for

DS

• Distributed scheduler:

A resource management component of a distributed operating system that focuses on judiciously and transparently redistributing the load of the system among the computers such that the overall performance of a system is maximized.

• More suitable for LANs than WANs


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Motivation • Need for load distributing because of

– Random arrival of tasks

– Random CPU service requirements

• Needed both for heterogeneous and homogeneous systems

• E.g. system of N identical and independent servers Let p be the utilization for each server

P0 = 1 – p; the probability that a server is idle

P be the probability that the system is in a state in which at least one task is waiting for service and at least one server is idle


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Motivation contd…


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Motivation contd… • Some Observations:

– For moderate system utilization the value of P is high i.e. higher potential for load distribution

– At high system utilization the value of P is low i.e. lower potential for load distribution

– At low system utilization the value of P is again low

– As the number of the server in the system increases, P remains high even at high system utilization


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Issues in Load Distributing

• Some terminology

– Performance of a system

• one of the metric is average response time of task which is the length of the time interval between its origination and completion

– Defining proper load index


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Issues in Load Distributing contd…

• Load

– CPU queue length as a load indicator

– CPU utilization as a load indicator


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Classification of load distributing algorithms

• Goal of Load distributing algorithm

– To transfer load from heavily loaded computers to idle or lightly loaded computers

• broadly characterized as

– Static

• Decision is hard wired in the algorithm using a priory knowledge of the system

– Dynamic

• Make use of system state information to make load distributing decisions


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Classification of load distributing algorithms contd…

– Adaptive

• Special class of dynamic algorithm

• they adapt their activities by dynamically changing the parameters of the algorithm to suit the changing system state


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Load balancing vs. Load sharing

• unshared state :

– A state in which one computer lies idle while at the same time tasks contend for service at another computer

• to reduce the likelihood of unshared state

• Load balancing algo:

– Attempt to equalize the loads at all computers

– Higher overhead than load sharing algo

• anticipatory task transfer

– To reduce the duration of unshared state


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Preemptive vs. Nonpreemptive transfers • Preemptive:

– Transfer of a task that is partially executed

• Non preemptive:

– Transfer of a task that has not yet started execution


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Components of Load Distributing algorithm

• Four components

– Transfer policy • Determines whether a node is in a suitable state to participate in a

task transfer

– Selection policy • determines which task should be transferred

– Location policy • determines to which node a task selected for transfer should be

sent

– Information policy • responsible for triggering the collection of system state

information


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Transfer Policy

• Threshold policy

– Thresholds are expressed in terms of units of load

– Decided upon the origination of new task

– Concept of sender and receiver

• On detecting imbalance in load amongst nodes in system


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Selection Policy • Selects a task for transfer

• Simplest approach: to select the newly originated task

• Overhead incurred in task transfer should be compensated by the reduction in the response time realized by the task

• Factors to consider:

– Overhead incurred by transfer should be minimal

– Number of location dependent system calls made by the selected task should be minimal


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Location Policy • To find suitable nodes to share load(sender or

receiver)

• Widely used method : polling

– Either serially or in parallel

– Either randomly or on a nearest-neighbor basis

• Alternative to polling

– Broadcast a query to find out if any node is available for load sharing


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Information Policy • To decide when, where and what information

about the states of other nodes on the system should be collected

• One of three types:

– Demand driven

• Node collects the state of the other nodes only when it becomes either a sender or a receiver

• dynamic policy

• can be sender-initiated, receiver-initiated or symmetrically initiated


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Information Policy contd…

– Periodic

• Nodes exchange load information periodically

• Do not adapt their activity to the system state

• Benefits are minimal at high system loads ???

– State change driven

• Nodes disseminate state information whenever their state changes by a certain degree

• Centralized and decentralized policy


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Load distributing algorithms

• Sender initiated algorithms

• Receiver initiated algorithms

• Symmetrically initiated algorithms


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Sender-Initiated algorithms • Initiative by overloaded node (sender) to send a task

to an underloaded node(receiver)

• Transfer policy :

– Threshold policy based on CPU queue length

• Selection Policy:

– Consider only newly arrived tasks for transfer

• Location policy:

– Random : • no remote state information

• task is transferred to a node selected at random


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Sender-Initiated algorithms

– Random :

• Useless task transfer can occur

• Treating a transferred task

• Thrashing problem : – Solution : limit the number of times a task can be transferred

• Substantial performance improvement over no load sharing at all


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– Threshold

• Polling a node to determine whether it is receiver or not

• PollLimit , limit on no. of nodes to poll


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– Shortest

• Choose best receiver for a task

• Make use of CPU queue length

• Information policy

– Demand driven

• Stability

– Instability at high system load


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Receiver-Initiated Algorithms

• Initiation by an underloaded node (receiver)

• Transfer policy – Threshold policy based on CPU queue length.

– Triggered when the task departs

• Selection policy – Any

• Location policy – Threshold policy


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Receiver-Initiated Algorithms (cont.)


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Receiver-Initiated Algorithms (cont.)


– Demand-driven type.

• Stability

– Do not cause system instability at high load. Why????

– Do not cause system instability at low load. Why????

• Drawback

– Most transfers are preemptive.

– What about sender-initiated algorithms????


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Comparison of Sender-Initiated and Receiver-Initiated Algorithms

• Stability

• Robustness

– Has an edge over the sender-initiated policies.

• Performs acceptably with a single value of threshold over entire load spectrum while sender-initiated policies requires adaptive location policy


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Comparison of Sender-Initiated and Receiver-Initiated Algorithms contd…


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Symmetrically Initiated Algorithms

• Both senders and receivers search for receivers and senders respectively

• Advantages and disadvantages of both sender and receiver initiated algorithms.

• Above average algorithm.


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The above average algorithm

• Proposed by Krueger and Finkel

• Tries to maintain the load at each node within an acceptable range of system average

• Why not exact system average ????


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Transfer Policy • Use two adaptive thresholds:

– Equidistant from the node’s estimate of the average load across all nodes

– E.g. average load is 2 the lower threshold = 1 and the upper threshold = 3

• A node whose load is greater than upper threshold a sender

• A node whose load is less than lower threshold a receiver.

• Nodes that have loads between these thresholds lie within the acceptable range, so they are neither senders nor receivers.

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Location Policy

• The location policy has the following two components: – Sender-initiated component

– Receiver-initiated component


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Sender-initiated component

• Sender node: – TooHigh message

– TooHigh timeout alarm

• Receiver node – TooLow timeout alarm

– accept message

– AwaitingTask timeout alarm

– Increases load before accepting a task. Why????

• What if sender receives TooLow message while waiting for Accept message??


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Sender-initiated component contd…

• On expiration of TooHigh timeout, if no Accept message is received, – Sender infers that its estimate of the average

system load is too low

– Hence, it broadcasts a ChangeAverage message to increase the average load estimate at the other nodes.


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Receiver-initiated component

• A node, on becoming a receiver, broadcasts a TooLow message, set a TooLow timeout, and starts listening for a TooHigh message.

• If a TooHigh message is received, the receiver performs the same actions that it does under sender-initiated negotiation

• If the TooLow timeout expires before receiving any TooHigh message, the receiver broadcasts a ChangeAverage message to decrease the average load estimate at the other nodes


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Selection and Information Policy

• Selection policy

– This algorithm can make use of any of the approaches discussed earlier.


– Demand-driven.


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Symmetrically initiated algorithm

• average system load is determined individually at each node

• load balancing actions adapts to the state of the communication network as well


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Adaptive Algorithms

• A stable symmetrically initiated algorithm

• A stable sender initiated algorithm


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A stable symmetrically initiated algorithm

• Instability in previous algorithms is due to indiscriminate polling by sender’s negotiation component.

• Utilize the information gathered during polling to classify the nodes in the system as either Sender/overloaded, Receiver/underloaded, or OK.

• The knowledge concerning the state of node is maintained by a data structure at each node: a sender list, a receiver list, and an OK list.

• Initially, each node assumes that every other node is a receiver.


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Transfer policy

• A threshold policy where decisions are based on CPU queue length.

• Trigger when a new task originates or when a task departs.

• Two threshold values: a lower threshold (LT), an upper threshold (UT).

• A node is said to be a sender if its queue length > UT, a receiver if its queue length < LT, and OK if LT ≤ node’s queue length ≤ UT.


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Location policy

• Sender initiated component

• Receiver initiated component


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Sender initiated component

• Triggered when node becomes sender

• Sender polls a node at the head of the receiver lists to determine whether it is receiver or not

• Processing at the polled node:

• Processing when the response arrives from the polled node:

• Polling stops if, – A suitable receiver is found

– The number of polls reaches a PollLimit

– The receiver list at the sender node becomes empty

– And the task is processed locally


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Receiver initiated component • Nodes polled are selected in following order,

– Head to tail in senders list

– Tail to head in OK list

– Tail to head in receivers list

• Receiver polls the selected node to determine whether it is sender

• Processing if polled node is sender

• Processing if polled node is not a sender

• Polling process stops if, – A sender is found

– If the receiver is no longer a receiver

– No. of polls reaches a PollLimit

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Selection and Information Policy

• Selection policy:

– The sender initiated component considers only newly arrived tasks for transfer.

– The receiver initiated component can make use of any of the approaches discussed earlier.

• Information policy: demand-driven.


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Discussion

• Future sender initiated polls at high system loads are prevented. How???

• What about Receiver initiated component at low system load ???

• Positive effect of updating the receiver list


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A stable sender initiated algorithm

• Two desirable properties:

– It does not cause instability

– Load sharing is due to non-preemptive transfer only.

• Uses the sender initiated load sharing component of the stable symmetrically initiated algorithm

• Has a modified receiver initiated component to attract the future non-preemptive task transfers from sender nodes.


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• The data structure (at each node) of the stable symmetrically initiated algorithm is augmented by a array called statevector.

• The statevector is used by each node to keep track of which list (senders, receivers, or OK) it belongs to at all the other nodes in the system.

• When a sender polls a selected node, the sender’s statevector is updated to reflect that the sender now belongs the senders list at the selected node, the polled node update its statevector based on the reply it sent to the sender node to reflect which list it will belong to at the sender


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• The receiver initiated component is replaced by the following protocol: – When a node becomes a receiver, it informs all the nodes that are are

misinformed about its current state. The misinformed node are those nodes whose receivers lists do not contain the receiver’s ID.

– The statevector at the receiver is then updated to reflect that it now belongs to the receivers list at all those nodes that were informed of its current state.

– By this technique, this algorithm avoids the receivers sending broadcast messages to inform other nodes that they are receivers.

• No preemptive transfers of partly executed tasks here.


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Performance comparision

• Symmetrically initiated load sharing

• Stable load sharing algorithms

• Performance under heterogeneous workloads


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Symmetrically initiated load sharing


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Stable load sharing algorithms


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Selecting a suitable load sharing algorithm

1. System under consideration never attains high loads

2. Systems that can reach high loads

3. Systems that experiences a wide range of load fluctuations

4. Systems that experiences a wide range of fluctuations in load and has a high cost of the migration of partly executed tasks

5. Systems that experiences heterogeneous work arrival


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Engineering

Distributed process and scheduling