• Good resource allocation schemes are needed to
fully utilize the computing capacity of the DS
• Distributed scheduler is a resource management
• It focuses on judiciously and transparently
redistributing the load of the system among the computers
• Target is to maximize the overall performance of the
• A locally distributed system consists of a collection of
autonomous computers connected by a local area communication network
• Users submit tasks at their host computers for processing• Load distributed is required in such environment because of
random arrival of tasks and their random CPU service time
• There is a possibility that several computers are heavily
loaded and others are idle of lightly loaded
• If the load is heavier on some systems or if some processors
execute tasks at a slower rate than others, this situation will occur often
• Consider a system of N identical and independent
• Identical means that all servers have the same task
• Let ? be the utilization of each server, than P=1- ?,
• If the ?=0.6, it means that P=0.4,• If the systems have different load than load can be
transferred from highly loaded systems to lightly load systems to increase the performance
- Resource queue lengths and particularly the CPU queue
- Measuring the CPU queue length is fairly simple and
- CPU queue length does not always tell the correct
situation as the jobs may differ in types
- Another load measuring criterion is the processor
- Requires a background process that monitors CPU
utilization continuously and imposes more overhead
- Used in most of the load balancing algorithms
• Basic function is to transfer load from heavily loaded
systems to idle or lightly loaded systems
• These algorithms can be classified as :
• decisions are hard-wired in the algorithm using a prior knowledge
• use system state information to make load distributing decisions
• special case of dynamic algorithms in that they adapt their
activities by dynamically changing the parameters of the algorithm to suit the changing system state
- Load sharing algorithms strive to reduce the possibility for
a system to go to a state in which it lies idle while at the same time tasks contend service at another, by transferring tasks to lightly loaded nodes
- Load balancing algorithms try to equalize loads at al
- Because a load balancing algorithm transfers tasks at
higher rate than a load sharing algorithm, the higher overhead incurred by the load balancing algorithm may outweigh this potential performance improvement
• Preemptive vs. Non-preemptive transfer
- Preemptive task transfers involve the transfer of a task
- Non-preemptive task transfers involve the transfer of the
tasks that have not begun execution and hence do not require the transfer of the task's state
- Preemptive transfer is an expensive operation as the
collection of a task's state can be difficult
- What does a task's state consist of?- Non-preemptive task transfers are also referred to as task
- determines whether a node is in a suitable state to participate in a
- requires information on the local nodes' state to make decisions
- determines which task should be transferred
- determines to which node a task selected for transfer should be
- requires information on the states of remote nodes to make
- responsible for triggering the collection of system state information- Three types are: Demand-Driven, Periodic, State-Change-Driven
• A system is termed as unstable if the CPU queues
grow without bound when the long term arrival rate of work to a system is greater than the rate at which the system can perform work.
• If an algorithm can perform fruitless actions indefinitely
with finite probability, the algorithm is said to be unstable.
• Activity is initiated by an overloaded node (sender)• A task is sent to an underloaded node (receiver)
• A node is identified as a sender if a new task originating at the
node makes the queue length exceed a threshold T.
• Only new arrived tasks are considered for transfer
• Random: dynamic location policy, no prior information exchange• Threshold: polling a node (selected at random) to find a receiver• Shortest: a group of nodes are polled to determine their queue
• Location policies adopted cause system instability at high loads
Yes QueueLength at "I" Task Arrives
• Initiated from an underloaded node (receiver) to
obtain a task from an overloaded node (sender)
• A node selected at random is polled to determine if transferring a
task from it would place its queue length below the threshold level, if not, the polled node transfers a task.
• Do not cause system instability in high system load, however, in
• Most transfers are preemptive and therefore expensive
Yes QueueLength at "I" Task Departure at "j"
• Both senders and receivers search for receiver and
senders, respectively, for task transfer.
• Thresholds are equidistant from the node's estimate of the
• Sender-initiated component: Timeout messages TooHigh,
TooLow, Accept, AwaitingTask, ChangeAverage
• Receiver-initiated component: Timeout messages TooLow,
LooHigh, Accept, AwaitingTask, ChangeAverage
• Similar to both the earlier algorithms
• A demand-driven type but the acceptable range can be
increased/decreased by each node individually.
• A Stable Symmetrically Initiated Algorithm
- Utilizes the information gathered during polling to classify the nodes
in the system as either Sender, Receiver or OK.
- The knowledge concerning the state of nodes is maintained by a data
structure at each node, comprised of a senders list, a receivers list, and an OK list.
- Initially, each node assumes that every other node is a receiver. - Transfer Policy
• Triggers when a new task originates or when a task departs. • Makes use of two threshold values, i.e. Lower (LT) and Upper (UT)
• Sender-initiated component: Polls the node at the head of receiver's list• Receiver-initiated component: Polling in three order
- Head-Tail (senders list), Tail-Head (OK list), Tail-Head (receivers list)
- Selection Policy: Newly arrived task (SI), other approached (RI)- Information Policy: A demand-driven type
• Receiver-initiated task transfers can improve
system performance at high system loads.
• Receiver-initiated transfers require
- Task Placement refers to the transfer of a task
that is yet to begin execution to a new location and start its execution there.
- Task Migration refers to that transfer of a task
that has already begun execution to a new location and continuing its execution there.
• The transfer of the task's state including information
e.g. registers, stack, ready/blocked, virtual memory address space, file descriptors, buffered messages etc. to the new machine.
• The task is frozen at some point during the transfer so
that the state does not change further.
• The task is installed at the new machine and is put in
the ready queue so that it can continue executing.
- To support remote execution, obtaining and transferring the state, and
- Refers to the amount of resources a former host of a preempted or migrated
task continues to dedicate to service requests from the migrated task. Implementations
• Attempts to reduce the freezing time of a migrating task by precopying the state. • The bulk of the task state is copied to the new host• It increases the number of messages that are sent to new host
• Makes use of the location-transparent file access mechanism provided by its file
• All the modified pages of the migrating task are swapped to file server
• Reduction in migration is achieved by using a feature called Copy-on-Reference• The entire virtual memory address space is not copied to the new host
• Services that are provided to user processes irrespective of
the location of the processes and services.
• In distributed systems, it is essential that the location
• Location transparency in principle requires that names (e.g.
process names, file names) be independent of their location (i.e. host names).
• Any operation (such as signaling) or communication that was
possible before the migration of a task should be possible after its migration
• Example - SPRITE - Location Transparency Mechanisms
- A location-transparent distributed file system is provided- The entire state of the migrating task is made available at the new
host, and therefore, any kernel calls made will be local at new host
- Location-dependent information such as host of a task is maintained
• Issues involved in Migration Mechanisms
- Decision whether to separate the policy-making modules
• It has implications for both performance and the ease of
• The separation of policy and mechanism modules simplifies the
- Decision to where the policy and mechanisms should
• The migration mechanism may best fit inside the kernel• Policy modules decide whether a task transfer should occur, this
- Interplay between the task migration mechanism and
• The mechanisms can be designed to be independent of one
another so that if one mechanism's protocol changes, the other'sneed not
• Comparing the performance of task migration
mechanisms implemented in different systems is a difficult task, because of the different,
• SPRITE consists of a collection of SPARCSTATION 1• CHARLOTTE consists of VAX/11-750 machines
- Operating systems- IPC mechanism- File systems- Policy mechanisms
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