Introduction DesirableFeaturesofGoodGlobalSchedulingAlgorithm TaskAssignmentApproach LoadBalancingApproach LoadSharingApproach

1. Sandeep Kumar Poonia
Head of Dept. CS/IT
B.E., M.Tech., UGC-NET
LM-IAENG, LM-IACSIT,LM-CSTA, LM-AIRCC, LM-SCIEI, AM-UACEE

2. Resource Management

Introduction

Desirable Features of Good Global
Scheduling Algorithm

Task Assignment Approach

Load Balancing Approach

Load Sharing Approach
Sandeep Kumar Poonia
11/10/2013
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3. Resource Management
A resource can be a logical, such as a shared file, or
physical, such as a CPU (a node of the distributed
system).
One of the functions of a distributed operating system is to
assign processes to the nodes (resources) of the
distributed system such that the resource usage, response
time, network congestion, and scheduling overhead are
optimized.
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4. Resource Management
Scheduling Techniques in DS
 Task Assignment Approach
 Load Balancing Approach
 Load Sharing Approach
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5. Resource Management
 Task
Assignment Approach, in which
each process submitted by a user for
processing is viewed as a collection of
related tasks and these tasks are
scheduled to suitable nodes so as to
improve performance.
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6. Resource Management
 Load-balancing
approach, in which all
the processes submitted by the users are
distributed among the nodes of the
system so as to equalize the workload
among the nodes.
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7. Resource Management
 Load-sharing
approach, which simply
attempts to conserve the ability of the
system to perform work by assuring that
no node is idle while processes wait for
being processed.
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8. Resource Management








No A Priori Knowledge about the Processes
Dynamic in Nature
Quick Decision-making Capability
Balanced System Performance and Scheduling
Overhead
Stability
Scalability
Fault Tolerance
Fairness of Service
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9. Resource Management

No a priori knowledge about the processes
Scheduling algorithms that operate based on the information
about the characteristics and resource requirements of the
processes pose an extra burden on the users who must
provide this information while submitting their processes for
execution.

Dynamic in nature
Process assignment decisions should be dynamic, I.e., be
based on the current load of the system and not on some
static policy. It is recommended that the scheduling algorithm
possess the flexibility to migrate a process more than once
because the initial decision of placing a process on a
particular node may have to be changed after some time to
adapt to the new system load.
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10. Resource Management

Quick decision making capability
Heuristic methods requiring less computational efforts
(and hence less time) while providing near-optimal
results are preferable to exhaustive (optimal) solution
methods.
 Balanced
system performance
scheduling overhead
and
Algorithms
that
provide
near-optimal
system
performance with a minimum of global state information
(such as CPU load) gathering overhead are desirable.
This is because the overhead increases as the amount of
global state information collected increases. This is
because the usefulness of that information is decreased
due to both the aging of the information being gathered
and the low scheduling frequency as a result of the cost of
gathering and processing the extra information.
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11. Resource Management
 Stability
Fruitless migration of processes, known as processor
thrashing, must be prevented. E.g. if nodes n1 and n2
observe that node n3 is idle and then offload a portion
of their work to n3 without being aware of the
offloading decision made by the other node. Now if
n3 becomes overloaded due to this it may again start
transferring its processes to other nodes. This is
caused by scheduling decisions being made at each
node independently of decisions made by other
nodes.
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12. Resource Management
 Scalability
A scheduling algorithm should scale well as the number
of nodes increases. An algorithm that makes scheduling
decisions by first inquiring the workload from all the
nodes and then selecting the most lightly loaded node has
poor scalability. This will work fine only when there are
few nodes in the system. This is because the inquirer
receives a flood of replies almost simultaneously, and the
time required to process the reply messages for making a
node selection is too long as the number of nodes (N)
increase. Also the network traffic quickly consumes
network bandwidth. A simple approach is to probe only m
of N nodes for selecting a node.
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13. Resource Management
 Fault
tolerance
A good scheduling algorithm should not be disabled
by the crash of one or more nodes of the system.
Also, if the nodes are partitioned into two or more
groups due to link failures, the algorithm should be
capable of functioning properly for the nodes within a
group. Algorithms that have decentralized decision
making capability and consider only available nodes
in their decision making have better fault tolerance
capability.
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 Fairness of service
Global scheduling policies that blindly attempt to balance
the load on all the nodes of the system are not good from
the point of view of fairness of service. This is because in
any load-balancing scheme, heavily loaded nodes will
obtain all the benefits while lightly loaded nodes will
suffer poorer response time than in a stand-alone
configuration. A fair strategy that improves response time
of the former without unduly affecting the latter is
desirable. Hence load-balancing has to be replaced by the
concept of load sharing, that is, a node will share some
of its resources as long as its users are not significantly
affected.
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Assumptions:
1.
2.
3.
4.
5.
6.
A process has already been split up into pieces called
tasks. This split occurs along natural boundaries (such as a
method), so that each task will have integrity in itself and
data transfers among the tasks are minimized.
The amount of computation required by each task and the
speed of each CPU are known.
The cost of processing each task on every node is known.
This is derived from assumption 2.
The IPC costs between every pair of tasks is known. The
IPC cost is 0 for tasks assigned to the same node. This is
usually estimated by an analysis of the static program. If two
tasks communicate n times and the average time for each
inter-task communication is t, them IPC costs for the two
tasks is n * t.
Precedence relationships among the tasks are known.
Reassignment of tasks is not possible.
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◦
◦
◦
◦
Minimization of IPC costs
Quick turnaround time for the complete process
A high degree of parallelism
Efficient utilization of system resources in general
These goals often conflict. E.g., while minimizing IPC costs tends to assign all
tasks of a process to a single node, efficient utilization of system resources
tries to distribute the tasks evenly among the nodes. So also, quick turnaround
time and a high degree of parallelism encourage parallel execution of the
tasks, the precedence relationship among the tasks limits their parallel
execution.
Also note that in case of m tasks and q nodes, there are mq possible
assignments of tasks to nodes . In practice, however, the actual number of
possible assignments of tasks to nodes may be less than mq due to the
restriction that certain tasks cannot be assigned to certain nodes due to their
specific requirements (e.g. need a certain amount of memory or a certain data
file).
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17. Resource Management

There are two nodes, {n1, n2} and six tasks {t1, t2, t3, t4, t5, t6}. There
are two task assignment parameters – the task execution cost (xab the
cost of executing task a on node b) and the inter-task communication
cost (cij the inter-task communication cost between tasks i and j).
Inter-task communication cost
Execution costs
t1
t2
t1 t2 t3 t4 t5 t6
0 6 4
0 0 12
6 0 8 12 3
0
Nodes
n1
n2
t1 5
10
t3
t4
t5
t6
4
0
0
12
t2
t3
t4
t5
8
12
3
0
0
0
11
0
0
0
5
0
11
5
0
0
0
0
0
0
2
4
6
5

4
3
2
t6 
4
Task t6 cannot be executed on node n1 and task t2 cannot be executed on node
n2 since the resources they need are not available on these nodes.
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1) Serial assignment, where tasks t1, t2, t3 are assigned to
node n1 and tasks t4, t5, t6 are assigned to node n2:
Execution cost, x = x11 + x21 + x31 + x42 + x52 + x62
= 5 + 2 + 4 + 3 + 2 + 4 = 20
Communication cost, c = c14 + c15 + c16 + c24 + c25 + c26
+ c34 + c35 + c36 = 0 + 0 + 12 + 12 + 3 + 0 + 0 + 11 +
0 = 38. Hence total cost = 58.
2) Optimal assignment, where tasks t1, t2, t3, t4, t5 are
assigned to node n1 and task t6 is assigned to node n2.
Execution cost, x = x11 + x21 + x31 + x41 + x51 + x62
= 5 + 2 + 4 + 6 + 5 + 4 = 26
Communication cost, c = c16 + c26 + c36 + c46 + c56
= 12 + 0 + 0 + 0 + 0 = 12
Total cost = 38
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Optimal assignments are found by first creating a static assignment graph. In this graph,
the weights of the edges joining pairs of task nodes represent inter-task communication
costs. The weight on the edge joining a task node to node n1 represents the execution
cost of that task on node n2 and vice-versa. Then we determine a minimum cutset in
this graph.
A cutset is defined to be a set of edges such that when these edges are removed, the nodes
of the graph are partitioned into two disjoint subsets such that nodes in one subset are
reachable from n1 and the nodes in the other are reachable from n2. Each task node is
reachable from either n1 or n2. The weight of a cutset is the sum of the weights of the
edges in the cutset. This sums up the execution and communication costs for that
assignment. An optimal assignment is found by finding a minimum cutset.
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Load-balancing
algorithms
Static
Deterministic
Dynamic
Probabilistic
Centralized
Distributed
Cooperative

Noncooperative
A Taxonomy of Load-Balancing Algorithms
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
Static versus Dynamic
◦ Static algorithms use only information about the
average behavior of the system
◦ Static algorithms ignore the current state or load of
the nodes in the system
◦ Dynamic algorithms collect state information and
react to system state if it changed
◦ Static algorithms are much more simpler
◦ Dynamic algorithms are able to give significantly
better performance
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
Deterministic versus Probabilistic
◦ Deterministic algorithms use the information about
the properties of the nodes and the characteristic of
processes to be scheduled
◦ Probabilistic algorithms use information of static
attributes of the system (e.g. number of nodes,
processing capability, topology) to formulate simple
process placement rules
◦ Deterministic approach is difficult to optimize
Probabilistic approach has poor performance
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
Centralized versus Distributed
◦ Centralized approach collects information to server
node and makes assignment decision
◦ Distributed approach contains entities to make
decisions on a predefined set of nodes
◦ Centralized algorithms can make efficient
decisions, have lower fault-tolerance
◦ Distributed algorithms avoid the bottleneck of
collecting state information and react faster
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
Cooperative versus Noncooperative
◦ In Noncooperative algorithms entities act as
autonomous ones and make scheduling decisions
independently from other entities
◦ In Cooperative algorithms distributed entities
cooperate with each other
◦ Cooperative algorithms are more complex and
involve larger overhead
◦ Stability of Cooperative algorithms are better
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26. Resource Management

Load estimation policy
◦ determines how to estimate the workload of a node

Process transfer policy
◦ determines whether to execute a process locally or remote

State information exchange policy
◦ determines how to exchange load information among nodes

Location policy
◦ determines to which node the transferable process should be sent

Priority assignment policy
◦ determines the priority of execution of local and remote processes

Migration limiting policy
◦ determines the total number of times a process can migrate
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27. Resource Management


To balance the workload on all the nodes of the
system, it is necessary to decide how to measure the
workload of a particular node
Some measurable parameters (with time and node
dependent factor) can be the following:
◦
◦
◦
◦

Total number of processes on the node
Resource demands of these processes
Instruction mixes of these processes
Architecture and speed of the node’s processor
Several load-balancing algorithms use the total
number of processes to achieve big efficiency
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
In some cases the true load could vary widely
depending on the remaining service time, which can
be measured in several way:
◦ Memoryless method assumes that all processes have the
same expected remaining service time, independent of the
time used so far
◦ Pastrepeats assumes that the remaining service time is equal
to the time used so far
◦ Distribution method states that if the distribution service
times is known, the associated process’s remaining service
time is the expected remaining time conditioned by the time
already used
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29. Resource Management




None of the previous methods can be used in modern
systems because of periodically running processes
and daemons
An acceptable method for use as the load estimation
policy in these systems would be to measure the CPU
utilization of the nodes
Central Processing Unit utilization is defined as the
number of CPU cycles actually executed per unit of
real time
It can be measured by setting up a timer to
periodically check the CPU state (idle/busy)
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

Most of the algorithms use the threshold policy to
decide on whether the node is lightly-loaded or
heavily-loaded
Threshold value is a limiting value of the workload of
node which can be determined by
◦ Static policy: predefined threshold value for each node
depending on processing capability
◦ Dynamic policy: threshold value is calculated from average
workload and a predefined constant

Below threshold value node accepts processes to
execute, above threshold value node tries to transfer
processes to a lightly-loaded node
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31. Resource Management

Single-threshold policy may lead to unstable
algorithm because underloaded node could turn to be
overloaded right after a process migration
Overloaded
Overloaded
High mark
Threshold
Underloaded
Single-threshold policy

Normal
Low mark
Underloaded
Double-threshold policy
To reduce instability double-threshold policy has
been proposed which is also known as high-low
policy
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
Double threshold policy
◦ When node is in overloaded region new local
processes are sent to run remotely, requests to
accept remote processes are rejected
◦ When node is in normal region new local processes
run locally, requests to accept remote processes are
rejected
◦ When node is in under loaded region new local
processes run locally, requests to accept remote
processes are accepted
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
Threshold method
◦ Policy selects a random node, checks whether the node is
able to receive the process, then transfers the process. If
node rejects, another node is selected randomly. This
continues until probe limit is reached.

Shortest method
◦ L distinct nodes are chosen at random, each is polled to
determine its load. The process is transferred to the node
having the minimum value unless its workload value
prohibits to accept the process.
◦ Simple improvement is to discontinue probing whenever a
node with zero load is encountered.
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34. Resource Management

Bidding method
◦ Nodes contain managers (to send processes) and contractors
(to receive processes)
◦ Managers broadcast a request for bid, contractors respond
with bids (prices based on capacity of the contractor node)
and manager selects the best offer
◦ Winning contractor is notified and asked whether it accepts
the process for execution or not
◦ Full autonomy for the nodes regarding scheduling
◦ Big communication overhead
◦ Difficult to decide a good pricing policy
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35. Resource Management

Pairing
◦ Contrary to the former methods the pairing policy is to
reduce the variance of load only between pairs
◦ Each node asks some randomly chosen node to form a pair
with it
◦ If it receives a rejection it randomly selects another node and
tries to pair again
◦ Two nodes that differ greatly in load are temporarily paired
with each other and migration starts
◦ The pair is broken as soon as the migration is over
◦ A node only tries to find a partner if it has at least two
processes
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36. Resource Management

Dynamic policies require frequent exchange of state
information, but these extra messages arise two
opposite impacts:
◦ Increasing the number of messages gives more accurate
scheduling decision
◦ Increasing the number of messages raises the queuing time
of messages

State information policies can be the following:
◦
◦
◦
◦
Periodic broadcast
Broadcast when state changes
On-demand exchange
Exchange by polling
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
Periodic broadcast
◦ Each node broadcasts its state information after the elapse of
every T units of time
◦ Problem: heavy traffic, fruitless messages, poor scalability
since information exchange is too large for networks having
many nodes

Broadcast when state changes
◦ Avoids fruitless messages by broadcasting the state only
when a process arrives or departures
◦ Further improvement is to broadcast only when state
switches to another region (double-threshold policy)
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38. Resource Management

On-demand exchange
◦ In this method a node broadcast a State-Information-Request
message when its state switches from normal to either
underloaded or overloaded region.
◦ On receiving this message other nodes reply with their own
state information to the requesting node
◦ Further improvement can be that only those nodes reply
which are useful to the requesting node

Exchange by polling
◦ To avoid poor scalability (coming from broadcast messages)
the partner node is searched by polling the other nodes on by
one, until poll limit is reached
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
Selfish
◦ Local processes are given higher priority than remote processes. Worst
response time performance of the three policies.

Altruistic
◦ Remote processes are given higher priority than local processes. Best
response time performance of the three policies.

Intermediate
◦ When the number of local processes is greater or equal to the number of
remote processes, local processes are given higher priority than remote
processes. Otherwise, remote processes are given higher priority than
local processes.
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
This policy determines the total number of times a
process can migrate
◦ Uncontrolled
 A remote process arriving at a node is treated just as a process
originating at a node, so a process may be migrated any number of
times
◦ Controlled
 Avoids the instability of the uncontrolled policy
 Use a migration count parameter to fix a limit on the number of time a
process can migrate
 Irrevocable migration policy: migration count is fixed to 1
 For long execution processes migration count must be greater than 1
to adapt for dynamically changing states
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41. Resource Management

Drawbacks of Load-balancing approach
◦ Load balancing technique with attempting equalizing the workload on
all the nodes is not an appropriate object since big overhead is generated
by gathering exact state information
◦ Load balancing is not achievable since number of processes in a node is
always fluctuating and temporal unbalance among the nodes exists every
moment

Basic ideas for Load-sharing approach
◦ It is necessary and sufficient to prevent nodes from being idle while
some other nodes have more than two processes
◦ Load-sharing is much simpler than load-balancing since it only attempts
to ensure that no node is idle when heavily node exists
◦ Priority assignment policy and migration limiting policy are the same as
that for the load-balancing algorithms
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


Since load-sharing algorithms simply attempt to
avoid idle nodes, it is sufficient to know whether a
node is busy or idle
Thus these algorithms normally employ the simplest
load estimation policy of counting the total number of
processes
In modern systems where permanent existence of
several processes on an idle node is possible,
algorithms measure CPU utilization to estimate the
load of a node
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43. Resource Management





Algorithms normally use all-or-nothing strategy
This strategy uses the threshold value of all the
nodes fixed to 1
Nodes become receiver node when it has no
process, and become sender node when it has
more than 1 process
To avoid processing power on nodes having zero
process load-sharing algorithms use a threshold
value of 2 instead of 1
When CPU utilization is used as the load estimation
policy, the double-threshold policy should be used
as the process transfer policy
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44. Resource Management

Location policy decides whether the sender node or
the receiver node of the process takes the initiative
to search for suitable node in the system, and this
policy can be the following:
◦ Sender-initiated location policy
 Sender node decides where to send the process
 Heavily loaded nodes search for lightly loaded nodes
◦ Receiver-initiated location policy
 Receiver node decides from where to get the process
 Lightly loaded nodes search for heavily loaded nodes
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45. Resource Management

Sender-initiated location policy
◦ Node becomes overloaded, it either broadcasts or randomly
probes the other nodes one by one to find a node that is
able to receive remote processes
◦ When broadcasting, suitable node is known as soon as
reply arrives

Receiver-initiated location policy
◦ Nodes becomes underloaded, it either broadcast or
randomly probes the other nodes one by one to indicate its
willingness to receive remote processes

Receiver-initiated
policy
require
preemptive
process migration facility since scheduling
decisions are usually made at process departure
epochs
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46. Resource Management

Experiences with location policies
◦ Both
policies
gives
substantial
performance
advantages over the situation in which no loadsharing is attempted
◦ Sender-initiated policy is preferable at light to
moderate system loads
◦ Receiver-initiated policy is preferable at high system
loads
◦ Sender-initiated policy provide better performance for
the case when process transfer cost significantly more
at receiver-initiated than at sender-initiated policy
due to the preemptive transfer of processes
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47. Resource Management


In load-sharing algorithms it is not necessary for the nodes
to periodically exchange state information, but needs to know
the state of other nodes when it is either underloaded or
overloaded
Broadcast when state changes
◦ In sender-initiated/receiver-initiated location policy a node
broadcasts State Information Request when it becomes
overloaded/underloaded
◦ It is called broadcast-when-idle policy when receiver-initiated
policy is used with fixed threshold value value of 1

Poll when state changes
◦ In large networks polling mechanism is used
◦ Polling mechanism randomly asks different nodes for state
information until find an appropriate one or probe limit is reached
◦ It is called poll-when-idle policy when receiver-initiated policy is
used with fixed threshold value value of 1
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48. Resource Management


Resource manager of a distributed system
schedules the processes to optimize combination of
resources
usage,
response
time,
network
congestion, scheduling overhead
Three different approaches has been discussed
◦ Task assignment approach deals with the assignment of
task in order to minimize inter process communication
costs and improve turnaround time for the complete
process, by taking some constraints into account
◦ In load-balancing approach the process assignment
decisions attempt to equalize the avarage workload on all
the nodes of the system
◦ In load-sharing approach the process assignment decisions
attempt to keep all the nodes busy if there are sufficient
processes in the system for all the nodes
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49. Resource Management
component faults



Transient faults: occur once and then disappear.
E.g. a bird flying through the beam of a microwave
transmitter may cause lost bits on some network. If
retry, may work.
Intermittent faults: occurs, then vanishes, then
reappears, and so on. E.g. A loose contact on a
connector.
Permanent faults: continue to exist until the fault is
repaired. E.g. burnt-out chips, software bugs, and
disk head crashes.
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50. Resource Management
There are two types of processor faults:
1.
2.
Fail-silent faults: a faulty processor just
stops and does not respond
Byzantine faults: continue to run but give
wrong answers
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51. Resource Management

Synchronous systems: a system that has
the property of always responding to a
message within a known finite bound if it
is working is said to be synchronous.
Otherwise, it is asynchronous.
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52. Resource Management
There are three kinds of fault tolerance
approaches:
1. Information redundancy: extra bit to recover
from garbled bits.(ex. Hamming code)
2. Time redundancy: do again(using atomic
transaction, useful in transient & intermittent
faults)
3. Physical redundancy: add extra components.
There are two ways to organize extra
physical equipment: active replication (use
the components at the same time) and
primary backup (use the backup if one fails).
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53. Resource Management
A
B
C
voter
A1
V1
B1
V4
C1
V7
A2
V2
B2
V5
C2
V8
A3
V3
B3
V6
C3
V9
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54. Resource Management


A system is said to be k fault tolerant if it
can survive faults in k components and still
meet its specifications.
K+1 processors can fault tolerant k failstop faults. If k of them fail, the one left can
work. But need 2k+1 to tolerate k Byzantine
faults because if k processors send out
wrong replies, but there are still k+1
processors giving the correct answer. By
majority vote, a correct answer can still be
obtained.
Sandeep Kumar Poonia
11/10/2013
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55. Resource Management
1. Request
Client
2. Do work
3. Update
Primary
6. Reply
4. Do work
Backup
5. Ack
Sandeep Kumar Poonia
11/10/2013
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56. Resource Management
Backward recovery – checkpoints.
 In
the
checkpointing
method,
undesirable situations can occur:

two
Lost message- The state of process Pi indicates
that it has sent a message m to process Pj. Pj has
no record of receiving this message.

Orphan message- The state of process Pj is such
that it has received a message m from the process
Pi but the state of the process Pi is such that it has
never sent the message m to Pj.
Sandeep Kumar Poonia
11/10/2013
56

57. Resource Management


A strongly consistent set of checkpoints
consist of a set of local checkpoints such that
there is no orphan or lost message.
A consistent set of checkpoints consists of a
set of local checkpoints such that there is no
orphan message.
Sandeep Kumar Poonia
11/10/2013
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58. Resource Management
Current checkpoint
Pi
m
Pj
failure
Current checkpoint
Sandeep Kumar Poonia
11/10/2013
58

59. Resource Management


a processor Pi needs to take a checkpoint
only if there is another process Pj that has
taken a checkpoint that includes the receipt
of a message from Pi and Pi has not recorded
the sending of this message.
In this way no orphan message will be
generated.
Sandeep Kumar Poonia
11/10/2013
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60. Resource Management

Each
process
takes
its
checkpoints
independently without any coordination.
Sandeep Kumar Poonia
11/10/2013
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61. Resource Management

Synchronous checkpoints are established in a
longer
period
while
asynchronous
checkpoints are used in a shorter period.
That is, within a synchronous period there are
several asynchronous periods.
Sandeep Kumar Poonia
11/10/2013
61

62. Resource Management
Two-army problem
 Two blue armies must reach agreement to
attack a red army. If one blue army attacks
by itself it will be slaughtered. They can
only communicate using an unreliable
channel: sending a messenger who is
subject to capture by the red army.

They can never reach an agreement on
attacking.
Sandeep Kumar Poonia
11/10/2013
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63. Resource Management

Now assume the communication is perfect
but the processors are not. The classical
problem is called the Byzantine generals
problem.
N generals and M of them are
traitors. Can they reach an agreement?
Sandeep Kumar Poonia
11/10/2013
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64. Resource Management
1
1
1
2
x
3
2
2
y
1
z
4
2
4
N=4
M=1
4
4
Sandeep Kumar Poonia
11/10/2013
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4

65. Resource Management

After the first round
1 got (1,2,x,4); 2 got (1,2,y,4);
3 got (1,2,3,4); 4 got (1,2,z,4)

After the second round
1 got (1,2,y,4), (a,b,c,d), (1,2,z,4)
2 got (1,2,x,4), (e,f,g,h), (1,2,z,4)
4 got (1,2,x,4), (1,2,y,4), (i,j,k,l)

Majority
1 got (1,2,_,4); 2 got (1,2,_,4); 4 got (1,2,_,4)

So all the good generals know that 3 is the
bad guy.
Sandeep Kumar Poonia
11/10/2013
65

66. Resource Management


If there are m faulty processors, agreement
can be achieved only if 2m+1 correct
processors are present, for a total of 3m+1.
Suppose n=3, m=1. Agreement cannot be
reached.
Sandeep Kumar Poonia
11/10/2013
66

67. Resource Management
1
1
2
2
2
x
1
y
3
After the first round
1 got (1,2,x); 2 got (1,2,y); 3 got (1,2,3)
After the second round
1 got (1,2,y), (a,b,c)
2 got (1,2,x), (d,e,f)
No majority. Cannot reach an agreement.
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11/10/2013
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