CprE 458/558: Real-Time Systems

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CprE 458/558: Real-Time Systems (G. Manimaran) 1 CprE 458/558: Real-Time Systems Distributed Real-Time Systems (contd.)

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CprE 458/558: Real-Time Systems. Distributed Real-Time Systems (contd.). Layered architecture of a node in a distributed real-time system. SENDER. RECEIVER. Local scheduling. Resource Reclaiming. Resource Reclaiming. Task Scheduling. Task Scheduling. Information Exchange. TP. SP. - PowerPoint PPT Presentation

Transcript of CprE 458/558: Real-Time Systems

Page 1: CprE 458/558: Real-Time Systems

CprE 458/558: Real-Time Systems (G. Manimaran) 1

CprE 458/558: Real-Time Systems

Distributed Real-Time Systems (contd.)

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Layered architecture of a node in a distributed real-time system

Location policy

Task Scheduling

Resource

Reclaiming

TP SP IP

Routi

ng

Sch

ed.Call

Admission

Control

Location policy

Task Scheduling

IP SP TP

Routi

ng

Sch

ed.Call

Admission

Control

Resource

Reclaiming

Routi

ng

Sch

ed.Call

Admission

Control

Message Flow

Real-Time Channel Establishment

Information Exchange

SENDER RECEIVER

INTERMEDIATE NODE

Local scheduling

Global scheduling

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Algo 1: Focused Addressing with Bidding (FAB)

• Information policy– Periodic– Fraction of CPU available

• Transfer policy– Local scheduler admission decision

• Selection policy– The task that fails the admission test

• Location policy– Focused node with bidding

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Focused addressing with bidding

• Focused node (Ns) may not have enough surplus for accommodating the migrated task, due to stale state info.

• In parallel, the sender sends request for bid (RFB) message to other lightly loaded nodes (based on estimate various times), asking them to send bid to Ns for receiving the migrated task. The RFB contains info about the task.

• Bid specifies how quickly the node can process the task, etc.

• If Ns cannot guarantee the task, it evaluates the bids and (re)migrates the task to the best bidder.

• In all theses calculations, the decision time, scheduling time, migration time are estimated and added with comp. time to see if the task can meet the deadline. If not, no bid is sent.

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Algo 2: Buddy set algorithm

• Transfer policy– Threshold-based – three thresholds are maintained based on

which the node’s state is identified as Underload (U), Normal, Overload

• Selection policy– The tasks that fail admission test at the local node

• Information policy– Based on buddy set.– When a node makes transition into or out of U state, it informs

its buddies of its state

• Location policy– One of the buddies is chosen as the receiver, based on the

load info provided by the info policy

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Buddy set algorithm (contd.) -- Issues

• Choosing buddy set– Too large set: high communication overhead– Too small set: may not be able to find a suitable receiver within a

buddy set– Topology needs to be taken into account while choosing the buddy

nodes

• Choice of thresholds– Larger Upper threshold: lower the rate at which tasks will be

migrated– The choices of thresholds depend on size of buddy set, topology,

network bandwidth

• Thrashing– A node, X, could be a buddy for several nodes. When many of these

several nodes become overloaded, they migrate their tasks to the node X and making it overloaded. This results in further migration of task.

– Therefore, the buddy set should be carefully constructed.

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Algo 3: Integrated scheme

• Information policy– Based on Maekawa set concept

• Transfer policy and Info policy– Load estimation based on tasks in the queue

• Location policy– Chooses receiver node not only based on node

state but also the link/path state so as to achieve feasible (bounded) task migration

• Promotes interaction among schedulers– Message scheduler and Transfer policy– Message scheduler and Location policy

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Maekawa set based information policy

• Based on symmetric set concept• Fully decentralized algorithm• Each node assumes equal responsibility in obtaining global state

• Each node maintains three sets

– Request set (Ri): Set of nodes to whom request the state info– Information set (Si): Set of nodes to whom sent your state information– Status set (Si): Set of nodes whose state is maintained by the given node

– For all i, j: Intersection(Ri,Rj) is not null; Keep the size of the set minimum.

• Message complexity for obtaining global info is K = O(Sqrt(N)) as opposed to O(N), where N is the number of nodes

– Optimal set size exists for: N = K * (K-1) + 1. Other values of N: degenerate case.

• Construction method: Finite projective plane, Grid method

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R1 = I1 = {1,2,4} S1 = {1,5,7}

R2 = I2 = {2,3,5} S2 = {1,2,6}

R3 = I3 = {3,4,6} S3 = {2,3,7}

R4 = I4 = {4,5,7} S4 = {1,3,4}

R5 = I5 = {5,6,1} S5 = {2,4,5}

R6 = I6 = {6,7,2} S6 = {3,5,6}

R7 = I7 = {7,1,3} S7 = {4,6,7}

Maekawa sets – example for 7 nodes

•Request set (Ri): Set of nodes to which it sends requests for state information

•Information set (Ii): Set of nodes to which it sends information about its state

•Status set (Si): Set of nodes whose state information it maintains