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

2. CprE 458/558: Real-Time Systems (G. Manimaran)2 Layered architecture of a node in a distributed real-time system Location policy Task Scheduling Resource Reclaiming TPSPIP Routing Sched. Call Admission Control Location policy Task Scheduling IPSPTP Routing Sched. Call Admission Control Resource Reclaiming Routing Sched. Call Admission Control Message Flow Real-Time Channel Establishment Information Exchange SENDERRECEIVER INTERMEDIATE NODE Local scheduling Global scheduling

3. CprE 458/558: Real-Time Systems (G. Manimaran)3 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

4. CprE 458/558: Real-Time Systems (G. Manimaran)4 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.

5. CprE 458/558: Real-Time Systems (G. Manimaran)5 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

6. CprE 458/558: Real-Time Systems (G. Manimaran)6 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.

7. CprE 458/558: Real-Time Systems (G. Manimaran)7 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

8. CprE 458/558: Real-Time Systems (G. Manimaran)8 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

9. CprE 458/558: Real-Time Systems (G. Manimaran)9 R 1 = I 1 = {1,2,4}S 1 = {1,5,7} R 2 = I 2 = {2,3,5}S 2 = {1,2,6} R 3 = I 3 = {3,4,6}S 3 = {2,3,7} R 4 = I 4 = {4,5,7}S 4 = {1,3,4} R 5 = I 5 = {5,6,1}S 5 = {2,4,5} R 6 = I 6 = {6,7,2}S 6 = {3,5,6} R 7 = I 7 = {7,1,3}S 7 = {4,6,7} Maekawa sets – example for 7 nodes Request set (R i ): Set of nodes to which it sends requests for state information Information set (I i ): Set of nodes to which it sends information about its state Status set (Si): Set of nodes whose state information it maintains