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Faculty of Sciences, University of Porto
On the Integration of Real-Time and Fault-Tolerance
in P2P Middleware
Rolando Martins
Scientific Advisors:
Lu´ıs Lopes, Faculty of Science - University of Porto
Fernando Silva, Faculty of Science - University of Porto
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 1
Faculty of Sciences, University of Porto
Target Systems
EFACEC’s Oporto light-train deployment
5 lines, 70 stations, trains multiplexed over 5 lines
70+ computational nodes (peers), 200+ sensors, arbitrary topology
Traffic comprised of normal operations, critical events, alarms
Tight timing, e.g., 2s for end-to-end response time
Deployments across cities/regions can be overwhelmingly large
What is needed to support such systems?
Peer-to-peer (P2P) infrastructure that mirrors physical deployment
Combined real-time and fault-tolerance guarantees
Hierarchical abstraction (cells) to scale to large deployments
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 2
Faculty of Sciences, University of Porto
In Search of a Solution
FT
FT+P2P
P2P
RT+P2P
RT+FT RT+FT+P2P
RT
Video
Streaming
Distributed
storage
Pastry
CORBA RT FT
DDS
CORBA FT
Stheno
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 3
Faculty of Sciences, University of Porto
Research Challenges and Opportunities
Challenges
FT mechanisms consume additional resources
FT mechanisms add overhead (e.g., additional latency)
Different traffic types have different soft-RT requirements
Different traffic types may require different FT configurations
RT requirements must continue to be met even under faults
Opportunities
P2P infrastructures have network-aware resilience
COTS operating systems have priority-based scheduling,
multi-threading and resource-reservation mechanisms
Proven FT configuration options exist (replication styles)
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 4
Faculty of Sciences, University of Porto
Research Question
Can we opportunistically leverage and integrate these proven strategies to
simultaneously support soft-RT and FT to meet the needs of our target
systems?
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 5
Faculty of Sciences, University of Porto
Scope
Non-Goals
Handling value faults and byzantine faults
Formal specification and verification of the system
Support for hard real-time
Fully optimized implementation
Testing in production (not yet)
Assumptions
Fault model: crash of a peer, message loss
Resource-reservation mechanisms are always available
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 6
Faculty of Sciences, University of Porto
Stheno: System Architecture
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 7
Faculty of Sciences, University of Porto
Stheno: Operating-System Interface
Problem: Control and monitor resource usage from userspace
Solution:
Leverage threads, priorities, /proc
Resource reservation
CPU partitioning
Example:
Highly critical surveillance feed has reserved amount of CPU for
processing
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 8
Faculty of Sciences, University of Porto
Stheno: Support Framework
Problem: Tasks have different RT requirements
Solution:
Leverage threading policies
QoS Daemon
Example:
Thread-per-Connection used for critical events in our target system to
achieve low latency
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 9
Faculty of Sciences, University of Porto
Stheno: P2P Overlay and FT Configuration
Problem: Tailor choice of P2P overlay and FT configuration to
application needs
Solution:
High-level API to support alternative overlays, e.g., P3, Pastry
Leverage proven replication styles, e.g., active, semi-active, passive
Configure replication properties, e.g., number and placement of replicas
Support service discovery
Example:
P3 mirrors regional hierarchy of target system
Active replication for critical tasks needing instantaneous fail-over
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 10
Faculty of Sciences, University of Porto
Stheno: Core
Problem: Manage services with different RT and FT requirements
Solution:
QoS daemon proxy
Service repository
Creator and coordinator of service instances and clients
Delegation of service discovery to the P2P layer
Example:
Service repository could include RPC, streaming service, etc
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 11
Faculty of Sciences, University of Porto
Stheno: Application and Services
Problem: Expose system functionalities and configuration options to
the user
Solution:
High-level APIs for querying and configuring different layers
Example:
Create a video streaming service from light-train station and set the
frame rate and replication style
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 12
Faculty of Sciences, University of Porto
Stheno: Interaction between Layers
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 13
Faculty of Sciences, University of Porto
Proof-of-Concept Prototype
First prototype implementation in Java had more than 50k SLOC
Current (unoptimized) prototype implementation in C/C++ with
more than 60k SLOC
P3 overlay plugin implementation
CPU resource reservation
Thread priorities: three classes corresponding to low, medium and
high criticality
Threading policies: Thread-per-Connection, Thread-per-Request,
Leader-Followers
Semi-active replication style
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 14
Faculty of Sciences, University of Porto
Empirical Evaluation
Goals: To quantify
Overhead of fault-tolerance mechanisms with/without faults
Impact of background workload and faults on end-to-end latency
Metrics:
End-to-end latency, jitter, recovery time
Experimental setup:
20 nodes, each quad-core AMD Phenom with 4GB RAM
100 Mbit/s switch
Experimental procedure:
Used a P3
-based overlay, semi-active replication
Run of 1000 invocations
Fault-injection mid-way through each run
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 15
Faculty of Sciences, University of Porto
End-to-End Latency Results
4 replicas, without resource reservation: max time of 1s/invocation
4 replicas, With resource reservation: max time of 1ms/invocation
0 10 20 30 40 50 60 70 80 90 100
Load (%)
100
101
102
103
104
Latency(ms)
Legend:
No FT
1 Replica
2 Replicas
4 Replicas
(a) Without resource reservation.
0 10 20 30 40 50 60 70 80 90 100
Load (%)
100
101
102
103
104
Latency(ms)
Legend:
No FT
1 Replica
2 Replicas
4 Replicas
(b) With resource reservation.
Stheno’s RT+FT support meets and exceeds target system
requirements (2s end-to-end response time, even under a fault)
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 16
Faculty of Sciences, University of Porto
Fail-over Latency Results
Without resource reservation: max fail-over time of 3s
With resource reservation: max fail-over time of 30ms
0 10 20 30 40 50 60 70 80 90 100
Load (%)
101
102
103
104
Latency(ms)
Legend:
1 Replica
2 Replicas
4 Replicas
(a) Without resource reservation.
0 10 20 30 40 50 60 70 80 90 100
Load (%)
101
102
103
104
Latency(ms)
Legend:
1 Replica
2 Replicas
4 Replicas
(b) With resource reservation.
Stheno’s RT+FT provides low fail-over latency that meets
target system requirements
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 17
Faculty of Sciences, University of Porto
Thesis Contributions
Stheno, an RT+FT+P2P middleware
Motivated by the timing, reliability and physical deployment
characteristics of our target systems
To the best of our knowledge, Stheno is the first system that
Supports traffic types with different soft-RT requirements
Supports different FT configurations
Supports configurability at multiple levels: P2P, RT and FT
Continues to meet RT requirements even under faults
Implementation of a proof-of-concept prototype
Empirical evaluation demonstrates that
Stheno meets and exceeds target system requirements for end-to-end
latency and fail-over latency
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 18
Faculty of Sciences, University of Porto
Thank You
Stheno, in Greek mythology, was
the eldest of the three Gorgons.
She was known to be the most
independent and ferocious, hav-
ing killed more men than both
of her sisters combined. (source
Wikipedia)
In many ways, Stheno represents
the complexity of the problem that
we set out to solve.
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 19
Faculty of Sciences, University of Porto
Publications
Rolando Martins, Lu´ıs Lopes and Fernando Silva. Lightweight Fault-Tolerance for Peer-to-Peer
Middleware (full version). Technical Report DCC-2011-01, Department of Computer Science, Faculty
of Sciences, University of Porto, 2011.
Rolando Martins, Priya Narasimhan, Lu´ıs Lopes, and Fernando Silva. Lightweight Fault-Tolerance for
Peer-to-Peer Middleware. In Proceedings of the 29th IEEE Symposium on Reliable Distributed Systems
(SRDS’10), pages 313-317, November 2010.
Rolando Martins, Priya Narasimhan, Lu´ıs Lopes and Fernando Silva. On the Impact of Fault-Tolerance
Mechanisms in a Peer-to-Peer Middleware. Technical Report DCC-2010-02, Department of Computer
Science, Faculty of Sciences, University of Porto, 2010.
Rolando Martins, Lu´ıs Lopes, and Fernando Silva. A Peer-to-Peer Middleware Platform for QoS and
Soft Real-Time Computing. Technical Report DCC-2008-02, Department of Computer Science,
Faculty of Sciences, University of Porto, 2008.
Rolando Martins, Lu´ıs Lopes, and Fernando Silva. A Peer-To-Peer Middleware Platform for
Fault-Tolerant, QoS, Real-Time Computing. In Proceedings of the 2nd Workshop on
Middleware-Application Interaction, part of DisCoTec 2008, pages 1-6, New York, NY, USA, June
2008. ACM.
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 20
Faculty of Sciences, University of Porto
Replication Groups Over Group Communications
(a) Semi-active (b) Passive
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 21
Faculty of Sciences, University of Porto
Resource Reservation Daemon
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 22
Faculty of Sciences, University of Porto
Multicore: Examples of CPU Partitioning.
(a) Quad-core partitioning. (b) Six-core partitioning.
(c) Eight-core partitioning.
Core Os: Threads belonging to the operating system
BE: Threads served by SCHED OTHER scheduling policy
RT: Threads served by SCHED {FIFO,RR} scheduling policies
Isolated RT: Isolated RT threads that are isolated from all other
threads present in the system
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 23
Faculty of Sciences, University of Porto
RT Support: Object-to-Object interactions.
(a) Direct calling with dif-
ferent partitions.
(b) Direct calling within the
same partition.
(c) Deferred calling with different partitions.
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 24
Faculty of Sciences, University of Porto
Threading Strategies
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 25
Faculty of Sciences, University of Porto
Minimizing Priority Inversion Through Traffic
Demultiplexing
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 26
Faculty of Sciences, University of Porto
Minimizing Priority Inversion Through Traffic
Demultiplexing
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 27
Faculty of Sciences, University of Porto
Putting It All Together
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 28
Faculty of Sciences, University of Porto
Putting It All Together (Continuation)
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 29
Faculty of Sciences, University of Porto
Execution Context/Execution Model (ECEM) Design
Pattern
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 30
Faculty of Sciences, University of Porto
Comparison with other Middlewares (RPC)
0 10 20 30 40 50 60 70 80 90 100
Load (%)
101
102
103
104
105
Latency(us)
Legend:
Stheno, No QoS
Stheno, QoS
ICE
TAO
RMI
Our approach enable us to provide a 200us latency even in the
presence of a 95% CPU workload
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 31
Faculty of Sciences, University of Porto
Related Work
1 - Decentralized scalability:
Lic´ınio Oliveira, Lu´ıs Lopes, and Fernando Silva. P3 : Parallel Peer to Peer - An Internet Parallel Programming
Environment. In Workshop on Web Engineering & Peer-to-Peer Computing, part of Networking 2002, volume
2376 of Lecture Notes in Computer Science, pages 274-288. Springer-Verlag, May 2002.
A. Rowstron and P. Druschel. Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale
Peer-to-Peer Systems. In Proceedings of the 2nd ACM/IFIP/USENIX International Middleware Conference
(Middleware’01), pages 329-350, November 2001.
2 - Modular FT:
Tudor Dumitra, Deepti Srivastava, and Priya Narasimhan. Architecting and Implementing Versatile
Dependability. In Rog´erio de Lemos, Cristina Gacek, and Alexander Romanovsky, editors, Architecting
Dependable Systems III, volume 3549 of Lecture Notes in Computer Science, pages 212-231. Springer Berlin /
Heidelberg, 2005.
P. Bond P. Barrett, A. Hilborne, Lu´ıs Rodrigues, D. Seaton, N. Speirs, and Paulo Ver´ıssimo. The Delta-4 Extra
Performance Architecture (XPA). 20th International Symposium on Fault-Tolerant Computing, pages 481-488,
1990.
3 - Resource reservation + CPU partitioning:
Chen Lee, R. Rajkumar and Cliff Mercer, Experiences with Processor Reservation and Dynamic QoS in
Real-Time Mach, In Proceedings of Multimedia Japan, March 1996
Luigi Palopoli, Tommaso Cucinotta, Luca Marzario, and Giuseppe Lipari. AQuoSA - Adaptive Quality of Service
Architecture. Software: Practice and Experience, 39(1):1-31, April 2009.
4 - Real-time support:
Priya Narasimhan, Tudor Dumitras , Aaron Paulos, Soila Pertet, Carlos Reverte, Joseph Slember, and Deepti
Srivastava. MEAD: Support for Real-Time Fault- Tolerant CORBA: Research Articles. Concurrency and
Computation: Practice & Experience 17(12):1527-1545, October 2005.
Douglas Schmidt, David Levine, and Sumedh Mungee. The Design of the TAO Real-Time Object Request
Broker. Computer Communications, 21(4):294-324, 1998.
Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 32

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PhDDefenseRolandoMartins

  • 1. Faculty of Sciences, University of Porto On the Integration of Real-Time and Fault-Tolerance in P2P Middleware Rolando Martins Scientific Advisors: Lu´ıs Lopes, Faculty of Science - University of Porto Fernando Silva, Faculty of Science - University of Porto Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 1
  • 2. Faculty of Sciences, University of Porto Target Systems EFACEC’s Oporto light-train deployment 5 lines, 70 stations, trains multiplexed over 5 lines 70+ computational nodes (peers), 200+ sensors, arbitrary topology Traffic comprised of normal operations, critical events, alarms Tight timing, e.g., 2s for end-to-end response time Deployments across cities/regions can be overwhelmingly large What is needed to support such systems? Peer-to-peer (P2P) infrastructure that mirrors physical deployment Combined real-time and fault-tolerance guarantees Hierarchical abstraction (cells) to scale to large deployments Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 2
  • 3. Faculty of Sciences, University of Porto In Search of a Solution FT FT+P2P P2P RT+P2P RT+FT RT+FT+P2P RT Video Streaming Distributed storage Pastry CORBA RT FT DDS CORBA FT Stheno Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 3
  • 4. Faculty of Sciences, University of Porto Research Challenges and Opportunities Challenges FT mechanisms consume additional resources FT mechanisms add overhead (e.g., additional latency) Different traffic types have different soft-RT requirements Different traffic types may require different FT configurations RT requirements must continue to be met even under faults Opportunities P2P infrastructures have network-aware resilience COTS operating systems have priority-based scheduling, multi-threading and resource-reservation mechanisms Proven FT configuration options exist (replication styles) Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 4
  • 5. Faculty of Sciences, University of Porto Research Question Can we opportunistically leverage and integrate these proven strategies to simultaneously support soft-RT and FT to meet the needs of our target systems? Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 5
  • 6. Faculty of Sciences, University of Porto Scope Non-Goals Handling value faults and byzantine faults Formal specification and verification of the system Support for hard real-time Fully optimized implementation Testing in production (not yet) Assumptions Fault model: crash of a peer, message loss Resource-reservation mechanisms are always available Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 6
  • 7. Faculty of Sciences, University of Porto Stheno: System Architecture Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 7
  • 8. Faculty of Sciences, University of Porto Stheno: Operating-System Interface Problem: Control and monitor resource usage from userspace Solution: Leverage threads, priorities, /proc Resource reservation CPU partitioning Example: Highly critical surveillance feed has reserved amount of CPU for processing Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 8
  • 9. Faculty of Sciences, University of Porto Stheno: Support Framework Problem: Tasks have different RT requirements Solution: Leverage threading policies QoS Daemon Example: Thread-per-Connection used for critical events in our target system to achieve low latency Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 9
  • 10. Faculty of Sciences, University of Porto Stheno: P2P Overlay and FT Configuration Problem: Tailor choice of P2P overlay and FT configuration to application needs Solution: High-level API to support alternative overlays, e.g., P3, Pastry Leverage proven replication styles, e.g., active, semi-active, passive Configure replication properties, e.g., number and placement of replicas Support service discovery Example: P3 mirrors regional hierarchy of target system Active replication for critical tasks needing instantaneous fail-over Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 10
  • 11. Faculty of Sciences, University of Porto Stheno: Core Problem: Manage services with different RT and FT requirements Solution: QoS daemon proxy Service repository Creator and coordinator of service instances and clients Delegation of service discovery to the P2P layer Example: Service repository could include RPC, streaming service, etc Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 11
  • 12. Faculty of Sciences, University of Porto Stheno: Application and Services Problem: Expose system functionalities and configuration options to the user Solution: High-level APIs for querying and configuring different layers Example: Create a video streaming service from light-train station and set the frame rate and replication style Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 12
  • 13. Faculty of Sciences, University of Porto Stheno: Interaction between Layers Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 13
  • 14. Faculty of Sciences, University of Porto Proof-of-Concept Prototype First prototype implementation in Java had more than 50k SLOC Current (unoptimized) prototype implementation in C/C++ with more than 60k SLOC P3 overlay plugin implementation CPU resource reservation Thread priorities: three classes corresponding to low, medium and high criticality Threading policies: Thread-per-Connection, Thread-per-Request, Leader-Followers Semi-active replication style Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 14
  • 15. Faculty of Sciences, University of Porto Empirical Evaluation Goals: To quantify Overhead of fault-tolerance mechanisms with/without faults Impact of background workload and faults on end-to-end latency Metrics: End-to-end latency, jitter, recovery time Experimental setup: 20 nodes, each quad-core AMD Phenom with 4GB RAM 100 Mbit/s switch Experimental procedure: Used a P3 -based overlay, semi-active replication Run of 1000 invocations Fault-injection mid-way through each run Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 15
  • 16. Faculty of Sciences, University of Porto End-to-End Latency Results 4 replicas, without resource reservation: max time of 1s/invocation 4 replicas, With resource reservation: max time of 1ms/invocation 0 10 20 30 40 50 60 70 80 90 100 Load (%) 100 101 102 103 104 Latency(ms) Legend: No FT 1 Replica 2 Replicas 4 Replicas (a) Without resource reservation. 0 10 20 30 40 50 60 70 80 90 100 Load (%) 100 101 102 103 104 Latency(ms) Legend: No FT 1 Replica 2 Replicas 4 Replicas (b) With resource reservation. Stheno’s RT+FT support meets and exceeds target system requirements (2s end-to-end response time, even under a fault) Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 16
  • 17. Faculty of Sciences, University of Porto Fail-over Latency Results Without resource reservation: max fail-over time of 3s With resource reservation: max fail-over time of 30ms 0 10 20 30 40 50 60 70 80 90 100 Load (%) 101 102 103 104 Latency(ms) Legend: 1 Replica 2 Replicas 4 Replicas (a) Without resource reservation. 0 10 20 30 40 50 60 70 80 90 100 Load (%) 101 102 103 104 Latency(ms) Legend: 1 Replica 2 Replicas 4 Replicas (b) With resource reservation. Stheno’s RT+FT provides low fail-over latency that meets target system requirements Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 17
  • 18. Faculty of Sciences, University of Porto Thesis Contributions Stheno, an RT+FT+P2P middleware Motivated by the timing, reliability and physical deployment characteristics of our target systems To the best of our knowledge, Stheno is the first system that Supports traffic types with different soft-RT requirements Supports different FT configurations Supports configurability at multiple levels: P2P, RT and FT Continues to meet RT requirements even under faults Implementation of a proof-of-concept prototype Empirical evaluation demonstrates that Stheno meets and exceeds target system requirements for end-to-end latency and fail-over latency Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 18
  • 19. Faculty of Sciences, University of Porto Thank You Stheno, in Greek mythology, was the eldest of the three Gorgons. She was known to be the most independent and ferocious, hav- ing killed more men than both of her sisters combined. (source Wikipedia) In many ways, Stheno represents the complexity of the problem that we set out to solve. Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 19
  • 20. Faculty of Sciences, University of Porto Publications Rolando Martins, Lu´ıs Lopes and Fernando Silva. Lightweight Fault-Tolerance for Peer-to-Peer Middleware (full version). Technical Report DCC-2011-01, Department of Computer Science, Faculty of Sciences, University of Porto, 2011. Rolando Martins, Priya Narasimhan, Lu´ıs Lopes, and Fernando Silva. Lightweight Fault-Tolerance for Peer-to-Peer Middleware. In Proceedings of the 29th IEEE Symposium on Reliable Distributed Systems (SRDS’10), pages 313-317, November 2010. Rolando Martins, Priya Narasimhan, Lu´ıs Lopes and Fernando Silva. On the Impact of Fault-Tolerance Mechanisms in a Peer-to-Peer Middleware. Technical Report DCC-2010-02, Department of Computer Science, Faculty of Sciences, University of Porto, 2010. Rolando Martins, Lu´ıs Lopes, and Fernando Silva. A Peer-to-Peer Middleware Platform for QoS and Soft Real-Time Computing. Technical Report DCC-2008-02, Department of Computer Science, Faculty of Sciences, University of Porto, 2008. Rolando Martins, Lu´ıs Lopes, and Fernando Silva. A Peer-To-Peer Middleware Platform for Fault-Tolerant, QoS, Real-Time Computing. In Proceedings of the 2nd Workshop on Middleware-Application Interaction, part of DisCoTec 2008, pages 1-6, New York, NY, USA, June 2008. ACM. Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 20
  • 21. Faculty of Sciences, University of Porto Replication Groups Over Group Communications (a) Semi-active (b) Passive Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 21
  • 22. Faculty of Sciences, University of Porto Resource Reservation Daemon Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 22
  • 23. Faculty of Sciences, University of Porto Multicore: Examples of CPU Partitioning. (a) Quad-core partitioning. (b) Six-core partitioning. (c) Eight-core partitioning. Core Os: Threads belonging to the operating system BE: Threads served by SCHED OTHER scheduling policy RT: Threads served by SCHED {FIFO,RR} scheduling policies Isolated RT: Isolated RT threads that are isolated from all other threads present in the system Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 23
  • 24. Faculty of Sciences, University of Porto RT Support: Object-to-Object interactions. (a) Direct calling with dif- ferent partitions. (b) Direct calling within the same partition. (c) Deferred calling with different partitions. Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 24
  • 25. Faculty of Sciences, University of Porto Threading Strategies Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 25
  • 26. Faculty of Sciences, University of Porto Minimizing Priority Inversion Through Traffic Demultiplexing Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 26
  • 27. Faculty of Sciences, University of Porto Minimizing Priority Inversion Through Traffic Demultiplexing Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 27
  • 28. Faculty of Sciences, University of Porto Putting It All Together Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 28
  • 29. Faculty of Sciences, University of Porto Putting It All Together (Continuation) Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 29
  • 30. Faculty of Sciences, University of Porto Execution Context/Execution Model (ECEM) Design Pattern Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 30
  • 31. Faculty of Sciences, University of Porto Comparison with other Middlewares (RPC) 0 10 20 30 40 50 60 70 80 90 100 Load (%) 101 102 103 104 105 Latency(us) Legend: Stheno, No QoS Stheno, QoS ICE TAO RMI Our approach enable us to provide a 200us latency even in the presence of a 95% CPU workload Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 31
  • 32. Faculty of Sciences, University of Porto Related Work 1 - Decentralized scalability: Lic´ınio Oliveira, Lu´ıs Lopes, and Fernando Silva. P3 : Parallel Peer to Peer - An Internet Parallel Programming Environment. In Workshop on Web Engineering & Peer-to-Peer Computing, part of Networking 2002, volume 2376 of Lecture Notes in Computer Science, pages 274-288. Springer-Verlag, May 2002. A. Rowstron and P. Druschel. Pastry: Scalable, Decentralized Object Location, and Routing for Large-Scale Peer-to-Peer Systems. In Proceedings of the 2nd ACM/IFIP/USENIX International Middleware Conference (Middleware’01), pages 329-350, November 2001. 2 - Modular FT: Tudor Dumitra, Deepti Srivastava, and Priya Narasimhan. Architecting and Implementing Versatile Dependability. In Rog´erio de Lemos, Cristina Gacek, and Alexander Romanovsky, editors, Architecting Dependable Systems III, volume 3549 of Lecture Notes in Computer Science, pages 212-231. Springer Berlin / Heidelberg, 2005. P. Bond P. Barrett, A. Hilborne, Lu´ıs Rodrigues, D. Seaton, N. Speirs, and Paulo Ver´ıssimo. The Delta-4 Extra Performance Architecture (XPA). 20th International Symposium on Fault-Tolerant Computing, pages 481-488, 1990. 3 - Resource reservation + CPU partitioning: Chen Lee, R. Rajkumar and Cliff Mercer, Experiences with Processor Reservation and Dynamic QoS in Real-Time Mach, In Proceedings of Multimedia Japan, March 1996 Luigi Palopoli, Tommaso Cucinotta, Luca Marzario, and Giuseppe Lipari. AQuoSA - Adaptive Quality of Service Architecture. Software: Practice and Experience, 39(1):1-31, April 2009. 4 - Real-time support: Priya Narasimhan, Tudor Dumitras , Aaron Paulos, Soila Pertet, Carlos Reverte, Joseph Slember, and Deepti Srivastava. MEAD: Support for Real-Time Fault- Tolerant CORBA: Research Articles. Concurrency and Computation: Practice & Experience 17(12):1527-1545, October 2005. Douglas Schmidt, David Levine, and Sumedh Mungee. The Design of the TAO Real-Time Object Request Broker. Computer Communications, 21(4):294-324, 1998. Rolando Martins On the Integration of RT & FT in P2P May 7, 2012 32