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Understand the design choices and scenarios in distributed systems, avoid deadlock efficiently, and implement interception and configuration patterns. Compare vertical and horizontal architecture designs. Learn about request-response systems and concurrency management. Study various strategies such as WaitOnReactor and Blocking techniques.
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E81 CSE 532S: Advanced Multi-Paradigm Software Development Deadlock Avoidance in Pattern Oriented Software Architecture Christopher Gill and Venkita Subramonian Department of Computer Science and Engineering Washington University, St. Louis cdgill@cse.wustl.edu
Main Themes of this Talk • Vertical vs. horizontal design of architectures • Consider how design choices have side effects • Design scenario case study • A distributed request-response system • Concurrency as a scarce resource • Avoiding deadlock efficiently • Also, illustrative as a Service Access and Configuration Pattern Language • Interceptor to manipulate concurrency at key points • Component Configurator to install DA protocol
Motivating Scenario • Request-response client server applications • E.g., CORBA, N-tier web servers, etc. • Any “component” can send requests, obtain results • Distributed data and analysis components • Requests may be sent locally or remotely • Processing a request may require making new requests • Thus, request chains may span endsystem boundaries • Raises new concerns related to liveness and safety • Assume a reactive/multithreaded concurrency architecture • Reactor threads service upcalls to clients • Number of threads overall is bounded (e.g., due to overhead) • Local thread management decisions impact global behavior • E.g., WaitOnReactor leads to stacking of result handling • E.g., Stackless approach increases request/result matching overhead • E.g., WaitOnConnection raises deadlock issues
Vertical Design of an Architecture Mixed Duration Request Handlers (MDRH) • From HS/HA & LF lecture • Designed to handle streams of mixed duration requests • Focused on interactions among local mechanisms • Concurrency and synchronization concerns • Hand-offs among threads • Well suited for “hub and spokes” or “processing pipeline” style applications • However, in some applications, a distributed view is more appropriate follower threads hand off chains enqueue requests leader thread reactor thread
Horizontal Design of an Architecture • Application components are implemented as handlers • Use reactor threads to run input and output methods • Send requests to other handlers via sockets, upcalls • These in turn define key interception points end-to-end • Example of a multi-host request/result chain • h1 to h2, h2 to h3, h3 to h4 handler h1 handler h2 handler h4 handler h3 socket socket reactor r3 reactor r1 reactor r2
WaitOnConnection Strategy • Handler waits on socket connection for the reply • Makes a blocking call to socket’s recv()method • Benefits • No interference from other requests that arrive while the reply is pending • Drawbacks • One less thread in the Reactor for new requests • Could allow deadlocks when upcalls are nested
WaitOnReactor Strategy • Handler returns control to reactor until reply comes back • Reactor can keep processing other requests while replies are pending • Benefits • Thread available, no deadlock • Thread stays fully occupied • Drawbacks • Interleaving of request reply processing • Interference from other requests issued while reply is pending
Blocking with WaitOnReactor • Wait-on-Reactor strategy could cause interleaved request/reply processing • Blocking factor could be large or even unbounded • Based on the upcall duration • And sequence of other intervening upcalls • Blocking factors may affect real-time properties of other end-systems • Call-chains can have a cascading blocking effect f2 f5 f3 f5reply queued blocking factor due to f2 f3 completes f2 completes f5 reply processed
“Stackless” WaitOnReactor Variant • What if we didn’t “stack” processing of results? • But instead allowed them to handled asynchronously as they are ready • Thanks to Caleb Hines for pointing out this exemplar from “Stackless Python” • Benefits • No interference from other requests that arrive when reply is pending • No risk of deadlock as thread still returns to reactor • Drawbacks • Significant increase in implementation complexity • Time and space overhead to match requests to results (hash maps, AO, pointer ACTs, etc. could help, though)
Could WaitOnConnection Be Used? • Main limitation is its potential for deadlock • And, it offers low overhead, ease of use • Could we make a system deadlock-free … • if we knew its call-graph … and were careful about how threads were allowed to proceed?
Deadlock Problem in Terms of Call Graph • Each reactor is assigned a color • Deadlock can exist • If there exists > Kc segments of color C • Where Kc is the number of threads in node with color C • E.g., f3-f2-f4-f5-f2 needs at least 2 & 1 f1 f2 f3 f4 f5 From Venkita Subramonian and Christopher Gill, “A Generative Programming Framework for Adaptive Middleware”, 37th Hawaii International Conference on System Sciences (HICSS ’04)
Simulation Showing Thread Exhaustion Server1 Server2 Clients send requests 3: Client3 : TRACE_SAP_Buffer_Write(13,10) 4: Unidir_IPC_13_14 : TRACE_SAP_Buffer_Transfer(13,14,10) 5: Client2 : TRACE_SAP_Buffer_Write(7,10) 6: Unidir_IPC_7_8 : TRACE_SAP_Buffer_Transfer(7,8,10) 7: Client1 : TRACE_SAP_Buffer_Write(1,10) 8: Unidir_IPC_1_2 : TRACE_SAP_Buffer_Transfer(1,2,10) Reactor1 makes upcalls to event handlers 10: Reactor1_TPRHE1 ---handle_input(2,1)---> Flow1_EH1 12: Reactor1_TPRHE2 ---handle_input(8,2)---> Flow2_EH1 14: Reactor1_TPRHE3 ---handle_input(14,3)---> Flow3_EH1 Flow1 proceeds 15: Time advanced by 25 units. Global time is 28 16: Flow1_EH1 : TRACE_SAP_Buffer_Write(3,10) 17: Unidir_IPC_3_4 : TRACE_SAP_Buffer_Transfer(3,4,10) 19: Reactor2_TPRHE4 ---handle_input(4,4)---> Flow1_EH2 20: Time advanced by 25 units. Global time is 53 21: Flow1_EH2 : TRACE_SAP_Buffer_Write(5,10) 22: Unidir_IPC_5_6 : TRACE_SAP_Buffer_Transfer(5,6,10) Flow2 proceeds 23: Time advanced by 25 units. Global time is 78 24: Flow2_EH1 : TRACE_SAP_Buffer_Write(9,10) 25: Unidir_IPC_9_10 : TRACE_SAP_Buffer_Transfer(9,10,10) 27: Reactor2_TPRHE5 ---handle_input(10,5)---> Flow2_EH2 28: Time advanced by 25 units. Global time is 103 29: Flow2_EH2 : TRACE_SAP_Buffer_Write(11,10) 30: Unidir_IPC_11_12 : TRACE_SAP_Buffer_Transfer(11,12,10) Flow3 proceeds 31: Time advanced by 25 units. Global time is 128 32: Flow3_EH1 : TRACE_SAP_Buffer_Write(15,10) 33: Unidir_IPC_15_16 : TRACE_SAP_Buffer_Transfer(15,16,10) 35: Reactor2_TPRHE6 ---handle_input(16,6)---> Flow3_EH2 36: Time advanced by 25 units. Global time is 153 37: Flow3_EH2 : TRACE_SAP_Buffer_Write(17,10) 38: Unidir_IPC_17_18 : TRACE_SAP_Buffer_Transfer(17,18,10) 39: Time advanced by 851 units. Global time is 1004 EH11 EH21 Client1 Flow1 EH31 EH12 EH22 Client2 Flow2 EH32 EH13 EH23 Client3 Flow3 EH33 Reactor1 Reactor2 • Increasing number of reactor threads may not always prevent deadlock • Can model this formally (UPPAL, IF)
Solution: Deadlock Avoidance Protocols • César Sánchez: PhD dissertation at Stanford • Paul Oberlin: MS project here at WUSTL • Avoid interactions leading to deadlock • a liveness property • Like synchronization, achived via scheduling • Upcalls are delayed until enough threads are ready • But, introduces small blocking delays • a timing property • In real-time systems, also a safety property
DA Protocol Overview • Designed* and proven+by Cesar Sanchez, Henny Sipma and Zohar Manna (Stanford) • Regulates upcalls based on # of available reactor threads and call graph’s “thread height” • Does not allow exhaustion • BASIC-P protocol implemented in the ACE TP Reactor • Using handle suspension and resumption • Backward compatible, minimal overhead Server1 Server2 EH11 EH21 Client1 Flow1 EH31 EH12 EH22 Client2 Flow2 EH32 EH23 EH13 Client3 Flow3 EH33 Reactor1 Reactor2 *Sanchez, Sipma, Subramonian and Gill, “Thread Allocation Protocols for Distributed Real-Time and Embedded Systems”, FORTE 2005 + Sanchez, Sipma, Manna, Subramonian, and Gill, “On Efficient Distributed Deadlock Avoidance for Real-Time and Embedded Systems”, IPDPS 2006
Choosing our First Patterns • Two main issues must be addressed • How reactors can know how many threads it’s safe to allocate at once to a handler • How reactors can use that information at run-time • For the first issue, need a way to obtain call graph depth (number of threads needed) • Can specify this a priori (give a table to reactor) • Can also ask objects to “call downstream” to obtain graph heights from their children • Can use ACT and Interceptor to implement this • Can use Component Configurator to decouple and enable installation of standard vs. (various) DA protocol services
Choosing our Next Patterns • Second Issue • How reactors can use that information at run-time • Need to determine when it’s ok to dispatch • Maintain counters of thread upcalls in progress • Can use Interceptor again to implement this • Need to block threads until it’s ok to proceed • Can use a form of Scoped Locking • But modify guard condition so it only proceeds when safe • Can think of this being similar to leader election in L/F • Need to record when threads complete • Again, scoped locking decreases “in-use count” • And may be done within an “upcall” interceptor
Timing Traces: DA Protocol at Work EH11 EH21 R1 R2 EH31 Flow1 EH12 EH22 R1 R2 EH32 Flow2 Timing traces from model/execution show DA protocol regulating the flows to use available resources without deadlock EH13 EH23 R1 R2 EH33 Flow3
DA Blocking Delay (Simulated vs. Actual) Model Execution Actual Execution Blocking delay for Client2 Blocking delay for Client3
Overhead of ACE TP reactor with DA Negligible overhead with no DA protocol Overhead increases with number of event handlers because of their suspension and resumption on protocol entry and exit
Concluding Remarks • Horizontal Design of Architectures • Often as important as vertical design • Not as frequently encountered/addressed • Design Choices Demand Further Effort • Needed deadlock avoidance theory/implementation to make WaitOnConnection an effective option • That Effort Leads to Further Design Choices • To implement deadlock avoidance efficiently • And in Turn Leads to Further Design Forces • For example, DA protocol blocking factors, costs