Univ. of TehranDistributed Operating Systems1 Advanced Operating Systems University of Tehran Dept. of EE and Computer Engineering By: Dr. Nasser Yazdani RPC (Remote Procedure Call) Lecture 10: RPC (Remote Procedure Call)

Univ. of TehranDistributed Operating Systems2 Communication in distributed systems How process communicates in DS. References Chapter 4 of the text book Andrew D. Birrell & Bruce J. Nelson, “Implementing Remote Procedure calls” Brain Bershad, Thomas Anderson, et.l, “Lightweight Remote Procedure Call” Chapter of “Computer Network, A system approach”, Section 5.3

Univ. of TehranDistributed Operating Systems3 Outline Why RPC Local Procedure Call Call semantics Different implementations Lightweight Procedure Call (LRPC).

Univ. of TehranDistributed Operating Systems4 Communication Models Communication of processes in distributed system environment. Communication is being done on the higher levels. Remote procedure call (RPC) Remote Object Invocation. Message passing queues Support for continuous media or stream

Univ. of TehranDistributed Operating Systems5 Remote procedure call A remote procedure call makes a call to a remote service look like a local call RPC makes transparent whether server is local or remote RPC allows applications to become distributed transparently RPC makes architecture of remote machine transparent Well-known method to transfer control and data among processes running on different machines

Univ. of TehranDistributed Operating Systems6 Developing with RPC 1. Define APIs between modules Split application based on function, ease of development, and ease of maintenance Don’t worry whether modules run locally or remotely 2. Decide what runs locally and remotely Decision may even be at run-time 3. Make APIs bullet proof Deal with partial failures

Univ. of TehranDistributed Operating Systems7 Goal of RPC Big goal: Transparency. Make distributed computing look like centralized computing Allow remote services to be called as procedures Transparency with regard to location, implementation, language Issues How to pass parameters Bindings Semantics in face of errors Two classes: integrated into prog, language and separate

Univ. of TehranDistributed Operating Systems8 Benefits of RPC A clean and simple semantic to build distributed computing. Transparent distributed computing Existing programs don't need to be modified Efficient communication! Generality: Enforces well-defined interfaces Allows portable interfaces Plug together separately written programs at RPC boundaries e.g. NFS and X clients and servers

Univ. of TehranDistributed Operating Systems9 Conventional Procedure Call a)Parameter passing in a local procedure call: the stack before the call to read b) The stack while the called procedure is active

Univ. of TehranDistributed Operating Systems10 Parameter Passing Local procedure parameter passing Call-by-value Call-by-reference: arrays, complex data structures Copy and store Remote procedure calls simulate this through: Stubs – proxies Flattening – marshalling Related issue: global variables are not allowed in RPCs

Univ. of TehranDistributed Operating Systems11 Client and Server Stubs Principle of RPC between a client and server program.

Univ. of TehranDistributed Operating Systems12 Stubs Client makes procedure call (just like a local procedure call) to the client stub Server is written as a standard procedure Stubs take care of packaging arguments and sending messages Packaging is called marshalling Stub compiler generates stub automatically from specs in an Interface Definition Language (IDL) Simplifies programmer task

Univ. of TehranDistributed Operating Systems13 Steps of a Remote Procedure Call 1. Client procedure calls client stub in normal way 2. Client stub builds message, calls local OS 3. Client's OS sends message to remote OS 4. Remote OS gives message to server stub 5. Server stub unpacks parameters, calls server 6. Server does work, returns result to the stub 7. Server stub packs it in message, calls local OS 8. Server's OS sends message to client's OS 9. Client's OS gives message to client stub 10. Stub unpacks result, returns to client

Univ. of TehranDistributed Operating Systems14 Passing Value Parameters (1) Steps involved in doing remote computation through RPC 2-8

Univ. of TehranDistributed Operating Systems15 Passing Value Parameters (2) a) Original message on the Pentium b) The message after receipt on the SPARC c) The message after being inverted. The little numbers in boxes indicate the address of each byte

Univ. of TehranDistributed Operating Systems16 Parameter Specification and Stub Generation a) A procedure b) The corresponding message.

Univ. of TehranDistributed Operating Systems17 Doors The principle of using doors as IPC mechanism.

Univ. of TehranDistributed Operating Systems18 Asynchronous RPC (1) a) Interconnection in a traditional RPC b) The interaction using asynchronous RPC 2-12 Why Asynchronous RPC?

Univ. of TehranDistributed Operating Systems19 Asynchronous RPC (2) A client and server interacting through two asynchronous RPCs 2-13

Univ. of TehranDistributed Operating Systems20 DCE RPC Distributed Computing Environment developed by Open Software Foundation. It is a middleware between network Operating Systems and distributed application. Distributed file service Directory service Security service Distributed time service

Univ. of TehranDistributed Operating Systems21 Binding a Client to a Server Client-to-server binding in DCE. 2-15

Univ. of TehranDistributed Operating Systems22 Writing a Client and a Server Uuidgen a program to generate a prototype IDL (Interface Definition Language) file. 2-14

Univ. of TehranDistributed Operating Systems23 Marshalling Problem: different machines have different data formats Intel: little endian, SPARC: big endian Solution: use a standard representation Example: external data representation (XDR) Problem: how do we pass pointers? If it points to a well-defined data structure, pass a copy and the server stub passes a pointer to the local copy What about data structures containing pointers? Prohibit Chase pointers over network Marshalling: transform parameters/results into a byte stream

Univ. of TehranDistributed Operating Systems24 Binding Problem: how does a client locate a server? Use Bindings Server Export server interface during initialization Send name, version no, unique identifier, handle (address) to binder Client First RPC: send message to binder to import server interface Binder: check to see if server has exported interface Return handle and unique identifier to client

Univ. of TehranDistributed Operating Systems25 Binding: Comments Exporting and importing incurs overheads Binder can be a bottleneck Use multiple binders Binder can do load balancing

Univ. of TehranDistributed Operating Systems26 Failure Semantics Client unable to locate server: return error Lost request messages: simple timeout mechanisms Lost replies: timeout mechanisms Make operation idempotent Use sequence numbers, mark retransmissions Server failures: did failure occur before or after operation? At least once semantics (SUNRPC) At most once No guarantee Exactly once: desirable but difficult to achieve

Univ. of TehranDistributed Operating Systems27 Failure Semantics Client failure: what happens to the server computation? Referred to as an orphan Extermination: log at client stub and explicitly kill orphans Overhead of maintaining disk logs Reincarnation: Divide time into epochs between failures and delete computations from old epochs Gentle reincarnation: upon a new epoch broadcast, try to locate owner first (delete only if no owner) Expiration: give each RPC a fixed quantum T; explicitly request extensions Periodic checks with client during long computations

Univ. of TehranDistributed Operating Systems28 Implementation Issues Choice of protocol [affects communication costs] Use existing protocol (UDP) or design from scratch Packet size restrictions Reliability in case of multiple packet messages Flow control Using TCP: too much overhead Setup time Keeping communication alive State information

Univ. of TehranDistributed Operating Systems29 Implementation Issues(2) Copying costs are dominant overheads Need at least 2 copies per message From client to NIC and from server NIC to server As many as 7 copies Stack in stub – message buffer in stub – kernel – NIC – medium – NIC – kernel – stub – server We might reduce overheads

Univ. of TehranDistributed Operating Systems30 Transparency? 4 properties of distributed computing that make achieving transparency difficult: Partial failures Concurrency Latency Memory access

Univ. of TehranDistributed Operating Systems31 Case Study: SUNRPC One of the most widely used RPC systems Developed for use with NFS Built on top of UDP or TCP TCP: stream is divided into records UDP: max packet size < 8912 bytes UDP: timeout plus limited number of retransmissions TCP: return error if connection is terminated by server Multiple arguments marshaled into a single structure At-least-once semantics if reply received, at-least-zero semantics if no reply. With UDP tries at-most-once Use SUN’s eXternal Data Representation (XDR) Big endian order for 32 bit integers, handle arbitrarily large data structures

Univ. of TehranDistributed Operating Systems32 Binder: Port Mapper Server start-up: create port Server stub calls svc_register to register prog. #, version # with local port mapper Port mapper stores prog #, version #, and port Client start-up: call clnt_create to locate server port Upon return, client can call procedures at the server

Univ. of TehranDistributed Operating Systems33 Rpcgen: generating stubs Q_xdr.c: do XDR conversion

Univ. of TehranDistributed Operating Systems34 Partial failures In local computing: if machine fails, application fails In distributed computing: if a machine fails, part of application fails one cannot tell the difference between a machine failure and network failure How to make partial failures transparent to client?

Univ. of TehranDistributed Operating Systems35 Strawman solution Make remote behavior identical to local behavior: Every partial failure results in complete failure You abort and reboot the whole system You wait patiently until system is repaired Problems with this solution: Many catastrophic failures Clients block for long periods System might not be able to recover

Univ. of TehranDistributed Operating Systems36 Where RPC transparency breaks True concurrency Clients run truely concurrently client() { if (exists(file)) if (!remove(file)) abort(“remove failed??”); } RPC latency is high Orders of magnitude larger than LPC’s Memory access Pointers are local to an address space

Univ. of TehranDistributed Operating Systems37 RPC implementation Stub compiler Generates stubs for client and server Language dependent Compile into machine-independent format E.g., XDR Format describes types and values RPC protocol RPC transport

Univ. of TehranDistributed Operating Systems38 RPC protocol Guarantee at-most-once semantics by tagging requests and response with a nonce RPC request header: Request nonce Service Identifier Call identifier Protocol: Client resends after time out Server maintains table of nonces and replies

Univ. of TehranDistributed Operating Systems39 RPC transport Use reliable transport layer Flow control Congestion control Reliable message transfer Combine RPC and transport protocol Reduce number of messages RPC response can also function as acknowledgement for message transport protocol

Univ. of TehranDistributed Operating Systems40 Implementing RPC (BiRREL et.l) The primary purpose to make Distributed computation easy. Remove unnecessary difficulties Two secondary Aims Efficiency (A factor of beyond network transmission. Powerful semantics without loss of simplicity or efficiency. Secure communication

Univ. of TehranDistributed Operating Systems41 Implementing RPC (Options) Shared address space among computers? Is it feasible? Integration of remote address space Acceptable efficiency? Keep RPC close to procedure call No timeout

Univ. of TehranDistributed Operating Systems42 Implementing RPC 1st solid implementation, not 1st mention – Semantics in the face of failure – Pointers – Language issues – Binding – Communication issues (networking tangents) Did you see those HW specs? “very powerful” == 1000x slower & smaller

Univ. of TehranDistributed Operating Systems43 RPC Semantics 1 Delivery guarantees. “Maybe call”: Clients cannot tell for sure whether remote procedure was executed or not due to message loss, server crash, etc. Usually not acceptable.

Univ. of TehranDistributed Operating Systems44 RPC Semantics 2 “At-least-once” call: Remote procedure executed at least once, but maybe more than once. Retransmissions but no duplicate filtering. Idempotent operations OK; e.g., reading data that is read-only.

Univ. of TehranDistributed Operating Systems45 RPC Semantics 3 “At-most-once” call Most appropriate for non-idempotent operations. Remote procedure executed 0 or 1 time, ie, exactly once or not at all. Use of retransmissions and duplicate filtering. Example: Birrel et al. implementation. Use of probes to check if server crashed.

Univ. of TehranDistributed Operating Systems46 Implementing RPC Extra compiler pass on code generates stubs – Client/server terminology & thinking

Univ. of TehranDistributed Operating Systems47 Implementing RPC ( Implementing RPC ( Rendezvous, binding) How does client find the appropriate server? Birrell&Nelson use a registry (Grapevine) Server publishes interface (type & instance) Client names service (& instance) Fairly sophisticated then, common now Simpler schemes: portmap/IANA (WW names) Still a source of complexity & insecurity

Univ. of TehranDistributed Operating Systems48 Implementing RPC ( Implementing RPC ( Marshalling) Representation Processor arch dependence (big vs little endian) Always canonical or optimize for instances Pointers No shared memory, so what about pointer args? Make RPC read accesses for all server dereferences? Slow! Copy fully expanded data structure across? Slow & incorrect if data structure is dynamically written Disallow pointers? Common Forces programmers to plan remote/local

Univ. of TehranDistributed Operating Systems49 Implementing RPC ( Implementing RPC ( Communication) Round trip response time vs data bandwidth One packet in each direction Connectionless (these days, sticky connections) RPC-specific reliability (bad idea we haven’t killed yet) Failure semantics & ordering RPC sequence number Idempotent (repeatable) operations vs exactly once Lost requests vs lost responses: repeat or replay cache Heartbeat (probes) to delay failure handling Server thread (process) pools & “affinity” binding

Univ. of TehranDistributed Operating Systems50 Binding How to determine where server is? Which procedure to call? “Resource discovery” problem Name service: advertises servers and services. Example: Birrel et al. uses Grapevine. Early versus late binding. Early: server address and procedure name hard- coded in client. Late: go to name service.

Univ. of TehranDistributed Operating Systems51 RPC Performance Sources of overhead data copying scheduling and context switch. Light-Weight RPC Shows that most invocations took place on a single machine. LW-RPC: improve RPC performance for local case. Optimizes data copying and thread scheduling for local case. Usually, designed and used with microkernels

Univ. of TehranDistributed Operating Systems52 The Common Case A large percentage of cross-domain calls are to processes on the same machine ( %) (V, Taos, Unix + NFS). Large and complex parameters are rarely passed during these calls. More than 50% of RPC only pass less than 200 bytes For null procedure for stub takes 70 micro-sec the rest are overhead, 650 micro-sec. This include buffer overhead, access validation, mesg transfer, scheduling, context switch, etc. Optimize for the common case! Optimize for the common case!

Univ. of TehranDistributed Operating Systems53 LW-RPC 1 Argument copying RPC: 4 times (2 on call and 2 on return); copying between kernel and user space. LW-RPC: common data area (A-stack) shared by client and server and used to pass parameters and results; access by client or server, one at a time.

Univ. of TehranDistributed Operating Systems54 LW-RPC 2 A-stack avoids copying between kernel and user spaces. Client and server share the same thread: less context switch (like regular calls). A client user kernel server 1. copy args 2. traps 3. upcall 4. executes & returns

Univ. of TehranDistributed Operating Systems55 Unoptimized Cross- domain RPC Procedure call - can’t be avoided Stub overhead marshalling parameters translating procedure call to the interface used by the RPC system

Univ. of TehranDistributed Operating Systems56 Unoptimized RPC Message buffer overhead allocating memory memory copies (client, kernel, server) Access validation validate message sender Message transfer enqueue and dequeue messages Scheduling overhead block client thread, schedule server thread Kernel trap and Context switch overhead Dispatch overhead interpret message maybe create new thread dispatch server thread to execute call

Univ. of TehranDistributed Operating Systems57 Observations Unoptimized RPC is between 5 and 10 times more expensive than the theoretical minimum e.g. Mach on CVAX: 90/754 microseconds

Univ. of TehranDistributed Operating Systems58 Optimizations: Overview Map message memory into multiple domains Handoff scheduling Passing arguments in registers Trade safety for performance Avoid dynamic allocation of memory Avoid data copies

Univ. of TehranDistributed Operating Systems59 LRPC Optimizations Do as much as possible at server bind time pre-allocate argument stacks (kernel) obtain entry address into the server domain for each procedure in interface allocate a linkage record to record client return address (kernel) return a non-forgeable Binding Object to the client and an argument stack list

Univ. of TehranDistributed Operating Systems60 LRPC Optimizations Argument stacks are preallocated and shared (mapped into client, kernel and server domains) Use the client thread to execute the call Optimize validation of client by using a capability (the Binding Object) Enforce security by using separate execution stacks

Univ. of TehranDistributed Operating Systems61 LRPC Optimizations Stubs are automatically generated in assembler and optimized for maximum efficiency Minimize the use of shared data structures On multiprocessors, if possible switch to a processor idling in the server domain Minimize data copying (1 instead of 4)

Univ. of TehranDistributed Operating Systems62 Next Lecture Naming Read Chapter 5 of the book