env/nanomsg/rfc/sp-request-reply-01.txt

Internet Engineering Task Force                          M. Sustrik, Ed.
Internet-Draft
Intended status: Informational                               August 2013
Expires: February 2, 2014


                   Request/Reply Scalability Protocol
                          sp-request-reply-01

Abstract

   This document defines a scalability protocol used for distributing
   processing tasks among arbitrary number of stateless processing nodes
   and returning the results of the processing.

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

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   This Internet-Draft will expire on February 2, 2014.

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   Copyright (c) 2013 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

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   described in the Simplified BSD License.





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1.  Introduction

   One of the most common problems in distributed applications is how to
   delegate a work to another processing node and get the result back to
   the original node.  In other words, the goal is to utilise the CPU
   power of a remote node.

   There's a wide range of RPC systems addressing the problem, however,
   instead of relying on simple RPC algorithm, we will aim at solving a
   more general version of the problem.  First, we want to issue
   processing requests from multiple clients, not just a single one.
   Second, we want to distribute the tasks to any number processing
   nodes instead of a single one so that the processing can be scaled up
   by adding new processing nodes as necessary.

   Solving the generalised problem requires that the algorithm executing
   the task in question -- also known as "service" -- is stateless.

   To put it simply, the service is called "stateless" when there's no
   way for the user to distinguish whether a request was processed by
   one instance of the service or another one.

   So, for example, a service which accepts two integers and multiplies
   them is stateless.  Request for "2x2" is always going to produce "4",
   no matter what instance of the service have computed it.

   Service that accepts empty requests and produces the number of
   requests processed so far (1, 2, 3 etc.), on the other hand, is not
   stateless.  To prove it you can run two instances of the service.
   First reply, no matter which instance produces it is going to be 1.
   Second reply though is going to be either 2 (if processed by the same
   instance as the first one) or 1 (if processed by the other instance).
   You can distinguish which instance produced the result.  Thus,
   according to the definition, the service is not stateless.

   Despite the name, being "stateless" doesn't mean that the service has
   no state at all.  Rather it means that the service doesn't retain any
   business-logic-related state in-between processing two subsequent
   requests.  The service is, of course, allowed to have state while
   processing a single request.  It can also have state that is
   unrelated to its business logic, say statistics about the processing
   that are used for administrative purposes and never returned to the
   clients.

   Also note that "stateless" doesn't necessarily mean "fully
   deterministic".  For example, a service that generates random numbers
   is non-deterministic.  However, the client, after receiving a new




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   random number cannot tell which instance has produced it, thus, the
   service can be considered stateless.

   While stateless services are often implemented by passing the entire
   state inside the request, they are not required to do so.  Especially
   when the state is large, passing it around in each request may be
   impractical.  In such cases, it's typically just a reference to the
   state that's passed in the request, such as ID or path.  The state
   itself can then be retrieved by the service from a shared database, a
   network file system or similar storage mechanism.

   Requiring services to be stateless serves a specific purpose.  It
   allows for using any number of service instances to handle the
   processing load.  After all, the client won't be able to tell the
   difference between replies from instance A and replies from instance
   B.  You can even start new instances on the fly and get away with it.
   The client still won't be able to tell the difference.  In other
   words, statelessness is a prerequisite to make your service cluster
   fully scalable.

   Once it is ensured that the service is stateless there are several
   topologies for a request/reply system to form.  What follows are the
   most common:

   1.  One client sends a request to one server and gets a reply.  The
       common RPC scenario.

   2.  Many clients send requests to one server and get replies.  The
       classic client/server model.  Think of a database server and
       database clients.  Alternatively think of a messaging broker and
       messaging clients.

   3.  One client send requests to many servers and gets replies.  The
       load-balancer model.  Think of HTTP load balancers.

   4.  Many clients send requests to be processed by many servers.  The
       "enterprise service bus" model.  In the simplest case the bus can
       be implemented as a simple hub-and-spokes topology.  In complex
       cases the bus can span multiple physical locations or multiple
       organisations with intermediate nodes at the boundaries
       connecting different parts of the topology.

   In addition to distributing tasks to processing nodes, request/reply
   model comes with full end-to-end reliability.  The reliability
   guarantee can be defined as follows: As long as the client is alive
   and there's at least one server accessible from the client, the task
   will eventually get processed and the result will be delivered back
   to the client.



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   End-to-end reliability is achieved, similar to TCP, by re-sending the
   request if the client believes the original instance of the request
   has failed.  Typically, request is believed to have failed when
   there's no reply received within a specified time.

   Note that, unlike with TCP, the reliability algorithm is resistant to
   a server failure.  Even if server fails while processing a request,
   the request will be re-sent and eventually processed by a different
   instance of the server.

   As can be seen from the above, one request may be processed multiple
   times.  For example, reply may be lost on its way back to the client.
   Client will assume that the request was not processed yet, it will
   resend it and thus cause duplicate execution of the task.

   Some applications may want to prevent duplicate execution of tasks.
   It often turns out that hardening such applications to be idempotent
   is relatively easy as they already possess the tools to do so.  For
   example, a payment processing server already has access to a shared
   database which it can use to verify that the payment with specified
   ID was not yet processed.

   On the other hand, many applications don't care about occasional
   duplicate processed tasks.  Therefore, request/reply protocol does
   not require the service to be idempotent.  Instead, the idempotence
   issue is left to the user to decide on.

   Finally, it should be noted that this specification discusses several
   features that are of little use in simple topologies and are rather
   aimed at large, geographically or organisationally distributed
   topologies.  Features like channel prioritisation and loop avoidance
   fall into this category.

2.  Underlying protocol

   The request/reply protocol can be run on top of any SP mapping, such
   as, for example, SP TCPmapping [SPoverTCP].

   Also, given that SP protocols describe the behaviour of entire
   arbitrarily complex topology rather than of a single node-to-node
   communication, several underlying protocols can be used in parallel.
   For example, a client may send a request via WebSocket, then, on the
   edge of the company network an intermediary node may retransmit it
   using TCP etc.







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   +---+  WebSocket  +---+    TCP    +---+
   |   |-------------|   |-----------|   |
   +---+             +---+           +---+
                      | |
        +---+   IPC   | |  SCTP  +---+    DCCP   +---+
        |   |---------+ +--------|   |-----------|   |
        +---+                    +---+           +---+

3.  Overview of the algorithm

   Request/reply protocol defines two different endpoint types: The
   requester or REQ (the client) and the replier or REP (the service).

   REQ endpoint can be connected only to a REP endpoint.  REP endpoint
   can be connected only to the REQ endpoint.  If the underlying
   protocol indicates that there's an attempt to create a channel to an
   incompatible endpoint, the channel MUST NOT be used.  In the case of
   TCP mapping, for example, the underlying TCP connection MUST be
   closed.

   When creating more complex topologies, REQ and REP endpoints are
   paired in the intermediate nodes to form a forwarding component, so
   called "device".  Device receives requests from the REP endpoint and
   forwards them to the REQ endpoint.  At the same time it receives
   replies from the REQ endpoint and forwards them to the REP endpoint:

                   --- requests -->

   +-----+   +-----+-----+   +-----+-----+   +-----+
   |     |-->|     |     |-->|     |     |-->|     |
   | REQ |   | REP | REQ |   | REP | REQ |   | REP |
   |     |<--|     |     |<--|     |     |<--|     |
   +-----+   +-----+-----+   +-----+-----+   +-----+

                   <-- replies ---

   Using devices, arbitrary complex topologies can be built.  The rest
   of this section explains how are the requests routed through a
   topology towards processing nodes and how are replies routed back
   from processing nodes to the original clients, as well as how the
   reliability is achieved.

   The idea for routing requests is to implement a simple coarse-grained
   scheduling algorithm based on pushback capabilities of the underlying
   transport.






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   The algorithm works by interpreting pushback on a particular channel
   as "the part of topology accessible through this channel is busy at
   the moment and doesn't accept any more requests."

   Thus, when a node is about to send a request, it can choose to send
   it only to one of the channels that don't report pushback at the
   moment.  To implement approximately fair distribution of the workload
   the node choses a channel from that pool using the round-robin
   algorithm.

   As for delivering replies back to the clients, it should be
   understood that the client may not be directly accessible (say using
   TCP/IP) from the processing node.  It may be beyond a firewall, have
   no static IP address etc.  Furthermore, the client and the processing
   may not even speak the same transport protocol -- imagine client
   connecting to the topology using WebSockets and processing node via
   SCTP.

   Given the above, it becomes obvious that the replies must be routed
   back through the existing topology rather than directly.  In fact,
   request/reply topology may be thought of as an overlay network on the
   top of underlying transport mechanisms.

   As for routing replies within the request/topology, it is designed in
   such a way that each reply contains the whole routing path, rather
   than containing just the address of destination node, as is the case
   with, for example, TCP/IP.

   The downside of the design is that replies are a little bit longer
   and that is in intermediate node gets restarted, all the requests
   that were routed through it will fail to complete and will have to be
   resent by request/reply end-to-end reliability mechanism.

   The upside, on the other hand, is that the nodes in the topology
   don't have to maintain any routing tables beside the simple table of
   adjacent channels along with their IDs.  There's also no need for any
   additional protocols for distributing routing information within the
   topology.

   The most important reason for adopting the design though is that
   there's no propagation delay and any nodes becomes accessible
   immediately after it is started.  Given that some nodes in the
   topology may be extremely short-lived this is a crucial requirement.
   Imagine a database client that sends a query, reads the result and
   terminates.  It makes no sense to delay the whole process until the
   routing tables are synchronised between the client and the server.





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   The algorithm thus works as follows: When request is routed from the
   client to the processing node, every REP endpoint determines which
   channel it was received from and adds the ID of the channel to the
   request.  Thus, when the request arrives at the ultimate processing
   node it already contains a full backtrace stack, which in turn
   contains all the info needed to route a message back to the original
   client.

   After processing the request, the processing node attaches the
   backtrace stack from the request to the reply and sends it back to
   the topology.  At that point every REP endpoint can check the
   traceback and determine which channel it should send the reply to.

   In addition to routing, request/reply protocol takes care of
   reliability, i.e. ensures that every request will be eventually
   processed and the reply will be delivered to the user, even when
   facing failures of processing nodes, intermediate nodes and network
   infrastructure.

   Reliability is achieved by simply re-sending the request, if the
   reply is not received with a certain timeframe.  To make that
   algorithm work flawlessly, the client has to be able to filter out
   any stray replies (delayed replies for the requests that we've
   already received reply to).

   The client thus adds an unique request ID to the request.  The ID
   gets copied from the request to the reply by the processing node.
   When the reply gets back to the client, it can simply check whether
   the request in question is still being processed and if not so, it
   can ignore the reply.

   To implement all the functionality described above, messages (both
   requests and replies have the following format:

   +-+------------+-+------------+   +-+------------+-------------+
   |0| Channel ID |0| Channel ID |...|1| Request ID |   payload   |
   +-+------------+-+------------+   +-+------------+ ------------+

   Payload of the message is preceded by a stack of 32-bit tags.  The
   most significant bit of each tag is set to 0 except for the very last
   tag.  That allows the algorithm to find out where the tags end and
   where the message payload begins.

   As for the remaining 31 bits, they are either request ID (in the last
   tag) or a channel ID (in all the remaining tags).  The first channel
   ID is added and processed by the REP endpoint closest to the
   processing node.  The last channel ID is added and processed by the
   REP endpoint closest to the client.



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   Following picture shows an example of request saying "Hello" being
   routed from the client through two intermediate nodes to the
   processing node and the reply "World" being routed back.  It shows
   what messages are passed over the network at each step of the
   process:

                           client
                     Hello    |    World
                      |    +-----+    ^
                      |    | REQ |    |
                      V    +-----+    |
               1|823|Hello    |    1|823|World
                      |    +-----+    ^
                      |    | REP |    |
                      |    +-----+    |
                      |    | REQ |    |
                      V    +-----+    |
         0|299|1|823|Hello    |    0|299|1|823|World
                      |    +-----+    ^
                      |    | REP |    |
                      |    +-----+    |
                      |    | REQ |    |
                      V    +-----+    |
   0|446|0|299|1|823|Hello    |    0|446|0|299|1|823|World
                      |    +-----+    ^
                      |    | REP |    |
                      V    +-----+    |
                     Hello    |    World
                           service

4.  Hop-by-hop vs. End-to-end

   All endpoints implement so called "hop-by-hop" functionality.  It's
   the functionality concerned with sending messages to the immediately
   adjacent components and receiving messages from them.

   In addition to that, the endpoints on the edge of the topology
   implement so called "end-to-end" functionality that is concerned with
   issues such as, for example, reliability.












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                      end to end
      +-----------------------------------------+
      |                                         |
   +-----+   +-----+-----+   +-----+-----+   +-----+
   |     |-->|     |     |-->|     |     |-->|     |
   | REQ |   | REP | REQ |   | REP | REQ |   | REP |
   |     |<--|     |     |<--|     |     |<--|     |
   +-----+   +-----+-----+   +-----+-----+   +-----+
      |         |     |         |     |         |
      +---------+     +---------+     +---------+
      hop by hop      hop by hop      hop by hop

   To make an analogy with the TCP/IP stack, IP provides hop-by-hop
   functionality, i.e. routing of the packets to the adjacent node,
   while TCP implements end-to-end functionality such resending of lost
   packets.

   As a rule of thumb, raw hop-by-hop endpoints are used to build
   devices (intermediary nodes in the topology) while end-to-end
   endpoints are used directly by the applications.

   To prevent confusion, the specification of the endpoint behaviour
   below will discuss hop-by-hop and end end-to-end functionality in
   separate chapters.

5.  Hop-by-hop functionality

5.1.  REQ endpoint

   The REQ endpoint is used by the user to send requests to the
   processing nodes and receive the replies afterwards.

   When user asks REQ endpoint to send a request, the endpoint should
   send it to one of the associated outbound channels (TCP connections
   or similar).  The request sent is exactly the message supplied by the
   user.  REQ socket MUST NOT modify an outgoing request in any way.

   If there's no channel to send the request to, the endpoint won't send
   the request and MUST report the backpressure condition to the user.
   For example, with BSD socket API, backpressure is reported as EAGAIN
   error.

   If there are associated channels but none of them is available for
   sending, i.e. all of them are already reporting backpressure, the
   endpoint won't send the message and MUST report the backpressure
   condition to the user.





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   Backpressure is used as a means to redirect the requests from the
   congested parts of the topology to to the parts that are still
   responsive.  It can be thought of as a crude scheduling algorithm.
   However crude though, it's probably still the best you can get
   without knowing estimates of execution time for individual tasks, CPU
   capacity of individual processing nodes etc.

   Alternatively, backpressure can be thought of as a congestion control
   mechanism.  When all available processing nodes are busy, it slows
   down the client application, i.e. it prevents the user from sending
   any more requests.

   If the channel is not capable of reporting backpressure (e.g.  DCCP)
   the endpoint SHOULD consider it as always available for sending new
   request.  However, such channels should be used with care as when the
   congestion hits they may suck in a lot of requests just to discard
   them silently and thus cause re-transmission storms later on.  The
   implementation of the REQ endpoint MAY choose to prohibit the use of
   such channels altogether.

   When there are multiple channels available for sending the request
   endpoint MAY use any prioritisation mechanism to decide which channel
   to send the request to.  For example, it may use classic priorities
   attached to channels and send message to the channel with the highest
   priority.  That allows for routing algorithms such as: "Use local
   processing nodes if any are available.  Send the requests to remote
   nodes only if there are no local ones available."  Alternatively, the
   endpoint may implement weighted priorities ("send 20% of the request
   to node A and 80% to node B).  The endpoint also may not implement
   any prioritisation strategy and treat all channels as equal.

   Whatever the case, two rules must apply.

   First, by default the priority settings for all channels MUST be
   equal.  Creating a channel with different priority MUST be triggered
   by an explicit action by the user.

   Second, if there are several channels with equal priority, the
   endpoint MUST distribute the messages among them in fair fashion
   using round-robin algorithm.  The round-robin implementation MUST
   also take care not to become unfair when new channels are added or
   old ones are removed on the fly.

   As for incoming messages, i.e. replies, REQ endpoint MUST fair-queues
   them.  In other words, if there are replies available on several
   channels, it MUST receive them in a round-robin fashion.  It must
   also take care not to compromise the fairness when new channels are
   added or old ones removed.



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   In addition to providing basic fairness, the goal of fair-queueing is
   to prevent DoS attacks where a huge stream of fake replies from one
   channel would be able to block the real replies coming from different
   channels.  Fair queueing ensures that messages from every channel are
   received at approximately the same rate.  That way, DoS attack can
   slow down the system but it can't entirely block it.

   Incoming replies MUST be handed to the user exactly as they were
   received.  REQ endpoint MUST not modify the replies in any way.

5.2.  REP endpoint

   REP endpoint is used to receive requests from the clients and send
   replies back to the clients.

   First of all, REP socket is responsible for assigning unique 31-bit
   channel IDs to the individual associated channels.

   First ID assigned MUST be random.  Next is computed by adding 1 to
   the previous one with potential overflow to 0.

   The implementation MUST ensure that the random number is different
   each time the endpoint is re-started, the process that contains it is
   restarted or similar.  So, for example, using pseudo-random generator
   with a constant seed won't do.

   The goal of the algorithm is to the spread of possible channel ID
   values and thus minimise the chance that a reply is routed to an
   unrelated channel, even in the face of intermediate node failures.

   When receiving a message, REP endpoint MUST fair-queue among the
   channels available for receiving.  In other words it should round-
   robin among such channels and receive one request from a channel at a
   time.  It MUST also implement the round-robin algorithm is such a way
   that adding or removing channels don't break its fairness.

   In addition to guaranteeing basic fairness in access to computing
   resources the above algorithm makes it impossible for a malevolent or
   misbehaving client to completely block the processing of requests
   from other clients by issuing steady stream of requests.

   After getting hold on the request, the REP socket should prepend it
   by 32 bit value, consisting of 1 bit set to 0 followed by the 31-bit
   ID of the channel the request was received from.  The extended
   request will be then handed to the user.

   The goal of adding the channel ID to the request is to be able to
   route the reply back to the original channel later on.  Thus, when



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   the user sends a reply, endpoint strips first 32 bits off and uses
   the value to determine where it is to be routed.

   If the reply is shorter than 32 bits, it is malformed and the
   endpoint MUST ignore it.  Also, if the most relevant bit of the
   32-bit value isn't set to 0, the reply is malformed and MUST be
   ignored.

   Otherwise, the endpoint checks whether its table of associated
   channels contains the channel with a corresponding ID.  If so, it
   sends the reply (with first 32 bits stripped off) to that channel.
   If the channel is not found, the reply MUST be dropped.  If the
   channel is not available for sending, i.e. it is applying
   backpressure, the reply MUST be dropped.

   Note that when the reply is unroutable two things might have
   happened.  Either there was some kind of network disruption, in which
   case the request will be re-sent later on, or the original client
   have failed or been shut down.  In such case the request won't be
   resent, however, it doesn't really matter because there's no one to
   deliver the reply to any more anyway.

   Unlike requests, there's no pushback applied to the replies; they are
   simply dropped.  If the endpoint blocked and waited for the channel
   to become available, all the subsequent replies, possibly destined
   for different unblocked channels, would be blocked in the meantime.
   That allows for a DoS attack simply by firing a lot of requests and
   not receiving the replies.

6.  End-to-end functionality

   End-to-end functionality is built on top of hop-to-hop functionality.
   Thus, an endpoint on the edge of a topology contains all the hop-by-
   hop functionality, but also implements additional functionality of
   its own.  This end-to-end functionality acts basically as a user of
   the underlying hop-by-hop functionality.

6.1.  REQ endpoint

   End-to-end functionality for REQ sockets is concerned with re-sending
   the requests in case of failure and with filtering out stray or
   outdated replies.

   To be able to do the latter, the endpoint must tag the requests with
   unique 31-bit request IDs.  First request ID is picked at random.
   All subsequent request IDs are generated by adding 1 to the last
   request ID and possibly overflowing to 0.




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   To improve robustness of the system, the implementation MUST ensure
   that the random number is different each time the endpoint, the
   process or the machine is restarted.  Pseudo-random generator with
   fixed seed won't do.

   When user asks the endpoint to send a message, the endpoint prepends
   a 32-bit value to the message, consisting of a single bit set to 1
   followed by a 31-bit request ID and passes it on in a standard hop-
   by-hop way.

   If the hop-by-hop layer reports pushback condition, the end-to-end
   layer considers the request unsent and MUST report pushback condition
   to the user.

   If the request is successfully sent, the endpoint stores the request
   including its request ID, so that it can be resent later on if
   needed.  At the same time it sets up a timer to trigger the re-
   transmission in case the reply is not received within a specified
   timeout.  The user MUST be allowed to specify the timeout interval.
   The default timeout interval must be 60 seconds.

   When a reply is received from the underlying hop-by-hop
   implementation, the endpoint should strip off first 32 bits from the
   reply to check whether it is a valid reply.

   If the reply is shorter than 32 bits, it is malformed and the
   endpoint MUST ignore it.  If the most significant bit of the 32-bit
   value is set to 0, the reply is malformed and MUST be ignored.

   Otherwise, the endpoint should check whether the request ID in the
   reply matches any of the request IDs of the requests being processed
   at the moment.  If not so, the reply MUST be ignored.  It is either a
   stray message or a duplicate reply.

   Please note that the endpoint can support either one or more requests
   being processed in parallel.  Which one is the case depends on the
   API exposed to the user and is not part of this specification.

   If the ID in the reply matches one of the requests in progress, the
   reply MUST be passed to the user (with the 32-bit prefix stripped
   off).  At the same time the stored copy of the original request as
   well as re-transmission timer must be deallocated.

   Finally, REQ endpoint MUST make it possible for the user to cancel a
   particular request in progress.  What it means technically is
   deleting the stored copy of the request and cancelling the associated
   timer.  Thus, once the reply arrives, it will be discarded by the
   algorithm above.



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   The cancellation allows, for example, the user to time out a request.
   They can simply post a request and if there's no answer in specific
   timeframe, they can cancel it.

6.2.  REP endpoint

   End-to-end functionality for REP endpoints is concerned with turning
   requests into corresponding replies.

   When user asks to receive a request, the endpoint gets next request
   from the hop-by-hop layer and splits it into the traceback stack and
   the message payload itself.  The traceback stack is stored and the
   payload is returned to the user.

   The algorithm for splitting the request is as follows: Strip 32 bit
   tags from the message in one-by-one manner.  Once the most
   significant bit of the tag is set, we've reached the bottom of the
   traceback stack and the splitting is done.  If the end of the message
   is reached without finding the bottom of the stack, the request is
   malformed and MUST be ignored.

   Note that the payload produced by this procedure is the same as the
   request payload sent by the original client.

   Once the user processes the request and sends the reply, the endpoint
   prepends the reply with the stored traceback stack and sends it on
   using the hop-by-hop layer.  At that point the stored traceback stack
   MUST be deallocated.

   Additionally, REP endpoint MUST support cancelling any request being
   processed at the moment.  What it means, technically, is that state
   associated with the request, i.e. the traceback stack stored by the
   endpoint is deleted and reply to that particular request is never
   sent.

   The most important use of cancellation is allowing the service
   instances to ignore malformed requests.  If the application-level
   part of the request doesn't conform to the application protocol the
   service can simply cancel the request.  In such case the reply is
   never sent.  Of course, if application wants to send an application-
   specific error massage back to the client it can do so by not
   cancelling the request and sending a regular reply.

7.  Loop avoidance

   It may happen that a request/reply topology contains a loop.  It
   becomes increasingly likely as the topology grows out of scope of a
   single organisation and there are multiple administrators involved in



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   maintaining it.  Unfortunate interaction between two perfectly
   legitimate setups can cause loop to be created.

   With no additional guards against the loops, it's likely that
   requests will be caught inside the loop, rotating there forever, each
   message gradually growing in size as new prefixes are added to it by
   each REP endpoint on the way.  Eventually, a loop can cause
   congestion and bring the whole system to a halt.

   To deal with the problem REQ endpoints MUST check the depth of the
   traceback stack for every outgoing request and discard any requests
   where it exceeds certain threshold.  The threshold should be defined
   by the user.  The default value is suggested to be 8.

8.  IANA Considerations

   New SP endpoint types REQ and REP should be registered by IANA.  For
   now, value of 16 should be used for REQ endpoints and value of 17 for
   REP endpoints.

9.  Security Considerations

   The mapping is not intended to provide any additional security to the
   underlying protocol.  DoS concerns are addressed within the
   specification.

10.  References

   [SPoverTCP]
              Sustrik, M., "TCP mapping for SPs", August 2013.

Author's Address

   Martin Sustrik (editor)

   Email: sustrik@250bpm.com















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