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Network Working Group                                     Changqiao Xu
Internet Draft                                                   BUPT
Intended status: Experimental                                 Kai Gao
Expires: October 2019                                               BUPT
                                                           Jiuren Qin
                                                                 BUPT
                                                      May 6, 2019

                   A Stochastic Optimal Scheduler for
             Multipath Transmission Control Protocol (MPTCP)
                      draft-xu-mptcp-sosmp-01.txt


Status of this Memo

   This Internet-Draft is submitted in full conformance with the
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   This Internet-Draft will expire on October 6, 2019.






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Copyright Notice

   Copyright (c) 2018 IETF Trust and the persons identified as the
   document authors. All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
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Abstract

   This memo presents a new stochastic optimal scheduler for the
   Multipath Transmission Control Protocol (MPTCP). The new scheduler is
   based on the Lyapunov optimatization technique, which can make online
   control decision for data scheduling. Considering the payment of
   users for different paths, this memo makes a trade off between the
   throughput utility and the cost. The new scheduler can not only
   satisfy the demand of service, but also minimize the cost as much as
   possible.

   Table of Contents


   1. Introduction ................................................ 3
      1.1. Motivation ............................................. 3
      1.2. Overview of SOS-MPTCP .................. 3
   2. Conventions ................................................. 3
   3. A New Stochastic Optimal Scheduler
... 3
      3.1. Admission Control
............................. 4
      3.2. Packets Allocation
........................... 4
      3.3. Purchasing Data Traffic ................. 4
   4. Building Queue ...................................... 4
   5. Transmission Performance and Problem Optimization ............ 5
   6. Stochastic Optimal Scheduler ................................. 5
   7. Security Considerations
 ...................................... 5
   8. Implementation Considerations  ................................ 5
   9. References .................................................. 5
      9.1. Normative References  .................................... 5
      9.2. Informative References  .................................. 6
   10. Acknowledgments ............................................ 6


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1. Introduction

   SOS-MPTCP is a new scheduler of MPTCP which can make online control
   decisions for data distribution. By taking advantage of queue
   stability, the new stochastic optimal scheduler can make a trade off
   between the throughput utility and the cost.

1.1. Motivation

   The scheduler plays an important role in the data distribution. In
   the heterogeneous wireless network, the cost of each path is quite
   diverse and depends on the amount of packets assigned by the
   scheduler. Traditional scheduler just focuses on the transmission
   performance without considering the payment cost of users. This memo
   intends to fill the gap with the Lyapunov optimatization technique.

1.2. Overview of SOS-MPTCP

   This demo mainly describes the new scheduler of MPTCP. The objection
   of this scheduler is to maximize the throughput and minimize the
   corresponding cost to different communication operators. To achieve
   this goal, the following three important control decisions are to be
   made:

   o How many packets of different connections can be admitted into
      transmission layer.

   o How to distribute the admitted packets to all paths.

   o How to purchase data traffic for different paths in advance.

2. Conventions

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
   document are to be interpreted as described in RFC-2119 [RFC2119].

3. A New Stochastic Optimal Scheduler

   A number of paths which are available are denoted by J={1,2,?j}. And
   there are different connections I={1,2,?i} of packets with diverse
   arrival rates from the application layer. In order to facilitate the
   analysis, we consider the system as a discrete time-slotted model
   divided by t={1,2,?T}. In each time slot t, a number of the ith
   connection of packets arrive at the system randomly. Let A i(t)



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   denote the number of data packets of connection i in time slot t.
   The unit price of path j is denoted by p_j.

3.1. Admission Control

   In each time slot, a lot of packets arrive at the transmission
   layer. To prevent the system from congestion, the admission control
   module decides that the total number of packets noticed by A_i(t).
   can be admitted into transmission layer. Therefore, A_i(t) SHOULD
   less than the number of arriving packets R_i(t).

3.2. Packets Allocation

   After the packets of connection i are admitted into the transmission
   layer, the packets allocation module assigns packets to each path.
   The number of packets of type i distributed to path j in time slot t
   is denoted as A_ij(t). And this assignment should satisfy the
   constraint: A_i(t)=SUM_i(A_ij(t)). Each path maintains a queue for
   each connection of packets which can be transmitted later. We define
   the queue backlog Q_ij(t) of ith connection of packets assigned on
   the jth path as the number of pending packets waiting in the queue.
   We also define S_ij(t) as the number of packets which have been sent
   successfully and acknowledged.
3.3. Purchasing Data Traffic

   In order to satisfy the service demand of users, they will purchase
   data traffic in advance from the communication operator. We use
   W_j(t) to denote the cost of paying for the path j belonging to
   respective operator in the time slot t. The total cost of the
   multipath transmission control system can be denoted by H_j(t) to
   maintain the consumption for the users.

4. Building Queue

   According to the control framework described above, the dynamic
   updating of queue backlog can be defined as the equation:

                Q_ij(t+1)=max[Q_ij(t)- S_ij(t),0]+ A_ij(t)

   Similarly, H_j(t) denotes the cost queue size of path j in the time
   slot t. Under the control decision of purchasing data traffic, the
   queue H_j(t) can be expressed as follows,

               H_j(t+1)= H_j(t)- SUM_j (S_ij(t)*p_j)+ W_j(t)




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5. Transmission Performance and Problem Optimization

   We define the time averaged throughput SUM_i (Thr_i(t))=lim_t (1/T)
   SUM_t E{S_i(t)}. We also define a cost utility function
   SUM_j(W_j(t))=lim_t(1/T)SUM j(E{W_j(t))}. It is challenging to
   tradeoff the transmission throughput and cost utility function. The
   transmission performance depends on the throughput and cost utility.
   Therefore, we NEED to construct an objective to take both sides into
   consideration.

   The problem of maximizing transmission performance is defined as

                 Max { SUM_i (Thr_i(t)) - SUM_j (W_j(t))}

                            s.t. Q_ij is stable

6. Stochastic Optimal Scheduler

   In order to solve the problem mentioned above, we design a
   distribution approach by using Lyapunov optimization [SNO2010] which
   contains Lyapunov draft and queue stability. The value of A_i(t),
   A_ij(t) are calculated by the queue H(t) and Q(t). And H(t) and Q(t)
   are updated by the calculation results.

7. Security Considerations

   This memo develops no new security scheme for MPTCP. SOS-MPTCP share
   the same security issues discussed in [RFC6824] with MPTCP.

8. Implementation Considerations

   This approach is a new scheduler for MPTCP, which is named as
   "stochastic". We can select the scheduler through the socket-option
   MPTCP_SCHEDULER from the following four schedulers: "default",
   "roundrobin", "redundant", "stochastic".

9. References

9.1. Normative References

   [RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
             Requirement Levels", BCP 14, RFC 2119, March 1997.







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9.2. Informative References

   [RFC6824] Ford, A., Raiciu, C., Handley, M., and O. Bonaventure,
             "TCP Extensions for Multipath Operation with Multiple
             Addresses", RFC 6824, January 2013.

   [SNO2010] M. J. Neely, Stochastic Network Optimization with
         Application to Communication and Queueing Systems, J. Walrand,
         Ed. San Rafael, CA,USA: Morgan & Claypool, 2010.

10. Acknowledgments

   This Internet Draft is the result of a great deal of constructive
   discussion with several people, notably Tengfei Cao and Jiangzhong
   Bai.

   This document was prepared using 2-Word-v2.0.template.dot.































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Authors' Addresses

   Changqiao Xu
   Beijing University of Posts and Telecommunications
   Institute of Network Technology, No. 10, Xitucheng Road,
   Haidian District, Beijing
   P.R. China

   Email: cqxu@bupt.edu.cn


   Kai Gao
   Beijing University of Posts and Telecommunications
   Institute of Network Technology, No. 10, Xitucheng Road,
   Haidian District, Beijing
   P.R. China

   Email: gaokai@bupt.edu.cn



   Jiuren Qin
   Beijing University of Posts and Telecommunications
   Institute of Network Technology, No. 10, Xitucheng Road,
   Haidian District, Beijing
   P.R. China

   Email: jrqin@bupt.edu.cn




















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