Internet DRAFT - draft-xu-mptcp-sosmp
draft-xu-mptcp-sosmp
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
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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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