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Run idnits with the --verbose option for more detailed information about the items above. -------------------------------------------------------------------------------- 2 Network Working Group Changqiao Xu 3 Internet Draft BUPT 4 Intended status: Experimental Kai Gao 5 Expires: April 2019 BUPT 6 Jiuren Qin 7 BUPT 8 November 5, 2018 10 A Stochastic Optimal Scheduler for 11 Multipath Transmission Control Protocol (MPTCP) 12 draft-xu-mptcp-sosmp-00.txt 14 Status of this Memo 16 This Internet-Draft is submitted in full conformance with the 17 provisions of BCP 78 and BCP 79. 19 This document may contain material from IETF Documents or IETF 20 Contributions published or made publicly available before November 21 10, 2008. 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Code Components extracted from this 60 document must include Simplified BSD License text as described in 61 Section 4.e of the Trust Legal Provisions and are provided without 62 warranty as described in the Simplified BSD License. 64 Abstract 66 This memo presents a new stochastic optimal scheduler for the 67 Multipath Transmission Control Protocol (MPTCP). The new scheduler is 68 based on the Lyapunov optimatization technique, which can make online 69 control decision for data scheduling. Considering the payment of 70 users for different paths, this memo makes a trade off between the 71 throughput utility and the cost. The new scheduler can not only 72 satisfy the demand of service, but also minimize the cost as much as 73 possible. 75 Table of Contents 77 1. Introduction ................................................ 3 78 1.1. Motivation ............................................. 3 79 1.2. Overview of SOS-MPTCP .................. 3 80 2. Conventions ................................................. 3 81 3. A New Stochastic Optimal Scheduler 82 ... 3 83 3.1. Admission Control 84 ............................. 4 85 3.2. Packets Allocation 86 ........................... 4 87 3.3. Purchasing Data Traffic ................. 4 88 4. Building Queue ...................................... 4 89 5. Transmission Performance and Problem Optimization ............ 5 90 6. Stochastic Optimal Scheduler ................................. 5 91 7. Security Considerations 92 ...................................... 5 93 8. Implementation Considerations ................................ 5 94 9. References .................................................. 5 95 9.1. Normative References .................................... 5 96 9.2. Informative References .................................. 6 97 10. Acknowledgments ............................................ 6 99 1. Introduction 101 SOS-MPTCP is a new scheduler of MPTCP which can make online control 102 decisions for data distribution. By taking advantage of queue 103 stability, the new stochastic optimal scheduler can make a trade off 104 between the throughput utility and the cost. 106 1.1. Motivation 108 The scheduler plays an important role in the data distribution. In 109 the heterogeneous wireless network, the cost of each path is quite 110 diverse and depends on the amount of packets assigned by the 111 scheduler. Traditional scheduler just focuses on the transmission 112 performance without considering the payment cost of users. This memo 113 intends to fill the gap with the Lyapunov optimatization technique. 115 1.2. Overview of SOS-MPTCP 117 This demo mainly describes the new scheduler of MPTCP. The objection 118 of this scheduler is to maximize the throughput and minimize the 119 corresponding cost to different communication operators. To achieve 120 this goal, the following three important control decisions are to be 121 made: 123 o How many packets of different connections can be admitted into 124 transmission layer. 126 o How to distribute the admitted packets to all paths. 128 o How to purchase data traffic for different paths in advance. 130 2. Conventions 132 The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", 133 "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this 134 document are to be interpreted as described in RFC-2119 [RFC2119]. 136 3. A New Stochastic Optimal Scheduler 138 A number of paths which are available are denoted by J={1,2,?j}. And 139 there are different connections I={1,2,?i} of packets with diverse 140 arrival rates from the application layer. In order to facilitate the 141 analysis, we consider the system as a discrete time-slotted model 142 divided by t={1,2,?T}. In each time slot t, a number of the ith 143 connection of packets arrive at the system randomly. Let A i(t) 144 denote the number of data packets of connection i in time slot t. 145 The unit price of path j is denoted by p_j. 147 3.1. Admission Control 149 In each time slot, a lot of packets arrive at the transmission 150 layer. To prevent the system from congestion, the admission control 151 module decides that the total number of packets noticed by A_i(t). 152 can be admitted into transmission layer. Therefore, A_i(t) SHOULD 153 less than the number of arriving packets R_i(t). 155 3.2. Packets Allocation 157 After the packets of connection i are admitted into the transmission 158 layer, the packets allocation module assigns packets to each path. 159 The number of packets of type i distributed to path j in time slot t 160 is denoted as A_ij(t). And this assignment should satisfy the 161 constraint: A_i(t)=SUM_i(A_ij(t)). Each path maintains a queue for 162 each connection of packets which can be transmitted later. We define 163 the queue backlog Q_ij(t) of ith connection of packets assigned on 164 the jth path as the number of pending packets waiting in the queue. 165 We also define S_ij(t) as the number of packets which have been sent 166 successfully and acknowledged. 167 3.3. Purchasing Data Traffic 169 In order to satisfy the service demand of users, they will purchase 170 data traffic in advance from the communication operator. We use 171 W_j(t) to denote the cost of paying for the path j belonging to 172 respective operator in the time slot t. The total cost of the 173 multipath transmission control system can be denoted by H_j(t) to 174 maintain the consumption for the users. 176 4. Building Queue 178 According to the control framework described above, the dynamic 179 updating of queue backlog can be defined as the equation: 181 Q_ij(t+1)=max[Q_ij(t)- S_ij(t),0]+ A_ij(t) 183 Similarly, H_j(t) denotes the cost queue size of path j in the time 184 slot t. Under the control decision of purchasing data traffic, the 185 queue H_j(t) can be expressed as follows, 187 H_j(t+1)= H_j(t)- SUM_j (S_ij(t)*p_j)+ W_j(t) 189 5. Transmission Performance and Problem Optimization 191 We define the time averaged throughput SUM_i (Thr_i(t))=lim_t (1/T) 192 SUM_t E{S_i(t)}. We also define a cost utility function 193 SUM_j(W_j(t))=lim_t(1/T)SUM j(E{W_j(t))}. It is challenging to 194 tradeoff the transmission throughput and cost utility function. The 195 transmission performance depends on the throughput and cost utility. 196 Therefore, we NEED to construct an objective to take both sides into 197 consideration. 199 The problem of maximizing transmission performance is defined as 201 Max { SUM_i (Thr_i(t)) - SUM_j (W_j(t))} 203 s.t. Q_ij is stable 205 6. Stochastic Optimal Scheduler 207 In order to solve the problem mentioned above, we design a 208 distribution approach by using Lyapunov optimization [SNO2010] which 209 contains Lyapunov draft and queue stability. The value of A_i(t), 210 A_ij(t) are calculated by the queue H(t) and Q(t). And H(t) and Q(t) 211 are updated by the calculation results. 213 7. Security Considerations 215 This memo develops no new security scheme for MPTCP. SOS-MPTCP share 216 the same security issues discussed in [RFC6824] with MPTCP. 218 8. Implementation Considerations 220 This approach is a new scheduler for MPTCP, which is named as 221 "stochastic". We can select the scheduler through the socket-option 222 MPTCP_SCHEDULER from the following four schedulers: "default", 223 "roundrobin", "redundant", "stochastic". 225 9. References 227 9.1. Normative References 229 [RFC2119] Bradner, S., "Key words for use in RFCs to Indicate 230 Requirement Levels", BCP 14, RFC 2119, March 1997. 232 9.2. Informative References 234 [RFC6824] Ford, A., Raiciu, C., Handley, M., and O. Bonaventure, 235 "TCP Extensions for Multipath Operation with Multiple 236 Addresses", RFC 6824, January 2013. 238 [SNO2010] M. J. Neely, Stochastic Network Optimization with 239 Application to Communication and Queueing Systems, J. Walrand, 240 Ed. San Rafael, CA,USA: Morgan & Claypool, 2010. 242 10. Acknowledgments 244 This Internet Draft is the result of a great deal of constructive 245 discussion with several people, notably Tengfei Cao and Jiangzhong 246 Bai. 248 This document was prepared using 2-Word-v2.0.template.dot. 250 Authors' Addresses 252 Changqiao Xu 253 Beijing University of Posts and Telecommunications 254 Institute of Network Technology, No. 10, Xitucheng Road, 255 Haidian District, Beijing 256 P.R. China 258 Email: cqxu@bupt.edu.cn 260 Kai Gao 261 Beijing University of Posts and Telecommunications 262 Institute of Network Technology, No. 10, Xitucheng Road, 263 Haidian District, Beijing 264 P.R. China 266 Email: gaokai@bupt.edu.cn 268 Jiuren Qin 269 Beijing University of Posts and Telecommunications 270 Institute of Network Technology, No. 10, Xitucheng Road, 271 Haidian District, Beijing 272 P.R. China 274 Email: jrqin@bupt.edu.cn