IEEE ICC 2014 - Communication QoS, Reliability and Modeling Symposium
Rate-Based Path Selection for Shortest Path Bridging in Access Networks Yu Nakayama NTT Access Network Service Systems Laboratories, NTT Corporation 1-1 Hikarinooka, Yokosuka-shi, Kanagawa, 239-0847 Japan Email:
[email protected] Abstract—With shortest path bridging MAC (SPBM) in an access network, shortest path transmission can be realized without a blocking port in any network topology. The approach is expected to use network resources efficiently and to simplify the operating procedure. Access networks can be flexibly constructed on demand with SPBM. However, if there is a deviation in the flow traffic rate, the paths of high rate flows can overlap on specific links and congestion occurs. It is important to avoid congestion by selecting the optimal path for each flow. This paper proposes a rate-based path selection algorithm for access networks with SPBM. The proposed algorithm assumes that a path with a low average rate will be congested because the rates of TCP flows decrease on a congested path. When a new flow arrives at an edge switch, it selects the path with the highest average rate on which it can be expected to realize a high rate. I confirmed with computer simulations that the proposed algorithm could efficiently utilize links and improve throughput fairness.
I. I NTRODUCTION In carrier networks, a layer-2 ring topology and ERP (Ethernet Ring Protection) [1] have been employed to connect layer-2 switches [2]. A layer-2 ring topology can realize high availability with the redundancy of nodes and links. At the same time, PBB (Provider Backbone Bridges) [3] has often been employed to interconnect a large number of users without losing each user’s individually defined VLANs. However, a layer-2 ring topology has certain problems. The links cannot be fully utilized because there are blocking ports for loop prevention. The need for this loop prevention configuration makes the operation procedure complicated in large-scale networks. Traffic is not necessarily transmitted along the shortest paths and unfairness of throughput and latency occurs. In recent years, server virtualization in data centers (DCs) has progressed significantly. To use resources efficiently and to simplify the operation of DC networks, Ethernet fabrics such as SPB (Shortest Path Bridging) [4] and TRILL (Transparent Interconnection of Lots of Links) [5] have been standardized. Ethernet fabrics employ IS-IS (Intermediate System to Intermediate System) [6] protocol to exchange link states. Frames are forwarded along the shortest paths based on routing tables. Unlike STP (Spanning Tree Protocol), blocking ports are eliminated to allow full use of the network links. We can consider employing Ethernet fabrics in access networks for connecting layer-2 switches. With Ethernet fabrics, access networks can be flexibly constructed on demand. The shortest path transmission is realized without a blocking port in any network topology. This approach can use network
978-1-4799-2003-7/14/$31.00 ©2014 IEEE
resources efficiently and simplify the operating procedure. In particular, the use of SPBM (SPB-MAC) is expected to allow smooth migration from existing networks because SPBM employs a PBB header as the outer MAC header. With SPBM, each switch calculates the end-to-end shortest path based on topology information shared with IS-IS. If there are multiple shortest paths, each path is registered on the routing table as an ECT (equal cost tree). When an edge switch (BEB) receives a frame from outside the SPBM network, it selects a path from ECTs and assigns a corresponding BVID (Backbone VLAN Identifier). A typical path selection operation is performed with a hash function using the frame header. If there is a deviation in the flow traffic rate, the paths of high rate flows can overlap on specific links and congestion occurs. I proposed a fairness algorithm for congestion in access networks [7]. However, it is important to avoid congestion by selecting the optimal path for each flow. In this paper, I propose a rate-based path selection algorithm for access networks with SPBM. The rest of the paper is organized as follows. Section II describes the system configuration and problems of an access network with SPBM. Section III describes the proposed algorithm. In Section IV, I evaluate the algorithm with computer simulations. Section V provides the conclusion. II. S UBJECT A. System configuration In this section, I describe in detail the system configuration of an access network with SPBM and its problems. Fig. 1 shows an example of an access network with SPBM. The SPBM network is composed of edge switches (BEBs; backbone edge bridges) and core switches (BCBs; backbone core bridges). BEBs can connect users through other systems such as PONs (passive optical networks). Some BEBs are linked to edge nodes, which are connected to other network. BEBs and BCBs can be located in multiple central offices. The links between switches that are located in different central offices are connected across the central offices. B. Traffic The assumptions about traffic are as follows. This paper focuses on unicast traffic. User nodes are connected to BEBs
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IEEE ICC 2014 - Communication QoS, Reliability and Modeling Symposium
Core Other Network Edge node
Edge node
Aggregation BEB
SPBM Network BCB
BCB
BCB
BEB
Edge BCB
BCB
BEB
BCB
Host BEB
BEB
BEB
Fig. 2.
Fat tree topology.
users
Fig. 1.
Access network with SPBM.
and compose multipoint connections through the SPBM network. The BEBs receive the traffic from the user nodes and the traffic from the edge nodes. At a BEB, frames are identified with a flow identifier such as a VLAN ID and encapsulated with a PBB header. Then the frames are transmitted to their destination nodes via the BCBs. At a BCB, frames are transmitted based on a routing table and their PBB header. Since an ECT is an end-to-end path, the path is selected only at BEBs. Although the priority of the traffic can be identified using a number of classes, for simplicity I assume that there is one priority class and a best effort (BE) class. The priority class traffic is a guaranteed service such as VoIP and is managed by the network operator. The frames of the priority class are transmitted first at each BEB and BCB. Therefore, I assumed that the priority class traffic does not become congested and the QoS is maintained. BE flows such as Internet traffic are not managed by the network operator. BE frames form one firstin-first-out (FIFO) queue per egress port at BEBs and BCBs. When the quantity of data transmitted into an SPBM network increases, it becomes congested. This paper focuses on BE throughput. C. Topology The main target of SPBM has been DC networks. A fat tree topology (Fig. 2) [8] is generally employed for a DC network. A fat tree topology is a widely used tree topology with multiple root nodes. There are many ECTs from hosts to hosts in this topology. Traffic is well load-balanced by ECTs. This topology can effectively utilize the shortest path and multipath transmission, which are features of SPBM. However, it is not realistic to connect the layer-2 switches and edge nodes in multiple central offices of an access network with a fat tree topology, because it needs many links across central offices and is costly. The ability to construct a network flexibly on demand is expected to be an advantage of employing SPBM. Therefore, in this paper I assume that an SPBM network in an access network is not restricted to specific topologies. When an arbitrary topology is constructed with SPBM, BE traffic often becomes congested on specific links. The paths of
many flows can overlap, because the routing table is computed automatically. Although network operators should decide the topology and metric taking load balancing with ECTs into consideration, the traffic rate of unmanaged BE flows can deviate and the paths of high rate flows can overlap on specific links. In such situations, it is difficult to avoid congestion on specific links with typical path selection performed by a hash function. In addition, unpredictable traffic paths can be generated with the updated routing table on link failures. It is difficult always to avoid the congestion on specific links. It is important to avoid congestion by selecting the optimal path for each flow. D. Related work There has been a lot of related work on load balancing in multipath networks [9]. Hash-based load balancing algorithms has been intensely investigated. Martin et al. [10] proposed dynamic hash-based load balancing algorithms. Jo et al. [11] developed Dynamic Hashing with Flow Volume (DHFV). DHFV eliminates unnecessary flow reassignments of small flows and achieves quick load balancing. Chim et al. [12] proposed Table-based Hashing with Reassignments (THR). THR selectively reassigns active flows from over-utilized paths to under-utilized paths. Kandula et al. [13] proposed Flowlet Aware Routing Engine (FLARE). FLARE operates on bursts of packets and avoid packet reordering by switching multiple paths. However, they focused on hop-by-hop equal-cost multipath (ECMP) routing. They cannot be used in SPBM networks, because an end-to-end path is selected at a BEB and BCBs only transmit frames along the seleced path in SPBM networks. Path selection based on queue length [14] does not work in SPBM networks if congestion occurs only at core bridges. Whereas multiple source routing [15] can select an end-to-end path at an edge node, it is difficult to employ this algorithm because BEBs need to know the RTT of all flows. Gao et al. [16] proposed a delay-based load balancing algorithm for MPLS networks. Average one-way delay is obtained between Label Switched Routers (LSRs) with probe packets. Traffic is dynamically distributed among Label Switched Paths (LSPs) according to this average. To employ this method in SPBM networks, a probing mechanism is required for BEBs. Moreover, the clocks in BEBs must be synchronized. Nakayama [17] proposed a path selection algorithm for SPBM. It optimizes the path selection probabilities of ECTs
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IEEE ICC 2014 - Communication QoS, Reliability and Modeling Symposium
TABLE I VARIABLES
j
0
j
1
Flow Rate i ri
BEB
Last arrival ti
Selected path pi
0
1
00:01
0
1
8
00:10
1
2
4
00:05
0
䞉
䞉
䞉
䞉
Item
Variable
flow identifier
i
selected path
pi
estimated input rate
ri
Path j
Average Aj
last frame arrival time
ti
0
4
40
10
path identifier
j
1
6
120
20
total rate
Rj
average rate
Aj
maximum rate
Mj
number of assigned flows
nj
current time
t
timeout value
δ
Fig. 3.
based on the amount of traffic expected on each link. Although it improves the link utilization and throughput fairness, it requires accurate estimation of the amount of traffic on each link. Therefore, it is difficult to employ this algorithm for any type of network.
Tables of BEB.
k
rinew = (1 − e−Ti /K )
A. Concept
B. Algorithm The details of the proposed algorithm are as follows. 1) Variables: Table I shows the variables used in this study. Let i denote a flow identifier. Let pi denote the selected path for flow i. Let ri denote the estimated input rate of i. ti denotes the time at which the last frame of i arrives at the BEB. Let j denote a path identifier for each path of ECTs. Rj denotes the total rate and Aj denotes the average rate of j. Mj denotes the maximum rate for j. nj denotes the number of flows assigned to j. Let t denote the current time and δ denote a timeout value.
Flow nj
2) Tables: Fig. 3 shows the tables that the BEB possesses. BEBs have two types of tables: flow tables and path tables. In the flow table, the BEB records the input rate ri , last arrival time ti , and selected path pi for each flow i from outside the SPBM network. The input rate can be obtained in many ways. For example, it can be estimated with the marking threshold of N rate N+1 color marking㸦NRN+1CM) [7] or the frame arrival time [18]. If the marking threshold of NRN+1CM [7] is used, ri is estimated by dw where d denotes the marking threshold and w denotes the token accumulation rate. If the frame arrival time [18] is used, ri is calculated as follows:
III. P ROPOSED ALGORITHM This paper proposes a rate-based end-to-end path selection algorithm for avoiding congestion in SPBM networks. The proposed algorithm assigns flows to ECTs at a BEB based on their traffic rate. First, I describe the concept of the proposed algorithm. With the proposed algorithm, a BEB selects the path for each flow from ECTs based on the rate distribution. When a new flow arrives at a BEB, the BEB selects the path with the highest average input rate of assigned flows, to avoid selecting a congested path. The proposed algorithm assumes that a path with a low average rate will be congested because the TCP flow rates decrease on a congested path. Therefore, the BEB selects the path with the highest average rate on which the new flow can expect to realize a high rate. The flow assignment can also consider the maximum rates of each path. Since the proposed algorithm expects an increase or decrease in the TCP flow rates, it does not work if most of the flows are UDP flows.
Total Rj
k lik + e(−Ti /K) riold Tik
(1)
where tki and lik denote the arrival time and length of the k th packet of i, and Tik = tki − tk−1 and K is a constant. i The BEB updates the path tables with the flow table. The path tables are generated for each set of ECTs. In Fig. 3, a path table that consists of j = 0 and j = 1 is described as an example. For each path j, the total rate Rj and the average rate Aj are calculated with (2) and (3), where nj denotes the number of flows assigned to j. ri s.t. pi = j (2) Rj = i
Aj =
Rj nj
(3)
Before Rj and Aj are calculated, the flows are sorted by ri and the highest rate flows can be excluded. The percentage of excluded flows can be decided by network operators. With this process, Rj and Aj are not affected by particular flows with a high input rate, because the number of such flows is assumed to be small. 3) Path selection: When a frame of i arrives, the BEB decides whether i is a new or continuous flow. If t − ti ≥ δ is satisfied, i is a new flow. Otherwise, i is a continuous flow. In both cases, ti and ri are updated. If i is a new flow, pi is newly decided. If there is j0 that satisfies Rj0 = 0, j0 is selected for the path for i and pi = j0 . If there is no j that satisfies Rj = 0, S is generated with (4).
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S = {j
| M ax(Aj )}
(4)
IEEE ICC 2014 - Communication QoS, Reliability and Modeling Symposium
S is a set of j with the maximum average rate Aj . The path for i is selected with (5). pi = j ∈ S
s.t.
M in(Rj )
(5)
From S, j with the minimum total rate Rj is selected. If i is a continuous flow, the BEB chooses the path that is selected for the last frame of i to avoid frame reordering. Let pi denote the previously selected path. pi = pi is satisfied. Therefore, flows are distributed at the BEB to avoid congestion. The BEB selects the path with the highest average rate on which the new flow can be expected to achieve a high rate, because the path with a low average rate is assumed to be congested. A parameter δ should be decided that does not cause frame reordering. 4) Maximum rate: The maximum rate Mj can be set for each path j. The path assignment for each flow is performed not to exceed the maximum rate Mj . j can be selected as long as Rj + ri ≤ Mj . If Rj + ri > Mj , j is not selected for i. If Rj + ri > Mj is satisfied for all j, j with the minimum Rj − Mj is selected. If a specific path is estimated to become congested with a high probability because of the network topology or the user distribution, the network operator can limit the traffic amount for that path from a BEB with Mj . IV. E VALUATION The performance of the proposed algorithm was evaluated with computer simulations using a network simulator ns2 [19]. First, I confirmed the path selection of the proposed algorithm with a simple network. Then, I confirmed that the flows were distributed to avoid congestion, and throughput fairness and the total throughput were improved in a more realistic multi-ring topology. The simulation conditions are shown in Fig. 4. A. Simple network 1) Assumptions: The simulation conditions are shown in Fig. 4a. There were 5 bridges that were connected with SPBM. The link to the destination node was 1 Gbps and other links were 100 Mbps. The link delay was 10 ms for SPBM bridge links and 0.05 ms for other links. The metric was assumed to be the same for all links. 25 users were linked to BEB0 and 100 users were linked to BEB1. The users sent flows to the destination node for 5 s. The users connected to BEB0 sent TCP flows and they had 2 ECTs. The users connected to BEB1 sent 5 Mbps UDP flows as background traffic. NRN+1CM [7] works in the SPBM network to provide throughput fairness when there is congestion. The input rate ri was estimated with a marking threshold of NRN+1CM. The parameters in [7] were set at the number of colors N + 1 = 16, token bucket length B = 2.5 KB, initial token 1 B xd = B(1− d+1 ), and yd = d+1 . The token accumulation rate was w = 0.5 Mbps. The frame length was 1.5 KB. To simplify the simulation, the PBB header length was not considered. To confirm the behavior of the proposed algorithm, the timeout value δ was set at a sufficiently large value. It was 80 ms. For
the total rate Rj and the average rate Aj calculation, 10 % of the highest rate flows were excluded. Under these conditions, I confirmed that BEB0 can select the path to BCB0 for TCP flows and avoid selecting the path to BCB1 because the BCB1-BEB2 link is expected to become congested with UDP flows. 2) Result: Fig. 5a shows the dynamics of the total rate Rj for each path at BEB0. Almost all the flows were assigned to the path to BCB0. Fig. 5b shows the distribution of the average throughput of the TCP flows. One flow was assigned to the path to BCB1 and the throughput was low. The throughput of the other flows was around 4 to 5 Mbps. This result matches the feature of the proposed algorithm whereby at least one flow is assigned to the congested path. For other flows, BEB0 selected the path to BCB0 and avoided selecting the congested path to BCB1. Therefore, the path selection operation of the proposed algorithm avoids selecting the congested path. B. Multi-ring topology 1) Assumptions: The simulation conditions were as follows. The network topology is shown in Fig. 4b. This is a simple case of a multi-ring topology that is expected to be employed in access networks. There were 9 bridges in the SPBM domain. The user nodes of users A, B, C, D, and E were linked to BEBs. All links were 1 Gbps and the link delay was 5 ms for SPBM bridge links, and 0.05 ms for the other links. The metric was the same for all links. Traffic is transmitted between the user nodes of users A, B, C, D, and E for 10 s. The flow paths are shown in Fig. 4b. There are ECTs for users A, B, and C. User nodes of A, B, and C each sent 200 TCP BE flows to other user nodes. For example, a user C node sent a total of 400 flows and received a total of 400 flows from other user C nodes. User nodes of D and E transmitted each 300 and 100 sessions of UDP priority flows to the other user nodes. The data rates were 2 Mbps. NRN+1CM works in the SPBM network. The parameters were the same as IV-A. The BE queue length of BEBs was 1 MB and the timeout value δ was 20 ms. I evaluated the throughput of BE TCP flows that are distributed to ECTs, which is easily affected by congestion on each path. The proposed algorithm is compared with the optimal probability method [17] and the hash function using the frame header. With the optimal probability method, flows are distributed at BEBs based on the optimal path selection probabilities that are calculated with the expected traffic amount on each link. The traffic weight for the optimal probability method was set at the same for all the sourcedestination combinations. 2) Result: The throughputs of TCP flows are averaged by source-destination combinations. The average and the standard deviation are shown in Fig. 6. Fig. 6a shows the result with the proposed algorithm. The standard deviation is small on the whole. The throughput fairness is realized for each source-destination combination. This is because BEBs could select the path on which the new flow can expect to achieve a high rate.
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IEEE ICC 2014 - Communication QoS, Reliability and Modeling Symposium
Link speed 1 Gbps
Link speed
Dest
1 Gbps 100 Mbps
A
C
2
3
C
E
user A path user B path
4
user C path
SPBM BEB2
user D path user E path
B BCB0
BCB1
1
8
5
B
0
7
6
SPBM
D
A
E
BEB0
BEB1 users
(a) Simple network Simulation conditions.
120
100
100
80
80
Frequency [%]
Toal rate [Mbps]
D
(b) Multi-ring topology Fig. 4.
60 40
60
40
20
20 0
C
To BCB0 To BCB1 0
1
2
3
4
0
5
0
Time [s]
(a) Total rate for each path
1
2
3
4 5 6 Throughput [Mbps]
7
8
9
10
(b) Average throughput Fig. 5.
Result for simple network.
Fig. 6b shows the result with the optimal probability method. The standard deviation at the path between BEB1 and BEB5 is small because all flows are transmitted on the path of BEB 1–0–7–6–5. The standard deviation is large at the paths of BEB 2–7, BEB 7–2, and BEB 6–3. Some flows obtain high bandwidth and others obtain low bandwidth because the traffic congestion states are different between ECTs. This fairness degradation is caused by the difference between the expected and actual amounts of traffic. Fig. 6c shows the result with the hash function. The standard deviation is large at the paths of BEB 2–7 and BEB 7–2. With the hash algorithm, traffic congestion was heavier and more of the frames of flows assigned to the congested path were discarded. Some of the flows that selected the uncongested path realized a large bandwidth. The proposed algorithm also improved the total throughput. The network resources were used efficiently. The flows were distributed to avoid congestion and throughput fairness was realized. C. Discussion A major concern about splitting frames to multiple paths is frame reordering. Frame reordering can be avoided by setting the timeout value δ at an appropriate value. δ has the same characteristics with Minimum Time Before Switch-ability (MTBS) for flowet switching [13]. MTBS is determined as
the difference between the maximum and minimum latencies of ECTs. As long as δ is larger than MTBS, flowlet switching does not cause frame reordering. In the multi-ring simulation, the link delay is the same for ECTs. The difference between the maximum and minimum latencies is caused by the queueing delay of each path. Since the BE queue length was 1 MB and the link bandwidth was 1 Gbps, the maximum queueing delay is 8 ms at each link. I estimated the difference between the maximum and minimum latencies at 50 % of the maximum queueing delay per hop, and δ was set at 20 ms. With this assumption, δ is larger than MTBS and the proposed algorithm does not cause frame reordering. The drawback of the proposed algorithm is cost. The implement cost for the proposed algorithm is larger than the one of hash function and the one of the optimal probability method. BEBs need to have flow tables and path tables. They record input rate, frame arrival time, and selected path for all flows in the flow tables. Then, they calculate the total rate and the average rate for each path and record them in the path tables. Among these functions, the most complicated function is the input rate estimation. If a rate-based fairness algorithm is employed, the proposed algorithm can use the rate estimated by the fairness algorithm as the input rate. Therefore, the implement cost is reduced by using the proposed algorithm
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2.5
2.5
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1.5 1 0.5 0
Throughput [Mbps]
3
Throughput [Mbps]
Throughput [Mbps]
IEEE ICC 2014 - Communication QoS, Reliability and Modeling Symposium
1.5 1 0.5
1- 5
5- 1
2- 7 7- 2 Src BEB - Dst BEB
3- 6
6- 3
0
1.5 1 0.5
1- 5
(a) Proposed algorithm
5- 1
2- 7 7- 2 Src BEB - Dst BEB
3- 6
(b) Optimal probability Fig. 6.
6- 3
0
1- 5
5- 1
2- 7 7- 2 Src BEB - Dst BEB
3- 6
6- 3
(c) Hash function
Result for multi-ring topology.
with a rate-based fairness algorithm. V. C ONCLUSION This paper described a rate-based path selection algorithm for access networks with SPBM. With SPBM in an access network, the shortest path transmission can be realized without a blocking port in any network topology. The approach is expected to use network resources efficiently and to simplify the operating procedure. Access networks can be flexibly constructed on demand with SPBM. However, if there is a deviation in the flow traffic rate, the paths of high rate flows can overlap on specific links and congestion will occur. It is important to avoid congestion by selecting the optimal path for each flow. This paper proposed a rate-based path selection algorithm for access networks with SPBM. The proposed algorithm assumes that a path with a low average rate will be congested because the TCP flow rates decrease on a congested path. When a new flow arrives at an edge switch, it selects the path with the highest average rate on which the new flow can be expected to realize a high rate. The flow assignment can also consider the maximum rates of each path. I confirmed with computer simulations that the proposed algorithm could efficiently utilize links and improve throughput fairness. Although I assumed there to be only one priority class and BE class for traffic, the proposed algorithm can be applied irrespective of the number of priority classes. As long as all of the higher priority classes are managed by the network operator in order to avoid congestion and transmitted prior to BE, BE flows are assigned to the path with the highest average rate by the proposed algorithm. Future work will constitute developing an algorithm that works even if there are many UDP flows.
[5] Routing Bridges (RBridges): Base Protocol Specification, RFC6325, July 2011. [6] OSI IS-IS Intra-domain Routing Protocol, RFC1142, February 1990. [7] Y. Nakayama and N. Oota, “Fairness with n rate n+1 color marking on cascade aggregation for access network,” in IEEE Global Telecommunications Conference (GLOBECOM 2011), December 2011, pp. 1–5. [8] M. Al-Fares, A. Loukissas, and A. Vahdat, “A scalable, commodity data center network architecture,” in ACM SIGCOMM Computer Communication Review, vol. 38, no. 4. ACM, 2008, pp. 63–74. [9] S. Prabhavat, H. Nishiyama, N. Ansari, and N. Kato, “On load distribution over multipath networks,” IEEE Communications Surveys & Tutorials, vol. 14, no. 3, pp. 662–680, 2012. [10] R. Martin, M. Menth, and M. Hemmkeppler, “Accuracy and dynamics of hash-based load balancing algorithms for multipath internet routing,” in 3rd International Conference on Broadband Communications, Networks and Systems (BROADNETS 2006). IEEE, 2006, pp. 1–10. [11] J.-Y. Jo, Y. Kim, H. J. Chao, and F. L. Merat, “Internet traffic load balancing using dynamic hashing with flow volume,” in The Convergence of Information Technologies and Communications (ITCom 2002). International Society for Optics and Photonics, 2002, pp. 154–165. [12] T. W. Chim, K. L. Yeung, and K.-S. Lui, “Traffic distribution over equal-cost-multi-paths,” Computer Networks, vol. 49, no. 4, pp. 465– 475, 2005. [13] S. Kandula, D. Katabi, S. Sinha, and A. Berger, “Dynamic load balancing without packet reordering,” ACM SIGCOMM Computer Communication Review, vol. 37, no. 2, pp. 51–62, 2007. [14] R. Krishnan and J. Silvester, “An approach to path-splitting in multipath networks,” in IEEE International Conference on Communications (ICC 1993), vol. 3. IEEE, May 1993, pp. 1353–1357. [15] L. Wang, Y. Shu, M. Dong, L. Zhang, and O. W. Yang, “Adaptive multipath source routing in ad hoc networks,” in IEEE International Conference on Communications (ICC 2001), vol. 3. IEEE, June 2001, pp. 867–871. [16] D. Gao, Y. Shu, S. Liu, and O. W. Yang, “Delay-based adaptive load balancing in mpls networks,” in IEEE International Conference on Communications (ICC 2002), vol. 2. IEEE, 2002, pp. 1184–1188. [17] Y. Nakayama, “Optimization of ECT selection probability in SPBM networks,” in IEICE Communication Express, vol. 3, no. 1, pp. 33–38, 2013. [18] I. Stoica, S. Shenker, and H. Zhang, “Core-stateless fair queueing: a scalable architecture to approximate fair bandwidth allocations in highspeed networks,” IEEE/ACM Transactions on Networking, vol. 11, no. 1, pp. 33–46, February 2003. [19] Network Simulator ns-2, available: http://www.isi.edu/nsnam/ns/.
R EFERENCES [1] Ethernet Ring Protection Switching, ITU-T Recommendation G.8032/Y.1344, June 2008. [2] J. Ryoo, H. Long, Y. Yang, M. Holness, Z. Ahmad, and J. Rhee, “Ethernet ring protection for carrier ethernet networks,” IEEE Communications Magazine, vol. 46, no. 9, pp. 136–143, 2008. [3] Provider Backbone Bridges, IEEE Standard 802.1ah, June 2008. [4] Shortest Path Bridging, IEEE Standard 802.1aq, March 2012.
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