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A survey of multipath routing for traffic engineering

Gyu Myoung Lee, Jin Seek Choi

Information and Communications University (ICU)

{gmlee, jin}@icu.ac.kr

Abstract Traffic engineering broadly relates to optimization of the operational performance of a network. This

survey discusses techniques like multi-path routing using traffic splitting, constraint-based routing, path-

protection etc. that are used for traffic engineering. Multipath routing can be effectively used for

maximum utilization of network reso urces. It gives the node a choice of next hops for the same destination.

The various algorithms discussed give solutions for effectively calculating the multipaths and ways to

minimize delay and increase throughput. Multipath routing is capable of aggregating the resources of

multiple paths and reducing the blocking capabilities in QoS oriented networks, allowing data transfer at

higher rate when compared to single path. It also increases the reliability of delivery. We surveyed the

various multipath routing mechanisms for traffic engineering. Especially, these works can be applied to

MPLS/GMPLS network, then enhance network performance through traffic engineering and meet the

QoS requirements.

1. Introduction

The unprecedented growth of the Internet has lead to a growing challenge among the ISPs to provide a

good quality of service, achieve operational efficiencies and differentiate their service offerings. ISPs are

rapidly deploying more network infrastructure and resources to handle the emerging applications and

growing number of users. Enhancing the performance of an operational network, at both the traffic and

the resource levels , are major objectives of traffic engineering [1]. Traffic engineering (TE) is defined as

that aspect of Internet network engineering dealing with the issue of performance evaluation and

performance optimization of operational IP networks [1]. The goal of performance optimization of

operational IP networks is accomplished by routing traffic in a way to utilize network resources

efficiently and reliably. Traffic engineering has been used to imply a range of objectives, including load-

balancing, constraint-based routing, multi-path routing, fast re-routing, protection switching etc.

Many implementation strategies for Traffic Engineering and Quality of Service are deployed. Popular

approaches such as virtual circuits and solutions based on MPLS use a sort of connection-oriented

mechanisms. MPLS uses label switched paths between hosts to distribute the incoming traffic among

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these paths. IETF calls for Integrated Services architecture with RSVP, but this is not a scalable solution

because of the per-flow overhead associated. Progress towards aggregation of flows to reduce the state

size and processing power at routers has been made. In Aggregated RSVP per-flow routing state has

given way to per source-destination routing state.

The Internet today provides only a single path between any pair of hosts that fundamentally limits the

throughput achievable between them. For example, dramatically faster large file transfer or higher frame-

rate video would be possible if applications could expect that multiple transport level sessions would be

mapped to different paths in the network, and they have control over splitting traffic between these

sessions. Multipath routing can be effectively used for maximum utilization of network resources. It gives

the node a choice of next hops for the same destination. The various algorithms discussed give solutions

for effectively calculating the multipaths and ways to minimize delay and increase throughput. Multipath

routing is capable of aggregating the resources of multiple paths and reducing the blocking capabilities in

QoS oriented networks, allowing data transfer at higher rate when compared to single path. It also

increases the reliability of delivery. We surveyed the various multipath routing mechanisms for traffic

engineering. Especially, these works can be applied to MPLS/GMPLS network, then enhance network

performance through traffic engineering and meet the QoS requirements.

The organization of this paper is as follows. In section 2, the concept and fundamental scheme of

multipath routing is explained. And then, we discuss the benefits of multipath routing. Section 3 presents

the existing multipath routing algorithms. Then, in section 4, we discuss the multipath routing in

traditional IP network. The multipath routing mechanisms applied to MPLS networks are discussed in

section 5. In section 6, we propose the multipath routing method using GMPLS control plane in IP over

optical networks. The conclusions and future work are given in section 7.

2. Multipath routing fundamentals

2.1. Multi path Routing

Multipath routing aims to exploit the resources of the underlying physical network by providing

multip le paths between source-destination pairs. Multipath routing has a potential to aggregate bandwidth

on various paths, allowing a network to support data transfer rates higher than what is possible with any

one path [2]. The work in the area of multi-path routing has focused mainly on extending intra-domain

routing algorithms (both RIP and OSPF) for multipath support [3], [4], [5] . There are two aspects of a

multi-path routing algorithm: computation of multiple loop-free paths and traffic splitting among these

multiple paths. Extensive work has been done in both these areas. Distributed multi-path routing

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algorithms can be viewed as an extension of hop-by-hop routing algorithms. Centralized multi-path

algorithms can be used in the MPLS framework to influence establishment of LSPs. However, traffic

splitting algorithms may be used to the traffic among multiple paths in both the cases.

2.2. Multipath Routing scheme

A host that provides multiple paths must first calculate the path sets between the source and destination.

Two of the characteristics that can be used for determining a path set are path quantity and path

independence. Path quantity is the number of available paths between nodes. The higher the number

better are the chances for load distribution. Uniform path sets are preferable over high variance path sets

i.e. a path set with every node having 5 paths is preferred than one with nodes having 1 path for some

path sets and 9 paths for other path sets. The second characteristic of path sets is path independence,

which is illustrated with Fig. 1. Consider a path set with 2 paths (a, b, c, d) and (a, f, c, d) and other path

set with 2 paths as (a, b, c, d) and (a, f, e, d). The second set is independent when compared to the first set.

af e

d

b c

af e

d

b c

Fig. 1. Illustration of multipath routing scheme

So the second set would lead to better usage of resources and is less likely to be congested because at

least one link in each path should be congested, whereas in the first set congestion at link (c, d) is

reflected in both the path sets. Multipath sets with these attributes facilitate for higher performance.

2.3. The benefits of multipath routing

l Load balancing

The main goal with load balancing is to make more use of available network resources in order to

minimize the risk of traffic congestion. Hopefully this would lead to less delay and packet loss. It could

however lead to additional propagation delay if the alternative routes are badly chosen. Some applications

are very sensitive to delays (e.g. VoIP). Others are more sensitive to packet loss.

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In SPF-algorithms, load balancing cannot be done over links with different assigned costs. When

manually configuring a good load balancing, the traffic demand must be predictable to avoid

unanticipated traffic congestions. Traffic or policy constraints are not taken into account in the static

splitting of traffic. The administrator responsible for the load-sharing configuration will have to be

attentive to changes in the traffic pattern. These changes could come from a change of routing policy in a

peering network, a link failure, a change of topology or a sudden change of popularity for an application.

As a result of this instability in traffic flow, the administrator will have to devote a lot of time tuning the

configuration to achieve a stable network load balance.

Load balancing requires an ability to control traffic flow precisely. In the traditional metric-based

control, an administrator can change only link metrics, and changes of some link metrics may affect the

overall traffic flow. To control traffic flow as the administrator wants, it is necessary to adjust the link

metrics over a network; however, sometimes this adjustment is impossible. Therefore, explicit route

based control, in which the administrator can control traffic as he wants, appears to be a far more

promising choice.

l Quality of Service

Several architectures have been proposed for implementing Quality of Service. In the IETF’s Integrated

Services architecture reservations are made on per-flow basis, which is not a scalable solution because

routers require large amount of memory to store routing and reservation states and maintaining

consistency, given network failures is complex. Another implementation uses stateless approach similar to

Differentiated Services. This is also not an efficient and scalable solution when link failures occur, as the

overhead and processing power for maintaining consistency is high.

Multipaths allow for aggregation of flows and provide a scalable solution. Flows are aggregated at

ingress router depending on class of service and destination. Flows are processed only on aggregate basis,

at core routers. Aggregation is done such that by providing quality to aggregated flow, quality is

guaranteed for individual flows within this aggregate.

3. Multipath routing algorithms

Most routing protocol in current use, such as RIP [6], EIGP [7], and OSPF [8], make very inefficient

use of bandwidth usage. To improve bandwidth utilization, and reduce delay, several improvements to the

basic routing protocols have been proposed. In this section we discuss various routing protocols that are

in research currently and/or are in use for construction of multipaths. Two factors to be considered for

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efficient routing graph construction are loop freedom and connectivity. We describe below Equal-cost

multi-path (ECMP), Multiple Path Algorithm (MPA), Discount Shortest Path Algorithm (DSPA),

Capacity Removal Algorithm (CRA), Multipath Distance Vector Algorithm (MDVA)-distance vector

algorithm, Multipath Partial Dissemination Algorithm (MPDA)-link state algorithm, MPATH- distance

vector algorithm with predecessor information and present a new algorithm QMPDA-Quality Multiple

Partial dissemination Algorithm that takes into account QoS provisioning and network failures.

Equal -cost multi-path (ECMP)

Equal-cost multi-path (ECMP) [8] is a routing technique for routing packets along multiple paths of

equal cost. Load is distributed equally over multiple equal-cost paths typically using simple round-robin

distribution. Optimal splitting with ECMP has been researched in OSPF-Optimized Multi Path (OMP) [9].

OSPF-OMP uses ECMP, but instead of depending upon weight assignments, it samples traffic load

information and floods it via opaque LSAs. This information is used to change local load splitting

decisions

Multiple Path Algorithm (MPA)

In [10], authors present Multiple Path Algorithm (MPA) that can be implemented as an extension to

OSPF. MPA finds only a subset of paths that satisfy a condition for loop-freeness. However, it does not

find all loop-free paths to a destination. A router only considers paths with next -hop such that the weight

of shortest path from next -hop to destination is less than the weight of the shortest path from router to

destination.

Discount Shortest Path Algorithm (DSPA) [11]

It is used for minimizing the delay. It takes into account the path quantity and path independence and

proposes paths that are compromises of Shortest K and link disjoint algorithms. This algorithm assumes

that there is a maximum acceptable cost on length, say Cmax. Paths are calculated between nodes a and b

such that the ith path is the least-cost path between a and b and is less than Cmax. The cost of ith path is

calculated after adding the increment in cost for each link in path j from a to b, where 1<= j < i , and cost

increment of path z is ( Cmax – (Cost(z)) / (Length(z))). The algorithm calculates the shortest path z from a

to b with cost Cz. Cmax is then calculated as L*Cz (where L is constant depending on implementation).

Cost increment for this path is given as Zincr = (Cmax+1) – Cz. This cost increment i.e. (Zincr / Length(z))

is then added uniformly to each link on path z. This process is repeated for other path calculations until

the shortest k paths are computed or until there are no paths from a to b with cost less than Cmax. Then the

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link costs are restored to original values and paths are computed for other nodes. The complexity of the

algorithm is O(K*E*lg(E)) . The complexity is K times greater than calculating single shortest path

between two nodes.

Capacity Removal Algorithm (CRA) [11]

It is used for maximizing throughput, which depends on varying traffic conditions. Assuming that

higher link capacity means higher bandwidth available, this algorithm calculates paths to increase flow

between nodes. As in Discount Shortest Path algorithm, Capacity Removal Algorithm calculates the

successive shortest paths. After calculating paths it decreases path capacity (the minimal capacity of all

links) from every link. Link capacity threshold is used to eliminate links in path calculation that fall

below this level. So for nodes a and b, the ith path is least-cost path with cost less than Cmax and capacity

greater than threshold capacity. Path i’s capacity is calculated after subtracting path j’s capacity from

every link in the path j, where 1<= j < i . The complexity of this algorithm is O(K*E*lg(E)) .

Used for maximizing throughput• Depends on varying traffic conditions• Calculates paths to increase flow between nodes

Capacity Removal Algorithm (CRA)

O(K*E*lg(E))K times greater than calculating single shortest path between two nodes

Used for minimizing the delay• Takes into account the path quantity and path independence• Proposes paths that are compromises of shortest k and disjoint algorithms

Discount Shortest Path Algorithm (DSPA)

ComplexityObjectiveAlgorithm

Used for maximizing throughput• Depends on varying traffic conditions• Calculates paths to increase flow between nodes

Capacity Removal Algorithm (CRA)

O(K*E*lg(E))K times greater than calculating single shortest path between two nodes

Used for minimizing the delay• Takes into account the path quantity and path independence• Proposes paths that are compromises of shortest k and disjoint algorithms

Discount Shortest Path Algorithm (DSPA)

ComplexityObjectiveAlgorithm

Table 1. Comparisons of DSPA and CRA

Multipath Distance Vector Algorithm (MDVA)

In [12], authors extend the DV algorithms to compute loop-free multi-paths at every instant. They

propose MDVA that is free from count-to-infinity problem, provides multiple next -hop choices for each

destination and the routing graphs implied by these paths are always loop-free. The MDVA algorithm has

been designed around a set of loop-free invariant conditions that ensure instantaneous loop-freedom and

prevents count-to-infinity.

Multipath Partial Dissemination Algorithm (MPDA)

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MPDA [13] is a link state algorithm. It uses the Partial Dissemination Algorithm (PDA) for computing

the shortest distance to destination. This algorithm extends PDA to incorporate the LFI (Loop-Free

Invariant) conditions to obtain MPDA. The PDA is a shortest path routing algorithm in its own right and

can be used in practice, but its advantage here is that it can be modified easily to enforce LFI conditions.

In MPDA, each LSU (Link State Update) message sent by a router is acknowledged by all its neighbors

before the router sends the next LSU. The inter-neighbor synchronization used in MPDA spans only a

single hop, unlike the synchronization in diffusing computations which potentially spans the whole

network.

MPATH

Routing protocols in general, use either link-state or distance-vectors for communication. MPATH [13]

is the first multipath algorithm that uses distance-vectors combined with identity of second-last-node (the

node just before destination), also called as predecessor node. MPATH is the first-finding algorithm that

builds multiple loop-free paths.

Quality Multiple Partial dissemination Algorithm (QMPDA)

QMPDA [11] is a link state algorithm and is an enhancement to MPDA algorithm described above.

QMPDA takes into account network failures and topology changes and provides a solution for supporting

diffe rent Class of Services. The main step is to aggregate flows along multipaths using flow classes. It is a

scalable solution and is simple to implement. Since bandwidth is limited, the performance benefits of

multipath routing are acceptable though there is a slight increase in the complexity of computing route

tables. Hence Multipath routing clearly provides a scalable solution for providing QoS. This algorithm

introduces a new step during an event, which is raised when a topology change occurs due to node or link

failure.

•Use distance vectors combined with identity of second-last-node (predecessor node)

Distance vector algorithm

MPATH

•Synchronizes the exchange of LSU’s(Link State Update) between neighbors•Takes into account network failure and topology changes (QMPDA)

Link state algorithm

Multipath Partial Dissemination Algorithm (MPDA),QMPDA

•Use Distributed Bellman-Ford (DBF) algorithm•Compute loop-free multipath

Distance vector algorithm

Multipath Distance Vector Algorithm (MDVA)

FeatureClassificationAlgorithm

•Use distance vectors combined with identity of second-last-node (predecessor node)

Distance vector algorithm

MPATH

•Synchronizes the exchange of LSU’s(Link State Update) between neighbors•Takes into account network failure and topology changes (QMPDA)

Link state algorithm

Multipath Partial Dissemination Algorithm (MPDA),QMPDA

•Use Distributed Bellman-Ford (DBF) algorithm•Compute loop-free multipath

Distance vector algorithm

Multipath Distance Vector Algorithm (MDVA)

FeatureClassificationAlgorithm

Table 2. Comparisons of MDVA, MPDA and MPATH

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4. Multipath routing in traditional IP network

4.1. Minimum Delay Routing Using Distributed Computation

In [14], authors developed a distributed computation framework for multi-path routing that guarantees

minimum average delays, assuming stationary inputs and links. (Quasi-static case in not studied and

might have implications to the update cost and noisier measurements of marginal link delays and node

flows). Also, the routing algorithm needs to start with an initial loop free set. While the proof assumes

infinitely divisible traffic, it remains to be seen how this will operate with coarser granularity flows.

The optimal routing algorithm of [14] is extremely difficult if not impossible to implement in real

networks because of its stationary or quasi-static assumptions and the requirement of the knowledge of

global constants. Several other algorithms have been proposed in literature [15], [16], [17], [18] that

improves this minimum delay algorithm of [14]. Extensions of the minimum delay algorithm to handle

topological changes are proposed in [15], [16] which use distributed routing techniques developed in [21].

An improved technique for measuring the marginal delays is presented in [16] while [15] uses second

derivatives to increase the convergence rate of the original minimum delay algorithm. In [19] a simpler

algorithm is proposed which can achieve near-optimal routing. The impact of granularity on network and

routing behavior is studied in [20]. The authors noticed that while finer granularity improved network

performance, this does not carry over when routing updates are made at smaller time scales. Finer

granularities also imply higher classification/processing at nodes/ingress that results in more expensive

packet forwarding.

A Minimum Delay Routing Algorithm Using Distributed Computation (1977)multi-path routing that guarantees minimum average delays

Using “A failsafe distributed routing protocol (1979)”

Second derivative algorithms for minimum delay distributed routing in networks (1984)second derivatives to increase the convergence rate of the original minimum delay algorithm

Distributed routing with on-line marginal delay estimation (1990)An improved technique for measuring the marginal delays

Extensions of the minimum delay algorithm to handle topological changes

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The modeling of adaptive routing in data-communication networks (1977)

A failsafe distributed protocol for minimum delay routing (1981)

Improve the minimum delay algorithm

A Simple Approximation to Minimum-Delay Routing (1999)A simpler algorithm can achieve near-optimal routing

On the impact of aggregation on the performance of traffic aware routing (2000)The impact of granularity on network and routing behavior

à A constrained multipath traffic engineering scheme for MPLS networks (2002)

Fig. 2. Minimum delay routing using distributed computation

4.2. Linear programming problem

Another approach is to associate a linear or piece-wise linear penalty function with every link in the

network and the objective is to minimize the penalty for all links in the network. Penalty function may be

chosen to approximate the packet drop rate or delay using M/M/1 queueing model. Then the traffic split

may be obtained by solving the linear-programming (LP) problem (referred to as optimal general routing

in [23]).

The bifurcation LP problem is formulated and heuristics for the non-bifurcating problem are proposed

[22]. Although [22] minimize the maximum of link utilization, it does not consider total network

resources and constraints

In [24], Wang et. al. have formulated a linear optimization problem to minimize the maximum of link

utilization. Optimal traffic split can be obtained by solving this LP problem. However, they have used the

dual formulation to obtain the link weights that would lead to optimal routing under the assumption of

arbitrary traffic splitting across multiple ECMPs. This is an important result because for a linear objective

function, any optimal routing can be implemented using the existing shortest path routing. One may note

that since this is a centralized approach, it also assumes knowledge of global demand matrix and quasi-

static traffic. The key contribution of this paper is to prove the fact that the traffic bifurcation LP problem

can be transformed into the shortest path problem by adjusting link weights

Simple local heuristics at the source/intermediate routers may also lead to a substantially improved

performance as compared to the default OSPF routing. A study of various traffic splitting techniques,

tradeoff of computational complexity and performance is an area open to research.

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Explicit routing algorithms for Internet traffic engineering (1999)Minimize the maximum of link utilization

Internet Traffic Engineering by Optimizing OSPF Weights (2000)Optimal general routing

Internet Traffic Engineering without Full Mesh Overlaying (2001)Optimal traffic split using LP

Fig. 3. Linear Programming (LP) problem

4.3. Packet splitting methods

While multi-path routing allows multiple paths between a source and destination, how packets are split

on these paths is an important issue. Sending TCP packets from a single flow on multiple paths with

different round-trip-time (RTT) would lead to out-of-order packet arrivals and hence, performance

degradation. Three main approaches modulo-N hash, hash-threshold and highest random weight have

been described and studied in RFC-2991 [25]. The most commonly used scheme is hash-threshold.

Performance of this scheme has been studied in greater detail in RFC-2992 [26]. However, if hashing is

done on the source-destination IP address using a CRC16, the traffic distribution can only be done with a

coarse granularity [27]. Using a 32-bit CRC to hash on source-destination IP address and port number

leads to a finer granularity. However, using TCP port numbers at every hop is expensive. In [27], authors

propose to treat UDP and TCP packets in a different fashion. Out-of-order packet arrival is not too

expensive for UDP packets. However, they propose a modified version of hash-threshold scheme. They

propose to generate and insert in the packet a random key based on the source-destination IP addresses

and port numbers. This is done at the source/ingress router. Within the core network the key is used to

determine the next -hop at each router. They propose to use the 13-bit fragment packet offset field to store

the hash key (if fragment packet offset field is zero, i.e. the packet is un-fragmented). They also propose

to use the TOS or DSFIELD bit to indicate whether the packet is a UDP or TCP packet. This eliminates

the need to read packet header at each hop and facilitates faster forwarding. However, the trade-off is out-

of-order arrival of fragmented packets.

4.4. Dynamic multipath routing schemes

In [28], authors describe briefly a dynamic multipath routing scheme that has been considered for

connection oriented homogeneous high speed networks. The fundamental objective of the scheme is to

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bridge the gap between routing and congestion control as the network becomes congested. Because

propagation delay far out shadows queueing and transmission delay in high speed networks, the proposed

routing scheme works as a shortest path (minimum hop) first algorithm under traffic conditions. However

as the shortest path become congested, the source node uses multiple paths when and if available in order

to distribute the load and reduce packet loss. The scheme is a cross between alternate path routing and

trunk reservation.

Under reasonable protocol and computational overheads, traditional approaches to load-sensitive

routing of IP traffic are ineffective, and can introduce significant route flapping, since paths are selected

based on out-of-date link-state information. Although stability is improved by performing load-sensitive

routing at the flow level, flapping still occurs, because most IP flows have a short duration relative to the

desired frequency of link-state updates. In, [29], to address the efficiency and stability challenges of load-

sensitive routing, authors introduce a new hybrid approach that performs dynamic routing of long-lived

flows, while forwarding short-lived flows on static pre-provisioned paths. By relating the detection of

long-lived flows to the timescale of link-state update messages in the routing protocol, route stability is

considerably improved. However, the flow trigger is considered only under the static network

provisioning policy.

When disseminating tra ffic into multiple paths, routers should adaptively allocate flows to each path in

order to achieve load balancing among multiple paths, as most IP flows are short-lived and the flow size

is not normally distributed. Moreover, routers should distribute packet streams belonging to a flow into

the same next -hop not to cause end-to-end performance degradation. An adaptive multi-path load control

method using a flow classifier which detects long-lived flows through the flow characteristics of the

duration and the size is proposed in [30]. By dividing flows into long-lived and short-lived, congestion

from the bursty transient flows may be avoided. It is shown by simulation experiments with the real

packet trace that the proposed algorithm adaptively controls the load of multiple paths satisfying the given

load ratio, and the minimal per-flow states at routers can be maintained by aggregating flows with the

destination network pre fix. In this paper, for flow assignment, flows which have long duration, high-bit

rate, and large flow size (called “base” flows) are distinguished from short-lived transient ones, and

assigned to the primary path. Fig. 4 depicts the ingress router with the flow classifier. Packets not

belonging to base flows (called “transient” flows) are forwarded to the secondary path.

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Fig. 4. The ingress router with load control

A dynamic multipath routing (DMRP) scheme to improve resource utilization of a network carrying

real time traffic by re-routing on going calls through shorter routes is proposed in [31], [32]. Dynamic

routing may hurt the network performance at times when the traffic is high. These approaches alleviate

instantaneous congestion by allowing rerouting of a call through a longer route. In contrast, in this paper,

rerouting of an ongoing connection connection-oriented call is allowed only if the new route is more

preferable (i.e., shorter) than the current one. This leads to the gain in network efficiency in terms of

reduced delay for a given resource utilization (or alternatively, reduced resource utilization for a given

delay). Moreover, this paper’s strategy takes into account the possibility of “cascaded repacking”. The

DMPR scheme works based on the route length, independent of the network congestion. The proposed

DMPR scheme is an on-line algorithm, acting at node in parallel to the on-going calls. Therefore, contrary

to the popular belief that on-line algorithms may lead to the increased network latency, this DPMR

scheme does not affect the latency.

Dynamic multi-path routing and how it compares with other dynamic routing algorithms for high speed wire area networks (1992)

The shortest path is used under light traffic conditions and multiple paths are utilized as the shortest path become congested

Load-sensitive routing for long-lived IP flows (1999)An adaptive flow-level load control scheme for multipath forwarding (2001)

The enhance routing scheme separating long-lived and short-lived flows

Dynamic multipath routing (DMPR): an approach to improve resource utilization in networks for real -time traffic (2001)

DMRP in networks and switches carrying connection-oriented traffic (2001)Improve resource utilization of a network carrying real-time traffic

by re-routing on going calls through shorter routes

Fig. 5. Dynamic multipath routing schemes

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4.5. QoS routing using multipaths

Recently, QoS routing has been studied intensively. There have been several studies on QoS routing

using multipath. In [33], QoS routing via multiple paths for the time constraint is proposed when the

bandwidth can be reserved, assuming all the reordered packets are recovered by the optimal buffer at the

receiver, which causes the overhead of the dynamic buffer adjustment at the receiver. In [34], the authors

propose an analysis for computing the burst blocking probability for each end-to-end connection in an

ATM network where multipath routing is used in conjunction with fast bandwidth reservation for QoS. It

is observed that the use of multipath routing may cause a small number of end-to-end connections to

experience more blockings than they would experience with single path routing, should too much traffic

of other connections be overflowing into some of the links they used. [35] has analyzed the performance

of multipath routing algorithms and has shown that the connection establishment time for multipath

reservation is significantly lowered.

In [36], author studies the impact of resource reservation on the multipath QoS routing schemes that

use global network state to make routing decisions. In cooperating resource reservation into multipath

QoS routing algorithms greatly changes the communication characteristics in a network system and

affects the performance the routing algorithms. In this paper, authors develop a QoS routing protocol that

combines resource reservation with the ticket-based distributed multi-path QoS routing scheme. When a

connection request arrives at the source node, a certain number (t) of tickets are generated and a

reservation packet with the t tickets is sent to the destination in search of paths that satisfy the QoS

constraints. Each reservation packet carries one or more tic kets. When an intermediate node receives a

reservation packet, it determines the next hops that can potentially establish connections for the request,

calculates the number of tickets to be distributed for each of the next hops, and sends a reservation packet

with its share of the tickets to each of the next hops.

In QoS routing, an essential issues is routing granularity. Most of researches adopt per-flow granularity

in the forwarding table. Some researches advocate per source-destination pair granularity in the

forwarding table with route pining. Flow based approach has finer granularity, thus more efficient on

traffic engineering and resource utilization. However, computation overhead and storage overhead are

also higher. On the other hand, the source-destination based granularity is more efficient on packet

processing and forwarding, but has higher blocking probability. Therefore, in [37], the author propose to

use a QoS routing mark, similar to the code-point in Differentiated Services, to reduce the complexity of

packet forwarding process of QoS routing. With a limited number of routing marks, the proposed routing

algorithm reduces the forwarding complexity and storage overhead significantly while yields very

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competitive performance in terms of fractional reward loss. When a connection request with QoS

requirement arrives, it is routed to the “best” path according to current network states. As s consequence,

flows between a source-destination pair may route on several different paths. However, flows that route

on the same path are forwarded identically at intermediate routers. Therefore, they can be aggregated,

from the routing point of view, into the same routing class.

QoS routing via multiple paths using bandwidth reservation (1998)QoSrouting via multiple paths for time constraint (buffer adjustment at the receiver)

Performance of fast bandwidth reservation with multipath routing (1998)Analysis of multi-path routing (1999)

The connection establish time for multipathreservation is significantly lowered

Impact of resource reservation on the distributed multi-path quality of service routing scheme (2001)

combines resource reservation with the ticket-based distributed multi-path QoS routing

Multipath QoS routing with bandwidth guarantee (2001)The concept of forwarding with routing marks à reduce forwarding complexity

Fig. 6. QoS routing using multipath

5. Multipath routing in MPLS networks

5.1. Traffic Engineering with MPLS

The emergence of MPLS with its efficient support of explicit routing provides basic mechanisms for

facilitating traffic engineering [38]. Explicit routing allows a particular packet stream to follow a pre-

determined path rather than a path computed by hop-by-hop destination-based routing such as OSPF or

IS-IS. With destination-based routing as in traditional IP network, explicit routing may be provided by

attaching to each packet the network-layer address of each node along the explicit path. This approach

generally incurs prohibitive overhead. In MPLS, a path (known as a LSP) is identified by a concatenation

of labels which are stored in the nodes. As in traditional virtual-circuit packet switching, a packet is

forwarded along the LSP by swapping labels. Thus, support of explicit routing in MPLS does not entail

additional packet header overhead.

Traffic engineering with MPLS requires the components of constraint based routing [39] and an

enhanced IGP. With MPLS when an enhanced IGP builds LSR’s forwarding table, it takes into account

LSPs originated by the LSR, so that LSPs can be used to carry traffic. IGPs using shortest path to forward

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traffic attempt to conserve resources but can lead to congestion. This can be due to different shortest paths

overlapping at some link or the traffic from a source to a destination exceeding the capacity of the

shortest path. MPLS helps address the above problems and more as described below.

Constraint based routing, along with some form of connection admission control, avoids placing too

many LSPs on any link, thus avoiding one of the problems. Similarly, if the traffic between two routers

exceeds the capacity of any single path, then multiple LSPs can be set up between them. The traffic is

split between these based on specified or derived load ratios. For example, the ratios may be proportional

to the bandwidths of the LSPs. Further, such LSPs can be placed on different physical paths to ensure

more even distribution of load. This also allows for graceful degradation in case one of the paths fails.

MPLS allows enforcement of some administrative policies in online path computation. For example,

resource color can be assigned to LSPs and links to achieve a degree of desired LSP placement. [40]

suggests an example where regional LSPs are to be kept from traversing inter-region links. To enforce this

scheme, all regional links may be colored green, and all inter-region links colored red. Regional LSPs are

then constrained to use only green links. If an operator chooses, paths for LSPs may be determined offline,

possibly based on global optimization and other administrative policies considerations. This allows

network administrators [41] to control traffic paths precisely.

In terms of support for network planning, an advantage of MPLS is the ability to gather per-LSP

statistics that can be used to provide point-to-point traffic matrix. In particular, such point-to-point traffic

matrix provides valuable historical data for longer term network planning. Such data can be used for

capacity planning. While capacity planning is the long-term solution to meet growing traffic demands, in

the medium term an operator has to work within the bounds of the given capacities. During this period the

traffic is growing and changing distribution. A powerful tool is the ability offered by MPLS to adjust the

bandwidth of existing LSPs in the network. This allows operators to adjust LSP bandwidths to reflect the

changing traffic distribution.

The priority feature in MPLS may be used in interesting ways for traffic engineering. For example,

[40] suggests a LSP that carries large amount of traffic to be given higher priority. This allows the LSP to

more likely take an optimal path resulting in better resource utilization fro m a global perspective. The

priority feature may be used in other ways as well, for example, to offer different grades of service.

Another feature that can be useful to an operator is the ability to re -optimize the path of an LSP.

Basically at the time an LSP is set up it may not obtain the best path between the source and the

destination due to existing paths. With time, however, resources may be added or freed up that cause

16

better paths to become available. A network operator may want to switch the LSP to a better path when it

becomes available. Re-optimization should be done with care in a controlled manner as it may introduce

instability.

Rerouting of a LSP is also desirable when a failure occurs along its path. Rerouting can be end-to-end

(global repair), where the whole path is rerouted from ingress to egress, or localized, where only a section

of the LSP is rerouted to avoid a failed link or node. In the case of failure, it may be even desirable to

reroute LSPs regardless of their bandwidth and other constraints. Rerouting and more generally

survivability in MPLS networks is an important topic [42], [43]. Exploiting the reroute capabilities of

MPLS requires the use of signaling to set up LSPs [44].

MPLS also offers two other key benefits. A Differentiated Services (DiffServ) over MPLS

implementation [45] allows the operator to combine traffic engineering with LSPs while supporting

differentiated services. This may be achieved in one way by setting up different LSPs for different classes

of traffic. In an alternative scheme a single LSP may carry traffic belonging to different classes. A detailed

discussion of Differentiated Services on MPLS is beyond the scope of this paper. The other key aspect

exploited about MPLS is not its capability of traffic engineering, but of mapping services like Virtual

Private Networks (VPN) to labels. Thus, core nodes transport these as LSPs, agnostic of the service being

carried inside.

5.2. Applying multipath routing to MPLS networks

Multipath Routingin MPLS networks

Finding traffic split ratio

MATE(measurement-based)

TE with AIMD(distributed, feedback-based)

Load balancing

Failure recovery(Fault tolerant)

Multipath Routingin MPLS networks

Finding traffic split ratio

MATE(measurement-based)

TE with AIMD(distributed, feedback-based)

Load balancing

Failure recovery(Fault tolerant)

Fig. 7. Multipath routing in MPLS networks

In previous section, we discuss the advantage of MPLS for traffic engineering. Recently, there have

been several approaches on applying multipath routing to MPLS networks. These works have the

17

common goal of solving the traffic engineering problems using multipath LSPs. Therefore, these

approaches are tightly related to load balancing, traffic splitting and fault tolerant etc. Fig. 7 shows the

multipath routing in MPLS networks. Now, we will discuss in some details.

l Finding traffic split ratio

Analytical framework for dynamic traffic partitioning in MPLS networks [46]

For differentiated services, finding the traffic split ratio to minimize the end-to-end delay and loss rate

is proposed in this paper. However how to find the appropriate multip le paths is not covered. Authors

investigate the use of a dynamic traffic partitioning and assignment methodology to adaptively map

ingress traffic into several parallel LSPs in MPLS -based IP networks. A stochastic framework for the

traffic partitioning problem is presented. Within this framework, a set of parallel edge disjoint LSPs is

modeled by parallel queues and a partitioning algorithm is devised for different service classes that is

adaptive to the prevailing state of the network.

Dynamic Constrained Multipath Routing for MPLS Networks [47]

This paper presents a heuristic algorithm for hop-count and path-count constrained dynamic Multipath

routing. The objective we adapted in this paper is to minimize the maximum of link utilization. We also

obtain the traffic split ratio among the paths, for routers based on traffic partitioning by hashing at flow

level. The extensive simulation results show that the proposed algorithm always minimize the maximum

of link utilization and reduces the number of blocked request.

Through splitting a traffic demand, it is expected that the maximal revenue can be achieved by

increasing the probability that more traffic demand requests will be accepted in the future. Also, the

utilization of the total network resource will be maximized. Instead of minimizing the sum of queuing

delay on a link, we use the objective of minimizing the maximum utilization which makes little difference

in routing performance.

A constrained multipath traffic engineering scheme for MPLS networks [48]

It is known that total traffic throughput in a network, hence the resource utilization, can be maximized

if the traffic demand is split over multiple paths. However, the problem formulation and practical

algorithms, which calculate the path and the traffic split taking the route considerations or policies into

consideration, have not been much touched. This paper proposes practical algorithms that find near

optimal paths satisfying the given traffic demand under constraints such as maximum hop count, and

18

preferred or not preferred node/link list. The mixed integer programming formulation also calculates the

traffic split ratio for multiple paths. The problems are solved with the split ratio of continuous or discrete

values. However, the split ratio solved with discrete values (0.1, 0.2 etc) are more suitable for easy

implementation at the network nodes. The proposed algorithms are applied to the MPLS that permits

explicit path setup. The paths and split ratio are calculated off-line, and passed to MPLS edge routers for

explicit LSP setup. The experiment results show that the proposed algorithms are fast and superior to the

conventional shortest path algorithm in terms of maximum link utilization, total traffic volume, and

number of required LSPs.

ConstraintsObjectivePaper Title

maximum hop count, and preferred or not-preferred node/link list (discrete split scheme)

To minimize the utilization of the most heavily used link in the network, or the maximum of link utilization

A constrained multipathtraffic engineering scheme for MPLS networks (2002)

maximum hop-count constraint, maximum path-count constraint

To minimize the maximum of link utilization, while satisfying the requested traffic demand

Dynamic Constrained Multipath Routing for MPLS Networks (2001)

QoS constraints (packet loss, delay) of EF and BE traffic

To minimize the end-to-end delay and loss rates (for DiffServ)

Analytical framework for dynamic traffic partitioning in MPLS networks (2000)

ConstraintsObjectivePaper Title

maximum hop count, and preferred or not-preferred node/link list (discrete split scheme)

To minimize the utilization of the most heavily used link in the network, or the maximum of link utilization

A constrained multipathtraffic engineering scheme for MPLS networks (2002)

maximum hop-count constraint, maximum path-count constraint

To minimize the maximum of link utilization, while satisfying the requested traffic demand

Dynamic Constrained Multipath Routing for MPLS Networks (2001)

QoS constraints (packet loss, delay) of EF and BE traffic

To minimize the end-to-end delay and loss rates (for DiffServ)

Analytical framework for dynamic traffic partitioning in MPLS networks (2000)

Table 3. Comparisons of traffic split ratio related papers

l MATE & Multipath AIMD

MATE: MPLS Adaptive Traffic Engineering [49]

Destination-based forwarding in traditional IP routers has not been able to take full advantage of

multiple paths that frequently exist in Internet Service Provider Networks. As a result, the networks may

not operate efficiently, especially when the traffic patterns are dynamic. This paper describes a multipath

adaptive traffic engineering scheme, called MATE, which is targeted for switched networks such as

MPLS networks. The main goal of MATE is to avoid network congestion by adaptively balancing the

load among multiple paths based on measurement and analysis of path congestion. MATE adopts a

minimalist approach in that intermediate nodes are not required to perform traffic engineering or

measurements besides forwarding packets. Moreover, MATE does not impose any particular scheduling,

buffer management, or a priori traffic characterization on the nodes. This paper presents an analytical

model, derives a class of MATE algorithms, and proves their convergence. Several practical design

19

techniques to implement MATE are described. Simulation results are provided to illustrate the efficacy of

MATE under various network scenarios.

The basic idea of MATE is as follows. The ingress node of each LSP periodically sends

probe packets to estimate a congestion measure on the forward LSP from ingress to egress. The

congestion measure can be delay, loss rate, or other performance metrics; see below for

measurement details. Each ingress node then routes incoming traffic onto multiple paths to its

egress node in a way that equalizes the marginal congestion measure (their derivatives). That is,

traffic will be shifted from LSPs with higher marginals to LSPs with lower marginals. In

equilibrium all LSPs that carry any flow will have minimum and equal marginals. As will be

shown in the next section, equalizing the marginal measure minimizes the total congestion

measure of the entire MPLS network. Fig. 8 shows a functional block diagram of MATE

located at an ingress node.

Fig. 8. MATE functions in an ingress node

Traffic Engineering with AIMD in MPLS Networks (Multipath-AIMD) [50]

This paper consider the problem of allocating bandwidth to competing flows in an MPLS network, subject to

constraints on fairness, efficiency, and administrative complexity. The aggregate traffic between a source and a

destination, called a flow, is mapped to LSPs across the network. Each flow is assigned a preferred (‘primary’) LSP,

but traffic may be sent to other (‘secondary’) LSPs. Within this context, we define objectives for traffic engineering,

such as fairness, efficiency, and preferred flow assignment to the primary LSP of a flow (‘Primary Path First’, PPF).

We propose a distributed, feedback-based multipath routing algorithm that attempts to apply additive-increase and

multiplicative-decrease (AIMD) to implement our traffic engineering objectives. The new algorithm is referred to as

multipath-AIMD. Authors use ns-2 simulations to illustrate the fairness criteria and PPF property of our multipath-

AIMD scheme in an MPLS network.

20

Additive-Increase Multiplicative-Decrease (AIMD) feedback algorithms are used extensively for flow

and congestion control in computer networks [51], [52], [53], [54], [55], [56] and are widely held to be

both efficient and fair in allocating traffic to network paths. These algorithms adjust the transmission rate

of a sender based on feedback from the network following an additive increase/multiplicative decrease

rule. If the network is free of congestion, the transmission rate of the sender is increased by a constant

amount. If the network is congested, the transmission rate is reduced by an amount that is proportional to

the current transmission rate. Note that in earlier instantiations of the AIMD rule the sending rate for a

given source is adjusted as though only one path exists for end-to-end communication. Multipath-AIMD

comes in two flavors: (1) basic multipath-AIMD, which seeks to provide a fair allocation of throughput to

each source, without special consideration of the PPF criterion, and (2) multipath-AIMD with PPF

correction, which augments the basic algorithm to reduce the volume of secondary path traffic. Both

algorithms rely upon binary feedback information regarding the congestion state of each of the LSPs and,

for the second version of the algorithm, a binary routing vector associated with each source. The revised

algorithm, multipath-AIMD with PPF correction, can reduce secondary path utilization (for the pooled

resources case) at the expense of fairness. From the perspective of Internet traffic engineering, multipath-

AIMD seems to provide a practical mechanism for improving the utilization of LSP resources, while

maintaining fairness and minimizing the complexity associated with multipath routing.

•distributed, feedback based (distributed rate allocation –multipath AIMD)

•Efficiency•Fairness•Primary path first•Simple and distributed allocation

Traffic engineering with AIMD in MPLS networks (2002)

•measurement based (packet delay and packet loss probability using probe packet)•Distributed adaptive load-balancing algorithm

Avoid network congestion by adaptively balancing the load among multiple paths based on measurement and analysis of path congestion

MATE: MPLS Adaptive Traffic Engineering (2001)

FeatureObjectivePaper

•distributed, feedback based (distributed rate allocation –multipath AIMD)

•Efficiency•Fairness•Primary path first•Simple and distributed allocation

Traffic engineering with AIMD in MPLS networks (2002)

•measurement based (packet delay and packet loss probability using probe packet)•Distributed adaptive load-balancing algorithm

Avoid network congestion by adaptively balancing the load among multiple paths based on measurement and analysis of path congestion

MATE: MPLS Adaptive Traffic Engineering (2001)

FeatureObjectivePaper

Table 4. Comparisons of MATE and Multipath-AIMD

l Failure recovery (fault tolerant)

Traffic engineering using multiple multipoint-to-point LSPs [57]

This paper proposes a traffic engineering scheme using multiple multipoint-to-point (m-t-p) Label

Switched Paths (LSPs) which can reduce the number of LSPs and required labels in links. The scheme

21

consists of m-t-p LSP creation and flow assignment. Routes are first selected, and m-t-p LSPs are

designed to include them. The m-t-p LSP design problem is formulated as an integer programming

problem. The flow assignment problem is formulated as a mixed integer programming problem in which

maximum link load, i.e., maximum congestion, is minimized. Numerical comparisons with the

conventional point-to-point LSP approach show that the m-t-p LSP approach can reduce the number of

required LSPs and labels. Moreover, numerical comparisons with conventional Shortest Path Fast based

flow assignment show that our flow assignment scheme can reduce maximum link load. In this paper

backup routes are used against failures. Hence, the alternate paths are used only when primary routes do

not work.

Fault tolerance and load balancing in QoS provisioning with multipath MPLS paths [58]

The paper presents approaches for fault tolerance and load balancing in QoS provisioning using

multiple alternate paths. The proposed multiple QoS path computation algorithm searches for maximally

disjoint (i.e., min imally overlapped) multiple paths such that the impact of link/node failures becomes

significantly reduced, and the use of multiple paths renders QoS services more robust in unreliable

network conditions. The algorithm is not limited to finding fully disjoint paths. It also exploits partially

disjoint paths by carefully selecting and retaining common links in order to produce more options.

Moreover, it offers the benefits of load balancing in normal operating conditions by deploying appropriate

call allocation methods according to traffic characteristics. In all cases, all the computed paths must

satisfy given multiple QoS constraints . Simulation experiments with IP Telephony service illustrate the

fault tolerance and load balancing features of the proposed scheme.

6. Multipath routing in optical Internet

In this section, we discuss the multipath routing in optical Internet. There is a general trend that the

control capability of optical network should utilize IP-based protocols for dynamic provisioning and

restoration of lightpaths within and across optical sub-networks. This is based on the practical view that

IP-based signaling and routing mechanisms could be re-used in optical networks [59]. However, there is

no multipath routing mechanism applied to optical Internet.

With the collaboration of UCL and Nortel, adaptive bandwidth management scheme in IP/photonic

networks is proposed in [60]. Here, adaptive multipath load balancing concept is applied. In the data-

driven approach to provisioning, the boundary routers use traffic measurement to autonomously control

the number of lightpaths. In the viewpoint of adaptive bandwidth management, availability of multiple

diverse paths provides opportunity to improve QoS for streams by dynamic load balancing across those

paths according to the value of the traffic and path characteristics. This would improve the utilization of

22

the network.

Notes: 1. The IP service and Photonic Network controller functions are embedded in the distributable resource Broker2. Message passing and Method invocations are local/ remote accordingly

Photonic Layer

O/P portwavelength

path:un/bind/modify

Photonic switch

Number of wavelengths

Wavelengthsused

per O/P port

Photonic switch

Wavelengthallocator

Photonic N/w Controller

Q R

Resource Controller

Photonic N/w ControllerResource

availabilityIP/ Photonicadapter

Abstract architecture for IP over Photonic network

Offered rate meterper path per O/P port

Q: QueryR: Response

Provisioning Request

IP Layer

R

Q

IP Border Router

Priority

IP Service Controller

Bandwidthallocation

IP Service Controller

Rate controlper path per O/P port

IP Border Router

IP/Photonictraffic adapter

Photonic/IP adapter

Provisioning Request

O-UNI

f[Policies, Request]

Fig. 9. The function block of optical Internet

m

.

.

2

1

Bin Number

m

.

.

2

1

Bin Number

Flow IDHash

Functionf{6-tuple..

etc}

O/P 1

O/P n

I/P 1

I/P i

Path B

Path A

Destination

1

.

.

n

1

O/PPort

1

.

.

n

1

O/PPortPort

AllocationmappingFunctionf{statics,

dynamics,CoS,

policy..etc}

IP/Optical border router-switch with multiple wavelength channels

(or MPLS switches with multiple LSPs)

Optical Cloud

Diverse andDisjoint paths

Fig. 10. Adaptive Multipath Load Balancing proposal for bandwidth management

23

7. Conclusions and future work

Multipath routing can be effectively used for maximum utilization of network resources. It gives the

node a choice of next hops for the same destination. The various algorithms discussed give solutions for

effectively calculating the multipaths and ways to minimize delay and increase throughput. Multipath

routing is capable of aggregating the resources of multiple paths and reducing the blocking capabilities in

QoS oriented networks, allowing data transfer at higher rate when compared to single path. It also

increases the reliability of delivery.

We surveyed the various multipath routing mechanisms for traffic engineering. Especially, these works

can be applied to MPLS/GMPLS network, then enhance network performance through traffic engineering

and meet the QoS requirements.

It is clear the traffic engineering is being developed at a tremendous pace, especially since MPLS and

GMPLS provide a common basis for their evolution. In particular, a range of Traffic Engineering

objectives ranging from QoS routing, multi-path routing/traffic splitting, load balancing, path protection

and fast re-route can be directly addressed by a connection-oriented MPLS/GMPLS based approach.

Therefore, for the future work, we will develop the traffic engineering mechanism using multipath in

GMPLS -based optical network. This mechanism will be satisfied the objectives of optical resource

optimization through load balancing, reducing blocking probability, fault tolerance and so on. For this

work, we will study traffic aggregation and classification mechanism and constrained-based multipath

explicit route setup algorithm using GMPLS-based unified control plane.

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