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On the Energy Efficiency of Optical Transport with. Time Driven Switching. Francesco Musumeci, Francesca Vismara, Vida Grkovic, Massimo Tornatore, Achille ...
This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE ICC 2011 proceedings

On the Energy Efficiency of Optical Transport with Time Driven Switching Francesco Musumeci, Francesca Vismara, Vida Grkovic, Massimo Tornatore, Achille Pattavina Politecnico di Milano, Department of Electronics and Information, 20131 Milan, Italy E-mail: [email protected]

Abstract—Reducing the Internet power consumption will become a challenging issue, since the Internet is expected to face a high growth in terms of traffic requirements. Simply scaling the network architecture, thus increasing its power consumption, proportionally to this growth would not be a practical solution. Various energy-efficient approaches have been considered, typically exploiting optical switching technologies at the core network layer since they allow to significantly reduce the quantity of high power-requiring optical/electronic/optical conversions and electronic processing operations. A further improvement can be obtained with Time Driven Switching (TDS), a technique which allows to switch “fractions” of wavelengths directly in the optical domain exploiting the time-coordination of all network components. In this paper we show the benefits, in terms of power saving, provided by the TDS architecture, by performing a comprehensive overview of different core network architectures and comparing the consumption obtained in the different cases. With such an architecture, power savings of more than 40% are demonstrated with respect to existing architectures.

I. I NTRODUCTION As the Internet traffic is estimated to grow up to 50 times within the next 10-15 years [1], power consumption of the whole telecommunication networks could be the major constraint for this growth, rather than bandwidth requirements. Optical technologies have been identified as key-enablers for energy-efficient solutions to cope with the expected increase of traffic. Specifically, optical networks employing the Wavelength Division Multiplexing (WDM) technique are capable to route wavelengths (i.e., lightpaths), each of them carrying one (or more) optical signal(s), from source to destination nodes, through a series of optical fiber links and, in most of cases, with no need to perform data processing, i.e., reducing the Optical/Electronic/Optical (OEO) conversions of the signal, which require high power consumption due to the opto-electronic devices and electronic processing needed. Many recent works have discussed the energy-efficiency of optical transport networks. The approach in [2] exploits the concept of lightpath-bypass in order to design an IPover-WDM network that minimizes power consumption by reducing the number of needed IP router ports. In [3] the authors evaluate the power consumption of an individual The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement n. 257740 (Network of Excellence “TREND”) and from the Italian Ministry of Education under PRIN 2008 grants for the project “BESOS” (Bandwidth efficiency and Energy Saving by sub-lambda Optical Switching).

lightpath and obtain the overall consumption of the network as a function of the number of established lightpaths. Ref. [4] also evaluates the power consumption in an optical network, considering that an efficient strategy for traffic aggregation (grooming) can be a means to reduce consumption overhead. In this paper, for the first time to the best of our knowledge, we provide a comprehensive overview of four IP-overWDM architectures by using Integer Linear Programming (ILP) formulations to model the different architectures. We also perform a power assessment of the various components employed in an optical transport network and show the benefits obtained by exploiting optical technology, especially in case of Time Driven Switching (TDS) technique1 . In Sec. II the consumption contributions of optical core networks are described. In Sec. III we describe the IP-overWDM architectures compared with respect to power consumption: IP with no Bypass (IP-NB), Transparent and Opaque IP with Bypass and Grooming (T.IP-BG and O.IP-BG) and Time Driven Switching (TDS). In Sec. IV the corresponding ILP models are shown. Numerical results are discussed in Sec. V whereas in Sec. VI we draw the conclusions of the paper. II. P OWER C ONSUMPTION C ONTRIBUTIONS Our energy-efficiency comparison mainly focuses on how switching and grooming are achieved, since these operations are differently performed in the four considered architectures. Traffic grooming allows efficient utilization of link capacity. However, since it is usually performed in the electronic domain, expensive routers and/or digital cross connects (DXC) are needed, and high power is consumed while performing massive OEO signal conversions and the related amount of traffic processing. TDS effectively addresses this issue by subdividing the wavelength capacity in smaller portions of bandwidth (sub-λ granularity), enabling grooming directly in the optical domain. In general, several components contribute to the consumption of an optical core network, such as transmission equipment (e.g., WDM transponders or shortreach interfaces), electronic traffic processing, electronic or 1 TDS is a slotted switching technique based on the availability of global time, retrievable from a variety of sources, such as GPS and Galileo. A basic time period, called Time Frame (TF), is identified and switched independently by reconfiguring the optical switches at the end of the TF based on the globaltime synchronization. Thus, the so-called Synchronous Virtual Pipes (SVPs) [5] are provisioned. TDS provides several benefits, such as buffer avoidance and efficient capacity utilization [1].

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This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE ICC 2011 proceedings

optical switching devices, optical amplifiers (typically, Erbium Doped Fiber Amplifiers, or EDFAs), and network control. For our purpose, some of these contributions have been considered as constant in all the architectures. E.g., in a first approximation, the contribution due to network control has been assumed to be independent of the architecture. Moreover, the EDFAs are supposed to be already deployed in the network, so that their number (and thus, their power consumption) can be considered constant in all cases. Finally, since the traffic processing in source and destination nodes requires the same consumption in each architecture, we only consider processing performed in intermediate nodes. Nonetheless, note that the neglected contributions do not represent the main power-requiring factors. Therefore, we focus our analysis on the following contributions: WDM transponders. They are used for OE and EO signal conversion and signal transmission or reception. We consider two kinds of WDM transponders, both operating at 10 Gbit/s: t1 ) the OE interfaces between the IP router and the transparent optical network, and t2 ) those transponders that are placed between the mux-demux stage and the opaque optical switch matrix and perform OEO conversion of signals (see, e.g., [2]). Short-reach2 (S-R) interfaces. Electronic routers are usually optically interconnected to an Optical Cross Connect (OXC) over a proper optical bandwidth. Therefore, S-R interfaces are used whenever EO or OE conversions are needed to interconnect such devices. 10 Gbit/s interfaces are considered. Electronic Processing. This contribution arises when performing routing or grooming operations in the electronic domain. Optical switching. Switches based over Micro-ElectroMechanical-Systems (MEMS), or Semiconductor Optical Amplifiers (SOAs) are considered. In the latter case, the additional power needed for the synchronization has been neglected. In the following, these contributions will be referred as Ptr , PSR , PIP and Po , respectively. III. C ORE N ETWORK A RCHITECTURES In the following we describe the four competing IP-overWDM architectures, which will be compared in terms of power consumption: IP with no Bypass (IP-NB), two implementations of IP with Bypass and Grooming (Transparent and Opaque IP-BG) and Time Driven Switching (TDS). IP-NB. As shown in Fig. 1, in the IP-NB architecture, the IP routers are interconnected by point-to-point optical fiber links; both switching and grooming of traffic are accomplished in the electronic domain, thus all traffic flows are electronically processed in every node. Therefore, in this architecture, we can neglect the optical switching contribution. T.IP-BG. In this case each node is equipped with a MEMSbased OXC connected to an IP router (see Fig. 2). Traffic can be groomed in the electronic domain by routers, as in the IPNB case, or can be switched directly in the optical domain by OXCs, thus IP flows can directly bypass intermediate routers 2 The

distance between components in the same network node is short if compared to the distance between different nodes, hence the term short-reach.

TABLE I P OWER CONTRIBUTIONS FOR THE DIFFERENT ARCHITECTURES . PIP Ptr PSR Po 14.5 W 34.5 W IP-NB per Gbit/s [6] [6] 14.5 W 34.5 W 1.5 W T.IP-BG per Gbit/s [6] [6] per λ [7] 14.5 W 18.25 W 16.25 W 1.5 W O.IP-BG per Gbit/s [6] [8] [6] per λ [7] 34.5 W 500 mW TDS [6] per SOA

via a cut-through lightpath; the number of transponders (t1 ) is reduced if compared to the IP-NB case. O.IP-BG. This architecture is shown in Fig. 3: transponders (t2 ) perform OEO conversion and signal regeneration to reduce the effect of physical impairments experienced by optical signals3 . While transponders t1 consume less than t2 , now in each network node the OXC has to be connected to the IP router via S-R interfaces (e.g., router ports). TDS. An optical layer using SOA-based optical switches is here deployed. SOAs are used since they support fast switching. Switching and grooming operations are performed in the optical domain and transponders are used only in source/destination nodes. The number of transponders is minimized (see Fig. 4) and depends on the number of nodes requiring connectivity and not on the total number of requests. Figs. 1-to-4 also show how three connections are routed and the power contributions needed in the four cases. The overall required bandwidth is assumed to fit in a single wavelength. Tab. I shows the power contributions values for the four architectures. IV. P OWER C ONSUMPTION M INIMIZATION We now formally define the power consumption minimization problem. Given a two-layer WDM network consisting of IP routers placed over an optical layer (OXCs connected by WDM links) and a set of traffic demands among the nodes, the power consumption of the core network is minimized, while satisfying two main constraints: i) all the requests have to be routed, and ii) each fiber supports limited number of wavelengths. Problem inputs can be defined as follows: • G = (N, A) is the physical topology of the network, consisting of a set N of nodes, corresponding to IP routers (in case, connected to an OXC), and a set A of bidirectional arcs, corresponding to fiber links, connecting the nodes; moreover, N m is the set of all nodes  adjacent to node m, i.e., Nm := n ∈ N |(m, n) ∈ A ; • R is the set of traffic requests; source and destination nodes of request r ∈ R and the corresponding required bandwidth are indicated as s(r), d(r) and tr , respectively; • L is the set of wavelengths carried by each fiber (for sake of simplicity, we consider mono-fiber links) and W is its cardinality; C is the capacity, in Gbit/s, of each λ; • power contributions: PIP , Ptr , PSR , Po (as in Tab. I). 3 We should consider physical impairments also in the transparent case, in which signal regeneration is performed only when grooming/degrooming operations are needed, but we will address this aspect in a future work.

This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE ICC 2011 proceedings

Req1

Req 2

Req 3

WDM Transponders (t1) PIP

IP layer WDM layer

Ptr

Ptr

Ptr

D E M U X

Ptr

Ptr

Ptr

M U X

A

Fig. 1.

PIP

B

C

D

IP-NB. Optical circuits are terminated at each node, where OE and EO conversions and grooming/degrooming of all requests are performed. Req1

Req 2

Req 3

WDM Transponders (t1)

PIP

IP layer WDM layer

Ptr

Ptr

D E M U X

OXC

M U X

Po

OXC

A

Po

Ptr

Ptr

Po

OXC

B

Po

Po OXC

C

D

Fig. 2. Transparent IP-BG. The requests can be groomed together (only one λ is needed) and traffic flows are electronically processed only when necessary: the IP router at node B is optically bypassed and at node C Req1 is processed in order to be degroomed by Req2 and groomed with Req3. Req1

Req 2

Short-Reach interfaces

IP layer WDM layer

PIP PSR

PSR

D E M U X

OXC

Po

Ptr

M U X

Ptr

A

Fig. 3.

Req 3

WDM Transponders (t2)

OXC

Po

Ptr

Ptr

B

1 if link (m, n) ∈ A is crossed by the request r ∈ R (binary).

Number of wavelengths used in (m, n) ∈ A (integer).       r minimize PIP Xni · tr + 2 · Ptr Ymn i

n∈Ni r|n=s(r)

(m,n)

⎧ Subject to: ⎪ if m = s(r) ⎨1   r r Xmn − Xnm = −1 if m = d(r) ⎪ ⎩ n∈Nm n∈Nm 0 otherwise



Po

Ptr

Po OXC

Ptr

D

wavelengths used in each link while imposing a maximum link-capacity (capacity constraint). 2) T.IP-BG: In this case the ILP model is a double-layer flow-formulation which considers the wavelength assignment (WA) problem for the optical layer. • Variables & objective: r Xij

1 if request r ∈ R is served by a lightpath between the nodes i, j ∈ N |i = j (binary).

vijl

Number of lightpaths established between i, j ∈ N |i = j over wavelength l ∈ L (integer).

ij Pmnl

1 if l ∈ L is used for the lightpath between i, j ∈ N |i = j and crosses (m, n) ∈ A (binary).

(1)

Vij

∀m ∈ N, ∀r ∈ R r Xmn

OXC

C

Ymn



Po

Opaque IP-BG. The three requests are served as for the transparent case, but OEO conversions are performed at each node.

A. ILP Optimization Models 1) IP-NB: The ILP model for IP-NB is a classical multicommodity flow formulation [9], where the routing assignment (RA) is modeled over a single layer topology. • Variables & objective: r Xmn

PSR

PSR

· tr ≤ C · Ymn ≤ C · W

l

∀(m, n) ∈ A (2)

+2 · Ptr

r

The objective is composed by two terms: the first computes the total power consumption due to electronic processing performed by IP routers in intermediate nodes of each connection request; the second accounts for the total power consumed by transponders (note that two transponders are needed for each lightpath). Eqn. (1) represents the classical flow conservation constraint [9], constraint (2) defines the number of

Number of lightpaths between i, j ∈ N |i = j (integer).      ij

vijl + minimize Po Pmnl  i



j=i

i

j=i

Vij + PIP

(m,n)

  i

r Xij · tr



j=i r|i=s(r)

Subject to: ⎧ ⎪ if i = s(r) ⎨1   r r Xij − Xji = −1 if i = d(r) ⎪ ⎩ j=i j=i 0 otherwise ∀i ∈ N, ∀r ∈ R

(3)

This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE ICC 2011 proceedings

Req1

Req 2

IP layer WDM layer

WDM Transponders (t1)

Ptr

Ptr

D E M U X

M U X

Po

OXC

Req 3

SOA-based OXC

OXC

A

Po

Ptr

Ptr Po

B

OXC

Po OXC

C

D

Fig. 4. TDS. The three connection requests need only one wavelength and electronic processing in intermediate nodes is not needed since grooming is performed directly in the optical domain by subdividing time into TFs and exploiting the time-coordination of all SOA-based OXCs.



ij Pmnl





n∈Nm

ij Pnml

n|m∈Nn

 r

⎧ ⎪ ⎨vijl = −vijl ⎪ ⎩ 0

if m = i if m = j otherwise

(4)

∀m, i, j ∈ N |i = j, ∀l ∈ L r Xij · tr ≤ C · Vij



vijl = Vij

∀i, j ∈ N |i = j

(5)

∀i, j ∈ N |i = j

(6)

l

 i

j=i

ij Pmnl ≤1

+2 · PSR

j=i

 i

j=i

(7)

(m,n)

Vij + 2 · Ptr

i

  (m,n)

i

ij Pmn



j=i

Constraints are similar to the T.IP-BG case, except (4) and (7), which have been relaxed as no WA is performed. 4) TDS: The model is a single (optical) layer RWA problem in which the number of transponders is computed according to the number of source/destination nodes, not to the number of lightpaths established. • Variables & objective: r Xmnl

Amount of traffic (in Gbit/s) of r ∈ R routed over wavelength l ∈ L (in terms of number of Synchronous Virtual Pipes, SVPs, occupied) (integer).

Sml

Number of transmitting transponders at wavelength l ∈ L installed in node m ∈ N (integer).

Number of receiving transponders at wavelength l ∈ L installed in node m ∈ N (integer). P       o r Sml +Dml + Xmnl minimize Ptr C r i Dml

l

∀(m, n) ∈ A, ∀l ∈ L

The objective consists of three terms: the optical switching contribution is computed by multiplying the elementary contribution Po by the sum of the number of wavelengths outgoing a node plus the term vijl , which accounts for the optical switching operations performed in nodes terminating lightpaths; the transponder contribution depends on the total number of lightpaths which have been established; finally, the third term represents the electronic processing consumption, computed counting the traffic carried by lightpaths terminated in intermediate nodes. Eqns. (3) and (4) are the solenoidality constraints at the logical and physical layer, respectively. Constraints (5) and (6) compute the number of lightpaths between a node pair, whereas (7) is the capacity constraint. 3) O.IP-BG: The ILP formulation can be easily derived by the previous case, relaxing the λ-continuity constraint at the physical layer, as in [2]. Since WA is trivial, we do not need ij of the previous the variables vijl , whereas the variables Pmnl ij case now become Pmn . So, the objective of the problem is:

     ij Vij + + PIP minimize Po Pmn Zi i

vlr

Amount of traffic (in Gbit/s) of r ∈ R routed on wavelength l ∈ L crossing (m, n) ∈ A (integer).



l

Subject to: ⎧ r ⎪ ⎨vl   r r Xmnl − Xnml = −vlr ⎪ ⎩ n∈Nm n∈Nm 0 

if m = s(r) if m = d(r) otherwise

(8)

∀m ∈ N, ∀l ∈L, ∀r ∈ R r Xmnl ≤C

r



(m,n)

 

∀(m, n) ∈ A, ∀l ∈ L

vlr = tr

∀r ∈ R

(9) (10)

l r Xmnl ≤ Sml · C

∀m ∈ N, ∀l ∈ L (11)

r Xnml ≤ Dml · C

∀m ∈ N, ∀l ∈ L (12)

r|m=s(r) n∈Nm





r|m=d(r) n∈Nm

In the objective, the first term computes the consumption of transmitting and receiving transponders and the second term evaluates the optical switching contribution. Note that opticalswitching power consumption depends on the time during which SOAs are active. Therefore, since the ratio between this time period and the total observation time is proportional to the ratio between the bandwidth of a SVP and the total capacity of a wavelength, the second term is weighted by the total capacity C. Eqn. (8) represents the solenoidality constraint and also imposes the λ-continuity. The capacity constraint is expressed by (9); eqn. (10) defines, for each request, the amount of traffic to be routed over a certain λ. The number of transmitting and receiving transponders used in each node is computed by constraints (11) and (12), respectively. Po refers to the power consumed when switching a single wavelength through a SOA-based OXC, and depends on the number of SOAs needed. This number depends on the connectivity of the node we are considering: at each node

This full text paper was peer reviewed at the direction of IEEE Communications Society subject matter experts for publication in the IEEE ICC 2011 proceedings

Optical switching

S-R interfaces

Fig. 5.

(b)

Network topologies: (a) NSFNET; (b) COST239.

demultiplexers split wavelengths coming from the same fiber link and each wavelength is sent towards an appropriate SOAswitch plane4 . Therefore, each plane receives as many signals as the number of incoming links, say n ¯ , and each channel ¯  SOAs. traverses f (¯ n) = 2 log2 n

NSFNET

6 5 4

3 2 1

IP-NB

5 4 3 2

1

T.IP-BG O.IP-BG

IP-NB

TDS

T.IP-BG O.IP-BG

TDS

70 IP-NB T.IP-BG O.IP-BG TDS

60 40

Ptot[kW]

We have considered two network cases: a non-uniform traffic matrix with 180 Gbit/s of aggregate traffic as in [10] has been applied to the NSFNET topology and a uniform traffic matrix with total amount of traffic of 350 Gbit/s has been mapped over the COST239 network topology (see Fig. 5). The total consumption and its contributions obtained by the previous models are shown in Fig. 6 for the two cases. In both the NSFNET and COST239 case TDS has the lowest power consumption, which is more than 40% lower than the other architectures, whereas IP-NB is the most power-consumptive architecture. This is mainly due to a high decrease in the number of transponders needed, which also is the most powerrequiring contribution. Electronic processing contribution is relevant especially in the IP-NB case, whereas TDS case, by avoiding it, saves a large amount of energy. T.IP-BG is more efficient than O.IP-BG, since the transponders used in the transparent case are replaced by a larger amount of OEO transponders and S-R interfaces used in the opaque case. In all the cases, optical switching is the least significant contribution. Power consumption of the different architectures has also been compared scaling the basic traffic matrix by a factor of 2, 3, 4, 5 and 10. Fig. 7 shows the total power consumed in the COST239 (similar results hold for the NSFNET) for the different architectures. TDS power consumption is maintained always below the consumption of the other architectures. For increasing traffic, the power requirement of IP-NB increases much more rapidly than the other architectures, whereas T.IPBG behavior gets closer to the TDS architectures since, for traffic request in the order of wavelengths, no traffic grooming is needed and the two architectures tend to be equivalent from the consumption point of view.

4 We assume that OXCs are made up of colored SOA-switches, each of them processing wavelengths of the same colour and coming from different links; therefore the number of planes used in each OXC is equal to the number of wavelengths used in the corresponding node.

COST239

6

Fig. 6. Total consumption and single contributions for the four architectures.

50

In this paper we have shown the benefit, in terms of power consumption, of the Time Driven Switching architecture. We

IP-processing

0

0

V. C ASE -S TUDIES AND R ESULTS

VI. C ONCLUSION

Transponders 7

Power contributions [kW]

(a)

Power contributions [kW]

7

30 20

10 0 T Fig. 7.

T*2

T*3

T*4

T*5

T*10

Total power consumption values for increasing traffic (COST239).

have performed a comparison between four competing optical core network architectures, providing four ILP formulations to compare the different solutions. Numerical results have shown that the TDS architecture is the most energy-efficient solution since it provides consumption at least 40% lower than the other architectures. This power assessment and comparison will be refined in future works. R EFERENCES [1] M. Baldi and Y. Ofek, “Time for a “Greener” Internet,” in IEEE International Conference on Communications (ICC) Workshops, DresdenGermany, 2009, pp. 1–6. [2] G. Shen and R. S. Tucker, “Energy-Minimized Design for IP Over WDM Networks,” IEEE Journal of Optical Communications and Networking, vol. 1, no. 1, pp. 176–186, June 2009. [3] E. Yetginer and G. Rouskas, “Power efficient traffic grooming in optical WDM networks,” in IEEE Global Telecommunications Conference, GLOBECOM 2009, Honolulu, Hawaii, Nov. 2009, pp. 1–6. [4] S. Huang, D. Seshadri, and R. Dutta, “Traffic Grooming: A Changing Role in Green Optical Networks,” in IEEE Global Telecommunications Conference, GLOBECOM 2009, Honolulu, Hawaii, Nov. 2009, pp. 1–6. [5] M. Baldi and Y. Ofek, “Fractional Lambda Switching - Principles of Operation and Performance Issues,” Transactions of the Society for Modeling and Simulation International, vol. 80, no. 7, July 2004. [6] “Cisco CRS-1 Carrier Routing System 16-Slot Line Card Chassis Specifications,” http://www.cisco.com. [7] Cisco 40-Channel Single-Module ROADM, http://www.cisco.com. [8] Alcatel-Lucent WaveStar OLS 1.6T product specification, http://www.alcatel-lucent.com. [9] R. K. Ahuja, T. L. Magnanti, and J. B. Orlin, Network Flows: Theory, Algorithms, and Applications. Prentice Hall, 1993. [10] Y. Miyao and H. Saito, “Optimal Design and Evaluation of Survivable WDM Transport Networks,” IEEE Journal on Selected Areas in Communications, vol. 16, no. 7, pp. 1190–1198, Sep. 1998.