a scheduling-based routing network architecture

A Scheduling-based Routing Network Architecture

Omar Y. Tahboub & Javed I. KhanMultimedia & Communication Networks Research Lab (MediaNet)

Kent State University

Outline Introduction

The Scheduling-based Routing Network Architecture

Case Study: An Institutional Remote Data Backup & Recovery Network

Performance Evaluation.

Conclusion and Future Work

Introduction Bandwidth-intensity will be dominating aspect in future emergent Internet

applications.

Will pose network capacity demands beyond imagination reaching Gigabytes and yet Terabytes per day.

Internet2 [1] model will likely be the reference architectural model for the next generation high-performance networks.

The Internet2 Dynamic Circuit Networking (DCN) [2] will also be the key communication paradigm.

Multi Protocol Labeling Switching (MPLS) [3] play a central role massive data flow routing, switching and forwarding

Introduction

Finally, on the basis of the case study, we carried out a performance evaluation study: Demonstrated two simulation experiments. Compared the performance between the scheduled data backup transfer to the

conventional non-scheduled.

We first describe a scheduling-based routing network architecture namely DCN@MPLS [4,5].

Implements DCN operation at the MPLS level.Enables time-scheduled route (LSP) information to be disseminated into MPLS domains.

Second, we present a case study focusing on remote backup and recovery networking application.

Utilized the Ohio Super Computing Network OSCnet backbone.Connects 11 universities in the state of Ohio,




Performance Evaluation



Figure 1: The DCN@MPLS Network Architecture [4][5]

The Network Tier

For each edge ei E, bwi denotes its bandwidth (bps) and li denotes its propagation delay in seconds.

Figure 2: The Network Tier

Represented by G = (N, E).

N = {n1, n2, …, nm} be the set of m label switch routers.

E = {e1, e2, …, en} be the set of edges (links),

Each edge ei in E connects a pair of label switch routers (nu, nv) N.

For each switch router ni in N, ci : service rate in bits per second (bps) and bi: the available storage buffer in bits.

The Edge Tier

Clients of this architecture are multi-disciplinary demanding various communication services: Telemedicine Content Distribution Distance Learning

Figure 3: The Edge Tier

Represents the user-groups requesting on-demand data flow transmissions via the network tier.

The Edge Tier

A FEC is further presented by a task t defined by the tuple (u , v , o, dl, s), where u: the ingress LER. v: the egress LER. o: the task origination time

in seconds. dl: the task completion

time deadline in seconds. s: the task size in bits.

Figure 4: The FEC as a Task

The Routing Tier

The main task of the route scheduling tier is computing time-scheduled routes in the underlying network domain.

Figure 5: The Routing Tier

Consists of the route scheduling solver.

The Routing Tier

Let set RT ={ r1, r2, …, ri,…, rn} defines a route schedule as a set of routes, where each task has a route (is committed to a task).

Figure 6: The LSP Specifications

Given a MPLS domain G = (N, E)

Let T denote the set of n tasks

Let the route (LSP) ri be a solution to task ti, defined as an ordered set of k node hops (switch routers)

Hi = {ui, ni,2,…, ni,j, …, ni,(k-1), vi}, or as k-1 link (edge) hops.

Li = {ei,1, ei,2,.., ei,j, …, ei,k-1}, where ei,j connects ni,(j-1) and ni,j.

Xi,1 = {xi,1,1,xi,1,1,…,xi,1,k,..., xi,1,n }

The Routing Tier

ti = {Xi,1, Xi,2}

dui,1,k

(seqi,i,k, szi,i,k, psi,i,k, pti,i,k, depi,i,k, arri,i,k)

Data Unit Schedule (dui,i,k)· seqi,i,k: Sequence Number· szi,i,k : Size (bits)· psi,i,k: Processing Starting Time (Seconds)· pti,i,k: Processing Time (Seconds)· depi,i,k: Departure Time (Seconds)· arri,i,k: Arrival Time (Seconds)

sti,1 = {dui,1,1,dui,1,1,…, dui,1,k,…, dui,1,n }

uti = {sti,1, sti,2}

The Scheduling Tier

Figure 7: The Scheduling Tier

This tier consists of three entities: Node Resource Information Base (NRIB) Link Resource Information Base (LRIB) and Router server.

The Scheduling TierThe Node Resource Information Base (NRIB)

Node resources information includes: Available service capacity

(bps)

Total service capacity (bps)

Total input/output buffers capacity (bytes) and

Available input/output buffer capacities (bytes).

Figure 8: The NRIBxi,j,k

a

xi,j,k

b

Insert (out-rsvi,j,k)1

(k, i, ni,j, szi,j,k,(depi,j,k – pti,j,k), depi,j,k)

Insert (in-rsvi,j,k)2

(k, i, ni,j+1, szi,j,k, arri,j,k)

The Scheduling TierThe Link Resource Information Base (NRIB)

Link resources information includes: Source LSR Destination LSR, Total link capacity

(bps), and Propagation delay

(seconds).

Figure 9: The NRIB

Insert (l-rsvi,j,k)

(k, i, ni,j, ni,j+1, szi,j,k, depi,j,k, arri,j,k)

The Scheduling Tier Network Resource Reservation

Figure 11: Network Resource Reservation

{ LER1, LER2, LSR1, LSR4, LSR5, LSR8, LSR10, LER5}

LSR Resource Reservation

{LER1, LER5, 1, 40, 100 Mb}

Link Resource Reservation

{e1, e4, e9, , e10, e13, e18, e19}

{LER1, LER5, 1, 40, 100 Mb}

The Scheduling TierRoute Schedule Dissemination

INQ

INQ

INQ

INQ

INQ

INQ

INQ

INQ

1

2 3

4

5

6

7

8RESP

RE

SP

RESP

RE

SP

RESP

RESPRE

SP

RE

SP

1

2

3

4

5

6

7

8

Lai = {(li1, lo1), (li2, lo2), …, (li7, lo7)}

{(0, 85), (85, 153), (153, 0), (0, 189), (189, 0), (0, 189), (189, 127), (127, -1)}

TIMIN

G

1

2 3

4

5

6

7

8

TIM

ING

TIMIN

G

TIMINGT

IMIN

G

TIMING

TIM

ING

TIMIN

G

Ωi = {(srti,1, endi,1),…, (srti,7, endi,7)}{(1, 2), (5, 6), (9, 10), (14, 15), (20, 21), (25, 26), (31, 32), (35, 36)}

Figure 12:Route (LSP) Schedule Dissemination


We utilize the Ohio Supercomputing Computing [6] network OSCnet as practical network backbone.

Safeguarding data and information against all types of disasters is an urgency.

Offline remote data backup & Recovery Networks serves an efficient solution.

In organizational Information centers, data & information backup is performed in a daily, weekly and monthly basis.

Case Study:The OSCnet Network Backbone

Figure 13: The OSCnet Network Backbone

Case Study:Backup Mirror Site Assignment

Table 1: Backup Mirror Sites Assignment

Case Study:Data Backup Transfer Demands

Table 2: Projected Daily Transfer Demands

Case Study:Critical Performance Challenges

Figure 14: Sample Average Shortest Path Length

Stable

Chaotic Will Chock out other bandwidth

contending Applications

Case Study:Critical Performance Challenges

Figure 15: Sample Aggregate Shortest Path Load

Figure 16: The Four-Tier OSCnet-based Network Architecture

Case Study: The Network Architecture

Performance Evaluation

To demonstrate the performance incentives of scheduled-based data transfer over the classical transfer scheme.

Compares the performance achieved by scheduled backup data transfer to the classical unscheduled scheme.

This study is conducted as a simulation study of the OSCnet network backbone shown by Figure 13.

Simulation Experiment-1 Setup

Link capacity allocation:

Unscheduled: Day = 100%, Night = 100% Scheduled: Day = 10%, Night = 90%

Number of Tasks: 156.

Performance Metrics: Average Shortest Path Length at Link Load 90% Aggregate Shortest Path Load at Link Load 90%

Simulation Experiment-2 Setup

Link capacity allocation: Day = 100%, Night = 100%

Number of Tasks: 156.

Performance Metrics: Overall Task Schedulability Percentage

The ration of number of tasks completed by their deadline to total of all tasks * 100%

Simulation Experiment-1 Results

Figure 16: Average Shortest Path Length

Unscheduled

Scheduled


Figure 17: Aggregate Shortest Path Load


Figure 17: Overall Task Schedulability


On the basis of the performance evaluation stud, it can be concluded that Scheduling-based routing significantly improves: The Average Shortest Path Length. The Aggregate Load of the Shortest Path. The Overall Task Schedulability.

Presented a four-tier scheduling-based routing architecture namely DCN@MPLS.

Demonstrated a OSCnet-based remote data backup case study.


The Scheduling-based data backup and recovery Near-optimal mirror site exploration and Selection Heuristics.

Hierarchical scheduling-based routing network architecture DCN@MPLS is a centralized architecture.

MPLS & CR-LDP Protocol Extensions Timed Route Schedule Dissemination in MPLS networks

Pathway Intermittency Route Scheduling in Physically/Logically Intermittent Networks

Thank You !

References

[1] The Internet2, Wikipedia, url: http://en.wikipedia.org/wiki/Internet2.

[2] Internet2 Consortium, “Internet2’s Dynamic Circuit Network”, 2008.

[3] E. Rosen, A. Viswanathan, and R. Callon, “Multiprotocol Label Switching Architecture”, RFC 3031, January, 2001.

[4] O. Tahboub, “DCN@MPLS: A Network Architectural Model for Dynamic Circuit Networking at Multiple Protocol Label Switching”, TR-2009-02-01, MediaNet Lab, , 2009.

[5] Tahboub, O., Khan, J., “DCN@MPLS: A Network Architectural Model for Dynamic Circuit Networking at Multiple Protocol Label Switching”, The First International Workshop on Concurrent Communication ConCom 2009, Seattle, WA, 2009.

[6] The Ohio Super Computing Network, url: http://www.osc.edu/oscnet/

a scheduling-based routing network architecture

Documents

mpls network architecture

network tierfor

network capacity

routing tierlet

route scheduling tier

underlying network domain

remote backup

route scheduling solver