Routing protocols

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Development of Complex Curricula for Molecular Bionics and Infobionics Programs within a consortial* framework**

Consortium leader

PETER PAZMANY CATHOLIC UNIVERSITY

Consortium members

SEMMELWEIS UNIVERSITY, DIALOG CAMPUS PUBLISHER

The Project has been realised with the support of the European Union and has been co-financed by the European Social Fund ***

**Molekuláris bionika és Infobionika Szakok tananyagának komplex fejlesztése konzorciumi keretben

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Ad hoc Sensor Networks

Routing protocols

Érzékelő mobilhálózatok

Útvonal választási protokollok

Dr. Levendovszky János

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Lecture 6 review

• The goal of medium access control

• Types of wireless networks

• Duplexing techniques

• Multiple Access

• Random Access

• MAC for Wireless Sensor Networks

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Outline

• Network layer functions

• Routing algorithm requirements and strategies

• Network of networks: Internet

• Routing in traditional networking technologies (Dijkstra, Belman- Ford routing algorithm)

• Routing in Mobile Ad Hoc Networks

• Routing as a quadratic optimization problem

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Layered Communication Approaches

3. Network layer: it responsible for all of the aspects of end-to-end (e2e) packet delivery, including routing packets from the source to the destination.

– Challenges: unreliable wireless links (but reliable communication is needed), node mobility (dynamic behaviour), energy awareness, etc.

– Route state dissemination: proactive and reactive or hybrid routing protocols.

– Topology: Single-hop, Multi-hop flat, clustered, multilevel hierarchical networks.

– Multipath routing: reduces the fault tolerance of a routing protocol and it provides better load balancing in the

network. Physical

Data link Network Transport Middleware

Application

Recall from Chapter 1

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Network layer protocols

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Routing Algorithm Requirements

• Correctness

• Simplicity

• Robustness: the ability of the network to deliver packets via some route in the face of localized failures and overloads.

• Stability: it does not “over react” to network changes.

• Fairness: as related to all other users.

• Optimality: as related to some criterion.

• Efficiency: as related to processing overhead.

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Elements of Routing Techniques

• Performance Criteria

– Number of hops, cost, delay, throughput.

• Decision Time

– Virtual Circuit--at connection establishment.

– Datagram--before packet is placed in outgoing buffer.

• Decision Place

– Each node, central node, originating node.

• Network Information Source

– None, local, adjacent nodes, nodes along the route, or all nodes.

• Network Information Update Timing

– Continuous, periodic, major load change, topology change.

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Routing strategies

• Fixed Routing

− A route is selected for each source-destination pair of nodes.

− A central routing directory can then be distributed to the various nodes.

− Routes are not changed unless topology changes.

− Simple (advantage) but inflexible (disadvantage.)

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Routing strategies (cont’)

• Flooding

A packet is sent out on every outgoing link except the link that it arrived on.

− Duplicates must be discarded.

− Hop counter could be used.

− Very robust (advantage.) but high traffic loads are generated (disadvantage.)

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Routing strategies (cont’)

• Random Routing

− Simplicity of flooding with much less load.

− Node selects one outgoing path for retransmission of incoming packet.

− An outgoing link is selected at random (based on a probability distribution.)

− Requires no use of network information (advantage.)

− Actual route will not be least-cost or minimum-hop route (disadvantage.)

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Routing strategies (cont’)

• Adaptive Routing

− These algorithms react to changing conditions of the network, for example failures and congestion.

− Advantages--can improve performance and aid in congestion control.

− Disadvantages--complex, requires extra "overhead" traffic to collect information, and may react too quickly (unstable.)

− Schemes can be characterized by

• Source of Network Information

• Distributed or Centralized Control

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Network of netwoks: Internet

• 1957: USSR launched Sputnik; US DoD formed Advanced Research Projects Agency (ARPA)

• 1961: First paper by Len Kleinrock on packet switching theory

• 1964: Paul Baran from RAND on design of packet switching networks

• 1965-1968: ARPANET plan: 3 independent implementation

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Network of netwoks: Internet (cont’)

• 1969: ARPANET commissioned: 4 nodes, 50kbps

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Network of netwoks: Internet (cont’)

• 1970: ALOHAnet, the first packet radio network, developed by Norman Abramson, Univ of Hawaii, becomes operational

• 1973: Bob Kahn poses the Internet problem---how to connect ARPANET, packet radio network, and satellite network

• 1974: Vint Cerf, Bob Kahn publish initial design of TCP (NCP) to connect multiple networks 1978: TCP (NCP) split to TCP/IP, 1983: TCP (NCP) converted to TCP/IP (Jan. 1)

• 1981: BITNET (Because It’s Time NETwork) between CUNY and Yale

• 1986: NSF builds NSFNET as backbone, links 6 supercomputer centers, 56 kbps; this allows an explosion of connections, especially from universities

• 1987: 10,000 hosts

• 1988: NSFNET backbone upgrades to 1.5Mbps

• 1989: 100,000 hosts

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Network of netwoks: Internet (cont’)

• 1990: ARPANET ceases to exist

• 1991: NSF lifts restrictions on the commercial use of the Net; Berners-Lee of European Organization for Nuclear Research (CERN) released World Wide Web

• 1992: 1 million hosts (RFC 1300: Remembrances of Things Past)

• 1994: NSF reverts back to research network (vBNS); the backbone of the Internet consists of multiple private backbones

• Today: backbones run at 10 Gbps, some updated to 40 Gbps, ~625 mil.

computers in 150 countries

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Internet Physical Infrastructure

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Summary of current wireless systems (cont’)

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Recall from Chapter 1

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Graph theoretic approach of routing algorithm

• Point to point routing algorithms (Unicast)

− Dijkstras algorithm (greedy algorithm)

− Bellman-ford algorithm (distributed algorithm)

• Shortest path routing (Least cost algorithm)

− What is a shortest path? Minimum number of hops? Minimum distance?

− There is a weight associated with each link: weight can be a measure of congestion in the link, propagation delay etc.

− Weight of a path is the sum of weight of all links

− Shortest path is the minimum weight path

• Point to multipoint routing (Multicast)

− Flloyd-Warshall algorithm (dynamic programming)

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Routing in traditional networking technologies

• Given: G{(V,E,d)}, where

− V denotes the vertices,

− E denotes the edges (links between two vertices),

− d denotes the link metrics associated with the edges, it can be additíve (e.g, distance, logCLP, MCD) or bottleneck (e.g. Bandwith, or available energy)

• A path is the sequence of edges leading from a given vertex (source) to another given vertex (destination):

• The optimal path

− in case of additive link metrics:

− in case of bottleneck type link metrics:

( ) ( ) ( )

{ ^, ^, ^, ^, ^, ^, }

i_→k

i j j n m k

ℜ = …

opt ( )

,

: min _ab

a b ℜ ∈ℜd

ℜ

∑

opt ( )

: max min, _ab

a b d

ℜ ∈ℜ

ℜ

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Dijkstra’s algorithm

• Goal: find the shortest paths from given source node s to all other nodes by developing paths in order of increasing path length

• The algorithm runs in stages (next slide) each time adding node with next shortest path

• The algorithm terminates when all nodes are processed by

algorithm (in set T)

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Dijkstra’s algorithm (cont’)

STEP 1: initialization

− T = {s} Set of nodes so far incorporated

− L(n) = w(s, n) for n ≠ s

− initial path costs to neighboring nodes are simply link costs

STEP 2: get next node

− find neighboring node not in T with least-cost path from s

− incorporate node into T

− also incorporate the edge that is incident on that node and a node in T that contributes to the path

STEP 3: update least-cost paths

− L(n) = min[L(n), L(x) + w(x, n)] for all n

∉

^T

− If latter term is minimum, path from s to n is path from s to x concatenated with edge from x to n

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Dijkstra’s algorithm: an example

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Dijkstra’s algorithm: an example (cont’)

Iter T L(2) Path L(3) Path L(4) Path L(5) Path L(6) Path

1 {1} 2 1–2 5 1-3 1 1–4 ∞ - ∞ -

2 {1,4} 2 1–2 4 1-4-

3

1 1–4 2 1-4–5 ∞ -

3 {1, 2, 4} 2 1–2 4 1-4-

3

1 1–4 2 1-4–5 ∞ -

4 {1, 2, 4, 5}

2 1–2 3 1-4-

5–3

1 1–4 2 1-4–5 4 1-4-5–

6 5 {1, 2, 3,

4, 5}

2 1–2 3 1-4-

5–3

1 1–4 2 1-4–5 4 1-4-5–

6 6 {1, 2, 3,

4, 5, 6}

2 1-2 3 1-4-

5-3

1 1-4 2 1-4–5 4 1-4-5-6

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Bellman-Ford algorithm

• Goal: find the shortest paths from given node subject to constraint that paths contain at most one link

• find the shortest paths with a constraint of paths of at most two links

• and so on

• The Bellman optimality criterion: let us assume that we have found an optimal from i to k via j

"

'

r r

r

i j k

• • •

then if r is optimal then r’ and r” are

also optimal

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Bellman-Ford algorithm (cont’)

STEP 1: initialization

− L0(n) =∞, for all n≠ s

− Lh(s) = 0, for all h

STEP 2: update

− for each successive h ≥ 0

− for each n ≠ s, compute: L_h+1(n)=min_j[L_h(j)+w(j,n)]

− connect n with predecessor node j that gives min

− eliminate any connection of n with different predecessor node formed during an earlier iteration

− path from s to n terminates with link from j to n

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Bellman-Ford algorithm (cont’)

• Distributed operation:

− Flooding the network with HELLO packets to discover its topology

− Sending ECHO packets to obtain link state information (e.g. by measuring the round-trip delay)

− Setting up the routing table according to Bellman-Ford algorithm

Adress Neighbouring node

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Bellman-Ford algorithm: an example

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Bellman-Ford algorithm: an example (cont’)

h L_h(2) Path L_h(3) Path L_h(4) Path L_h(5) Path L_h(6) Path

0 ∞ - ∞ - ∞ - ∞ - ∞ -

1 2 1-2 5 1-3 1 1-4 ∞ - ∞ -

2 2 1-2 4 1-4-3 1 1-4 2 1-4-5 10 1-3-6

3 2 1-2 3 1-4-5-3 1 1-4 2 1-4-5 4 1-4-5-6

4 2 1-2 3 1-4-5-3 1 1-4 2 1-4-5 4 1-4-5-6

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Comparison

• Bellman-Ford:

− calculation for node n needs link cost to neighbouring nodes plus total cost to each neighbour from s

− each node can maintain set of costs and paths for every other node

− can exchange information with direct neighbors

− can update costs and paths based on information from neighbors and knowledge of link costs

• Dijstra:

− each node needs complete topology

− must know link costs of all links in network

− must exchange information with all other nodes

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Asynchronous Bellman-Ford algorithm

• No notion of global iterations

− each node updates at its own pace

• Asynchronously each node i computes

using last received value dij from neighbor j.

• Asyncrhonously node j sends its estimate to its neighbor i:

− there is an upper bound on the delay of estimate packets (no worry for out of order)

min

( )

(

ⁱ

)

i j N i ij j

d =

_∈

d + d

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Asynchronous Bellman-Ford: an example

A

E D

C B

7

8 10

2 1

2

d_E

Distance table

from neighbours Computation E’s distance table

A B D A B D

A 0 7 ∞ 10 15 ∞ A:10

B 7 0 ∞ 17 8 ∞ B:8

C ∞ 1 2 ∞ 9 4 C:4

D ∞ ∞ 0 ∞ ∞ 2 D:2

Below is just one step!

The protocol repeats forever!

10 8 2

distance table E sends to its neighbours

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Asynchronous Bellman-Ford (cont’)

• Distributed: each node communicates its routing table to its directly-attached neighbors

• Iterative: continues periodically or when link changes, e.g. detects a link failure

• Asynchronous: nodes need not exchange info/iterate in lock step!

• Convergence in finite steps, independent of initial condition if network is connected

• Propagate properties (counting-to-infinity)

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This is called the counting-to-infinity

problem

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Asynchronous Bellman-Ford (cont’)

• Good news propagate fast

• Bad news propagate slowly

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• a set of mobile hosts, each with a transceiver

• no base stations; no fixed network infrastructure

• multi-hop communication

• needs a routing protocol which can handle changing topology

Mobile Ad Hoc Networks (MANET)

Édouard Manet

23 January 1832 – 30 April 1883

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Single-hop vs. Multi-hop communication

Single-hop ad hoc Multi-hop ad hoc

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Single-hop vs. Multi-hop communication (cont’)

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MANET typical applications

• Personal area networking

− cell phone, laptop, ear phone, wrist watch

• Military environments

− soldiers, tanks, planes

• Civilian environments

− car network

• meeting rooms

− sports stadiums

− boats, small aircraft

• Emergency operations

− search-and-rescue

− policing and fire fighting

• (See more in Chapter 11)

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MANET characteristics and challenges

• Characteristics and requirements:

− Distributed operation

− Dynamic network topology

− Fluctuating link capacity

− Low-power devices

• Challenges:

− Broadcast nature of the wireless medium (Hidden terminal problem)

− Packet losses due to transmission errors

− Mobility-induced route changes and packet losses

− Battery constraints

− Potentially frequent network partitions

− Ease of snooping on wireless transmissions (security hazard)

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MANET routing protocols

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Table Driven Routing Protocols

• Proactive protocols

• Continuously evaluate the routes

• Attempt to maintain consistent, up-to-date routing information (when a route is needed, one may be ready immediately)

• When the network topology changes: the protocol responds by propagating updates throughout the network to maintain a consistent view

• Example: DSDV(Destination Sequence Distance Vector)

− C.E. Perkins and P. Bhagwat, “Highly dynamic destination-sequenced distance-vector routing (DSDV) for mobile computers,” ACM SIGCOMM Computer Communication Review, vol. 24, 1994, pp. 234–244.

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Table Driven Routing Protocols : DSDV

• Based on the Bellman-Ford algorithm

• Each node keeps a routing table to all other nodes based on next- hop routing

• Path discovery through packet caching and header examination.

• Entries have a sequence number.

• Incremental updates possible.

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Comparision of Table-Driven Routing Protocols

Parameters DSDV CGSR WRP

Route Complexity O(x = N) O(x = N) O(x = N)

Route Philosophy Flat Hierarchical Flat

Loop Free Yes Yes Yes

Multicast Capability No No No

Required Tables 2 2 4

Freq Of Updated Transmission Periodically and as needed

Periodically Periodically and as needed Updates Transmitted to Neighbors Neighbors and cluster heads Neighbors

Utilize Seq. No / Hello Packets Yes/No Yes/No Yes/Yes

Critical Nodes No Yes(cluster head) No

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On Demand Routing Protocols

• Reactive protocols

• On-demand style: create routes only when it is desired by the source node

− route discovery: invoke a route-determination procedure

− the procedure is terminated when 1. a route has been found

2. no route is found after all route permutations are examined

• longer delay: sometimes a route may not be ready for use immediately when data packets come

• Example AODV

− C.E. Perkins, E. Belding-Royer, and S. Das, “Ad hoc On-demand Distance Vector (AODV),” Request For Comments (RFC), vol. 3561, 2003.

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Comparision of On Demand Routing Protocols

Performance Parameters AODV DSR TORA ABR

Communication Complexity

O(2N) O(2N) O(2N) O(N+y)

Routing / Loop Free Flat / Yes Flat / Yes Flat / Yes Flat / Yes

Multicast Capability Yes No No No

Beaconing Requirements No No No Yes

Multiple Route Possibilities

No Yes Yes No

Route Reconfiguration Erase Route, Notify Source

Erase Route, Notify Source

Link reversal, route repair

Localized broadcast

query Route Maintained in Route table Route cache Route table Route table Routing Metric Fresh and Shortest Shortest Associativity

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Table Driven vs. On Demand Routing Protocol

Parameters On Demand Table Driven

Availability of Routing Information

Available when needed Always available regardless of need

Routing Philosophy ^Flat Mostly Flat

Periodic route updates Not Required Yes

Coping with Mobility Using Localized route discovery in ABR

Inform other nodes to achieve consistent routing

tables

Signaling Traffic Generated

Grows with increasing mobility of active nodes

Greater than that of On Demand Routing

QoS Support Few Can Support QoS Mainly Shortest Path as QoS Metric

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Routing as a quadratic optimization problem

- Random flow of packets, - Congestions

- Random delays - High utilization

- Given cell loss rate

- Given end-to-end delays (real-time)

??

Analogic optimization algorithms to enforce QoS communication possibly

implemented on analogic computers

Objectives:

Develop traffic management algorithms which can be implemented on analogic computing architectures (i.e., try to reduce routing and switching problems to quadratic optimization).

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Routing as a quadratic optimization problem (cont’)

• Technological motivation: Even though BF algorithm is running in polynomial time it is slow on present work station, thus substitute it with analogic computations.

• Scientific motivation: Try to provide efficient, suboptimal solutions to NP hard routing problems, such as routing with incomplete information.

• Proposed solution:

Analogic computers

real-time optimization of quadratic forms over a binary space

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Routing as a quadratic optimization problem (cont’)

QoS routing

Representation

Quadratic programing

Binary data structure

Algorithm Analogic

computing (HN, CNN)

Binary representation of the optimal path De-representation

Optimal path which

opt { }

1,1

: min 2

∈ − N ^T − ^T

y

y y Wy b y

( ) ( )

1

1 sgn

N

l lj j l

i

y k W y k b

=

 

+ = −  − 



∑



mod_N

l = k

Recall from DSP course

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Binary representation

a

b c

d

e f ^{( )}

0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 1 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 1

G

a b c d e f

 

 

=  

 

 

V

nodes

time

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Quadratic programming

• d_ij is the additive routing measure between node i and node j

• The goal function with constraint of permutation matix (for valid solution):

1

opt 1 , , 1, 2 , , 3 , ,

1 , ,

2 2 2

4 , , 5 , , 6 ,

: min

1 1

k

n i i j n j i n j n n i n j

i j n i j j i n i j j i n

i j i j i j i j i j

i j i j i j

V d V V V V V

V S V E V k

α α α

−

= + ≠ ≠

+ + +

     

− + − + −

     

     

∑∑∑ ∑ ∑ ∑ ∑ ∑ ∑

∑∑ ∑∑ ∑∑

V V

1 2

nN m nm

V = y

⁺

+

{ }^1,1 ²

min 2

N

T T

∈ − −

y

y Wy b y

2

1

( 1) sgn ( )

N

l lj j l

j

y k W y k b

=

 

+ = −  − 



∑



k l = mod_N

Complexity ≈ O N( 4)

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Performance analysis

Performace of methods

0.394212381

0.969142857 0.923021667 0.9698

0 0.2 0.4 0.6 0.8 1 1.2

Hopfield - complete - normal - without

noise

Hopfield - complete - with noise

CNN - complete - normal - without

noise

CNN - complete - normal - with noise

Belmann-Ford

method

( , )

( , ) ( , )

method

( , )

( , ) ( , )

( )

u v

b V f V u v R b f

u v

b V f V u v R b f

d

G d

η ^∈ ^∈ ^∈

∈ ∈ ∈

=

∑ ∑ ∑

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Summary

• The routing protocols belong to the network layer.

• Ultimate objectives: getting connected to the Internet (the last miles in wireless) .

• There four different routing strategies (fixed, flooding, random, adaptive).

• Unicast routing has traditional polynomial-time algorithms (Dijkstra, Bellman- Ford).

• Multihop communications in Mobil Ad Hoc Networks poses several challenges (mobility, QoS, hidden terminal problem, etc.).

• Two approaches for MANET routing (Table Driven and On Demand routing).

• In the case of random metrics due to incomplete information, routing becomes NP hard but by using quadratic programming (HNN and CNN) it can be run in polynimial time.

Routing protocols

Ad hoc Sensor Networks

Routing protocols

Dr. Levendovszky János

Lecture 6 review

• The goal of medium access control

• Types of wireless networks

• Duplexing techniques

• Multiple Access

• Random Access

• MAC for Wireless Sensor Networks

Outline

• Network layer functions

• Routing algorithm requirements and strategies

• Network of networks: Internet

• Routing in traditional networking technologies (Dijkstra, Belman- Ford routing algorithm)

• Routing in Mobile Ad Hoc Networks

• Routing as a quadratic optimization problem

Layered Communication Approaches

Network layer protocols

Routing Algorithm Requirements

• Correctness

• Simplicity

• Robustness: the ability of the network to deliver packets via some route in the face of localized failures and overloads.

• Stability: it does not “over react” to network changes.

• Fairness: as related to all other users.

• Optimality: as related to some criterion.

• Efficiency: as related to processing overhead.

Elements of Routing Techniques

• Performance Criteria

• Decision Time

• Decision Place

• Network Information Source

• Network Information Update Timing

Routing strategies

• Fixed Routing

Routing strategies (cont’)

• Flooding

Routing strategies (cont’)

• Random Routing

Routing strategies (cont’)

• Adaptive Routing

Network of netwoks: Internet

• 1957: USSR launched Sputnik; US DoD formed Advanced Research Projects Agency (ARPA)

• 1961: First paper by Len Kleinrock on packet switching theory

• 1964: Paul Baran from RAND on design of packet switching networks

• 1965-1968: ARPANET plan: 3 independent implementation

Network of netwoks: Internet (cont’)

• 1969: ARPANET commissioned: 4 nodes, 50kbps

Network of netwoks: Internet (cont’)

Network of netwoks: Internet (cont’)

Internet Physical Infrastructure

Summary of current wireless systems (cont’)

Graph theoretic approach of routing algorithm

• Point to point routing algorithms (Unicast)

• Shortest path routing (Least cost algorithm)

• Point to multipoint routing (Multicast)

Routing in traditional networking technologies

• Given: G{(V,E,d)}, where

• A path is the sequence of edges leading from a given vertex (source) to another given vertex (destination):

• The optimal path

( ) ( ) ( )

{ , , , , , , }

i j j n m k

ℜ = …

∑

Dijkstra’s algorithm

• Goal: find the shortest paths from given source node s to all other nodes by developing paths in order of increasing path length

• The algorithm runs in stages (next slide) each time adding node with next shortest path

• The algorithm terminates when all nodes are processed by

algorithm (in set T)

Dijkstra’s algorithm (cont’)

STEP 1: initialization

STEP 2: get next node

STEP 3: update least-cost paths

∉

Dijkstra’s algorithm: an example

Dijkstra’s algorithm: an example (cont’)

Bellman-Ford algorithm

• Goal: find the shortest paths from given node subject to constraint that paths contain at most one link

{ ^, ^, ^, ^, ^, ^, }