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Routing Load of Route Calculation and RouteMaintenance in Wireless Proactive Routing

ProtocolsD. Mahmood, N. Javaid, U. Qasim‡, Z. A. Khan$

‡University of Alberta, Alberta, Canada.Department of Electrical Engineering, COMSATS

Institute of Information Technology, Islamabad, Pakistan.$Faculty of Engineering, Dalhousie University, Halifax, Canada.

Abstract—This paper presents mathematical framework andstudy of proactive routing Protocols. The performance analysis ofthree major proactive routing protocols: Destination-SequencedDistance Vector (DSDV) , Fish-eye State Routing (FSR) andOptimized Link State Routing (OLSR) are under considerationin this work. Taking these routing protocols into account, weenhance existing framework. In the next step we further discussand produce analytical framework by considering variations indifferent network and protocol parameters. Finally, experimentsare performed regarding above mentioned routing protocolsfollowed with detailed comparison and analysis of differentenvironments.

Index Terms—Overhead, Routing, Proactive, Protocols, Route,Discovery, Maintenance, Trigger, Periodic, Messages, Analytical,Modeling.

I. I NTRODUCTION

Wireless Multi-hop Networks (WMhNs) are the solutionfor infrastructure less communication. They give a networkofdifferent nodes that intercommunicate with each other withoutany help of structured or wired devices. Hence, every nodeacts as a transceiver and relay a message from one node toanother until message reaches its destined node. The mainconcept of WMhNs is to ensure freedom of communicationswith low costs and energy. To ensure such freedom, mobilityand scalability are two major aspects which are to be tackled.No doubt such networks are gaining popularity day by dayhowever, also give challenges for researchers in terms ofefficiency.

Protocols, being vital factor that governs WMhNs com-munications, are functioning on different layers. Amongstallrouting protocols, network layer protocols play an importantrole in providing smooth, and efficient functionality of a net-work. Actually a network layer protocol is wholly responsiblefor creating and maintaining all the data regarding routingofmessages to their prescribed destinations.

Reactive and proactive routing protocols are two majorclasses of network routing protocols in WMhNs. Reactiveapproach is based on immediate response factor i.e., a routeissearched only when it is required while proactive class is basedon pre-searching of route, prior to its requirement [1]. Though,hybrid routing protocols, which actually are combination of

reactive and proactive routing protocols, are also gainingpopularity. Numerous experiments and simulations are under-taken with respect to proactive routing protocols while lessmathematical framework is produced. In this paper we presentmathematical framework that discusses behaviors of routingprotocol under different environments and with variationsindifferent network and protocol parameters. For this purpose,we take three routing protocols from proactive routing i.e.,DSDV [2], OLSR [3] and FSR [4]. In proactive routing,there are two main steps involved: i.e., route calculation androute maintenance. These steps are discussed analyticallyandexperimentally in later sections.

II. RELATED WORK AND MOTIVATION

Authors in [6] discuss and present a combined frameworkof reactive and proactive routing protocols. Their modelsdeals with scalability factor. In [7], authors give analyticalmodel which deals with effect of traffic on control overheadwhereas, [8] presents a survey of control overhead of bothreactive and proactive protocols. They discuss cost of energyas routing metric. Nadeemet.al. [9], enhancing the work of[8], calculate control overhead of FSR, DSDV and OLSRseparately in terms of cost of energy as well as cost oftime. I.D Aron et.al presents link repairing modeling bothin local repairing and source to destination repairing alongwith comparison of routing protocols in [10]. X. Wuet.al.[14] give detailed network framework where nodes are mobileand provides“statistical distribution of topology evolution”. In[11], authors present brief understanding of scalability issuesof network however, impact of topology change was not suf-ficiently addressed. Authors of [12] and [13] present excellentmathematical network model for proactive routing protocols.We modify the said model by adding control overhead oftriggered update messages within the network.

In our work, we initially take route calculation overheadcalculated by [12] as proactive control overhead. We modifygiven framework by adding route monitoring overhead andtrigger update overhead, respectively. In next step, we calculatethe aggregate routing overhead. For this purpose, differentparameters of network and protocol as, number of nodes in

network, route life time, periodic hello message interval forlink monitoring and number of hops of network to calculatevariation in routing overhead are taken. Finally, we simulaterouting protocols and give a brief discussion on their respectivebehaviors according to different environments.

III. ROUTING PROTOCOLS

Routing protocols make the communication among differentnodes possible as they are responsible of finding routes,creating routing tables and maintaining them. Besides thesefunctionalities, they also deal with other data communicationprocedures. Whenever, a route is disturbed due to mobilityfactor or any other radio problem, routing protocol is respon-sible to rectify and establish the route again [1]. In this workwe are confined to one prominent class of routing protocolsi.e., proactive routing protocols.

A. Proactive Routing

Proactive protocols are table driven routing protocols andare meant amongst dense networks. In such protocols, routinginformation of next hop is preserved on the initializationof network regardless of communication requests. As, thenetwork initializes, periodic control packets are flooded amongnodes to uphold the paths or link states. In this way, theyform a table on each node describing the paths to or fromeach node. In other words, when a network initiates, theseprotocols start discovering the routes within all the nodesofnetwork regardless of use of that route. Such procedures maycause network over burden for specific time however, reducedelay on other hand.

1) Route Calculation:Route calculation in proactive rout-ing is a bit different with respect to reactive routing. Inproactive routing, as the network initiates, every node huntseach and every possible destination in the network. This allinformation is than stored in routing tables.

2) Route Maintenance:As in proactive approach, everynode keeps the information of all paths to every possibledestination with the help of periodic messages. If a changeoccurs within the periodic message interval, than in someprotocols, trigger message is issued. In this way, routes aremaintained in proactive routing protocols.

IV. M ODELING ROUTING OPERATIONS

In this work, we presents a framework of proactive protocolsfor routing overhead. In this section, we give overall controloverhead of proactive routing protocols i.e., overhead duetoroute calculation, un-reached destination packets, and triggermessages. Following with analyzing variations in differentnetwork and protocol parameters. Afterwards we discuss andcompare the behaviors of proactive routing protocols in dif-ferent environments and scenarios .

A. Proactive Route Calculation Overhead

As, we know that in proactive approach, whenever, anetwork initializes, than all routes are created immediatelyusing flooding mechanism. Routing table is updated peri-odically with the help of periodic messages. If any change

occurs between two periodic messages, a trigger messageis broadcasted, as described in DSDV [2]. In a dynamicnetwork, there may be loss of packets due to broken linkswhich are not updated at that vary instance. Hence, routingoverhead of proactive protocols can be stated as the sum ofnumber of packets failed to reach destination due to linkbreakage, periodic messages and trigger update messages.Periodic messages are issued after a specific interval of timewhile trigger messages are generated only when a changein topology occurs. Mathematically, we can write the abovestatement as:RO = PF + PR+ TRRO stands for routing overhead,PF refers to the number of

packets failed to reach destination andPR stands for periodicmessages while,TR represents trigger messages.

Normally there are two types of errors that lead to packetfailure and are discussed in detail in [9]. In either case, theprobability of packet loss is increased.

1) Route Failure Impact:During periodic update time span(Tpr), number of packets encountering route failure is definedin [12] as:

RO(PF ) = (∑

piεPA

li∑

r=0

Qlr(Tpr)Na(Tpr)) (1)

RO(PF ) denotes routing overhead of packet failures due to linkbreakage,Ql

r(Tpr) is probability that during firstr hopes, the uplinkstate does not change its state to down link,Na(Tpr) specifiesnumber of data packets arriving at timeTpr while Tpr representsperiodic route update time,Li stands for length ofPi (ith Path)andPA is set of all paths in the network.

2) Periodic Message Overhead:Periodic message overhead in proactive routing protocols can be stated as size ofrouting table per periodic route update time. While routingtable size is equivalent to the size of network. Combining itwith the complexity of routing overhead we get the periodicmessage update, as discussed in [12].

RO(PR) =kn3

BTpr

(2)

RO(PR) deonates routing overhead due to periodic updates,B

is the bandwidth,n represents Number of nodes in a network andK

is used to adjust routing protocol impulse factor.

B. Proactive Route Maintenance overhead

Coming to the next important aspect of aggregate routingoverhead, the triggered messages, we have to understand whenand how, a trigger message is updated.

Consider that there is a node in a network that moves insuch a way that it changes its topology in between two periodicmessages, i.e., in betweenTpr andTpr + 1, say at timeT 0.Routing protocol does not wait for next periodic message toupdate this change in topology instead; it immediately broad-cast a triggered message. The concept of triggered message isportrayed in Fig.1.

Com Range

Perio

dic

Me

ssa

ge

inte

rva

l (T

ime

)

T1

T2

T3

T4

1 2 3 4

Node

A

Node

A

Triggered Update

Periodic Message

Periodic Message

Periodic Message

Periodic Message

T0

Fig. 1. Node A Travels between T1 and T2 from Com Range 1 to 2, Resultinga Trigger update at T0

Analytically we can express this illustration as:Tpr < T < Tpr + 1.

As, discussed in [14] this notation can be expressed as:

RO(TR)i =

⌈

TTpr

⌉

TTpr

(3)

RO(TR)i represents routing overhead due to one triggeredupdate message. In mathematics, ceiling operator should besolved by taking the highest possible values. In a networkwhere only one node moves within a time span ofTpr

and Tpr + 1, the above equation qualifies but considering ahighly mobile environment where all the nodes of networkare mobile, the maximum overhead due to triggered updateduringTpr andTpr + 1 is:

RO(TR) =n∑

i=1

⌈

TTpr

⌉

TTpr

(4)

RO(TR) refers trigger message overhead andT represents triggeredupdate.

C. Aggregate Proactive Overhead

Combining the respective values ofEq.1, Eq.2 andEq.4we get the analytical equation expressing the aggregate routingoverhead of the network.

RO = (∑

piεPA

li∑

r=0

Qlr(Tpr)Na(Tpr)) + (

kn3

BTpr) +

n∑

i=1

⌈

TTpr

⌉

TTpr

(5)

Let, RO be the optimized function“y′′ having differentparameters then we get:

y(n, Tpr, µk, T, λ) = (∑

piεPA

li∑

r=0

Qlr(Tpr)Na(Tpr))(

kn3

BTpr) +

n∑

i=1

⌈

TTpr

⌉

TTpr

(6)

As, discussed in [7]:

Qlr(Tpr) = 1− e

−

rTprµk (7)

We can say thatλ is the average number of packets arrivedsuccessfully at node,µk is the uplink time,T is triggeredupdate messages andn stands for number of nodes in anetwork. Substituting the value fromEq.7 to Eq.6, we have:

y(n, Tpr, µk, T, λ) = (∑

piεPA

li∑

r=0

1 − e−

rTprµk λ(Tpr)) +

(kn3

BTpr) +

n∑

i=1

⌈

TTpr

⌉

TTpr

(8)

To analyze variation in these parameters, we take partialderivative of functiony to get:

∂y/∂Tpr = (C)

Lavg∑

r=0

1 − e−

rTprµk +

rTpr

µk

e−

rTprµk −

kn3

b(Tpr)2+

n∑

i=1

⌈−T

(Tpr)2⌉ + T

(Tpr)2

T2/(Tpr)2(9)

whereC representsPNavg.λThe partial derivative with respect to the rate of packet

arrival is expressed as:

∂y/∂λ = (PNavg)

Lavg∑

r=0

Tpr(1− e−rTpr

µk

) (10)

Similarly, if we take partial derivative with respect toT , weget:

∂y/∂T =n∑

r=0

⌈ 1(Tpr)2

⌉ − 1(Tpr)2

T 2/(Tpr)2(11)

Rate of change in link arrival time is:

∂y/∂µk = (PNavgλTpr)

Lavg∑

r=0

−rTpr

(µk)2(e

−rTprµk ) (12)

It is obvious that number of nodes of a network plays a vitalrole to create routing overhead. We can calculate the impactof change in number of nodes of a network:

∂y/∂n =3kn2

BTpr

(13)

ConsideringEq.13, that is partial derivative with respect ton, we can infer that as number of nodes of a network increases,its routing overhead increases though, if number of nodes de-creases than three nodes, the overhead of the network reduces.Assuming mobility and scalability constant,consideringEq.9

andEq.11, we can say thatTpr andT are two variables thatare dependent on each other. As, periodic message intervalexceeds, then trigger messages are also increased. In the sameway, if we reduce periodic update interval time, the ratioof generation of triggered updates is lowered if, all otherparameters mainly mobility and number of nodes in a networkremain constant. To further analyze this change, we take totalderivative ofTpr andT variables of functiony.

dy

dTpr

=∂y

∂Tpr

+∂y

∂T(dT

dTpr

) (14)

dy =∂y

∂Tpr

(dTpr) +∂y

∂T(dT ) (15)

putting the values:

dy = (C)

Lavg∑

r=0

1 − e−

rTprµk +

rTpr

µk

e−

rTprµk −

kn3

b(Tpr)2+

n∑

i=1

⌈ −T

(Tpr)2⌉ + T

(Tpr)2

T2/(Tpr)2(dTpr) +

n∑

r=0

⌈ 1(Tpr)2

⌉ − 1(Tpr)2

T2/(Tpr)2(dT ) (16)

In static environment, longerTpr do not affect performanceof routing protocol and favor reducing routing overhead how-ever, if in mobile environments, longerTpr is used, it resultsin high rate of triggered messages.Eq.16 shows thatTpr andT are two variables which are tied with nonlinear relationshipwith one another.

ConsideringEq.12 and Eq.10, it is obvious that if thereis always an uplink for for the entire life of the network, orthere is no periodic interval i.e., ifµk tends to infinity andTpr is zero, both partial derivatives with respect toλ andµkis zero[12]. Assuming,∂y/∂Tpr = 0s, we get:

C

Lavg∑

r=0

(1 − e

−rTprµk ) + e

−rTprµk =

kn3

(Tpr)2−

⌈ −T

(Tpr)2⌉ + T

(Tpr)2

T2/(Tpr)2(17)

The ratio between periodic update time and uplink time canbe termed as update coefficient [5]. Let us denote that updatecoefficient ash = Tpr/µk or Tpr = µk ∗h. Placing the valuesgives us optimized network analytical model.

C

Lavg∑

r=0

(1 − e−rh

) + (r ∗ h)−rh

=kn3

B(µk ∗ h)2−

n∑

i=1

−⌈ T(µk∗h)2

⌉ + T (µk ∗ h)2

T2

(µk∗h)2

(18)

Eq.18 shows that if average link uptime increases, updatecoefficient (h) also increases though, this increase do notlinearly affect the periodic interval time. As depicted before,here again this equation shows the same, as number ofnodes increases, the routing overhead is also increased non-linearly. According to [3], there are four periodic messages inOLSR. HELLO, Topology Control messages (TC), MultipleInterface Declaration messages(MID) and host and NetworkAssociation messages(HNA). Mostly HELLO and TCmessages are taken into considerations. If we look into themeof OLSR routing protocol, we come to know thatHELLOmessages are used to gain the neighborhood knowledge andto select Multi-Point Relay (MPR) set (MPR set is the only

set which is allowed to retransmit or broadcast the receivingmessage). The nodes including inMPR set are responsiblefor broadcastingTC messages. Hence,HELLO message asgiven in [3], is of 1 sec whileTC message interval is 2 sec.In other words, [3] propose thatHELLO message intervalshould be taken as half of theTC message interval.

Placing the values ofHELLO message andTC messagein composed analytical model, we get the equation:

ROOLSR = (PNavg)

Li∑

r=0

(1 − e− rTpr

µk

)λ(Tpr) +kn3

B ∗ H+

kn3

B ∗ 2H+

n∑

i=1

⌈ TH+2H

⌉

TH+2H

(19)

H =HELLO message interval,2H = TC message interval(twice the HELLO message

interval).To analyze the rate of change inHELLO andTC interval,

we partially derivate the above mentioned equation byH andwe get:

∂y/∂H = −kn3

B ∗ H2−

kn3

B ∗ 2H2+

n∑

i=1

⌈−T

(H+2H2)⌉ + T

(H+2H)2

T2

(H+2H)2

(20)

With the help of same model, we can calculate desiredoverhead, whether to find overhead due toHELLO messageemission orTC message overhead or the overhead due to lostpackets.

V. SIMULATED RESULTS AND DISCUSSIONS

Simulations of DSDV, OLSR [15] and FSR [16] are per-formed using NS-2. Our main concern is scalability andmobility factors in WMhNs. Simulation parameters are givenbelow:

Simulation Parameters1. Number of nodes =502. Bandwidth =2 Mbps

3. Packet Size =512 bytes

4. Size of network =1000 m2.5. Simulation setup runs on CBR

Within these parameters, we take the following threemetrics.1. Throughput2. End to end Delay3. Normalized routing Load.

A. Simulation Results

For Proactive experiments, we take FSR, DSDV and OLSR,and simulate these routing protocols with respect to mobilityand scalability by taking metrics of throughput, end to enddelay and normalized routing load (NRL).

1) Throughput of Proactive Routing Protocols:Mobility Factor:

DSDV outperforms among all selected protocol i.e., FSRand OLSR. Main reason of this result is basic functioning ofDSDV protocol, that a packet is sent only on the best possibleroute due to route settling time. Moreover, un-stabilized routes

200 400 600 800

Pause Time (s)

Fig. 2. Simulation Results of Proactive Protocols: DSDV, FSR, OLSR

that have the same sequence number in DSDV routing protocolare also advertised with delay. These features of DSDVresults in accurate routing hence, throughput is increased.On the other hand, taking OLSR into account, its ability toconverge declines as the mobility increases, thus results inlower throughput. Though, in static environment, due to MPRmechanism in OLSR, it gives better throughput than FSR andDSDV. Whenever, a link breaks, there is a concept of triggeredmessages in DSDV routing protocol that also increase the routeaccuracy where as in FSR there is no availability of triggeredupdates. OLSR triggers TC message only when status ofMPRs changes.

Scalability Factor:

In high scalabilities, OLSR outperforms among chosenprotocols. OLSR uses MPR for lowering the routing overheadbut periodic messages used to calculate and compute a MPRset for a node take more bandwidth. Though its throughput ismore than that of DSDV however. Throughput of FSR alsoincreases as it uses multilevel fisheye scope. This techniqueresults in lower overhead and less consumption of bandwidthwhich is a major plus point for throughput. DSDV usesNetwork Protocol Data Units (NPDUs) for lower overheadthough, triggered messages create routing overhead, consum-ing bandwidth and resulting in lower throughput. FSR is highlyscalable as it uses different frequencies for different scopes i.e.at different time intervals.

TABLE ICOMPARISON: PROACTIVE ROUTING PROTOCOLS

Feature FSR OLSR DSDVProtocoltype

Link state Link state DistanceVector

Route main-tained in

Routingtable

Routingtable

Routingtable

Multipleroutediscovery

Yes No No

Multi cast Yes Yes YesPeriodicbroad cast

Yes(with in lim-ited range)

Yes Yes

Topology in-formation

Reducedtopology

Fulltopology

Fulltopology

Update des-tination

Neighbors MPR sets Source

Broadcast Local/limited

Limited byMPR Set

Full

Reuse ofroutinginformation

Yes Yes yes

Route selec-tion

Shortest hopcount

Hop count Shortest hopcount

Route recon-figuration

Link statemechanismwithsequencenumber

Link statemechanism/ Controlmessagessend inadvance

Sequencenumberadopted

Routediscoverypackets

Link statemessages

Via controlmessage linksensing

Via controlmessages

Limitingoverhead,collisionavoidance,networkcongestion

Fisheyeprocedure,broadcastlimitedonly totransmissionrange

Concept ofMultipointrelays

Concept ofsequencenumber

Limitingoverhead,collisionavoidance,networkcongestion

MAC layerprotocolsonly

MAC layerprotocolsonly

MAC layerprotocolonly

Updateinformation

Only neigh-bor informa-tion

2 Hop neigh-bor informa-tion

By controlmessages

2) End to End Delay of Proactive Routing Protocols:Mobility Factor:

DSDV proves to be the best for throughput but whenconsidering delay, it bears the worst conditions with respect toFSR and OLSR. Moreover, delayed advertisements of unstableroutes results in overall high end to end delay. In DSDV,this is done to reduce the routing overhead and provide routeaccuracy but it compromises on delay. In such scenario, OLSRperforms better than DSDV. FSR produce the highest end toend delay among the studied protocols. As, in the basic themeof FSR, when the mobility increases, the accuracy of far awaydestined nodes fades. However, as the packet gets closer todestined node, the routing information gets accurate.

Scalability Factor:

As, the network gets dense, end to end delay of discussedrouting protocols i.e., FSR, DSDV and OLSR increases. FSRexchanges routing updates with its neighbors in small intervalswhile information shared at far away nodes has some largerinterval. The network become more scalable, end to end delayincreases in FSR. In DSDV, end to end delay is due to thetwo procedures, i.e., finding some routes and then choosing thebest route. The network gets denser; end to end also increases.As in proactive nature, the information is spread in wholenetwork. OLSR use MPRs’ and in less scalable environment,end to end delay using OLSR is lowered. This is because ofMPR concept that presents well organized flooding controlinstead of flooding a packet on whole network.

3) Routing Load of Proactive Routing Protocols:Mobility Factor:

Among the studied proactive routing protocols, OLSR gen-erates highest routing load due to MPRs computation. DSDVagain proves to be a good choice amongst FSR and OLSR interms of routing overhead. Considering FSR, it bears loweroverhead due to control and periodic messages as comparedto OLSR. FSR’s control messages are periodic based ratherevent driven based as in OLSR. This feature helps FSR toreduce routing overhead. Moreover, there is limited floodingin FSR i.e., link state information is not flooded among wholenetwork besides, every node manage a link State table whichis derived on the basis of up to date information is received.This information is not broadcasted or flooded but is sharedamongst neighbors.

Scalability Factor:OLSR gives the highest routing overhead due to MPR

computational messages andTC messages. DSDV and FSRhave lower overhead in dense environments. DSDV reducesoverhead with the help of NPDUs. The simulated results showthat FSR stands best amongst DSDV and OLSR in a denseand mobile environment in terms of overhead.

B. Discsussion

The protocol that uses minimum resources by its controlpackets can provide better data flow. Hence, the environmentswhere traffic load is very high, protocols having low routingoverhead will survive. If we consider scalability, in proactiverouting, OLSR stands tall as it limits retransmissions dueto use of MPR concept but only in dense environments. Ifmobility with the number of nodes of network increases, thanFSR is a good choice as it generates low routing overhead thatleads to high data rates within the limited bandwidth.

Considering throughput, DSDV proves itself to be the bestamongst FSR and OLSR. DSDV sends a packet only on thebest possible route which is verified by the protocol twicewith a procedure that makes a DSDV route more accurate.This is the reason that DSDV outperforms the rest two routingprotocols. OLSR’s converging ability minimizes when theenvironment is mobile else it would prove itself to be thebest due to MPR concept.

Considering routing overhead, OLSR is worst due to max-imum number of periodic messages for computation of mul-

tipoint relays. DSDV proves to be a good choice consideringrouting overhead as well. Whereas, FSR bears lowest routingload. The feature of Fisheye scope in FSR helps in reducingthe routing overhead, as, there is limited flooding i.e., linkstate information is not flooded among the entire network butis shared with neighbors of a scope only.

VI. CONCLUSION

In this work, we give analytical model for generalized rout-ing overhead of proactive routing protocols. For this purposewe divide the said task into small phases. In first phase wecalculate the routing overhead due to route calculation andthen routing overhead due to route monitoring and finallywe combined them altogether that gives us the aggregaterouting overhead of proactive routing protocols. Once we getthe aggregate routing overhead, we then apply variations indifferent network and protocol’s parameters and give a briefdiscussion on behavior of networks due to such variations.In experimental phase of our work, we simulate three mostprominent proactive routing protocols keeping mobility andscalability factors into perspective along with the metrics ofthroughput, end to end delay and normalized routing load. Wegive a brief discussion of the individual behaviors of eachrouting protocol in different scenarios and situations.

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