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INTERNATIONAL JOURNAL OF INNOVATIVE TECHNOLOGY AND CREATIVE ENGINEERING (ISSN:2045-8711) VOL.3 NO.8 AUGUST 2013

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International Journal of Innovative Technology and Creative Engineering 1a park lane, Cranford London TW59WA UK E-Mail: [email protected] Phone: +44-773-043-0249

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IJITCE PUBLICATION

International Journal of Innovative Technology & Creative Engineering

Vol.3 No.8

August 2013

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From Editor's Desk

Dear Researcher, Greetings! Research article in this issue discusses about AODV routing protocol, probabilistic Reactive Routing Protocol. Let us review research around the world this month; Space station poised to launch open-source satellites. Want to

do your own space experiment? Now, you will be able to run science projects on the world's first open-source

satellites. And it won't break the bank. ArduSat-1 and ArduSat-X were launched to the International Space Station

(ISS) on 3 August aboard a Japanese resupply vehicle (which is also carrying fresh food, supplies and a talking

humanoid robot). Known as CubeSats, each mini satellite packs an array of devices – including cameras,

spectrometers and a Geiger counter – into a cube just 10 centimetres to a side. The cargo ship carrying the

CubeSats should arrive at the ISS on 9 August, and the satellites will then be deployed using a robotic-arm

technique tested last year. The method can put several small satellites into orbit around Earth, eliminating the need

for dedicated launch vehicles and making citizen-science missions like ArduSat more affordable.

Plants could soon have robotic counterparts. Barbara Mazzolai from the Italian Institute of Technology in Genoa and

colleagues are creating a system that mimics the behaviour of roots. The team plans to use bespoke soft sensors

for underground exploration, tips that grow by unwinding material and a mechanism to reduce friction when

penetrating the soil. The artificial system will be equipped to detect gravity, water, temperature, touch, pH, nitrate

and phosphate. When Pierre Legagneux of the University of Quebec at Rimouski and Simon Ducatez of McGill

University in Montreal, both in Canada, were working together in France in 2006, they began studying the birds they

encountered on the drive home from the lab.

Birds are aware of speed limits on roads. Birds cannot read road signs, but they know that some roads have higher

speed limits than others. They will take off further away from an approaching car on a faster road than on a slower

road – regardless of the speed of the car. They found that where there was a 50-kilometre-per-hour speed limit,

birds on the road typically took off when the car was about 15 metres away, whereas on a 110-km-per-hour road,

they took off when a car was nearer 75 metres away. They did this even when faced with a car travelling faster on

the slow road or slower on the fast road.

It has been an absolute pleasure to present you articles that you wish to read. We look forward to many more new technologies related research articles from you and your friends. We are anxiously awaiting the rich and thorough research papers that have been prepared by our authors for the next issue. Thanks, Editorial Team IJITCE


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Contents

Performance study of AODV routing protocol using ETX as a metric by Chaitra Gaonkar, Vishalaxi Tandel, Vikash Kumar...........................................................................[109] An assessment of probabilistic Reactive Routing Protocol For MANET’s by Aditya Pare, Prof. Gaurav shrivastav…............................................................................................................[116]


109 www.ijitce.co.uk

Performance study of AODV routing protocol using ETX as a metric

Chaitra Gaonkar 1, Vishalaxi Tandel 2, Vikash Kumar 3

Department Of Computer Science and Engineering, B.V.Bhoomaraddi College of Engineering and Technology Hubli, Karnataka-India

1 [email protected]

2 [email protected]

3 [email protected]

Abstract - Due to unstable link states and interference

between neighbour nodes, routing in wireless mesh

network (WMN) is much more complicated and

unpredictable than wired network. As the simplest and

most primitive routing metric, hop count does not always

work well in WMN where routing with least hop count does

not bring the best performance. Recent research shows

that radio metrics, such as ETX reflect more accurately the

link conditions in a mesh network in terms of delay, loss,

bandwidth, and so on. The ETX metric routing method is

used with a cross-layer design taking the asymmetry of a

wireless link into account, in which monitoring and

measurement functions provide metrics in both forward

and reverse directions and captures the link state between

the node and each of its neighbours. This method is

applied to Ad-hoc On-demand Distance Vector (AODV)

routing protocol during the route discovering operation.

AODV-ETX finds the best path based on value of the ETX

by sending the probe packets to find the delivery ratios in

the forward and reverse directions, from source to

destination and from destination to source respectively.

We evaluate performance of the AODV-ETX protocol

using NS-2 simulator. The results show that the AODV-

ETX outperforms the original AODV, where the results

show a significant reduction of delay compared to the

original AODV and also the packet delivery ratio is

comparable to the packet delivery ratio in the original

AODV.

Keywords: AODV, ETX, internetwork, MAC, Mesh topology, Network traffic, NS-2.34, Radio nodes, X-graphs

I. INTRODUCTION

Wireless Networks have been an emerging technology in recent years due to their attributes such as flexibility, high robustness and bandwidth efficiency. There are many kinds of wireless topologies and wireless mesh networks (WMN) is one among them. Recently, wireless mesh networks have attracted much attention. Wireless mesh networks is a communications network made up of radio nodes organized in a mesh topology. A mesh network is reliable and offers redundancy. Wireless mesh networks can self form and self heal. Such networks, also known as ‘‘community wireless networks’’, can be used for various applications such as shared broadband access, neighbourhood gaming, video surveillance, and media repository.

In wireless mesh networks data will hop from one

device to another until it reaches its destination. Dynamic routing algorithms implemented in each device allow this to happen. To implement such dynamic routing protocols, each device needs to communicate routing information to other devices in the network. Each device then determines what to do with the data it receives — either pass it on to the next device or keep it, depending on the protocol. The routing algorithm used should attempt to always ensure that the data takes the most appropriate (fastest) route to its destination. Routing refers to the process of selecting paths in a network along which to send network traffic. Routing involves two basic activities: determining optimal routing paths and forwarding packets through an internetwork. The routing process usually directs forwarding on the basis of routing tables which maintain a record of the routes to various network destinations. Constructing routing tables, which are held in the router's memory, is very important for efficient routing. The problem of routing flow in a network of computers is extremely complex.



Routing protocols periodically probe the links to determine appropriate routes across the network. Routing protocols try to find the shortest, least cost, highest throughput, minimum delay and minimum overhead paths between a source and the destination. The common purpose of routing protocols is to compute the best route for data delivery. Routing protocols use metrics to evaluate what path will be the best for a packet to travel. A metric is a standard of measurement, such as path bandwidth, that is used by routing algorithms to determine the optimal path to a destination. To use or design an appropriate routing metric for a routing protocol, it is important to understand the characteristics of Wireless networks and identify what challenges will be faced. Therefore, to guarantee link quality, a good routing metric must take into account the metric characteristics to improve the performance of the routing protocol. A good routing metric should address the issues related to the key characteristics, such as, throughput, delay and overhead.

The routers in mesh networks are static, and thus

dynamic topology changes are much less of a concern in such networks. As a consequence, the main design goal for routing protocols is shifted from maintaining connectivity between source and destination nodes to finding high-throughput paths between the nodes. Towards this goal, more sophisticated routing metrics than the hop-count metric need to be used to find paths that achieve high throughput, as protocols based on the hop-count metric often choose long links which tend to be lossy and give low throughput.

There are various kinds of routing metrics like hop

count, ETX, ETT and so on. The concept of hop-count is quite simple where every link is counted as one unit and is independent of the quality of the link and hence it is the most widely used metric in routing protocols. The existence of error-free links is the implicit assumption made when hop count metric is chosen and hence while selecting the path for routing a packet it chooses the path with the smallest number of hops and ignores the quality of a link which ignores the possibility that a longer path might actually offer higher throughput.

ETX makes use of delivery ratios which are measured

using dedicated link probe packets. Each node broadcasts link probes of a fixed size, at a fixed time period. Every node remembers the probes it receives during last interval which allows it to calculate the delivery ratio. In this paper we describe about implementation of ETX (Expected transmission count) metric in AODV (Ad hoc On-Demand Distance Vector) routing protocol. Since Ns-2 is a widely used tool to simulate the behaviour of wired and wireless

networks we choose NS-2 as the network simulator to evaluate the performance of ETX metric with AODV routing protocol.

Rest of the paper is organized as follows: Section 2

describes the related work about AODV and ETX. Section 3 firstly explains why minimum hop-count often finds routes with significantly less throughput than the best available and then it presents the design, implementation, and evaluation of the ETX metric. Finally, it describes a set of detailed design changes to the AODV protocols (to which ETX is an extension), that enable them to more accurately choose routes with the best metric. Section 4 shows the results displayed after evaluating ETX metric by making use of X-graphs and execution of AWK scripts, and Section 5 concludes the paper.

II. RELATED WORK

In this section, we give an overview of various research works that has already been carried out in AODV and ETX. These works have helped us in implementing ETX metric in AODV.

In order to successfully implement ETX in AODV we need to first understand the working and behaviour of AODV [6] protocol. The Ad hoc On-Demand Distance Vector (AODV) algorithm enables dynamic, self-starting, multi-hop routing between participating mobile nodes wishing to establish and maintain an ad hoc network and to enable operation in AODV, Various message formats defined such are Route Requests (RREQs), Route Replies (RREPs), and Route Errors (RERRs).

Now to implement ETX in AODV, an extra packet

type is required to sense the link quality between the source and destination. Thus, the widespread ETX metric [3] is calculated by sending probe packets to neighbours and calculating the loss ratio of the probe packets. The ETX is used as an indicator for the congestion level and the collision probability.

To implement ETX in any of the protocol researchers

[5] tried to understand the meaning and complete definition of ETX. And then they came up with an ETX formula that can easily be applied and implemented for any of the protocol. Researchers defined ETX as Expected transmission count (ETX) is a metric that finds high throughput paths on multi-hop wireless networks incorporating the effects of link loss ratios and interference among the Successive links of a path.

Research has further been carried out [9] to show

that ETX metric performs better than hop count metric.



Minimum hop-count metric regardless of large differences in throughput, chooses different paths of same minimum length. This metric also account to issues like interference between successive hops among multi-hop paths. ETX metric provides better improvement for paths with two or more hops, suggesting that transmission count offers increased benefit as networks grows larger and paths become longer. Research has been done on various steps [7] to implement new protocol in ns2.A detailed description on various procedures and files to be included in ns2 was proposed by the researchers.

III. PROPOSED WORK

In this section we describe the plug-in of ETX as a routing metric in AODV routing protocol for wireless mesh networks. ETX metric uses both MAC layer and network layer features like number of transmissions from MAC and based on ETX routing will happen at the network layer. The ETX in AODV proves to be an appealing cost metric because minimizing the total no of transmissions and retransmissions maximizes the throughput of an individual link and then overall network. We shall discuss the modifications to be done for some of the files in NS-2 to include ETX metric in AODV. We also present the changes to be made to AODV protocol to calculate the value of ETX which is used while routing the packets.

The AODV algorithm enables dynamic, self-starting,

multi-hop routing between participating mobile nodes wishing to establish and maintain an ad hoc network. AODV allows mobile nodes to respond to link breakages and changes in network topology in a timely manner. And on the other hand, the ETX measures MAC transmissions and retransmissions to recover from frame losses.ETX of the wireless link is the estimated average number of transmissions of data frames and ACK frames necessary for the successful transmission of the packet. Alternatively, ETX of the link can also be defined as inverse of the probability of successful packet delivery or link reliability. Using ETX in AODV is advantageous because once the ETX value is known data packets can be transmitted and the calculated ETX will be used by the packets to choose best path to travel from its source to destination. Hence ETX does produce higher throughput than other routing metrics. Implementing ETX in AODV has shown better results with respect to some of the performance parameters than AODV alone.

To begin with the implementation the files already

present in NS-2 are to be changed according to the files presented in [1]. The detailed description of the modifications shall be discussed in the next section. To

reflect the changes mentioned in the following section we need to understand the dependencies that exist between different files in AODV and then configure NS-2 to analyse the results.

A. Changes to be made to AODV to calculate ETX

No more than 3 levels of headings should be used. All headings must be in 10pt font. Every word in a heading must be capitalized except for short minor words as listed in Section III-B.

1) Aodv_rtable.cc: AODV is a routing protocol, and it deals with route table management. Route table information must be kept even for short-lived routes, such as are created to temporarily store reverse paths towards nodes originating RREQs. The different fields used by AODV with each route table entry are Destination IP Address, Destination Sequence Number, Valid Destination Sequence Number flag, Other state and routing flags (e.g., valid, invalid, repairable, being repaired), Network Interface, Hop Count (number of hops needed to reach destination) Next Hop, List of Precursors, Lifetime (expiration or deletion time of the route) In order to include the value of ETX while routing another field named ETX should be added to the above mentioned fields.

2) Aodv.cc: In the TCL script, when the user configures AODV as a routing protocol by using the command “ $ns node-config -adhocRouting AODV” the pointer moves to the “start” and this “start” moves the pointer to the Command function of AODV protocol. In the Command function, the user can find three extra timers in the “start”. The first timer is used for sending ETX probe packets, the second timer handles the probe window timer and the third timer is used to manage the ETX probe packets.

When the timer for sending ETX probes is set an appropriate interval of Probe Packets is defined to schedule the packets. The node receiving the packet will check for different packets types and calls the respective receive mechanisms function.

On receiving an ETX probe packet the forward delivery ratio of a link is calculated using the formula

probes count

_

Forward delivery ratioPROBE WINDOW

When the timer for handling the probe window timer is set an interval for Probe Window is defined to handle the window of the probe packets. The reverse delivery ratio is calculated for the number of probe packets



received by a node from each neighbours during the last interval and then the timer is rescheduled.

On receiving an ETX probe packet the reverse delivery ratio of a link is calculated using the formula

probes neighbors[neighbor]Reverse

_delivery ratio

PROBE WINDOW

Finally the timer for managing ETX probes is set to some interval which removes all the old probe packets i.e. the packets that have expired.

Routing table Management: The routes chosen for routing the packets should consider the ETX value while updating the routing table in order to keep the latest information regarding the link quality. Whenever the route is down the ETX value is set to INFINITY (which is a very high value) which indicates the absence of a link.

Packet Reception Management: When a node receives a packet of type REQUEST, it firstly creates an entry for reverse route and calculates the value of ETX. Once the ETX value is known if we have a fresher sequence number or if we have a better link for the same sequence number then the routing table entry is updated with the new link quality as indicated by the ETX value. After taking care of the reverse route the receiving node now checks if it can send a route reply, if the receiving node itself is the destination it sends a reply with zero ETX value else if it is not the destination, but it has a fresh enough route then it sends a reply with the appropriate ETX value otherwise it simply forwards the route request.

When a node receives a packet of type REPLY, it adds a forward route table entry if a newer route is found to be better by comparing the ETX values of the newer and the older routes and updates the routing table entry. If the REPLY packet is destined for the receiving node then discard the packet else forward the route reply using the ETX value if the route is UP.

Packet Transmission Management: A node disseminates a RREQ when it determines that it needs a route to a destination and does not have one available. This can happen if the destination is previously unknown to the node or if a previously valid route to the destination expires or is marked as invalid. It fills out the RREQ packet and sets the ETX field to zero and sends the REQUEST messages. The first time a source node broadcasts a RREQ, it waits for a fixed interval of time for the reception of a RREP. If a RREP is not received within that time, the source node sends a new RREQ.

A node generates a RREP if either, it is itself the destination, or it has an active route to the destination where the destination sequence number in the node's existing route table entry for the destination is valid and greater than or equal to the Destination Sequence Number of the RREQ and also the ETX value in the node's existing route table entry is better the ETX vale of the RREQ packet. Once created, the RREP is sent towards the originator of the RREQ, as indicated by the route table entry for that originator. As the RREP is forwarded back towards the node which originated the RREQ message, the Hop Count field is incremented by one at each hop and the ETX of the route is maintained. Thus, when the RREP reaches the originator, the Hop Count represents the distance, in hops, and ETX represents the link conditions of the route from the destination to the originator.

The expected transmission count (ETX) metric which is based on the expected number of transmissions required to send a unicast packet over a link, including retransmissions. To calculate ETX, each node measures the probability that a packet successfully reaches the receiver, denoted as df, and the probability that an ACK is successfully received by the sender, denoted as dr. The ETX value of the link is given by

1

f rd d

ETX

The AODV routing algorithm then selects the path with the least sum of ETX values of its constituent links. To measure df and dr, each node broadcasts a probe packet every second. Each such probe contains the number of probes the node received from each of its neighbours in the last probe interval. Since the 802.11 MAC layer protocol does not retransmit broadcast packets, nodes use this information to estimate the forward and reverse delivery probabilities.

3) Aodv_packet.h: Here all kinds of packets used in AODV is defined. Since ETX is calculated by looking for the number of transmissions and retransmissions of the probe packets, we need to include an extra packet type. This packet type is probe packet. A new packet format named PROTOCOLETXTYPE_PROBE is defined by using a header macro for probe types. Another field named etx is defined and included while calculating the size of the structure defining the header of the request and reply type. Thus, a new structure to hold the probe packet information is defined as follows:

struct hdr_protocoletx_probe {



Packet Type

Source IP Address

Broadcast ID

Number of neighbours from which probes

have been received

Their addresses

Number of the probes received

Timestamp when it was sent

size= sizeof(hdr_protocoletx_probe);

Return size

}

This probe packet type structure defined must be included while calculating the header space reservation which affects the packet header class defined for AODV routing protocol as shown below:

static class AODVETXHeaderClass:

public PacketHeaderClass {

AODVETXHeaderClass ():

PacketHeaderClass "PacketHeaderAODVETX", size of (hdr_all_aodvetx)) {

bind_offset (&hdr_aodvetx:: offset_;

bind ();

}

As we know packets are used to exchange information between objects in the simulation, and our aim is to add our new struct hdr_protoname_pkt to them.

Doing so our control packets will be able to be sent and received by nodes in the simulation. And hence probe packets are an extension to the already available types of control packets in AODV. The structure defined earlier defining the probe packet is now added to struct hdr_protoname_pkt which is used to bind our packet header to Tcl interface.

An extra probe packet is being used to determine the link quality and thus this packet type should be added to the function named format_aodv () defined within the file “ ns-allinone-2.34\ns-2.34\trace\cmu-trace\.cc”.

IV. RESULT ANALYSIS

In this section, we present simulation results comparing the performance of AODV-ETX with AODV under different performance parameters.

B. Simulation setup

1) Scenario: NS 2.34 simulator is used for the simulation study. The model parameters that have been used in the following experiments are summarized in Table I.

TABLE I FONT SIZES FOR PAPERS

Sl. No

Parameter

Values

1. Simulator NS-2.34

2. Routing protocol

AODV, AODV-ETX

3. Channel wireless

4. Simulation time 45

seconds

5. Number of nodes

150

6. Bandwidth 1Mbps

7. Traffic Type FTP

8. Packet Size 512 bytes

2) Evaluation: The following performance parameters are used to evaluate the protocol:

Average End to End delay: This metric represents average end- to-end delay and indicates how long it took for a packet to travel from the source to the application layer of the destination. It includes all possible delay caused by buffering during route discovery latency, transmission delays at the MAC, queuing at interface queue, and propagation and transfer time. It is calculated using the formula:

received - time sentAED

time

Total data packets received

Packet delivery ratio: This parameter is defined as the

ratio of total number of packets successfully received by the destination nodes to the number of packets sent by the source nodes throughout the simulation which is given as:



PDR

Number of received packets

Number of sent packets

Normalized Routing Load: This parameter is defined as the ratio of total no of routing packets received to the total number of data packets received which is given as:

Re NRL

Re

ceived routing packets

ceived data packets

C. Results

In this section we present the performance results in the form of numerically calculated values of Average end to end delay, packet delivery ratio, normalized routing overhead for both AODV and AODV-ETX. We also compare the performance of AODV-ETX versus AODV in the form of x-graph obtained after simulation which shall prove that performance of AODV-ETX is better than AODV alone.

1) Results Of Numerical Calculation

The numerical results obtained after the execution of AODV and AODV-ETX are given in the Table II:

TABLE III FONT SIZES FOR PAPERS

Sl. No

Performance Parameter

AODV AODV-ETX

1. Average End-End Delay

654.553ms

557.266ms

2. Packet Delivery Ratio

43.4783 43.8483

3. Normalized Routing Load

51.766 55.390

2) Results in the form of X-graphs

Average End to End delay: We assume, in AODV only singular path exists between

a source and destination node and hence during a link break the packet would not reach the destination due to unavailability of another path from source to destination. This packet increases the traffic which leads to the congestion in the network. In AODV-ETX when a link breaks the ETX value changes to INFINITY (some large value) which indicates the absence of the link. In such a case another path with the lowest ETX value is considered by the node to forward the packet. Thus an alternate path exists from source to destination during link failure.

Fig 1. Comparison on the basis of End-End delay

Whenever a link is busy in case of AODV the sending

node waits until the link gets free whereas in AODV-ETX another path is chosen to forward the packet instead of waiting for the link to get free. This extra time spent by the sender waiting for a free link increases the total delay.

Thus, AODV has an average delay of 654.553 ms to AODV-ETX’s average delay of 557.266 ms which reveals that note that AODV-ETX has a better average delay than AODV. There is 17.46% improvement in average delay from AODV to AODV-ETX. Packet delivery ratio:

Fig 2. Comparison on the basis of Packet Delivery Ratio



The X-graph of packet delivery ratio versus the simulation time indicates that for most of the time the packet delivery ratio of AODV-ETX is higher than that of AODV and thus the average value of packet delivery ratio for the entire simulation time of AODV-ETX is higher than AODV. Thus, AODV has a packet delivery ratio of 43.4783 to AODV-ETX’s packet delivery ratio of 43.8483. Thus there is 0.37 increase in packet delivery ratio from AODV to AODV-ETX. Normalized routing overhead:

Fig 3. Comparison on the basis of Packet Delivery

Ratio The normalized routing load is number of routing

packets sent per number of data packet received. From Fig 3 it can be observed that AODV-ETX has more routing overhead compared to AODV. In AODV-ETX extra probe packets are used to determine the link quality apart from RREQ, RREP packets as used in AODV. And thus the routing overhead for AODV-ETX is 7% higher than AODV.

V. CONCLUSION AND FUTURE SCOPE

This paper evaluates the performance of AODV and AODV-ETX using NS-2. Comparison was based on the packet delivery ratio, end-to-end delay and normalized routing load. We concluded that in the network with the simulation time of 45 seconds, AODV-ETX gives better performance as compared to AODV in terms of packet delivery fraction and end-end delay whereas AODV gives better performance in terms of routing overhead.

As future work, we intend to develop a module with ETX as a metric for routing in all the reactive protocols like

DSR, TORA and release a patch that can be easily plugged-in to any of the reactive routing protocols.

ACKNOWLEDGMENT

The scene of contentment and elation that accompanies the successful completion of our task would be incomplete without mentioning the names of the people who have helped in accomplishment of this work, whose constant guidance, support and encouragement resulted in realization.

We would like to express our sincere thanks to Principal, B. V. Bhoomaraddi College of Engineering and Technology, Dr. Ashok Shettar and Head of the Department, Computer science, Prof.K.R.Biradar, for providing all necessary support.

We thankfully acknowledge the help we received from Prof. Jayalaxmi G.N. for guiding us in completing the work successfully in accordance with the University requirements’.

REFERENCES

[1] https://code.google.com/p/wisnes/source/browse/trunk/aodv-etx-metric

[2] Lijun Chen,Steven H. Low and John C. Doyle,”Cross-layer design in multihop wireless networks”,2010.

[3] Douglas S.J De Couto,Daniel Aguayo, John Bicket and Robert Morris ,” A High-Throughput Path Metric for Multi-Hop Wireless Routing”2010.

[4] A. K. Dwivedi, Sunita Kushwaha and O. P. Vyas, “Performance of Routing Protocols for Mobile Adhoc and Wireless Sensor Networks: A Comparative study”, volume 2, International Journal of Recent Trends in Engineering, November 2010.

[5] Nadeem javaid, Akmal Javaid and Imran Ali Khan and Karim Djouani, "Performance study of ETX based wireless routing metrics".

[6] C. Perkins and E. Belding-Royer and S. Das, "Ad hoc On-demand Distance Vector (AODV) Routing", IETF RFC 3561,july,2003.

[7] Francisco J. Ros and Pedro M. Ruiz, "Implementing a new MANET unicast routing protocol in NS-2",December,2004.

[8] Douglas C. Schmidt, "Software Design principles and guidelines",2003.

[9] Sumathy S, Dr.R Saravanan, ETX metric for extremely opportunistic routing to improve the performance of the hybrid wireless network",volume 2, International Journal of Ad hoc Sensor and Ubiquitous Computing,December 2011.

[10] Sumathy S and Dr. R Saravanan, "ETX metric for extremely opportunistic routing to improve the performance of hybrid wireless networks",2011.

https://code.google.com/p/wisnes/source/browse/trunk/aodv-etx-metric

https://code.google.com/p/wisnes/source/browse/trunk/aodv-etx-metric



An assessment of probabilistic Reactive Routing Protocol For MANET’s

Aditya Pare#1 Prof. Gaurav shrivastav#*2 M.tech Research scholar

#*2Assistant Professor Dept of computer science

RKDF IST,Bhopal RKDF IST,Bhopal Abstract— MANET is an temporary decentralized infrastructure less network where each node can behave like receiver and transmitter and having a permission to move any were across the network without loss the connectivity with rest of network. Message sharing is an important task of MANET, MANET have verity of routing protocol to serve massage sharing .Performance of these routing protocol depend upon collision rate ,reach ability, rebroadcasting and average latency. Message sharing scheme in MANET is categorized namely into deterministic and probabilistic schemes. This paper give an bird eye over MANET and its routing algorithms mainly probabilistic scheme for routing and also include recent research towards better performance in term of lower collision rate, battery consumption, rebroadcasting rate and higher degree of reach ability ,average latency

.

Keywords: MANET, Probabilistic Algorithm,

Bayesian Approach

I. INTRODUCTION

With incredible expansion of uses of personal computers and mobile computers lead to need a wireless network for sharing the information among the different computers. Wireless networks come in picture in mid of 1970s and their interest has been growing gradually. But during the last two decade, because of internet (also known as global information sharing system) importance of Wireless network has been exploded [3]. But at that time information sharing between mobile node in limited resource and without uses of any centralized administration is difficult.But now this day a temporary infrastructure less wireless network having no central access point or any centralized administration is in existence and known as Mobile Ad-Hoc Network (MANET) [1]. Mobile ad-hoc networks encompass number of quality, use dynamic network topology, having limited bandwidth and consume less battery power. Mobile ad hoc network is significant for military operation to provide communication

between squads, emergency case in out-of-the-way places, medical control etc. Whereas higher degree of node mobility lead to changes network topology because of that routing is a challenging task in ad-hoc network ever since it’s came into existence [2].

This paper gives a descriptive overview regarding ad-hoc network and their routing protocol especially reactive routing protocol along with probabilistic routing algorithm, Bayesian probabilistic routing algorithm and value of affinity index, mutual affinity index and other parameter for probabilistic routing algorithms.

The presented paper concludes in total seven sections including this one. The second section gives an idea of mobile ad-hoc network, third section describe different routing protocol and their hierarchy. The fourth section illustrates probabilistic routing approach over MANET. Fifth section throws some light on previous work of MANET. Finally the paper concludes in six section and reference in seven

th section.

II. MOBILE AD-HOC NETWORK

Mobile ad-hoc network is temporary infra structure less computer network where node of network can be move any were within the network without any centralized authority. MANET initially introduce and used by military in the field of war and at the time of natural digesters in sort duration of time with limited resource in order to establish communication channel. Each node in MANET works as independent router having both transmitter and receiver and communicate directly with other node that’s comes under its radio range (radio range is generally transmitting and receiving range of any node) as show in figure 1 number with dark circle is an independent node whereas dashes circle represent radio range of respective node [1,4]. MANET is also known as Cooperative ad-hoc networks Communication over the mobile ad-hoc network is performed by stations cooperation with each other, i.e., if any node want to communicate



with other node that’s not comes under its radio range then it is the responsibility of intermediate node also know as relay node to maintain communication between source and destination. MANET is very advantageous to use provide services and sharing the information regardless of geographical position, time and resources. Because of above special feature mobile ad-hoc network windy used in Military operation , rescue operation by disaster management team ,police

exercises in remote aria ,Sensor networks, VNET, PAN for communication of several portable devices etc [5]. Along with above encouraging points there are some limitations in MANET. MANET has higher degree of security threads, lack of authorization facilities and Volatile network topology makes its very hard to identify misbehave nodes due to volatile network topology [4,5].

A

B

C

Radio Range

of Node C

Radio Range

of Node A Radio Range of

Node B

Figure 1 Scenario of MANET

III. PROTOCOLS USED IN MANET

Routing protocol used in MANET for establishment of communication over network between mobile nodes is namely divided into three types proactive, reactive and hybrid. Figure 2 shows the hierarchy of the protocols.

i. Proactive protocol: - Proactive MANET routing protocol (PMPs) is a table driven routing protocol, need to continuously update network topology information and guarantee that it is presented to all nodes. PMPs lead to reduce time delay of packet

over the network but simultaneously increase data overhead by continuously updating routing information. DSDV, WRP, CGSR are the example of proactive protocols.

ii. Reactive MANET protocols:-Reactive

MANET protocols is an on demand routing protocol, need to path hunting only when there is need of the path. Lower protocol data over head is advantage with Reactive protocol but having longer packet delays. There is number of reactive protocol like AODV, DSR and TORA.



iii. Hybrid MANET routing protocols:-The Hybrid MANET routing protocols is an advantageous amalgamation of both proactive and reactive MANET protocols with better resultant protocol overhead and packet delay than any of individual protocols[6]. It is also capable of regulating packet dynamically on the basis of different network conditions. ZRP protocol is an example of hybrid model.

This paper gives a main concentration over probabilistic approach of routing and present different flavor of probabilistic reactive routing

protocol as suggest in recent research in related work section of this paper. Some of basic reactive routing protocols are describe below. DSR:- DSR routing protocol is used to suggest Multiple routes and for Promiscuous overhearing but its suffer from scalability problem and large delay. AODV:-AODV is highly applicable for dynamic topology but it also suffer form scalability and larger delay problem along with that AODV having higher degree of protocol overhead.

Figure 2 Hierarchy of MANET Routing Protocol



In recent research AODV is might to be updated and gives AODV-BR, AOMDV[18], AODV-ABR[19].Where AODV-BR having higher throughput than AODV but even efficient for frequently changing network. AOMDV lead to minimized routing overhead and coordination overhead by intermediate node but performance of AOMDV going to degrade in moderate and sparse network. AODV-ABR is more appreciable in higher dynamic network with lower control overhead but having lower probability to find alternate route. TORA:- TORA provides the reliable supports for sensing link status towards neighbor node that’s comes under its radio range. TORA supports higher degree of security authentication and lower degree of control

overhead [17, 18]. It depends on synchronized clocks

among nodes in the ad hoc network & dependence over intermediate lower layers for certain functionality presumes with higher overhead[17].

IV. PROBABILISTIC ALGORITHM

In probabilistic routing algorithms for MANET calculation for route suggestion between any sources to destination end is depend upon probability of past lower rebroadcasting rate. Probabilistic approach tries to minimized rebroadcast. In a probabilistic scheme, nodes transmit a message with a pre determined probability p.

Figure 3:- Classification of Probabilistic routing

algorithms Recent research shows that rebroadcasting rate in probabilistic approach is significantly lower as compared to blind flooding in deterministic routing approach. Probabilistic schemes that’s had been proposed in past comes under three categories namely probability-based, counter-based and distance-based.

Each probability model is represented by the equation [5,6,7]:

Where Pn is the probability of successful transmission

via radio node (rn) from source node (s) that comes under the radio range of source node (s). The function f depends on the specific protocol being analyzed. Bayesian approach is one of most popular probabilistic method that’s works on the basis of historical record of successful transmission via any intermediate node. Figure 3 shows the basic functionality of the Bayesian Approach.

O

X

P

R

A

S

Historical data

Bayesian Approach

Figure 3 Bayesian Approach

Bayesian probabilistic approach depend upon singular affinity index (SAI) ie any node want to transmits any packet towards destination then source node (A) apply Bayesian probability over all of its radio node and find most probabilistic node on the basis of historical data and send packet via that selected node. As show in figure 3 solid arrow line show selected node for transmission. But degree of accuracy in case of singular affinity index is not up to mark; mostly during the initiation of network probability of rebroadcast is very high. Where some enhancement version of Bayesian approach used mutual affinity index to calculate probability of any successive node for packet forwarding which is depend upon belief function, procedure of calculation belief function is show in equation 1 [9,10].

∑ …1

⌈ ⌉

Probabilistic Routing

Algorithm

Probability based

Counter-based

Distance based



⌈

∑

⌉

Now since we are multiplying the probabilities of each and every attribute hence; even if one of the attributes has a zero probability; the whole index will become zero. Because of this; zero probability will be replaced with a very low probability (0.001).

V. PREVIOUS WORK

Many research works has been done in this area. Some of them are presented here. The author presents and shows obtained results in his research. This work is based on Bayesian approach, Queuing theory and reliability theory. Here the methods bound of application of Bayesian approach to some problems of queuing theory and reliability theory. This approach could be used, for instance, for calculating moment and quintile characteristics for performance and reliability characteristics of large groups of systems or devices [11]. Nadia Bali [12] proposed a hierarchical Markov model for the sources with a common hidden classification field which is modeled via a Potts–Markov field. Classical methods of dimensionality reduction in hyper spectral imaging use classification methods either to classify the spectra or to classify the images in classes where is, in general, much less than the number of spectra or the number of observed images. However, these methods neglect either the spatial organization of the spectra or the spectral property of the pixels along the spectral bands. The processes for decision making problems based on the use of the Dempster-Shafer (D-S) theory can be able in different ways according to the requirements of each single problem. In this input the authors present a decision making scheme based on Dempster-Shafer (D-S) theory. Jose M. Merigo [13] proposed the use of a hybrid averaging operator (2-THA) which uses the 2-tuple linguistic representation model. Due to use of 2-THA in D-S theory, obtained a new aggregation operator: the belief structure - 2-THA (BS-2-THA) operator and studied some of its main properties and then show the descriptive example of the new approach in a decision making problem. Nidhi S Kulkarni [14] study and analyses the on demand routing protocols in deep and gives an overview of the existing on demand routing protocols and a parametric comparison is made with the recently developed protocols, also covers some important conventional routing protocols and the recently proposed extensions of AODV. These protocols are the multipath extensions of Ad Hoc On Demand Distance Vector routing protocol (AODV) such as AODV with break avoidance (AODV-BR), Scalable Multipath on demand routing (SMORT). One of the typical routing methods in mobile ad-hoc networks use on demand distance vector, or Ad-hoc On-demand Distance Vector (AODV). The key concern in this protocol is the cost of route establishment. Rusheel Jain [15] suggested an efficient routing algorithm for mobile ad-hoc networks with a route establishment technique using Bayesian approach. They consider both

time and space information to compute the route from source to destination. The results show that there is major improvement in delivery ratio, control packets overhead w.r.t. mobility and control packet overhead w.r.t. network size .

VI. CONCLUSION

This paper gives a bird eye over routing algorithm in MANET. Routing algorithm generally classify into two subtype deterministic and probabilistic routing algorithms. Deterministic routing algorithm suffer from blind flooding whereas probabilistic routing algorithm overcome the problem of blind flooding and maintain historical record of time and space for all node to maintaining network traffic in order to reduce probability of collision, rebroadcast at the expense of reach ability and enhanced scheme has higher throughput, lower latency and better reach ability.

REFERENCES [1]. B. Williams and T. Camp, Comparison of broadcast in

techniques for mobile ad hoc networks. In Proc. ACM Symposium on Mobile Ad Hoc Networking & Computing (MOBIHOC 2002), pp. 194–205, 2002.

[2]. S.-Y. Ni, Y.-C. Tseng, Y.-S. Chen, and J.-P. Sheu, “The broadcast storm problem in a mobile ad hoc network”, Proc.Mobicom_99, 1999.

[3]. Y. Sasson, D. Cavin, and A. Schiper, Probabilistic Broadcast for flooding in wireless mobile ad hoc networks, In Proc. IEEE Wireless Communications & Networking Conference (WCNC 2003), pp. 1124–1130, March 2003.

[4]. J. Wu and W. Lou, "Forward-node-set-based broadcast in clustered mobile ad hoc networks," Wireless Communication and Mobile Computing, vol. 3, pp. 155 – 173, 2003.

[5]. A. Keshavarz-Haddad, V. Ribeiro, and R. Riedi, "Color- Based Broadcasting for Ad Hoc Networks," in Proceeding of the 4th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Network (WIOPT' 06). Boston, MA, 2006, pp. 1 - 10.

[6]. J. Cartigny and D. Simplot, "Border node retransmission based probabilistic broadcast protocols in ad hoc networks," Telecommunication Systems,, vol. 22, pp. 189-204, 2003.

[7]. C. E. Perkins, and E. M. Royer, “Ad-hoc on-demand distance vector routing,” 2nd IEEE Workshop on Mobile Computing Systems and Applications, Monterey, California, USA: Feb 25 – 26, 1999: 90-100.

[8]. H D-Ferriere, M Grossglauser, and M Vetterli, “Age Matters: Efficient Route Discovery in Mobile Ad Hoc Networks Using Encounter Ages,” 4th ACM International Symposium on MANET and Computing, 2003

[9]. C. E. Perkins, E. M. Belding-Royer, and S. Das, “Ad hoc on-demand distance vector (AODV) Routing,” RFC 3561, July 2003,

[10]. David Johnson, David Maltz and Yih-Chun Hu, “The Dynamic Source Routing Protocol for Mobile Ad Hoc Networks,” Internet Draft, draft-ietf-manet-dsr10.txt,July 2004



[11]. Alexey Kudryavtsev and Sergey Shorgin, “On the Bayesian Approach to the Analysis of Queueing Systems and Reliability Characteristics”, IEEE 2010, pp 1042-1045.

[12]. Nadia Bali and Ali Mohammad-Djafari, “Bayesian Approach With Hidden Markov Modeling and Mean Field Approximation for Hyperspectral Data Analysis”, IEEE 2008, pp 217-225.

[13]. Jose M. Merigo, Montserrat Casanovas and Luis Martinez, “A Decision Making Model Based on Dempster-Shafer Theory and Linguistic Hybrid Aggregation Operators”, IEEE 2008, pp 180-185.

[14]. Nidhi S Kulkarni, Balasubramanian Ramant, and Indra Gupta, “On Demand Routing Protocols for Mobile Ad Hoc Networks: A Review”, IEEE 2009, pp 586-591.

[15]. Rusheel Jain, Murali Parameswaran and Chittaranjan Hota, “An Efficient On-Demand Routing Protocol for MANETs using Bayesian Approach”, IEEE 2011

[16]. Mehran Abolhasan, Tadeusz Wysocki, Eryk Dutkiewicz,“A review of routing protocols for mobile ad hoc networks” in Elsevier,2004

[17]. TamilarasanSanthamurthy,“A Quantitative Study and Comparison of AODV, OLSR and TORA Routing Protocols in MANET” in International Journal of Computer Science Issues, Vol. 9, Issue 1, No 1, January 2012

[18]. Sunil Taneja and Ashwani Kush“A Survey of Routing Protocols in Mobile Ad Hoc Networks” in International Journal of Innovation, Management and Technology, Vol. 1, No. 3, August 2010 ,ISSN: 2010-0248

[19]. Pankaj Palta and Sonia Goyal,“Comparison of OLSR and TORA Routing Protocols Using OPNET Modeler” in International Journal of Engineering Research & Technology (IJERT),Vol. 1 Issue 5, July – 2012,ISSN: 2278-01

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