performance evaluation of routing protocols in dtn...

© 2016, IJARCSSE All Rights Reserved Page | 179

Volume 6, Issue 9, September 2016 ISSN: 2277 128X

International Journal of Advanced Research in Computer Science and Software Engineering Research Paper Available online at: www.ijarcsse.com

Performance Evaluation of Routing Protocols in DTN,

Heterogeneous and Homogeneous Sensor Networks Srigitha. S. Nath

Saveetha Engineering College, Chennai,

Tamilnadu, India

Dr. K. Helenprabha

R.M.D Engineering College, Chennai,

Tamilnadu, India

Abstract— In this paper, we propose performance evaluation of routing protocols in DTN, heterogeneous and

homogeneous sensor networks. In these networks, sensor nodes may not use the same path for transmitting message

between each other. To overcome this drawback, we proposed a layer based protocol (LEERP) which handles

asymmetric link to find a suitable reverse path for sending acknowledgement packets. LEERP selects the relay nodes

based on layer level values and residue energy of the nodes. We also propose another algorithm ARS which is efficient

in controlling congestion using Rigid and Gentle plan, where energy is also saved. ERPPro is the upgraded version in

the series and it finds the energy efficient path to forward packets. It applies exponential upper bound value for

estimating average mean and variance of residue energy to select a valid reverse route. Simulation results comparing

proposed and existing protocols displayed that LEERP, ARS, and ERPPro delivers assured rate, reduced overhead,

less delay and saves more energy.

Keywords— Performance Guarantee; asymmetric Link; Energy efficient; WHSN, DTN.

I. INTRODUCTION

Cyber-Physical Systems (CPS) has a very important role in our day-to-day life which focuses on wireless sensor

networks (WSN). Some of its other applications are smart homes, security, habitat monitoring, target tracking.

A variety of asymmetric communication such as asymmetric sensor networks is applied when there is a issue due to

the problem in WSN where the same path cannot be used to communicate between two end nodes. There are so many

issues in WSN which has led to the significance of ASNs. Some of them are heterogeneous networks, packet drops or

loss, congestion (ARS), energy reduction in a node (LEERP, ERPPro).

In the survey we found that the routing algorithms already available are designed for symmetric. These routing

protocols have not taken asymmetric links into account for finding suitable neighbour nodes, exact path for the passing of

packets with reliability.

The most important parameters such as reliable packet delivery, minimum or reduced overhead, conservation of

power, latency, and throughput are evaluated here using proposed routing algorithms with respect to asymmetric links.

All WSN applications are effective based on network lifetime. In this paper, we will study about all proposed routing

protocol performance to improve energy efficiency and packet delivery ratio.

Improving network lifetime and achieving desired delivery rate in WHSN are huge challenges. The neighbour

relationships of nodes have to be detected and checked for the four types such as bidirectional neighbour, uplink

neighbour, downlink neighbour, non-neighbour. Next detecting the asymmetric links and then monitoring and managing

these links have to be done. Finally, finding energy efficient reverse paths for the asymmetric links are computed.

Meanwhile, the efficient forward and reverse path has to be selected for routing the packets.

Reactive protocols such as AODV and DSR found paths using Route Request Packet and Route Reply Packet. DSR

supported asymmetric links but whereas AODV eliminated these links in the path. ProHet which is a probabilistic based

routing protocol for large and dynamic networks. It has more overhead in each path when trying to find new paths.

These challenges inspired us to proposed new routing protocols to improve new routing protocols to improve

network lifetime and assured delivery rate by avoiding congestion in WHSN. We proposed an algorithm to control

congestion using an alternate path for various types of traffic in the network. Link capacity and packet service ratio are

evaluated and used to control congestion. Here both node level as well as channel level congestion are addressed. We

propose LEERP and ERPPro utilizing asymmetric link to ensure less consumption of energy and improve delivery rate.

Here we propose a reverse path algorithm to find the asymmetric link and also provide the level values and energy

threshold value to identify the forwarding nodes in the neighbour list of each node. This protocol is a source based

routing protocol and improves network performance and management. In this paper, we will study efficient routing

protocols LEERP, ERPPro and ARS for less dynamic networks.

In the past, traditional routing protocols prefer only symmetric link due to the difficulties in finding the reverse path.

Contradictory to the above kind of concept, the BRA [2] protocol designed a reverse path for asymmetric link. The

unidirectional link routing (UDLR) proposed a algorithm which utilizes the concept of tunneling and encapsulation to

forward multi hop acknowledgements at the link layer. Meanwhile, in some papers, they use unidirectional links

http://www.ijarcsse.com/

Nath et al., International Journal of Advanced Research in Computer Science and Software Engineering 6(9),

September - 2016, pp. 179-185


comprising of control packets passing through a tunnel using multi-hop reverse routes to the upstream nodes. In our

paper, we described a reverse path algorithms (ERPPro, LEERP) for asymmetric links, for easier maintenance and

performance. The remainder of this paper is organized as follows. Section 2 presents Preliminary Phase. Section 3

proposes LEERP [10], ERPPro [8] and ARS [9]. Section 4 explains result and discussion. Conclusion is in section 5.

II. PRELIMINARY

We consider a WHSN with large number of sensor nodes and a Base Station (BS). Let us assume, Due to different

radio capabilities, the nodes have different transmission ranges which result in asymmetric links in the networks. The

nodes relationship is shown in fig 1.

Neighbor Discovery

Let us assume that each node in the network aware of its own location. To determine its neighbour relationship, each

node broadcast ―Hello‖ message in the network which contains its available energy (NRE), Node id (N_id), and

geographical location (Nloc). When a node receives ―Hello‖ message, it adds the information in its NT (Neighbour Table)

and assigns that node as one its upstream nodes. After the ―Hello‖ packet broadcasting, now each node broadcast its NT

in the network. Each node checks its NT list with its neighbour‘s NT. If the node find its id in the other‘s NT, then it adds

that nodes as Bidirectional node. Otherwise, the node confirms the neighbour node as upstream node [8],[10].

Fig 1. The neighbour relationship between two nodes. a) A and B are bidirectional link node. b) B is a downstream node

for A and A is an upstream node for A.

Algorithm 1: Identifying Nearby node Relationship

/* Identify the nearby and link*/

Node X (NX) and Node Y (NY) broadcasts ―HELLO‖ message;

If ((NY receives ―HELLO‖ message of NX) && (NX receives "ACK_HELLO" reply of NY) && (NX receives

―HELLO‖

message of NY) && (NY receives "ACK_HELLO" reply of NX)) 𝐭hen

/*Get the Node id (Nid-Y) that reply and Store in In-out Nearby List of Node X*/

Bidirectional_Neighlist_X = Nid_Y;

/*Get the Node id (Nid-X) that reply and Store in In-out Nearby List of Node Y*/

Bidirectional_Y = Nid_X;

Symmetric_linkXY = true; // Link connecting NX and NY is symmetric

else if (NX gets ―HELLO‖ message of NY) && (NX fails to receive "ACK_HELLO" response of NY) 𝐭hen

In_Neighlist_X = Nid_Y; // NY is its In-nearby of NX

Asymmetric_linkXY = true;

Uplink_node = NY;

Downlink_node = NX;

else (NY receives ―HELLO‖ message of NX) && (NY fails to receive "ACK_HELLO" response of NX) 𝐭hen

In_Neighlist_Y = Nid_X; // NX is its In-neighbour of NY

Asymmetric_linkXY = true;

Uplink_node = NX;

Downlink_node = NY;

else

broken_linkXY = true; // There is no link between NX and NY or the link is broken link

end

Reverse Path:

Our idea is to set up reverse path for unidirectional link i.e. reverse path from a node to its upstream node. Nodes

with upstream nodes broadcast ―Find‖ message that contain Find(SN_id,DN_id,Hopcount,NRE) provided node_id and

residual energy of relay nodes are alone appended during reverse path establishment. When the hop limit is set as 3 hops,

we can obtain 90-97 % of connectivity in the network. Thus, we considered the maximum reverse path routing length is

three.


September - 2016, pp. 179-185


Fig 2. Energy efficient Reverse Path identification for Asymmetric Links.

From the fig 2, we consider five sensor nodes A, B, C, D and E. Initially, node A broadcast ―Hello‖ message in the

network. The node B and C reply with ―ACK_Hello‖ packet to node A. Thus, Node A adds B and C as bidirectional

nodes in its NT. After sometimes, node B, C and E sends ―Hello‖ packets to node A. Now, node A aware of the link is

unidirectional from node E, because it couldn‘t receive ―ACK_Hello‖ of its own ―Hello‖ packet from node E. Therefore,

Node A tries to find reverse path for node E. Now, node A broadcast “Find (A,E,3)” message, where A- Source Id, E-

Destination Id and 3 is maximum hop limit. Except the source node, the relay node adds their residual energy in the

―Find‖ message. Node B and C receives “Find (A,E,3)” message from A. Since both nodes are not intended destination

node, they append their own id, residual energy, reduce the hop limit by one and further broadcast the ―Find‖ message.

This process continues until ―Find‖ message reaches Node E within three hops. Now, node E has two reverse paths for

node A. It sends both reverse paths to node A which is shown in figure.

III. PROPOSED PROTOCOLS

Next, we present three routing protocols LEERP, ERPPro, and ARS for WHSN.

3.1 LEERP:

LEERP [10] has two phases. First phase is to set the level value for each node in the network and Second phase is

routing and acknowledgement.

3.1.1 Assigning Level Value:

Initially, the BS (Base Station) broadcasts ‗Ping‖ message with level value set as ‗0‘. The node which receives ‗ping‘

message from BS adds one to its level value and rebroadcast the message. Level values are assigned to each sensor node

based on their distance (No. of Hops) from the BS. This process continues until all the nodes set their level value. The

network topology is shown in fig. The layer number is dynamically updated during the whole lifetime of the node due to

lossy links.

Fig 3. Level value of each node


September - 2016, pp. 179-185


3.1.2 Routing:

When a node needs to send data to BS, it searches in its routing table whether it has direct link to BS. If so, it sends

data directly to BS. Otherwise, the source node search in its routing table and find the neighbor nodes whose level value

is lower and their available energy is equal to or greater than the ―Eth‖. The total energy consumption to relay packet

from higher level node to lower level node is ―Etotal = 3n Eele+n εfsd2+n εfsd

2‖.

Algorithm 1: Relaying Message

a) Node_ X searches its NL (Neighbour List) to find lower level node. (LY>LX)

b) If X <--> Y (bidirectional) or X Y (Downstream node) && REY ≥ Eth.

c) then, Node_X selects Node_Y

d) else Node_X selects the node in the same level

3.1.3 Acknowledgement:

Once the BS receives forwarded packets from source node, it replies with ACK message. When a relay node

receives ACK packet, it checks whether the connection to the previous node is bidirectional or unidirectional. If it is

bidirectional, it can directly send the ACK. Otherwise, the relay node uses reverse path to transmit the ACK message.

3.2 ERPPro:

ERPPro is an energy efficient reverse path routing protocol which increases the performance of the network. It

calculates the average mean and variance of residual energy alongside with link quality of relay nodes by applying

exponential upper bound. ERPPro has two processes, i) Forward path selection, ii) Reverse path selection.

3.2.1 Forward Path Selection:

It selects forwarding mechanism rather than flooding to avoid overhead in the network. It uses probabilistic

approaches to selects energy efficient relay nodes. Thus, the neighbour nodes with minimum usability, maximum energy,

and lesser hop count have the highest probability to be selected as next relay node. The residual energy of nodes

frequently updated during ―Hello‖ message broadcasting. Initially, threshold value is set using average energy of nodes.

Let the WSN consists of ‗N‘ nodes. The average energy (Eavg) consumption of the network is,

Eavg = j (1)

Where Ei is the difference between the initial (Einitial) and final energy (Efinal)

Ej = Einitial - Efinal (2)

Thus the energy consumed by each node in WSN is the sum of energy consumed for transmission (ETxion) and

reception (ERxion). ie.,

Ej = Einitial – (ETxion - ERxion) (3)

Therefore, for a source node (S) the average energy of neighbouring nodes (M) can be calculated as follows,

Eavg = j (4)

Fig 4. Using ERPPro, forward path selection

3.2.2 Reverse Path Selection Process The BS ready to receive transmitted message from source up to three routing path i.e. remaining duplicated

messages will be dropped. BS assigns weight factors for received packets. The packet which has arrived earlier is


September - 2016, pp. 179-185


allotted with higher weight factor because the route possibly will less congestion path or shortest path. Here, the most

important task of the BS is to find the best reverse path to the source which should be efficient incase of delivery ratio,

less congestion, low delay and error. It uses Chernoff bound (CB) to select best reverse path. Once the numerous packets

from various paths reach BS, it stores the received information (sources of the received packets, relay nodes, no of hops,

and residual energy) in its NT table. Using the recorded information, the BS analyze the unequal proportionate (mean and

variance) for multiple paths to select the legitimate path.

3.3 ARS:

It is a congestion control based routing protocol. It controls the congestion based on two methods such as 1) Gentle

Plan and 2) Rigid Plan. It maintains priority queue for different types of traffics (Continuous and Event-driven) in the

network.

In Gentle plan, the possibility of congestion is detected earlier by calculating Packet Service Ratio.

PSR = TrMAX /

n

i

Ri0

(5)

If the incoming packets of a node is greater than its outgoing rate, then the node send a notification to the source

node to find an alternative path. Then, the source node tries to change its routing path, this just an optional one. If source

node couldn‘t find any alternative path, it can still able to transmit its packets using the same relay node. So, Rigid plan

advices the source node to choose an alternative path.

In Rigid plan, the node is asked to change its routing path, whenever it receives packet with flag value set as zero.

The flag is set to zero for three reasons. 1) Buffer occupancy, 2) Residue Energy, 3) Unavailability of lower level node.

Whenever the buffer capacity of a sensor node reaches the threshold value, the node set its flag to zero and broadcast that

message. Similarly, if the node couldn‘t find any relay the packet further, it sets flag to zero. The node considers residue

energy as one of its parameters to detect congestion.

After ignoring the congested node, the selection of new node will be selected based on level values (no. of. Hop

count from BS). The node which has lower level value or same level (level value of congested node) is chosen for

alternative path selection.

IV. RESULTS AND DISCUSSIONS

In our experiments, the nodes are deployed in 1000m x 1000m area. The transmission range for each node varies

from 20m to 60m range. Whenever the variance in transmission range increases, the asymmetric link in the network also

gets increased. During the simulation, nodes are selected randomly and send their message to BS. The Network

Simulator-2 (NS-2) with Mannasim is used in our simulation.

Whenever the network density increases, the connectivity between the nodes also increases, thereby increasing the

chances for a message to reach the BS. Subsets of energy efficient nodes are only chosen as relay nodes by ERPPro

during forward path selection and one of these routes is opted for reverse path to send the ACK or data. By adopting this

technique energy is conserved and successful delivery rate is assured by reducing packet replication. While considering

the number of hops taken by a node to forward messages from source to sink, ERPPro has shown better performance

than LEERP and ProHet. On analyzing the various factors such as residual energy, number of hops and usability to select

the relay nodes altogether makes it unique in finalizing the energy efficient shortest path to reach BS. As a result ERPPro

attains the desired delivery rate before LEERP shown in fig 5 (a),(b),(c) .

Energy Consumption:

More energy is consumed by control packets as well as by repetition of packets. The delivery ratio was analyzed in

simulation, when nodes run out of energy. We assumed that each node has initial energy (E ini). For transmitting ‗n‘ bits

over a distance‗d‘, the energy for transmission and reception are evaluated as:

ETxion (t,d) = Eini x n + Eamp x n x d2

(6)

ERxion (t) = Eini x n (7)

Where, Eini = 50nJ/bit and Eamp=100 pJ/bit/m2. The energy consumption for a node to transmit a unit-sized packet,

the cost is one unit of energy whereas for reception it is zero cost of energy. ERPPro can able to provide better energy

efficient in three networks shown in fig 8 (a),(b),(c)

Delay:

In our ARS paper, the congestion avoidance concept is done using two schemes such as ‗Rigid plan‘ and ‗Gentle

plan‘. In Rigid plan, based on the flag status of three parameters such as Buffer Occupancy, Residue Energy and Lower

level node unavailability, a notice is sent to the source to select an alternative node for forwarding packets whereas in

Gentle plan, the node which is in the brim of congestion advices the source node to select another suitable path for

forwarding packets. The above mentioned two schemes help us in detecting congestion earlier and thereby avoiding

retransmission of packets. Therefore, this technique fully reduces delay. ERPPro and LEERP also reduce delay, because

it finds the reverse path for all asymmetric links in the network in the setup phase itself. But ProHet searches route in

each hop which result in delay, packet replication and overhead shown in fig 6 (a),(b),(c).


September - 2016, pp. 179-185


5 (a) 5 (b) 5 (c)

5(a) Delivery ratio in heterogeneous networks, 5(b) Delivery ratio in homogeneous networks, 5(c) Delivery ratio in DTN

Network

6 (a) 6 (b) 6 (c)

6(a) Delay in heterogeneous networks, 6(b) Delay ratio in homogeneous networks, 6(c) Delay ratio in DTN Network

Overhead:

In both LEERP and ARS paper, we proposed layer based routing which utilizes more number of control packets

during setup phase and this generated overhead in the initial stage. In addition, the congestion control scheme applied in

ARS, consumes slightly more control packets for congestion notification. But, this issue was addressed in ERPPro which

utilizes the asymmetric link for route discovery reducing overhead. In this approach, we evaluate the average of energy

of all the neighboring nodes and then choose an efficient path for forwarding packets in fig 7 (a), (b), (c).

We have simulated the performance of ERPPro, LEERP and ARS in Delay Tolerant Network by adopting mobility.

The bandwidth and capacity of each node in DTN is limited. We assumed that the buffer capacity of each node is

unlimited for its own sensed packets whereas it is limited for the received packets from neighbors.

In addition, if the lifetime (TTL) of a packet expires, the packet will be dropped. Here, we further assumed that the

mobility of nodes is not solely random but the nodes follow some predictable pattern. If a node visits a location

frequently, then the probability of that node to visit that location again is very high.

Both ERPPro and ARS can able to achieve the maximum delivery rate of SSAR which is a dedicated routing

protocol for delay tolerant network. SSAR selects the relay node based on three parameters such as buffer occupancy,

node‘s willingness and nodes with minimum usability. Since ERPPro and LEERP select the energy efficient node as their

relay node, it can able to achieve delivery rate assured by SSAR.

7 (a) 7 (b) 7 (c)

7(a) Overhead in heterogeneous networks, 7(b) Overhead in homogeneous networks, 7(c) Overhead in DTN Network


September - 2016, pp. 179-185


8 (a) 8 (b) 8 (c)

8(a) Energy efficient heterogeneous networks, 8(b) Energy efficient in homogeneous networks, 8(c) Energy efficient in

DTN Network

V. CONCLUSION

In this paper, we designed three performance guaranteed protocols whose performance is compared in three different

types of networks. In heterogeneous network, we used reverse path algorithm to solve the problem of asymmetric.

LEERP and ERPPro can attain assured delivery rate, low energy consumption compared to ProHet and SSAR. Then, we

presented ARS which is a congestion control routing protocol whose aim is to achieve low delay by avoiding

retransmission. SSAR is a dedicated DTN protocol. In our protocols by adopting mobility and buffer capacity, we

compared the performance with SSAR. LEERP, ERPPro and ARS can able to achieve nearer assured delivery rate in

DTN too. In this paper, we focused on developing performance guaranteed routing protocols for homogeneous,

heterogeneous and DTN networks.

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