erfla camera ready final

ERFLA: Energy Efficient Combined Routing, Fusion,

Localization Algorithm in Cognitive WSN

G.Lakshmi Phani#1

, K.Venkat Sayeesh#2

, K.Vinod Kumar#3

, G.Rama Murthy*4

Communication Research Centre *International Institute of Information Technology, Hyderabad, India

#National Institute of Technology, Warangal, India.

1phani.l.gadde@gmail.com 2sayeesh.nitw@gmail.com

3vinodreddy.nitw@gmail.com

4rammurthy@iiit.ac.in

Abstract— Recent advancements in wireless communications

enabled the development of small and cheap nodes capable of

sensing, communication and computation. These nodes in a

network co-ordinate to perform distributed sensing of

environmental phenomenon in various fields such as health,

military, home. Research on energy sensitive routing in static

WSN has led to the development of many routing protocols

that ensure max life time of network. In this paper we explore

ERFLA which will effectively use the limited resources of a

sensor node to improve the network lifetime. We explore and

evaluate this algorithm on a simple WSN analytically and

experimentally. Our evaluation indicates that our algorithm

has shown 30%-40% improvement in the network lifetime

over comparable protocols like leveling, PASCAL [4].We also

present a theoretical model of cognitive sensor network which

uses few specialized nodes which have capabilities of spectrum

sensing.

Keywords—Wireless Sensor Networks (WSN), Cognitive Radio

(CR), PASCAL, Levelling, Clustering, Flooding, Gossiping,

sectroid, spectrum sensing, Dynamic Spectrum Access (DSA).

I. INTRODUCTION

Recent technological advancements have made the

development of small, low-power, low-cost, multifunctional,

distributed devices, which are capable of wireless

communication, a reality. Such nodes which have the ability

to local processing are called sensor nodes (motes).Limited

amount of processing is only possible in a sensor node. Wireless Sensor networks are the key to gathering the

information needed by industrial, smart environments,

weather in buildings, utilities, home, automation,

transportation systems, shipboard or elsewhere. Recent

guerilla warfare counter measures need a distributed network

of sensors that can be deployed using, e.g. an aircraft. In such

applications cabling or, running wires is generally impractical.

A sensor network is required which is fast to maintain and

easy to install.

Wireless sensor networks satisfy these requirements.

Desirable functions for sensor nodes include: ease of

installation, self-identification, self-diagnosis, reliability, time

awareness for coordination with other nodes, some software

functions and DSP, and standard control protocols and

network interfaces.

As per the statistics we see that the spectral utilization is varying from 15% to 85%, indicating that the spectrum is

underutilized. So, the cognitive radio techniques provide

capability to use or share spectrum in opportunistic manner.

Dynamic Spectrum Access techniques allow the cognitive

radio to operate in the best available channel.

In this paper an energy efficient method for routing the data

in the network is proposed. We present a network in which

clustering, leveling and sectoring are done along with sleep

and wake modes for a node. First, the clustering of nodes is

completed, after which the nodes are leveled into different

levels. Next the whole sensor network is divided into equiangular sectors and each node is assigned its sector id and

level id. Using our proposed algorithm the nodes will switch

their modes from awake to sleep and viceversa.

Wireless systems today are characterized by wasteful static

spectrum allocations, fixed radio functions, and limited

network coordination. Some systems like WSN in unlicensed

frequency bands have achieved great spectrum efficiency, but

are faced with increasing interference that limits network

capacity and scalability. Cognitive radio systems offer the

opportunity to use dynamic spectrum management techniques

to help prevent interference, adapt to immediate local

spectrum availability by creating time and location dependent in “virtual unlicensed bands”, i.e. bands that are shared with

primary users.

In the rest of the paper we see the related work in 2nd

section, Theoretical model of CR based WSN in 3rd section,

assumptions in the 4th section, proposed algorithm in 5th

section, simulation results in 6th section and finally we

conclude the paper by telling how it is better than the already

existing algorithms

II. RELATED WORK

Flooding [1] is an algorithm that relays message from the

source node to all other nodes in the network. Network

flooding is the common and the most important algorithm that

it is used in almost every higher routing protocol. The main

drawback of flooding is redundancy of messages, complexity

and it is not energy aware. Gossiping [1] was implemented to

overcome the drawbacks of flooding. In gossiping node

selects one of its neighbor nodes and sends the data to that

particular node and this process continues until the message

reaches the destination node. Here the redundancy and

complexity decreases. Here the major disadvantage is that the

time taken for the message to reach the destination may be

large or the message may not reach the destination. LEACH [1] is a popular hierarchical routing algorithm for the sensor

networks. The sensor network field is divided into (small)

groups called clusters. Each cluster has a cluster head. The

data fusion, aggregation and processing is local to the cluster.

Communication occurs mostly between cluster heads and they

spend more energy than any other node in the cluster.

Technically, PASCAL [4] (power aware sectoring based

clustering algorithm for wireless sensor networks) is

implementation of leveling, sectoring and clustering with

proposed routing algorithm. In the routing algorithm nodes are

considered to be static or have a very low mobility with respect to signal propagation. In this algorithm, the packets

are forwarded by flooding. When an event occurs, packets are

flooded from the event occurring node to other nodes in the

direction of base station. The node receiving the packet checks

if the packet is from higher level, or else the packet is dropped

and if it is from one-hop sector of higher level, then the packet

is forwarded. And if the packet is from same level or if it is

from the same level and different sector then the packet is

dropped. In this paper the authors used the concept of mode

switching for PASCAL to improve the lifetime of the sensor

network.

III. ASSUMPTIONS

1. All the nodes in the network have similar capabilities.

2. The sensor network is densely deployed.

3. Base station has ability to transmit signals at various

power levels.

4. Base station has directional antenna.

5. Nodes can be operated in both sleep and awake modes.

6. All the nodes are static or having very low mobility.

IV. MODEL OF CR BASED WSN

In this section we discuss about a theoretical model of

WSN where we dynamically allocate the spectrum using

Cognitive Radio. The main functions for a cognitive radio can

be summarised as follows[9]:

1. Spectrum Sensing: Detecting unused spectrum

and sharing the spectrum without harmful

interference to other users.

2. Spectrum Management: Capturing the best

available spectrum to meet user communication

requirements.

3. Spectrum Mobility: Maintaining seamless

communication requirements during the transition

to better spectrum.

4. Spectrum Sharing: Providing the fair spectrum

scheduling method among coexisting secondary

users.

In the model we consider that there are some coordinator nodes in the network which have special capabilities. They

can sense the spectrum and can detect the white holes. Then

these coordinators communicate and share the spectrum

sensing details with a spectrum broker (Base Station in this

case).

Fig.1 CR based WSN

After processing the information, the spectrum broker

intimates every node to communicate in a particular band of spectrum which doesn’t cause any harmful interference to the

primary users. Once these sensor nodes start using the

frequency band suggested by the broker, the coordinators still

sense the spectrum for any primary user intruding in to his

licensed band. When the incumbent signal is above some

threshold level, the coordinator nodes forward this

information to the broker. Then the broker assists all the

sensors to switch to some other spectrum white space.

V. PROPOSED ALGORITHM

The base idea in this algorithm is to divide the field in to

sectors and route the events by using nodes which can switch between SLEEP and WAKE modes.

Step 1 : Levelling

As per our assumptions, we consider a densely deployed

sensor field. Initially the Base station sends signals with a

minimum power level and all those sensor nodes that receive

this information will set their level to one. Then the Base

station will increase its power level and transmit the signal.

This time those nodes which receive the signal for the first

time set their level to two. This procedure continues till all the

nodes in the network have their level ids determined [5]. To

counter the effects of fading in wireless channels, hop-count[4]

based leveling can also be done.

Step 2 : Sectorization

Using the directional antenna, the Base station will send

signals with maximum power and divide the sensor field in to

equiangular sectors with an angle of θ (consider θ as 45o).

Now, every node in the network is aware of its level and

sector [8].

Step 3 : Clustering

Clusters of sensor nodes are formed based on the signal

strength and use these local cluster heads as routers to sink. Optimal number of cluster heads is estimated to be 5% of total

number of nodes. The decision is made by choosing a random

numbers between 0 and 1. The node becomes a cluster head

for the current round if the random number is less than the

threshold value T(n).

T(n) =

Where p is the desired percentage of cluster heads (e.g.

0.05), r is the current round, and G is the set of nodes that

have not been cluster heads in last 1/p rounds [1]. Step 4 : Mode Setup

The part of a sector which is in a particular level is called

sectroid. If an event occurs in the sector(L,S), these nodes

flood very small metadata packets contain the level id and

sector id of the node where the event has occurred (Source

node). Each node that receives this packet will read the

location of source sectroid (L,S), if the level of this sectroid is

L or L-2 or L-4……. and sector S-1 or S+1 will go to SLEEP

mode. the sectroids with level L-1 or L-3 ….. and sector S go

to into SLEEP mode.( If and only if there is no transmission in

that particular sectroid).

Fig. 2 Sectroids in their appropriate modes

Figure.2 shows a part of a sensor network where an event

has occurred. The shaded sectroids are in the sleep mode and

the sectroids which are not shaded stay in wake mode.

The conditions for sectroid to go into SLEEP mode are :

Condition 1 :

Level ∈ { L , L-2 , L-4 ,……..} and

Sector ∈ {S-1 , S-2 }

Condition 2 :

Level ∈ { L-1 , L-3 , L-5 ,……… } and

Sector ∈ { S }

Fig. 3 Schematic diagram for PASCAL

Fig. 4 Schematic diagram for our Proposed algorithm

Step 5 : Routing Algorithm

After this setup is completed, the source node floods the

data packets in the direction of Base station. The node that

receives the packet checks for two conditions, one is the level

id and the other is the sector id. If the data is from higher level

and it checks for sector id. If the packet is from neighboring

sector of higher levels than the packet is forwarded and in

other case the packet is discarded.

Fig. 5 State flow Graph for Our Proposed Protocol

Fig. 5 state flow graph for our proposed protocol.

The proposed algorithm follows this flowchart procedure as in fig.5:

1. When an event occurs at a node, the node floods the

data packets to every neighbor.

2. Only the nodes which are in WAKE mode will receive

the packet and nodes in SLEEP mode don’t receive the

packets.

3. Then the nodes that receive data packets check the level

id and sector id of the packet.

4. If the level id from the source is lesser than its level id

the packet is dropped. 5. If the level id from a source is larger then the node

checks whether the sector id is from neighboring

sectors i.e. which are at 1 hop distance. If not the packet

is dropped.

VI. SIMULATION RESULTS

After performing extensive simulation experiments, the

results show that the proposed protocol has better network life

than that of the existing protocols. We compared the proposed

protocol with directional flooding (levelling), power aware

routing protocol. The network life time is defined as the time

taken for the failure of 10% of nodes in the network.

The values in table 1 correspond to the number of events

occurred in the network (before network fails) by simulating

each protocol for different number of nodes.

TABLE I

NUMBER OF EVENTS VARIOUS PROTOCOLS

.

Fig.6 ERFLA vs Levelling

Fig.7 ERFLA vs PASCAL

Number of

nodes/Routing Protocol

500

nodes

800

nodes

1000

nodes

1200

nodes

1500

nodes

Levelling 560 445 460 391 363

PASCAL 609 488 496 442 362

ERFLA 824 816 799 791 810

Fig 6. Shows the plot between the number of events

occurred in the sensor network on Y axis and the number of

nodes in the network on X axis comparing ERFLA with Levelling. We can say that ERFLA is a more energy efficient

than Levelling as the network lifetime of ERFLA is 42%

higher than that of Levelling

Fig 7. shows the graph plotted between number of events

occurred and network size comparing the performance of

ERFLA and PASCAL. The plot shows that ERFLA comes out

better than PASCAL by 34 % in terms of network lifetime

VII. CONCLUSIONS

In this paper we discussed a theoretical model for

implementing CR based WSN and described ERFLA which applies the concept of switching modes (sleep and awake) in a

localized sensor field. Network lifetime is a very important

criterion for deciding the efficacy of a routing protocol.

Simulation results and comparisons with the existing

protocols prove that ERFLA is better in terms of prolonged

network lifetime and energy efficiency.

VII. FUTURE WORK

Wireless Sensor Networks have very limited resources like

battery power, processing capabilities. So, the main concern in

a protocol design is to minimize the energy consumption. In

future we would like to combine routing with other layers and

make cross layer design which brings down power

consumption by a significant amount.

VII. REFERENCES

[1] Ian.F.Akyildiz, Weilian Su, Yogesh Sankarasubramaniam, and Erdal Gayirci, “A Survey on Sensor Networks,”IEEE Communications Magazine, August 2002

[2] Santosh Bheema, Anil Gogada and Rammurthy Garimella, “A Tsunami Warning System Employing Level Controlled Gossiping in Wireless Sensor Networks,”ICDCIT 2007, LNCS 4882, pp.306-313, 2007.

[3] Arora, Shashank, M.B.Srninvas, G.Ramamurthy “Power Aware, Probabilistic and daptable Routing Algorithm for Wireless Sensor Networks” National Conference on Communications (NCC 2004), IISc,Bangalore, pp. 60-64.

[4] Md.Aquil Mirza, Ramamurthy Garimella,” PASCAL: Power Aware Sectoring Based Clustering Algorithm for Wireless Sensor Networks”,2009

[5] K.Dheerendra Nath Reddy, Abdul Faheem Mohed, Rama Murthy Garimella,” Leveled Meshed Multipath Routing:A Novel Approach”,TENCON 2008.

[6] Jamal N. Al-Karaki ,Ahmed E. Kamal,” Routing Techniques in Wireless Sensor Networks: A Survey”, pp. 6-

28,2004. [7] Md. Aquil Mirza, Abdul Faheem Mohed, Ramamurthy

Garimella,” Energy Efficient Sectoring Based Routing in Wireless Sensor Networks for Delay Constrained Applications: A Mixed Approach”, RACE,2008.

[8] W.Heinzelman, A. chadrakasan, and H. Balakrishna, “Energy-efficient communication protocol for wireless sensor networks,” in the Proceeding of the Hawaii International conference System Science, Hawaii, January

2000.

[9] I. F. Akyildiz, W.-Y. Lee, M. C. Vuran and S. Mohanty, “NeXt Generation/Dynamic Spectrum Access/Cognitive

Radio Wireless Networks: A survey”, Computer Networks,

vol. 50 nº 13, pp. 2127-2159, Sep. 2006.