erfla camera ready final
TRANSCRIPT
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.
[email protected] [email protected]
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.