This paper presents a Parametric Energy Efficient Cluster Head Selection .... where the transmitter dissipates energy to run the radio electronics and the power.
Int. Jr. of Advanced Computer Engineering & Architecture Vol. 2 No. 2 (June-December, 2012)
P-EECHS: Parametric Energy Efficient Cluster Head Selection protocol for Wireless Sensor Network Anindita Ray1, Debashis De2 Department of Computer Science & Engineering BF-142, Sector 1, Salt Lake City, West Bengal University of Technology, Kolkata – 700064, West Bengal. e-mail: {1aninrc, 2dr.debashis.de}@gmail.com Abstract This paper presents a Parametric Energy Efficient Cluster Head Selection (P-EECHS) protocol which improves LEACH protocol and aims to reduce energy consumption within the wireless sensor network. This paper improves LEACH protocol by improving the election strategy of the cluster-head nodes based on remaining energy of sensor nodes, distance from base station and the number of consecutive rounds in which a node has not been a cluster head. Also it considers the parameter that whether the nodes remaining energy is sufficient enough to send the aggregate data to the base station or not. If the nodes remaining energy is not sufficient enough it cannot be selected as cluster head. Considering these parameters, simulation results shows that the proposed protocol could better reduce energy consumption and prolong lifetime of the wireless sensor network with respect to the parameters FND (First Node Dies), HND (Half Node Dies) and LND (Last Node Dies) comparative to LEACH and EECHS. Keywords: BEC, EECHS, LEACH, PECRP, PEGASIS, WSN. 1
Introduction
In past few years there have been growing interests in the potential use of wireless sensor networks (WSNs) in applications [1] such as, health monitoring, environment monitoring, disaster management, military application, and security surveillance. Sensors in these applications are expected to be remotely deployed in large numbers and to operate autonomously in unattended environments. One of the major challenges in WSNs is to ensure an extended lifetime to the sensor nodes. To support scalability, nodes are often grouped into disjoint and mostly non-overlapping clusters. Clustering is introduced to WSNs because of its network scalability, energy-saving attributes and network topology stabilities. The main objective of most of the existing clustering algorithms [217] lies on how to prolong the lifetime of the network and how to make a more efficient use of the critical resources, such as buttery power. Our proposed protocol P-EECHS improves LEACH protocol [2] by improving the election strategy of the cluster-head nodes, considering residual energy, distance from base station, number of consecutive rounds in which a node has not been a cluster head and the factor that whether the nodes remaining energy is sufficient enough to send the aggregate data to the base station or not. If the nodes remaining energy is not sufficient enough it cannot be selected as cluster head. Simulation result shows that the proposed protocol has better performance than LEACH [2], the protocol referred in [3] and EECHS [17]. 2
Back Ground and Related Work
Low Energy Adaptive Clustering Hierarchy (LEACH) [2] is the first hierarchical cluster-based routing protocol for wireless sensor network which partitions the nodes into clusters, in each cluster a dedicated node with extra privileges called Cluster Head (CH) is responsible for creating and manipulating a TDMA schedule and sending aggregated data from nodes to the base station (BS). Remaining nodes are cluster members. In order to select
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cluster-heads each node n determines a random number between 0 and 1. If the number is less than a threshold T(n), the node becomes a cluster-head for the current round. The threshold is set as follows:
T (n) =
p 1 1 − p × r mod p
∀n ∈ G
T (n) = 0
∀n ∉ G
(1)
with P as the cluster-head probability, r as the number of the current round and G as the set of nodes that have not been cluster-heads in the last 1/P rounds. This algorithm ensures that every node becomes a cluster-head exactly once within 1/P rounds. Although the randomization of electing cluster-head nodes can distribute the load among the network, it suffers from the following drawbacks•
LEACH randomly elects cluster-head and prone lead to the unbalanced energy level reserved nodes.
•
The election of cluster-head nodes ignores the residual energy information about the nodes and this will easily result in the cluster head nodes disable.
•
It ignores the distance factor between the nodes and the base station
in
Since LEACH has many drawbacks, many researchers have tried to make this protocol performs better [3-17] by improving cluster head selection algorithm by several parameters and also some authors follow multi-hop communication [12][16] for that. LEACH's [2] stochastic cluster head selection algorithm is extended in [3] by adjusting the threshold T(n) denoted in equation (1), relative to the nodes remaining energy as follows:
T (n) = (
Where
E residual 1 E initial 1 − p × r mod p p
(2)
K opt )
Eresidual is the remaining energy of the sensor nodes and Einitial is the initial energy of the node before
transmission.
K opt = Where
N 2π
ε
fs
M
(3)
ε mp d to2 BS
K opt is the optimal cluster head number, N is the total number of sensor nodes, M is the length of nodes
distributing fields,
d to BS is the distance between the nodes and the Base Station as in [5].
In EECHS [17] LEACH's stochastic cluster head selection algorithm is extended by adjusting the threshold T(n) denoted in equation (1), considering residual energy of the nodes, distance between the nodes and the base station and the number of consecutive rounds in which a node has not been a cluster head as parameters as follows:
T (n ) =
p 1 1 − p × r mod p
× [ E ( i ) + (1 − D ( i )) + (s div r ) ] ∀n ∈ G
T (n) = 0 Here residual energy factor is
E (i ) = where
(4)
∀n ∉ G
E residual (i )
(5)
E initial
Eresidual ( i ) is the remaining amount of energy of node i and Einitial is the initial energy of node before
transmission as in [10].
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Distance factor Where
d iB
(6)
d Farthest
d iB is the distance from node i to BS as follows:
( X i − X BS )2 + (Yi − YBS )2
d iB = and
D(i ) =
(7)
d Farthest is the distance of the farthest node from the BS as in [10]. Here (< X BS , YBS >) is the location of
the BS. In third parameter (s div r) of equation (4), s is the number of consecutive rounds in which a node has not been a cluster head and r is the number of the current round. Here P, n and G in the equation (4) express the same meaning as in equation (1).
3
Proposed Approach
3.1
Network Model
For our proposed model, we adopt a few reasonable assumptions of the network model based on [8][17] as follows: (i) The base station is fixed at a far distance from the sensor nodes. (ii)The sensor nodes are homogeneous and energy constrained with uniformly energy. (iii) No mobility of sensor nodes and all nodes are able to reach BS. (v) Nodes RAM size should be sufficient enough to store the distance of the nodes from Base station.
3.2
Radio Energy Dissipation Model
In order to predict the performance of our proposed protocol, a simple model for the radio hardware energy dissipation is used where the transmitter dissipates energy to run the radio electronics and the power amplifier, and the receiver dissipates energy to run the radio electronics, as in [5]. For the experiments described here, both the free space and the multi path fading channel models were used, depending on the distance between the transmitter and the receiver. If the distance is less than a threshold, the free space (fs) model is used; otherwise, the multi path (mp) model is used as in [5]. Thus, to transmit a k-bit message a distance d, the radio expends:
ETx (k , d ) = ETx −elec (k ) + ETx − amp (k , d )
ETx (k , d ) = E elec × k + ε fs × k × d 2
ETx (k , d ) = E elec × k + ε mp × k × d 4
if
d 〈 d0
if
d ≥ d0
(8)
Where the threshold
d0 =
ε fs ε mp
(9)
and to receive this message, the radio expends
E Rx (k ) = E Rx −elec (k ) = E elec × k
(10)
Since the base station is at a far distance from the sensor nodes, the energy dissipation of cluster head nodes follows the multipath model and is calculated as in [5] as follows:
N N 4 ECH = lE elec − 1 + lE DA + lE elec + lε amp d toBS K K
(11)
Where N is the total number of sensor nodes distributed uniformly in the sensor region, K is the number of clusters; l the number of bits in each data message is,
EDA is the energy for data aggregation and d toBS is the
distance from the cluster head node to the BS. On the other hand each non-cluster head node only needs to transmit its data to the cluster head once during a frame and since the distance to the cluster head is small; the energy dissipation follows the free-space model which is calculated as in [5] as follows: 2 E non−CH = lEelec + lε fs d toCH
(12)
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3.3
Parametric Energy Efficient Cluster Head Selection (P-EECHS)
In our proposed work Cluster head selection algorithm considers the nodes remaining energy, distance of the nodes from the base station and the number of consecutive rounds in which a node has not been a cluster head as the parameters as in EECHS [17]. Also it considers an additional parameter that whether the nodes remaining energy is sufficient enough to send the aggregate data to the base station or not. If the nodes remaining energy is not sufficient enough it cannot be selected as cluster head. To ensure an even energy load distribution over the whole network, this additional parameter is considered to optimize the process of cluster-head selection. Energy Sufficient Flag (ESF): If the nodes remaining energy is not sufficient enough to send the aggregate data to the base station then a flag variable called ESF (energy sufficient flag) will be taken as 0.And if the remaining energy is sufficient then it will be taken as 1. Since the base station is at a far distance from the sensor nodes, the energy dissipation of cluster head nodes follows the multipath model. Considering the additional parameter ESF with all three parameters as in [17] the modified threshold T(n) becomes
T(n) =
p 1 1 − p × r mod p
∀n∈G
×[E(i) + (1− D(i)) + (s div r)]× ESF (i)
∀n ∉ G
T (n) = 0
(13)
Here E(i), D(i), r and s express the same meaning as in equation(4). P, n and G in this equation express the same meaning as in equation (1) and (4). ESF (i) indicate the value of the energy sufficient flag variable for node i. In order to select cluster-heads each node determines a random number between 0 and 1. If the number is less than the threshold T(n), the node becomes a cluster-head for the current round. If ESF value of the node is 0 then threshold T(n) becomes 0 and the node cannot be selected as cluster head. 3.4
The process of forming clusters and data aggregation
After the cluster-heads are determined, the proposed algorithm uses the same clustering process as LEACH [2] and EECHS [17]. Firstly, the cluster head nodes advertise clustering message towards surroundings and the normal nodes determine which cluster-head node they will join, in according to the strength of the message. The cluster heads generate TDMA schedule for every member node in order to make the member nodes transmit data in their own schedule non-interferingly. 4
Simulation Results and analysis
The simulation environment is composed of 100 sensor nodes and sensor nodes are distributed in a region of 100mX100m randomly. Table 1 lists the simulation parameters. Table 1: Simulation Parameters Parameter
Value
No. of nodes Network size BS’s Location Cluster Head probability Initial energy of node
100 100X100 m2 (100,100) .05 0.25/0.5/1 Joule
Node Distribution Data Packet E elec ε mp ε fs
Randomly distributed 4000 bits 50 nJ/bit 0.0013 pJ/bit/m4 10pJ/bit/m2
D Farthest Energy for data aggregation (E DA)
100m 5nJ/bit/signal
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Fig.1 shows the number of the alive nodes of LEACH, the protocol [3], EECHS and proposed protocol PEECHS in the network based on number of rounds. Fig.2 shows the amount of Energy consumption of LEACH, the protocol [3], EECHS and P-EECHS based on number of rounds. P-EECHS shows better performance than LEACH, the protocol [3] and EECHS.
Fig. 1 Number of alive nodes of LEACH, Protocol[3], EECHS and proposed protocol P-EECHS.
Fig. 2 Energy consumption of LEACH, Protocol [3], EECHS and P-EECHS
Table 2 shows the comparison of Network lifetime of LEACH, the protocol [3], EECHS and P-EECHS having initial energy 1 J/node with respect to the parameters FND, HND and LND. Here P-EECHS is 41.7% better than LEACH, 26.2% better than the protocol [3] mentioned by equation (2) and 15.2 % better than EECHS with respect to the parameter FND. And P-EECHS is 31.6% better than LEACH, 23.5 %better than the protocol [3] and 11.1% better than EECHS with respect to the parameter HND .And P-EECHS is 25.5% better than LEACH, 19.6% better than the protocol [3] and 9.7% better than EECHS with respect to the parameter LND. Table 2: Comparison of Network Lifetime with respect to FND HND and LND Protocol (initial energy = 1 J/node ) LEACH Protocol [3]
Round First Node Dies(FND)
Round Half Node Dies(HND)
Round Last Node Dies(LND)
1870 2100
2280 2430
2670 2800
EECHS
2300
2700
3050
P-EECHS
2650
3000
3350
The comparison of Network lifetime of LEACH and Proposed protocol P-EECHS having initial energy 0.25 J, 0.5 J and 1 J/node which are randomly distributed in 100m X 100m network are shown in Table 3.
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Table 3: Comparison of Network Lifetime with different amount of initial energy Initial Energy(J/node)
Protocol
Round First Node Dies(FND)
Round Last Node Dies(LND)
0.25
LEACH P-EECHS LEACH P-EECHS LEACH P-EECHS
400 525 850 1150 1870 2650
780 1000 1500 1700 2670 3350
0.5 1
5
Conclusion and Future Work
This paper presents an improved version of LEACH protocol which aims to reduce energy consumption within the wireless sensor network and prolong the lifetime of the network. This paper improves LEACH protocol by improving the election strategy of the cluster-head nodes, considering the parameters residual energy, distance from base station , number of consecutive rounds in which a node has not been a cluster head and the parameter that whether the nodes remaining energy is sufficient enough to send the aggregate data to the base station or not. Simulation result shows that the proposed protocol gives better performance than LEACH, the protocol in [3] and EECHS with respect to the number of alive nodes, energy consumption based on number of rounds. The proposed protocol is 41.7% better than LEACH with respect to FND, 31.6 % better than LEACH with respect to HND and 25.5% better than LEACH with respect to LND. In our proposed approach it is assumed that the nodes are static i.e. there is no mobility in deployed sensor nodes and also the sink is considered as static. In future the proposed protocol can be modified in such a way so that it can support mobility both in case of sensor nodes and sink and it can be implemented for reactive type of networks. Also in near future we can incorporate multi-hop communication in data aggregation for better performance. For simulation C-coding has been used .In future we will use NS2 and other simulators and will compare the results. ACKNOWLEDGMENT Authors are grateful to Department of Science and Technology (DST) for sanctioning a research Project under Fast Track Young Scientist scheme reference no.: SERC/ET-0213/2011 under which this paper has been completed. REFERENCES [1] Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “A Survey on Sensor Networks”, IEEE Communications Magazines, August 2002, Vol. 40, No. 8, pp. 102-114. [2] W. Heinzelman, A. Chandrakasan, and H. balakrishnan, “Energy- Efficient Communication Protocol for Wireless Microsensor Networks”, Proc. IEEE 33 Hawaii International Conference on System Sciences, January 2000. [3] M.C.M.Thein, T.Thein, “An energy efficient cluster head selection for wireless sensor network” Proc. IEEE International Conference on Intelligent Systems, Modelling and Simulation, 2010, pp. 287 - 291. [4] Fan Xiangning, Song Yulin, “Improvement on LEACH Protocol of Wireless Sensor Network”, International Conference on Sensor Technologies and Applications, 2007, pp. 260 - 264 [5] W. Heinzelman,A. Chandrakasan, and H. balakrishnan, , “An Application-Specific Protocol Architecture for Wireless Microsensor network.” IEEE transactions on wireless communications. 2002, vol. 1, no 4, pp 660 - 670. [6] V.Loscri, G.Morabito and S.Marano. “A Two-levels Hierarchy for Low-Energy Adaptive Clustering Hierarchy”. Vehicular Technology Conference, 2005. [7] Xu Yi Xu Yong-qiang, “Energy efficient distributed clustering algorithm based on coverage”, Ninth International Symposium on Distributed Computing And Applications to Business, Engineering and Science, 2010. [8] S.Lindsey and C.Raghavendra, “PEGASIS: Power Efficient Gathering in Sensor Information Systems”,Proc. IEEE Aerospace Conference, March 2002, pp. 1 - 6. [9] Linlin Wang,Jie Liu,Wei Wang, “An improvement and simulation of LEACH protocol for Wireless Sensor Network”.Proc. IEEE First International conference on Pervasive Computing, Signal Processing And
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