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A Distance-based Clustering Routing Protocol in Wireless Sensor Networks LEACH-SC Presented By M. Jaffar Khan 1.

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Presentation on theme: "A Distance-based Clustering Routing Protocol in Wireless Sensor Networks LEACH-SC Presented By M. Jaffar Khan 1."— Presentation transcript:

1 A Distance-based Clustering Routing Protocol in Wireless Sensor Networks LEACH-SC Presented By M. Jaffar Khan 1

2 Abstract Classical LEACH protocol widely used until now because it has many advantages in – energy efficiency, – data aggregation and so on… In this paper, based on the LEACH protocol, we propose a new distance-based clustering routing protocol, LEACH-SC (LEACH- selective cluster). In LEACH-SC, a new method is used to choose cluster heads, i.e. – an ordinary node A will choose a cluster head which is the closest to the center point between A and the sink. The simulation results show that compared with LEACH, – LEACH-SC protocol can greatly reduce the overall network energy consumption, – balance the energy consumption among the sensors – extend the lifetime of the network. 2

3 I. INTRODUCTION In recent years, many routing protocols for WSNs have been proposed [1- 6] which can be classified into four classes: 1.clustering-based routing protocols, groups sensor nodes where each group of nodes has a cluster-head(CH) or a gateway. 2.data centric routing protocols, 3.geographic-based routing protocol 4.hybrid routing protocol. Many clustering-based routing protocols have been proposed such as LEACH[3], LEACH-C[4], HEED[5], TEEN[6] etc. – Among them, LEACH is the most popular hierarchical routing algorithm for sensor networks. [1] Ming Yu, Leung, K.K. “A dynamic clustering and energy efficient routing technique for sensor networks”. IEEE on Wireless Communications, Vol: 6(8): pp , August 2007, [2] F. Bouabdallah, N. Bouabdallah and R. Boutaba. “Cross-Layer Design for Energy Conservation in Wireless Sensor Networks”. In IEEE International Conference on Communications, 2009, June 2009, Accession Number: [3] Wendi Rabiner Heinzelman et al.“Energy-Efficient Communication Protocol for Wireless Microsensor Networks” . n Proceeding of the 33 rd Hawaii International Conference on System Sciences , January 2000,pp1-10 [4] Heinzelman WR. “Application-Specific protocol architectures for wireless networks [D].” Boston: MIT, Doctor thesis,2000. [5]Younis O, Fahmy S. “Heed: A hybrid, energy-efficient, distributed clustering approach for ad-hoc sensor networks”. IEEE Trans. on mobile Computing, 2004,3(4), pp 660−669. [6] Manjeshwar A, Grawal DP. “TEEN: A protocol for enhanced efficiency in wireless sensor networks”. In Proc. of the 15th Parallel and Distributed Processing Symp. San Francisco: vol. 3, pp.30189a 3

4 I. INTRODUCTION LEACH[3] is a self-organized, adaptive clustering protocol that uses – randomization to distribute the energy load evenly among the sensors in the network. The operation of LEACH is divided into rounds. – Each round begins with a set-up phase when the clusters are organized, followed by a steady-state phase – In the set-up phase, there are cluster-head electing phase and the cluster formation phase. After the cluster-heads have been chosen, sensor nodes which are chosen as cluster-heads broadcast an advertisement message to inform non-cluster sensor nodes that the chosen sensor nodes are new cluster-heads. Then non- cluster sensor nodes join the cluster with strongest signal strength. – a steady-state phase when data are transferred from the nodes to the cluster head and on to the BS. [3] Wendi Rabiner Heinzelman et al.“Energy-Efficient Communication Protocol for Wireless Microsensor Networks” . In Proceeding of the 33 rd Hawaii International Conference on System Sciences , January 2000,pp1-10 4

5 I. INTRODUCTION LEACH-C(Leach centralized)[4]modified LEACH by using global information and centralized clustering algorithm for cluster formation in order to realize uniform distribution of cluster heads throughout the network. – But LEACH-C is quite complex and the overhead is relatively high. 5

6 I. INTRODUCTION TEEN[6] makes use of a hierarchical scheme along with a data centric mechanism. – The working process is similar to the LEACH, but TEEN defines soft threshold and hard threshold to reduce the number of transmissions. – The first time a parameter from the attribute set reaches its hard threshold value, the node switches on its transmitter and sends the sensed data. – If the range of variation of the monitoring data reaches the soft threshold, the node forwards the latest data. – drawback if the thresholds are not reached, the nodes will never communicate. [6] Manjeshwar A, Grawal DP. “TEEN: A protocol for enhanced efficiency in wireless sensor networks”. In Proc. of the 15th Parallel and Distributed Processing Symp. San Francisco: vol. 3, pp.30189a 6

7 II. A DISTANCE-BASED CLUSTERING PROTOCOL 2.1 The shortage of LEACH 2.2 LEACH-SC Protocol – System model – Optimization Goals – Optimization analysis 2.3 Analysis of the Protocol 7

8 2.1 The shortage of LEACH The working procedure of LEACH is – to select cluster heads randomly and then broadcast an advertisement. – Non-CH nodes pick the advertisement packet with the strongest received signal strength then join that cluster. The algorithm itself has one severe problem in some conditions. – For example, As the topology graph shows in Fig 2-1, some nodes may choose a cluster so that the distance between its cluster-head and the sink is even further than the distance between the node itself and the sink. According to the energy model of LEACH protocol, the energy cost will increases as the communication distance d increases. – That’s to say, selecting cluster heads in such a random way will increase the communication cost of nodes and decrease the energy efficiency of the system. 8

9 2.1 The shortage of LEACH Figure 2-1 Routing for the network using LEACH 9

10 2.2 LEACH-SC Protocol to save the energy cost of the sensor networks and prolong the system’s lifetime, – we propose a distance-based clustering protocol, LEACH- SC ( LEACH-selective cluster). The basic idea of the protocol is as follows: Firstly some assumptions are addressed in this paper: – sink is located relatively close to the WSN field. – cluster heads and nodes has the knowledge of its location information. There are many ways for sensors to know their location information without GPS, such as APIT[7], GFF[8] etc. 10

11 2.2 LEACH-SC Protocol The operation of LEACH-SC is also divided into rounds. – Each round begins with a set-up phase and steady phase. – We do not change the way LEACH elects its cluster heads but changed the cluster formation algorithm. – After the cluster heads are selected, – cluster-heads broadcast an advertisement message that includes the cluster-head ID and location information to inform non-cluster head nodes. – Non-cluster head nodes first record all the information from cluster heads within their communication range. – Then the node finds the cluster head which is closest to the middle- point between the node itself and the sink and joins that cluster. In other words, how nodes join the cluster in order to prolong the system lifetime. 11

12 2.3 Analysis of the Protocol Next the mathematical analysis will be introduced to prove – why it is most energy-efficient when ordinary nodes choose the cluster head which is closest to the midpoint between itself and the sink. 12

13 2.2.1 System model As we know in wireless communications, – free Space channel model is used if the communication distance is less than distance threshold d 0 ; otherwise, multi-path fading model is used. So the transmission energy of transmitting a k-bit message over a distance d using this radio model is: is the transmitter circuitry dissipation per bit. The receiving cost is: 13

14 2.2.2 Optimization Goals to minimize the energy cost in the network and to prolong the lifetime, so the mathematical model we build is: – E total is total energy cost in the network. – E T is the transmission cost, – E R is the receiving cost, – E I is the energy cost while being in idle state, – E S is the energy cost while sensing. In general, the receiving cost, idle cost and sensing cost for a node is almost constant – while its transmission cost is variable. As a result, it’s the transmitting cost that determine the network’s overall cost. So the Equation 2-4 can be changed to: 14

15 2.2.2 Optimization Goals According to the transmitting cost in the wireless model we can also change Equation 2-5 into: – k is the number of bit forwarding on the distance d. – E elec is the transmitter circuitry dissipation per bit. – ε is the transmit amplifier dissipation per bit. From the eq.(2-6) we can see that – d has a crucial impact on the network’s energy cost. Then we can simplify the system model into: – n is set to 2 or 4. The communication distance between nodes in wireless sensor networks are usually short and mostly is the two-way communication. In the paper we set n=2, which means the optimization goal is 15

16 2.2.2 Optimization Goals distance between a node and a cluster head as d toCH the distance between a cluster head and the sink as d CHtoSink. According to our wireless model, we further simplify the optimization goal into: 16

17 2.2.3 Optimization analysis As it’s shown in Fig, we define – M as the midpoint between the Node and the Sink. – A perpendicular is drawn from Cluster Head to the line between the Sink and the node and H is the Perpendicular foot. To make it simpler, we define – d toSink (Distance between node and sink) as c, – d toCH as b, – d CHtoSink as a, – the distance between H (Perpendicular Foot) and M (Mid Point)is x, – the distance between Cluster Head and M is d, – the distance between Cluster Head and H is h. 17

18 2.2.3 Optimization analysis We can see from the trigonometric formulas that: Because we have,substituting, we get 18

19 2.2.3 Optimization analysis From (2-10), we can see that when the value of d toSink is fixed, is only related to d, i.e – is equivalent to. As a result, if a node chooses its cluster head which is closest to the midpoint of this node and the sink, – the squared distance of their communication is smallest. 19

20 Conclusion: is to actually – minimize the distance between the cluster head and the midpoint of a node and the sink when the distance between the node and the sink is fixed. So in LEACH-SC, – non-cluster nodes need to select the cluster head which is closest to the midpoint between itself and the sink as its communication cluster head in order to optimize the communication cost. 20

21 III. SIMULATION AND ANALYSIS NS-2[9] to simulate 100 stationary sensors and one sink. The nodes are supposed to be randomly deployed within the WSN field which is a square area of X*X. we set the initial energy of all nodes to 200 J. 21

22 III. SIMULATION AND ANALYSIS 1.Energy Consumption with different Sink Locations 2.System lifetime with different sink locations 3.Energy consumption under different network size 4.System lifetime under different network size 22

23 III. SIMULATION AND ANALYSIS 1.Energy Consumption with different Sink Locations – energy consumption of LEACH-SC protocol was investigated versus that of LEACH protocol, over various values of locations of the sink node. – The simulation was conducted in an area of 100*100, and we evaluated the energy consumption when sink located at (50,50), (50,100), (50,150 ) and (50,200) respectively. 23

24 1-Energy Consumption with different Sink Locations Different lines represent different sink locations with LEACH and LEACH-SC. LEACH-SC protocol outperforms the LEACH protocol in terms of energy consumption with different sink locations. When the sink node moves farther away from the sensor field, – the performance of LEACH and LEACH-SC protocols was significantly decreased, – but the performance of LEACH- SC is always better than LEACH. Figure: Energy consumption versus time with different sink locations 24

25 (2) System lifetime with different sink locations The number of nodes remaining alive over time was simulated for both protocols which is shown in Fig. We can see LEACH-SC protocol extends the network lifetime – when compared with LEACH protocol, no matter what the position of the sink is. Figure: Number of survival nodes versus time with different sink locations 25

26 (3) Energy consumption under different network size We conducted the following four experiments to evaluate the energy consumption with different network size. We set a square area of the sensor field to (50x50), (100x100), (200x200) and (500x500) respectively. And the sink is located in the center. The simulation results are displayed in Fig. We can find that energy consumption of LEACH-SC is conserved in all simulation scenarios. The curve of LEACH-SC protocol is smoother than that of LEACH, indicating that LEACH-SC’s energy consumption is more evenly distributed and increased more slowly over time. Figure: energy consumption versus time with different network size 26

27 (4) System lifetime under different network size We use the same simulation scenarios as described in recently previous slide. The simulation results are shown in Fig. – We can see in any cases, the overall system lifetime of LEACH-SC is prolonged when compared to LEACH. – We can also find that the performance of LEACH and LEACH-SC degrades as the network size increases. But no matter what size the network is, LEACH-SC always outperforms the LEACH in terms of system life and energy dissipation Figure: Simulation of system lifetime vs. time with different network size 27


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