A Performance Study of LEACH and Direct Diffusion Routing Protocols in Wireless Sensor Network

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1 A Performance Study of LEACH and Direct Diffusion Routing Protocols in Wireless Sensor Network (2) S. Fakher (1), M.I. Moawad (2), M. Shokair (2), and K. Sharshar (1) (1) Radiation Engineering Department, NCRRT, Atomic Energy, Egypt Electronics and Electrical Communications Department, Faculty of Electronic Engineering, Menoufia University, Egypt Received: 13/7/2015 Accepted: 5/10/2015 ABSTRACT The Wireless Sensor Network (WSN) is composed of a large number of sensor nodes with limited computation communication, and battery facilities. One of the common applications of this network is environment monitoring through sensing motion, measuring temperature, humidity and radiation. One of the basic activities in WSN is data gathering which represents a great challenge. Many routing protocols are proposed for that network to collect and aggregate the data. The most popular ones are hierarchy and data centric routing protocols. The main goal of this study is to identify the most preferable routing protocol, to be used in each mobility model. This paper studies the performance of LEACH (Low Energy Adaptive Clustering Hierarchy) from hierarchy routing protocol and direct diffusion from data centric routing protocol which is not clarified until now. Moreover, a comparison between LEACH and direct diffusion protocol using NS2 simulator will be made, and an analysis of these protocols will be conducted. The comparison includes packet delivery ratio, throughput, average energy ratio, average delay, network lifetime, and routing overhead. The performance is evaluated by varying the number of sensor nodes under three mobility models Reference Point Group Mobility Model (RPGM), Manhattan and random waypoint mobility model. Simulation results show that LEACH routing protocol has a good performance in RPGM and Manhattan than random waypoint mobility model. Direct diffusion has a good performance in random waypoint mobility model than in RPGM and Manhattan mobility model. Keywords: WSN, LEACH, Direct Diffusion, RPGM, Manhattan and Random Waypoint 1- INTRODUCTION WSN grows rapidly due to the development of low power wireless communication. Usually, a WSN includes a large number of sensor nodes characterized by low cost, low power consumption, small volume and short transmission. As sensor nodes are deployed in the sensing field, they can help people to monitor and aggregate data. Gathering is the process of aggregation the data using one of the gathering approaches previously described in (1,2). Therefore, data gathering is one of the main issues in WSN. To overcome these issues, many routing protocols to collect the data to transmit it to base station (BS) have been used. Some of them are studied in this paper. Routing protocols are assumed to have some characteristics such as energy efficiency, security and reliability. In this paper, the performance study of LEACH routing protocol under Manhattan, RPGM and random waypoint mobility model will be studied. The performance is evaluated through the following parameters (packet delivery ratio, throughput, routing overhead, average delay, network lifetime and average energy ratio), which is not clarified until now. Moreover, a comparison between LEACH and direct diffusion routing protocol under that mobility models will be investigated. The remainder of this paper is organized as follows: Section 2 presents related work. Classification of routing protocols is made in 34

2 Section 3. Section 4 describes the mobility models that are used. The simulation results are discussed in Section 5. Conclusions will be made in Section RELATED WORK A classification of hierarchy routing protocol in WSN was made in a (3). Comparison between SPIN and LEACH routing protocol in WSN was investigated in (4). It was shown that in LEACH packet delivery ratio is less as compared to SPIN and LEACH has more delay as compared to SPIN. The performance of LEACH and HEED cluster based protocol were compared in (5). It was obtained that HEED is more energy efficient routing for WSN as compared to LEACH protocol in the form of energy consumption and cost of sensor nodes. SPIN data centric routing protocol was compared with hierarchy routing protocol from the point of view of two parameters (throughput and delay VS time) in (6). Analysis of data centric routing protocol for WSN was studied in (7). M-SPIN achieves energy savings by discarding packet transmission to the opposite direction of sink node. But one major problem in M-SPIN is that few sensor nodes may be used several times and those nodes may dissipate energy and may be destroyed earlier than other nodes in the network. This paper more focuses on the performance study of LEACH from hierarchy routing protocol. Moreover, comparisons between direct diffusion and LEACH with different number of sensor nodes under three mobility models (RPGM, Manhattan and Random waypoint) will be implemented. 3- CLASSIFICATION OF ROUTING PROTOCOLS Routing protocols are necessary for data gathering routing protocols are broken down into four groups which are data centric, hierarchy, location based and quality of services based on (8). Hierarchy and data centric routing protocol will be investigated in this paper. Hierarchy protocols are proposed for energy consumption challenges of sensor network. Sensor nodes form cluster heads that aggregate the data and transmit it to sink node. Moreover, cluster head form layers of clusters to aggregate the data transmit the data to the sink in (9, 10). Our paper will study LEACH from hierarchy protocols. Data centric routing protocol requires attribute based on naming. That system is more interested in querying an attribute of the phenomenon, rather than querying an individual node. The BS sends queries to a certain area for information and waits for replying from the nodes of that particular region. Since data is requested through queries, attribute based naming is required to specify the properties of the data. Depend on the query, sensor collects a particular data from the area of interest and this particular information is only required to transmit to BS (11). Our paper focuses also on direct diffusion from data centric protocols. 3-1 Leach LEACH protocol includes the following features that are data aggregation, self-configuration of cluster heads and low energy media access. In LEACH, the nodes organize themselves into clusters. All non-cluster heads transmit their data to the cluster head. It performs signal processing function on the data (data aggregation and transmits data to the base station). Since the cluster head node knows all clusters members. It can create TDMA and tells each cluster member where can transmit its data (12,13). The operation of LEACH is divided into rounds each round begins with setup phase followed by steady state phase. The steady state phase is large as compared with setup phase as shown in Fig. 1. setup steady state frame time Fig. (1): Setup phase and steady state phase In LEACH, sensor nodes elect themselves to be cluster head at the beginning of the round r+1 that starts at time t with a certain probability. Each node will be a cluster head once in N/ k round. The probability for each sensor node (i) to be a cluster head at time (t) is given by (13), 35

3 k N k *( r mod N / k) C i (t) 0 P i(t) = 0 C i(t) =0.. (1) Where: K: is the expected number of cluster head. N: is the total number of nodes in the network. r: is the current round and the expected number of nodes that have not been a cluster head in the round r is (N-K*r). When c i (t) =0, the node will be chosen to be cluster head. In set up phase, once the nodes have elected themselves to be a cluster head. The cluster head nodes must tell all the other nodes in the network that they have chosen to be cluster head for current round. Cluster head broadcasts an advertisement message. Each non cluster head node determines to which it belongs by choosing the cluster head that requires the minimum communication energy based on received signal strength of the advertisement from each cluster head. Each non cluster head transmits a join request message back to its chosen cluster head. In steady state phase, the nodes send their data to the cluster head that was chosen by the nodes. The data is transmitted at frames using TDMA. Each node has slot to transmit data in it. Once cluster receives data, it can operate on the data and transmit it to BS (14) as shown in Fig. 2. BS CH Normal node 3-2 Direct Diffusion Routing Protocol Fig. (2): LEACH routing protocol Direct diffusion based on interest which is a query that specifies what user wants. The sink node sends an interest to its neighbor nodes. Nodes receive the interest and send to its neighbors which are known as diffusion process. Direction state created at each node that receives interest creates gradient, gradient direction is toward the neighboring node which is the interest received. The gradient from the source back to the sink are setup. When the event is sensed it is flowing from the originators of interests along multiple gradient paths (15,16) as shown in Fig. 3. Source Normal node Sink A-Propagation path b-setup path c-data delivery along reinforced path Fig. (3): Direct diffusion routing protocol 36

4 4- MOBILITY MODELS The mobility models are used to produce a set of mobility scenarios that are used to evaluate the protocol performance in WSN. In this paper, three mobility models are applied which are RPGM, Manhattan and random waypoint mobility models. At RPGM, each group has a logical center (group leader) that determines the group motion as each group of members belong to one group leader and at each instant, every node has a speed and direction that is derived by randomly deviation from that of group leader. At Manhattan Mobility Model (MH), the movement of mobile nodes on streets are defined by maps. That map is composed of horizontal and vertical streets. Mobile nodes are allowed to move along with that map and at the intersection of horizontal and Vertical Street; the mobile nodes can turn left, right or go to straight with a certain probability. At Random Waypoint Mobility Model (RW) in this model at every instant a node randomly chooses a destination and moves toward it with a velocity chosen uniformly randomly from [0, v max], where v max is the maximum allowable velocity for every mobile node. After reaching the destination, the node stops for duration of time after that time it chooses a random destination and repeats the whole process until the simulation end (17). 5- SIMULATION RESULTS AND DISCUSSION Two routing protocols are evaluated through NS2 simulation by using these simulation parameters that are described in Table 1. Table (1): Simulation parameters The performance of two routing protocols are evaluated according to the following metrics parameters, packet delivery ratio, network lifetime, average energy ratio, average delay, throughput, and routing overhead which are investigated as follows : 5-1 Under Manhattan Mobility Model Fig. (4): Throughput Vs. number of sensor nodes at MH model 37

5 Fig. (5): Network lifetime Vs. number of sensor nodes at MH model Figure 4 shows through Vs. number of sensor nodes. We can conclude from this figure that throughput decreases as the number of sensor nodes increase. As the number of nodes increase that increase the traffic which causes more congestion and more bits loss. Minimum throughput occurs at 200 sensor nodes at which LEACH increases throughput by 7.2% as compared with direct diffusion. While maximum throughput occurs at 10 sensor nodes at which LEACH increases throughput by 4.15% as compared with direct diffusion. Therefore, on average we can notice that LEACH can increase throughput by 5.71% as compared with direct diffusion. Figure 5 shows network lifetime Vs. number of nodes. As the number of nodes increase network lifetime increases, as number of nodes increase more nodes will be available for sensing, that will increase number of sensor nodes still alive. Minimum network lifetime occurs at 10 sensor nodes at which LEACH prolongs network lifetime by 1% as compared with direct diffusion. While maximum network lifetime occurs at 200 sensor nodes at which LEACH prolongs network lifetime by 41% as compared with direct diffusion. Therefore, on average we can observe that LEACH can prolong network lifetime by 11.86% as compared with direct diffusion. Fig. (6) Packet delivery ratio Vs. number of sensor nodes at MH model 38

6 Fig. (7): Average energy ratio Vs. number of sensor nodes at MH model Figure 6 illustrates packet delivery ratio Vs. number of sensors. As the number of sensor nodes increase packet delivery ratio decreases. As number of sensor nodes increase, it cause more congestion that cause more packet loss. Minimum packet delivery ratio exists at 200 sensor nodes at which LEACH increases packet delivery ratio by 11.1% as compared with direct diffusion. The maximum packet delivery ratio occurs at 10 sensor nodes at which LEACH increases packet delivery ratio by 8% as compared with direct diffusion. Therefore, on average LEACH can improve packet delivery ratio by 9.66% as compared with direct diffusion. Figure 7 shows average energy ratio Vs. number of sensors. Average energy ratio increases when the number of sensor nodes increased. As number of sensor nodes increase, it cause more traffic that require more energy for data transfer. Minimum average energy ratio exists at 10 sensor nodes, at which LEACH decreases average energy ratio by 9.1% as compared with direct diffusion. While maximum average energy ratio occurs at 200 sensor nodes at which LEACH decreases average energy ratio by 3.2% as compared with direct diffusion. Therefore, on average we can realize that LEACH more energy saving by 7% as compared with direct diffusion. Fig. (8): Average delay Vs. number of sensor nodes at MH model 39

7 Fig. (9): Routing overhead Vs. number of sensor nodes at MH model Figure 8 shows average delay Vs. number of sensors. As the number of sensor nodes increase average delay increases. When number of nodes increased that cause more traffic which cause more delay at data transfer. Minimum delay happens at 10 sensor nodes at which LEACH decreases the delay by 0.142% as compared with direct diffusion, while maximum average delay exists at 200 sensor nodes at which LEACH decrease the delay by % as compared with direct diffusion. Therefore, on average direct diffusion causes more delay by 0.125% as compared with LEACH. Figure 9 declares number of nodes Vs. routing overhead. As number of sensor nodes increase routing overhead increases. As number of sensor nodes increase require more control bits to be transmitted between sensor nodes to setup connection. Minimum routing overhead occurs at 10 sensor nodes at which LEACH increases overhead bits by 0.225% as compared with direct diffusion, while maximum routing overhead exists at 200 sensor nodes at which LEACH have the same overhead bits as compared with direct diffusion. Therefore, on average we can recognize that LEACH requires more control bits to setup connection by % as compared with direct diffusion. 5-2 Under RPGM Mobility Model Fig. (10): Throughput Vs. number of sensor nodes at RPGM model 40

8 Fig. (11): Network lifetime Vs. number of sensor nodes at RPGM model Figure 10 shows throughput Vs. number of nodes. Throughput decreases as the number of sensor nodes increase. Minimum throughput occurs at 200 sensor nodes at which LEACH increases throughput by 13.5% as compared with direct diffusion. While maximum throughput happens at 10 sensor nodes at which LEACH increases throughput by 10% as compared with direct diffusion. Therefore, on average we can implement that LEACH can increase throughput by 11.64% as compared with direct diffusion. Figure 11 shows network life time Vs. number of nodes. As the number of sensor nodes increase network lifetime increases. Minimum network lifetime occurs at 10 sensor nodes at which LEACH prolongs network lifetime by 2% as compared with direct diffusion. While maximum network lifetime exists at 200 sensor nodes at which LEACH prolongs network lifetime by 41% compared with direct diffusion. Therefore, on average LEACH can prolong Network lifetime by 15.9% as compared with direct diffusion. Fig. (12): Packet delivery ratio Vs. number of sensors nodes at RPGM model 41

9 Fig. 13 Average energy ratio Vs. number of sensors nodes at RPGM model Figure 12 shows packet delivery ratio Vs. number of sensors. As the number of sensor nodes increase data packet delivery ratio decreases. Minimum packet delivery ratio happens at 200 sensor nodes at which LEACH increases packet delivery ratio by 28.5% as compared with direct diffusion. While maximum packet delivery ratio exists at 10 sensor nodes at which LEACH increases packet delivery ratio by 9.7% as compared with direct diffusion. Therefore, on average it is shown that LEACH can improve packet delivery ratio by 16.69% as compared with direct diffusion. Figure 13 shows average energy ratio Vs. number of nodes. Average energy ratio increases when the number of sensor nodes increased. Minimum average energy ratio occurs at 10 sensor nodes which LEACH decreases average energy ratio by 9.6 % as compared with direct diffusion. While maximum average energy ratio occurs at 200 sensor nodes at which LEACH decrease average energy ratio by 10.6% as compared with direct diffusion. Therefore, on average it is illustrated that LEACH can achieve more energy saving by 9.6 % as compared with direct diffusion. Fig. (14): Average delay Vs. number of sensor nodes at RPGM 42

10 Fig. (15): Routing overhead Vs. number of sensor nodes at RPGM model Figure 14 shows average delay Vs. number of sensors. When the number of sensor nodes increase average delay increases. Minimum delay occurs at 10 sensor nodes at which direct diffusion decreases the delay by % as compared with LEACH, while maximum average delay happens at 200 sensor nodes at which direct diffusion decreases the delay by % as compared with LEACH. Therefore, on average we can recognize that LEACH achieves more delay by % as compared with direct diffusion. Figure 15 shows routing overhead Vs. number of nodes. As number of sensor nodes increase routing overhead increases. Minimum routing overhead exists at 10 sensor nodes at which LEACH increases overhead bits by % as compared with direct diffusion, while maximum routing overhead occurs at 200 sensor nodes at which LEACH increases overhead bits by as compared with direct diffusion. Therefore, on average it is illustrated that LEACH requires more control bits to setup connection by % as compared with direct diffusion. 5-3 Under Random Waypoin Fig. (16): Throughput Vs. number of sensor nodes at RW model 43

11 Fig. (17): Network lifetime Vs. number of sensor nodes at RW Figure 16 shows throughput Vs. number of nodes. Throughput decreases as the number of sensor nodes increase. Minimum throughput occurs at 200 sensor nodes at which direct diffusion increases throughput by 3% as compared with LEACH. While maximum throughput occurs at 10 sensor nodes at which direct diffusion increases throughput by 4% as compared with LEACH. Therefore, on average we can realize that direct diffusion can increase throughput by 3.2% as compared with direct diffusion. Figure 17 shows network lifetime Vs. number of sensors. When the number of sensor nodes increase network lifetime increases. Minimum network lifetime happens at 10 sensor nodes at which direct diffusion prolongs network lifetime by 1% as compared with LEACH. While maximum network lifetime occurs at 200 sensor nodes at which direct diffusion prolongs network lifetime by 45% compared with LEACH. Therefore, on average it is obtained that direct diffusion can prolong network lifetime by 13.57% as compared with direct diffusion. Fig. (18): Packet delivery ratio Vs. number of sensor nodes at RW model 44

12 Fig. (19): Average energy ratio Vs. number of sensor nodes at RW model Figure 18 shows packet delivery ratio Vs. number of nodes. When the number of sensor nodes increased packet delivery ratio decreases. Minimum packet delivery ratio exists at 200 sensor nodes at which direct diffusion increases packet delivery ratio by 10.4% as compared with LEACH. While maximum packet delivery ratio happens at 10 sensor nodes at which LEACH increases packet delivery ratio by 6.8% as compared with direct diffusion. Therefore, on average we can implement that direct diffusion can improve packet delivery ratio by 8.46% as compared with LEACH. Figure 19 shows average energy ratio Vs. number of sensors. Average energy ratio increases when the number of nodes increased. Minimum average energy ratio occurs at 10 sensor nodes at which direct diffusion decreases average energy ratio by 4.1% as compared with LEACH. While maximum average energy ratio exists at 200 nodes at which direct diffusion decreases average energy ratio by 5.7% as compared with LEACH. Therefore, on average it is illustrated that direct diffusion can achieve more energy saving by 3.7 % as compared with LEACH. Fig. (20): Average delay Vs. number of sensor nodes at RW model 45

13 Fig. (21): Routing overhead Vs. number of sensor nodes at RW model Figure 20 shows average delay Vs. number of nodes. As number of sensor nodes increase average delay increases. Minimum delay happens at 10 sensor nodes at which LEACH decreases the delay by % as compared with direct diffusion, while maximum average delay occurs at 200 sensor nodes at which LEACH decreases the delay by % as compared with LEACH, therefore, on average we can realize that direct diffusion achieves more delay by % as compared with LEACH. Figure 22 illustrates routing overhead Vs. Number of sensors. As number of sensor nodes increase routing overhead increases. Minimum routing overhead happens at 10 sensor nodes at which LEACH increases overhead bits by % as compared with direct diffusion, while maximum routing overhead exists at 200 sensor nodes at which LEACH increases overhead bits by as compared with direct diffusion. Therefore, on average we can recognize that LEACH requires more control bits to setup connection by % as compared with direct diffusion. 6- CONCLUSIONS Based on the study of the LEACH and direct diffusion routing protocols, under three mobility models it is illustrated that at RPGM mobility model, it is shown that LEACH routing protocol has a good performance and desirable features of a good energy consumed, throughput, packet delivery ratio, and network lifetime than direct diffusion, but it has more delay and routing overhead as compared with direct diffusion routing protocol. As obtained from results delay increases in LEACH routing protocol by very small value, and it has a small increment in routing overhead than direct diffusion protocol that not effect on total energy consumed in it. At random waypoint, it is obtained that direct diffusion has desirable specifications of a good energy consumed, throughput, packet delivery ratio, network lifetime, and routing overhead, but it has more increment in delay than LEACH. Under Manhattan mobility model, it is observed that LEACH has desirable features of a good energy consumed, throughput, packet delivery ratio, network lifetime and has less delay than direct diffusion but it has small increment in routing overhead than direct diffusion that not effect on total energy consumed in it. REFERENCES (1) D. culler, D. Estrin, M. Srivastava. Overview of sensor Networks, IEEE Computer Magazine, August (2) Samra Boulfekhar Mohammed Benmohammed A Novel Energy Efficient and Lifetime Maximization Routing Protocol in Wireless Sensor Networks, Wireless Personal Communications, Sept- 2013, Vol.72, Sept- 2013, pp

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