Printer Friendly

Emseep--Effective Modelling of Scalable Energy Efficient Protocol In Wireless Sensor Network.

INTRODUCTION

One of the most advance technologies in wireless technology is the wireless sensor network (WSN), these are basically sensors which are placed in desired location to monitor certain parameter, and the sensor and the server are connected through a sink node. The main invention of these WSN were to do some basic functions like studying the environment in which they are placed and monitoring them all the time from the server and controlling them and collecting the information about environment and sending it to the server.

The entire wireless sensor networks comprises of sensor nodes, sink node and the monitoring station. The Sensor nodes are placed in the area where the monitoring is needed, these sensors can be a camera or a motion sensor or any electronic devices which can sense any event happening in that particular place and the sink node is the intermediate node which acts as the connector between the sensor nodes and the server. The sink node collects the data from the sensor node and sends it to the monitoring station. The energy of the sensor node has to be utilized properly as in most of the application the sensor node are placed at the location where humans can't go often, as the location is remote. Some of the applications of the WSN are military, tracking the wild animals and industrial control.

To ensure the effective utilization of the energy of the sensor node various clustering based techniques are proposed [1-3]. Clustering technique is grouping the sensor nodes and choosing the one node to be the CH. The diagram shown in the figure 1 gives the formation of clusters among the group of sensor nodes.

In this case there are three clusters and each cluster will have a CH. The CH takes the responsibility of collecting the data from the group of sensors and sends it to the base station or the sink node. Two or more sensor nodes belong to the same cluster if they are close. So based on the adjacent distance between the nodes the cluster is formed. This is a distance based clustering technique. In our proposed work the cluster head is chosen based upon the two criteria namely the energy level of the sensor node and the location of the node. When two nodes have the same energy, the node which is located at the center of the cluster is chosen as the CH. When the CH is at the center of the cluster then the data from the sensor node reaches the CH in a single hop communication.

Related Work:

I.F.Akyildiz describes the concept of sensor network which is a recent advancement in micro--electro mechanical systems technology [4]. A sensor network senses real value parameters like temperature, pressure, moisture level extra and converts the sensed value to an equivalent electrical value and sends it to the sink node. In most of the application the sensor nodes are placed in a remote location or in industrial processing environment. In health care application the sensor size should be very less in the range of micro or even nano meters. Based upon the sensor output the control function is carried out mechanically during surgery. They are also used in military, environment and home applications.

Rajashree. V. Biradar shows the structural view of a sensor network [5]. Each node typically consists of the four components: sensor unit, Central Processing Unit (CPU), power unit and communication unit. The sensor and Analog to Digital (ADC) converter combines to form sensor unit. It is responsible for collecting and translating the data. The processor and storage are collectively known as CPU which is directly connected with all the other units of the sensor node. The sensor measure the parameter of interest which is always analog in nature to process and to store the data it is necessary to convert the information into digital data and for this purpose ADC is used.

D. J. Dechene explains about the clustering process and the clustering algorithms for wireless sensor network [6]. Clusters are the collection of a group of sensor network and the objective of the formation of the group reduce the interference caused in the denser network and thereby ensuring effective communication. The group of nodes combines to form a cluster. Each node in the cluster need to send data to the base station which is also known as sink. So the cluster members in the cluster elect one head which is known as CH. With the help of the cluster head the data are collected and sent to the sink. The clustering phenomenon plays an important role in not just organization of the network, but can dramatically affect network performance.

Abdul Gani Khan explained briefly about the various routing protocol [7]. In order to enhance the performance, the routing protocols are classified as flat based, hierarchical based and location based protocols. A hierarchical routing protocol gives the preference to a node with highest energy to be called as CH. The main advantage of this routing protocol is that the overall energy of the sensor nodes is distributed and it is an energy efficient protocol. This protocol arranges a group of node to form a cluster and in each cluster one or more CH will be selected. By following these principles the overall latency is reduced, packet loss is less and more energy efficient. The direct communication between a sensor and the sink may force nodes to emit their messages with such a high power that their resources could be quickly depleted. Therefore, the nodes coordinate among themself so that the node which is at far distance sends the data to the sink node through the multi hop communication with the help of the intermediate nodes. In this way messages are propagated by intermediate nodes so that a route is established with multiple hops to the sink.

HarneetKour proposed a new protocol known as Heterogeneous--Hybrid Energy Efficient Distributed Protocol (H-HEED) to prolong the network lifetime and effective data packet transmission [8]. The hybrid energy efficient distributed clustering (HEED) protocol considers the energy of the sensor nodes as one of the important parameter of interest. The other parameter is the distanceof the cluster head with the other sensor nodes in the clusters. These two parameters are considered for efficient load balancing in the WSN. In HEED protocol the cluster head formation is based on the following assumption, nodes have similar processing and communication capabilities and equal significance and nodes location are unaware i.e. it is not equipped by the GPS capable antenna. The CH selection is primarily based on the residual energy of each node. Since the energy consumed per bit for sensing, processing, and communication is typically known the residual energy can be estimated.

Dechene proposed design goals for clustering process [9]. Some of the attributes are cost of clustering, selection of cluster heads and cluster, real time operation, synchronization, data aggregation, repair mechanisms and quality of services (QoS). Also classifications of clustering schemes have been given. It is mainly classified as heuristic, weighted, hierarchical and grid. Heuristic scheme is again classified as LCA (linked cluster algorithm) which was the first clustering algorithm developed and is mainly based on unique identification number.

Weighted scheme is again classified as weighted clustering algorithm (WCA) in which clustering algorithm tries to find a long lasting architecture during the first cluster head selection. Another important aspect of the algorithm is that it is fully distributed meaning that all the models in the mobile network shares the same responsibility acting as cluster heads.

Hierarchical scheme is further classified as LEACH which is a major improvement on conventional clustering protocol [10, 11]. This protocol provides a balancing of energy usage by random rotation of cluster heads. Secondly it is classified as an energy efficient clustering scheme is a clustering algorithm in which CH candidate compete for the ability to elevate to cluster head for a given round [12]. This protocol improves the distribution of energy throughout the network resulting in better resource usage and extended network lifetime. Finally it is classified HEED which is a multi-hop clustering algorithm with a focus on efficient clustering by proper selection of cluster heads based on the physical distance between the nodes [13]. CH selection is based on two parameters namely, the residual energy of node and intra cluster communication.

Stephanie Lindsey proposed a new energy efficient routing protocol known as Power Efficient Gathering in Sensor Information Systems (PEGASIS) in which the sensor nodes are arranged in a linear fashion hence it is named as the chain based protocol [14]. In this protocol the sensor node which want to transmit the data don't sent the data directly to the sink node but it transmit the data to the sensor node which is close to it. This node collects the data from other sensor nodes to transmit the data to the sink node. Each time a sensor node takes the responsibility of collecting and sending the data to the sink node thereby the energy of a particular sensor node is not depleted [15, 16]. In this method every sensor node is given a chance of collecting the sensed data and forwarding it to global sink and hence the energy dissipation is shared equally by all the sensor nodes. In this approach the node which is having the highest energy is chosen as the leader node. The all other sensor node transmit the sensed data to this leader node and the leader node forwards the data to the sink node. To begin the process the nodes which are distributed are arranged in a linear fashion one after another to form a chain structure and once the structure is formed the data is sent to the leader node which has the highest energy among other sensor node.

Proposed Protocol:

Energy efficient and lifetime aware WSN design is still a challenging issue in sensor network. Cluster based wireless sensor network is a proven approach of power aware routing. A new challenge of cluster based approach is handling dynamic cluster, selection of cluster heads and balancing of energy consumption of member node of a cluster.

We propose an energy efficient routing method for dynamic hierarchical clustering architecture. In our proposal CH are selected using decision making technique for energy efficiency and load balancing. The effective modelling of scalable energy efficient clustering protocol (EMSEEP) is used in WSN which analysis the various parameters for clustering formation like residual energy and the distance between the source node and the sink node.

When the sensor nodes are deployed randomly in the area, the sensor nodes are clustered and then the distance is calculated from the cluster centre to each node of the cluster member. If the energy of the node in the cluster is higher than the average energy of the cluster, it will become the candidate CH. At last the candidate cluster head becomes the CH according to the distance calculated from the cluster centre of the candidate CH. The simulation shows that the proposed protocol could improve energy efficiency caused by the uneven distribution of the CH in LEACH protocol. Thus it can balance the load and extent the life cycle of the WSN. On the basis of decision making technique the node selects the cluster in the defined area. The data aggregation is done from the cluster node to the base station i.e. the data is sent to the CH by the cluster node without any data interference. Then the gathered information is arranged in a linear manner so that the CH easily transfers the data to the base station.

On the process of transferring of this collected information to base station, the energy efficiency plays a vital role in the clustering process. The energy is considered as the major factor because the cluster should maintain the energy efficiency periodically while transferring the data. If the CH loses the energy on the transmission of data, the CH tends to die at the particular time period and the process gets terminated. This termination process is undergone by the conventional protocols.

In our proposed method EMSEEP for continuous data transmission the periodic switching of the CH is carried out. Henceforth the switching process is simple and is implemented in the EMSEEP. This switching process will be undemanding when the cluster is centralized. The privilege of the centralized node is that the data can be easily transmitted even if the node is in the edge. If the CH is assigned to the nodes in the edge of the cluster then the data transmission requires more power and thereby it is avoided.

On account of the cluster switching many parameters like the energy efficiency is analysed and simulated. The essential parameters which are analysed practically are latency, throughput and energy level of the sensor nodes. The flow chart shown in the figure 2 gives the details about the functioning of the protocol

Energy Consumption Characteristics of EMSEEP:

Power consumption of a wireless network depends on the cluster formation. The power consumed will be in the following three cases namely Transmit mode, receive mode and idle mode.

The initial energy E (Initial) in a cluster group is given by equation 1

E(Initial)=E(CHinitial)+ [[SIGMA].sup.n.sub.k=1] E (SN) (1)

Where E (CH) is the initial cluster head energy and E (SN) is the initial energy of the sensor node in the cluster group and n is the number of sensor node in the cluster group.

The energy spent by the CH for transmission of data to the sink is given by equation 2

E(CH) = [[SIGMA].sup.n.sub.k=1]E(t) + [[SIGMA].sup.n.sub.k=1]E(r) (2)

E(CH) = [[SIGMA].sup.n.sub.k=1][E(t) + E(r)] (3)

Where E (t) is the energy spent for transmitting the data by CH to sink and E(r) is the energy spent for receiving the data from the entire sensor nodes in the cluster group.

In the case of multi hop communication the total energy spent is given by equation 4

E(T)=E(CH) + [[SIGMA].sup.n.sub.k=1]E(SNt) + [[SIGMA].sup.m.sub.k=1](E(It) + E(Ir) (4)

Where E (T) is the total energy spent, E (SNt) is the transmission energy of sensor node; E (It) and E (Ir) are the transmission and reception energy of the intermediate node. These intermediate node help in multi hop communication when the CH and sensor node are at far distance. And m indicates the total number of intermediate nodes.

Transmit mode:

The EMSEEP minimizes the transmit energy consumption in WSN by considering the distance between the transmitting node and the cluster head. The measured distance between the transmitting node and the cluster head is compared with the reference distance called ad optimum distance dop. If the distance is below the optimum distance then the transmission takes place through single hop communication otherwise the data is transmitted with the help of the intermediate node through multi hop communication. Thus the optimal broadcast strategy to minimize the transmit energy dissipation in a network is to use a multi hop communication, when the transmission distance is more than the optimum distance. Furthermore the total transmits energy dissipation increases with the number of retransmissions of a broadcast packet. Thus reduction of number of rebroadcasts in cluster formation results in higher energy savings.

Receive mode:

Substantially in broadcasting, many redundant version of the same packet are received by each node, which results in receive energy dissipation for no gain. An efficient solution to this problem is information summarization prior to data transmission through shortest distance path from the cluster head.

The cluster node that already received a packet will be prevented from receiving redundant copies of a same packet, which is achieved by collecting the data from the sensor node through TDMA. So each sensor node can transmit the data only during the time allocated to it thereby avoiding interference and preventing the reception of the duplicate packets.

Idle mode:

It is important to ensure that the energy dissipation is utmost zero during the idle mode. Many approaches have been proposed for minimizing the idle energy dissipation in multi hop wireless networks. The WSN includes an energy saving mechanism when it is utilized in cluster infrastructure.

A sink that needs to save the energy informs the CH of its entry to the energy saving mode, where it cannot receive data and switches to sleep mode. The CH buffers the packets from the network. When the sleeping sink wakes up it listens for the packet from the CH and CH then forwards the packets that arrived during the sleep period to the sink node. This energy saving method results in additional delays at the cluster nodes that may affect QoS (Quality of service). Henceforth this approach is not directly applicable in single hop networks.

Operation Methods:

The techniques in our proposed method are as follows,

* Analysis of minimum distance.

* CH selection.

* Even distribution of data.

* Responsible for data gathering.

* Stable cluster node.

The decision making task is done by analysing the distance and energy level of the cluster nodes to select the appropriate CH. The CH is selected so that it can collect the data from the various sensor nodes in its cluster.

In our proposed method the CH is chosen near to the center of the cluster. The data is transferred easily only when the nodes are arranged in the shortest path with the CH. Henceforth this process is done in a defined area. Whenever the CH is switched and if a sensor node is far away from the CH, then the sensor node is attached to some other cluster whose CH is at shorter distance to this sensor node.

5.1 Algorithm:

Step 1: Start the process.

Step 2: Initialization of the network parameter and number of nodes

Step 3: calculate the distance in a defined area

Step 4: cluster nodes alignment i.e. cluster formation

Step 5: cluster head (CH) selection by decision making technique

Step 6: Transmission of data in the cluster

Step 7: calculate the energy efficiency during the transmission

Step 8: Cluster switching is undergone when the energy drains out.

Step 9: calculate the parameters like energy efficiency, throughput and delay.

Step 10: Stop the process

5.2 Operations:

The operation can be classified into two stages.

* Initialization Stage.

* Active Stage.

In Initialization stage, the group of nodes are combined together to form a cluster and the CH is chosen based on the energy level of the sensor node and its distance from the sink node. The main purpose of calculating the distance is to minimize the delay and also to decrease the energy dissipation of the nodes.

5.3 Initialization Stage:

In the initialization stage the CH is chosen from each cluster. Few sensor nodes will be considered as a choice of CH and among them one sensor node will be finalized to be a cluster head after analysing the energy level and the distance from the sink. Among these nodes the nodes which has the maximum energy and which is at close location to the all the sensor nodes and the sink is chosen as the cluster head. Once the CH is chosen then it intimates the various sensor nodes in its cluster by sending a message so that they can send the sensed data to the CH.

On receiving the message from CH, the sensor node joins the cluster. Suppose if a sensor node receives two messages from two different CH then it joins any one cluster based on the strength of the message signal from CH. The sensor node eventually joins a CH which has good message signal strength. Once the cluster is formed the CH collect the data from sensor nodes by TDMA. This principle enables to avoid the interference.

5.4 Active Stage:

During the active stage, the sensor nodes i.e. the non-cluster head nodes starts sensing data and sends it to their CH according to the TDMA schedule. The CH, after receiving data from all the member nodes, aggregates it and sends it to the base station. Whenever the CH switches, then the network again goes back into the initialization phase for the further process. This is done in order to reduce interference from nodes belonging to the other cluster.

Performance Evaluation:

In our proposed method EMSEEP, the result is simulated in NS2 and the various parameters like throughput, latency and power are analysed and compared with the existing LEACH protocol. The table 1 shown below indicates the various simulation parameters.

The important parameters like power consumption, throughput and latency of the EMSEEP is compared with the Leach protocol and the comparisons result shown in the figure 3, figure 4 and figure 5 clearly shows that the proposed EMSEEP perform well in the WSN.

Conclusion:

The proposed EMSEEP consider both the residual energy and the distance between the CH and the sink. The sensor node is chosen as the CH by ensuring the location of the CH so that the sensor node can transmit the data through the single hop communication itself. These procedure help in saving the energy of the sensor nodes, reduces the delay and improves throughput of the network.

REFERENCES

[1.] Heinzelman, Wendi B., Anantha P. Chandrakasan and HariBalakrishnan, 2002. "An application-specific protocol architecture for wireless microsensor networks." IEEE Transactions on wireless communications, 1(4): 660-670.

[2.] Shen, Bo, Shi-Yong Zhang, and Yi-Ping Zhong, 2006. "Cluster-based routing protocols for wireless sensor networks." RuanJianXueBao(Journal of Software) 17(7): 1588-1600.

[3.] Muruganathan, Siva D., et al., 2005. "A centralized energy-efficient routing protocol for wireless sensor networks." IEEE Communications Magazine, 43(3): S8-13.

[4.] Akyildiz, I.F., W. Su, Y. Sankarasubramaniam, E. Cayirci, 2002. "Wireless sensor networks: a survey" Computer Networks, 38: 393-422.

[5.] Rajashree, V., V.C. Biradar, Patil, Dr. S.R. Sawant, Dr. R.R. MudholkarMiao, 2009. "Classification and Comparison of routing protocols in wireless sensor networks" Special Issue on Ubiquitous Computing Security Systems, 4(2): 704-711.D.J.

[6.] Dechene, P., Kumaraadu, M. Luccini, A. Sauer, 2008. "Algorithms for Node Clustering in Wireless Sensor Networks: A Survey" Information and Automation for sustainability, 2008.ICIAFS 2008. 4th international conference on, pp: 295-300.

[7.] Khan, Abdul Gani, Abdur Rahman and Neeti Bisht, 2013. "Classification of hierarchical based routing protocols for wireless sensor networks." International journal of innovations in engineering and technology, pp: 2319-1058.

[8.] Kour, Harneet and Ajay K. Sharma, 2010. "Hybrid energy efficient distributed protocol for heterogeneous wireless sensor network." International Journal of Computer Applications, 4(6): 1-5.

[9.] Dechene, D.J., A. El Jardali, M. Luccini and A. Sauer, 2010. A Survey of Clustering Algorithms for Wireless Sensor Networks, Network-Based Information Systems (NBiS), 2010 13th International Conference on Networking & Broadcasting, pp: 14-16.

[10.] Handy, M.J., Marc Haase and Dirk Timmermann, 2002. "Low energy adaptive clustering hierarchy with deterministic cluster-head selection." Mobile and Wireless Communications Network, 2002. 4th International Workshop on. IEEE.

[11.] Fu, Chunyao, et al., 2013. "An energy balanced algorithm of LEACH protocol in WSN." International Journal of Computer Science., 10(1): 354-359.

[12.] Ye, Mao, et al., 2005. "EECS: an energy efficient clustering scheme in wireless sensor networks." Performance, Computing, and Communications Conference, 2005. IPCCC 2005. 24th IEEE International. IEEE.

[13.] Younis, Ossama, and Sonia Fahmy, 2004. "HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks." IEEE Transactions on mobile computing, 3(4): 366-379.

[14.] Lindsey, Stephanie and Cauligi S. Raghavendra, 2002. "PEGASIS: Power-efficient gathering in sensor information systems." Aerospace conference proceedings, IEEE. 3.

[15.] Sen, Feng, Qi Bing, and Tang Liangrui, 2011. "An improved energy-efficient PEGASIS-based protocol in wireless sensor networks." Fuzzy Systems and Knowledge Discovery (FSKD), 2011 Eighth International Conference On. 4.

[16.] Nehra, Vibha, and Ajay K. Sharma, 2013. "PEGASIS-E: Power efficient gathering in sensor information system extended." Global Journal of Computer Science and Technology, 13: 15-E: 15.

(1) Sivaramakrishnan S and (2) Kesavamurthy T

(1) Assistant Professor, Department of ECE, United Institute of Technology, India.

(2) Associate Professor, Department of ECE, PSG College of Technology, India.

Received 14 September 2017; Accepted 15 October 2017; Available online 30 October 2017

Address For Correspondence:

Sivaramakrishnan S, Assistant Professor, Department of ECE, United Institute of Technology, India. E-mail: sivaramkrish.s@gmail.com

Caption: Fig. 1: Formation of Cluster.

Caption: Fig. 2: Flow Chart for the Proposed Protocol

Caption: Fig. 3: Energy Comsumption

Caption: Fig. 4: Throughput

Caption: Fig. 5: Latency
Table 1: Simulation Parameters

Parameters               Values

Network Area             500 * 500 [m.sup.2]
Number of Sensor Nodes   200
Number of Sink           1
MAC Protocol             802.11
Antenna Type             Omni
Propagation Model        2 ray model
Initial Power            10 W
Transmitting and         49 mW and 29 mW
  Receiving Power
Packet Size              1000 s
COPYRIGHT 2017 American-Eurasian Network for Scientific Information
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2017 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Author:S., Sivaramakrishnan; T., Kesavamurthy
Publication:Advances in Natural and Applied Sciences
Article Type:Report
Date:Oct 1, 2017
Words:4139
Previous Article:Designing a Hybrid Codec with the help of Integer-MDCT and to estimate the audio quality by means of SPL and CR.
Next Article:Actual situation and solutions for reducing the traffic jams and congestion in Vietnam.
Topics:

Terms of use | Privacy policy | Copyright © 2019 Farlex, Inc. | Feedback | For webmasters