Journal of Global Research in Computer Sciences

Journal of Global Research in Computer Sciences

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ISSN: 2229-371X

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HETEROGENEOUS PROTOCOLS FOR INCREASING LIFETIME OF WIRELESS SENSOR NETWORKS

Samayveer Singh*1, A K Chauhan2, Sanjeev Raghav3, Vikas Tyagi4, Sherish Johri5
  1. Department of IT, RKG Institute of Technology, Ghaziabad, Uttar Pradesh, India
  2. Department of IT, RKG Institute of Technology, Ghaziabad, Uttar Pradesh, India
  3. Department of IT, RKG Institute of Technology, Ghaziabad, Uttar Pradesh, India
  4. Department of IT, IMS Engineering College, Ghaziabad, Uttar Pradesh, India
  5. Department of IT, IMS Engineering College, Ghaziabad, Uttar Pradesh, India
Corresponding Author: Samayveer Singh, E-mail: samayveersingh@gmail.com
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Abstract

In this paper, the heterogeneous energy-efficient data gathering protocols for lifetime of wireless sensor networks have been reported. The main requirements of wireless sensor network are to prolong the network lifetime and energy efficiency. Here, Heterogeneous - SEP: A Stable Election Protocol for clustered heterogeneous (H-SEP) for Wireless Sensor Network has been proposed to prolong the network lifetime. In this paper, the impacts of heterogeneity in terms of node energy in wireless sensor networks have been mentioned. Finally the simulation result demonstrates that H-SEP achieves longer lifetime and more effective data packets in comparison with the SEP and LEACH protocol.

Keywords
Wireless Sensor Networks, Energy-Efficiency, Heterogeneity, maximize lifetime.

INTRODUCTION
A wireless sensor network (WSN) can be defined as a network consists of low-size and low-complex devices called as sensor nodes that can sense the environment and gather the information from the monitoring field and communicate through wireless links; the data collected is forwarded, via multiple hops relaying to a sink (also called as controller or monitor) that can use it locally, or is connected to other networks [1]. A sensor node usually consists of four subsystems [2] i.e. sensing unit, processing unit, communication unit and power supply unit.
In WSN, the sensor nodes are deployed in a sensor field. The deployment of the sensor nodes can be random (i.e. dropped from the aircraft), regular (i.e. well planned or fixed) or mobile sensor nodes can be used. Sensor nodes coordinate among themselves to produce high-quality information about the physical environment.
Each sensor node bases its decisions on its mission, the information it currently has, and its knowledge of its computing, communication, and energy resources. Each sensor nodes collect the data and route the data to the base station. All of the nodes are not necessarily communicating at any particular time and nodes can only communicate with a few nearby nodes. The network has a routing protocol to control the routing of data messages between nodes. The routing protocol also attempts to get messages to the base station in an energy-efficient manner.
The base station is a master node. Data sensed by the network is routed back to a base station. The base station is a larger computer where data from the sensor network will be compiled and processed. The base station may communicate with the Remote Controller node via Internet or Satellite [2, 3]. Human operators controlling the sensor network send commands and receive responses through the base station.
HEED (Hybrid Energy Efficient Distributed) protocol [4] is the clustering protocol. It uses using residual energy as primary parameter and network topology features (e.g. node degree, distances to neighbors) are only used as secondary parameters to break tie between candidate cluster heads, as a metric for cluster selection to achieve load balancing. In this all nodes are assumed to be homogenous i.e. all sensor nodes are equipped with same initial energy. But, in this paper we study the impact of heterogeneity in terms of node energy. We assume that a percentage of the node population is equipped with more energy than the rest of the nodes in the same network - this is the case of heterogeneous sensor networks. As the lifetime of sensor networks is limited there is a need to re-energize the sensor network by adding more nodes. These nodes will be equipped with more energy than the nodes that are already in use, which creates heterogeneity in terms of node energy, leads to the introduction of H-SEP protocol.
The remainder of the paper is organized as follows. In Section 2, we briefly review related work. Section 3 describes the clusters formation in the SEP protocol. Section 4 describes heterogeneous H-SEP protocol and the network radio model for energy calculations. Section 5 shows the performance of H-SEP by simulations and compares it with SEP and LEACH. Finally, Section 6 gives concluding remarks.

RELATED WORK
Heinzelman et al. [5] propose LEACH, a substitute clustering based algorithm. In order to save energy, LEACH deals with the heterogeneous energy condition is the node with higher energy should have larger probability of becoming the cluster head. Each sensor node must have an approximation of the total energy of all nodes in the network to compute the probability of becoming a cluster head but it cannot make decision of becoming a cluster head only by its local information, so the scalability of this scheme will be influenced.
S. Lindsey and C. Raghavendra [6] introduced Power Efficient Gathering in Sensor Information Systems (PEGASIS) protocol in 2002. It is an improved version of LEACH. Instead of forming clusters, it is based on forming chains of sensor nodes. One node is responsible for routing the aggregated data to the sink. Each node aggregates the collected data with its own data, and then passes the aggregated data to the next ring. The difference from LEACH is to employ multi hop transmission and selecting only one node to transmit to the sink or base station. Since the overhead caused by dynamic cluster formation is eliminated, multi hop transmission and data aggregation is employed, PEGASIS outperforms the LEACH. However excessive delay is introduced for distant nodes, especially for large networks and single leader can be a bottleneck.
In 2001, A. Manjeshwar and D. P. Agarwal [7] proposed Threshold sensitive Energy Efficient sensor Network Protocol (TEEN) protocol. Closer nodes form clusters, with a cluster heads to transmit the collected data to one upper layer. Forming the clusters, cluster heads broadcast two threshold values. First one is hard threshold; it is minimum possible value of an attribute to trigger a sensor node. Hard threshold allows nodes transmit the event, if the event occurs in the range of interest. Therefore a significant reduction of the transmission delay occurs. Unless a change of minimum soft threshold occurs, the nodes don’t send a new data packet.
Threshold sensitive Energy Efficient sensor Network Protocol (APTEEN) protocol in 2002. The protocol is an extension of TEEN aiming to capture both time-critical events and periodic data collections. The network architecture is same as TEEN. After forming clusters the cluster heads broadcast attributes, the threshold values, and the transmission schedule to all nodes. Cluster heads are also responsible for data aggregation in order to decrease the size data transmitted so energy consumed. According to energy dissipation and network lifetime, TEEN gives better performance than LEACH and APTEEN because of the decreased number of transmissions. The main drawbacks of TEEN and APTEEN are overhead and complexity of forming clusters in multiple levels, implementing threshold-based functions and dealing with attribute based naming of queries.
In 2004, G. Smaragdakis, I. Matta and A. Bestavros [9] proposed Stable Election Protocol (SEP) protocol. This protocol is an extension to the LEACH protocol. It is a heterogeneous aware protocol, based on weighted election probabilities of each node to become cluster head according to their respective energy. This approach ensures that the cluster head election is randomly selected and distributed based on the fraction of energy of each node assuring a uniform use of the nodes energy. In this protocol, two types of nodes (two tier in-clustering) and two level hierarchies were considered.
In 2005, M. Ye, C. Li, G. Chen and J. Wu [10] proposed Energy Efficient Clustering Scheme (EECS) protocol. It is novel clustering scheme for periodical data gathering applications for wireless sensor networks. It elects cluster heads with more residual energy through local radio communication. In the cluster head election phase, a constant number of candidate nodes are elected and compete for cluster heads according to the node residual energy. The competition process is localized and without iteration. The method also produces a near uniform distribution of cluster heads. Further in the cluster formation phase, a novel approach is introduced to balance the load among cluster heads. But on the other hand, it increases the requirement of global knowledge about the distances between the clusterheads and the base station.
In 2006, Q. Li, Z. Qingxin and W. Mingwen [11] proposed Distributed Energy Efficient Clustering Protocol (DEEC) protocol. This protocol is a cluster based scheme for multi level and two level energy heterogeneous wireless sensor networks. In this scheme, the cluster heads are selected using the probability based on the ratio between residual energy of each node and the average energy of the network. The epochs of being cluster-heads for nodes are different according to their initial and residual energy. The nodes with high initial and residual energy have more chances of the becoming cluster heads compared to nodes with low energy.
O. Younis and S. Fahmy proposed [4] Hybrid Energy Efficient Distributed clustering Protocol (HEED) protocol in 2004. It extends the basic scheme of LEACH by using residual energy as primary parameter and network topology features (e.g. node degree, distances to neighbors) are only used as secondary parameters to break tie between candidate cluster heads, as a metric for cluster selection to achieve power balancing. The clustering process is divided into a number of iterations, and in each iterations, nodes which are not covered by any cluster head double their probability of becoming a cluster head. Since these energy-efficient clustering protocols enable every node to independently and probabilistically decide on its role in the clustered network, they cannot guarantee optimal elected set of cluster heads.

CLUSTER FORMATION OF SEP PROTOCOL
In this section, we describe the network model. Assume that there are N sensor nodes, which are randomly dispersed within a 100m*100m square region (Figure 1). Following assumptions are made regarding the network model is:
1. Nodes in the network are quasi-stationary.
2. Nodes locations are unaware i.e. it is not equipped by the GPS capable antenna.
3. Nodes have similar processing and communication capabilities and equal significance.
4. Nodes are left unattended after deployment.
Cluster head 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, and hence residual energy can be estimated. Intra cluster communication cost is considered as the secondary parameter to break the ties. A tie means that a node might fall within the range of more than one cluster head.
image
When there are multiple candidate cluster heads, the cluster head yielding lower intra-cluster communication cost are favored. The secondary clustering parameter, intra-cluster communication cost, is a function of (i) cluster properties, such as cluster size, and (ii) whether or not variable power levels are permissible for intra cluster communication.
image
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homogenous nodes die very fast which will result in sparse network field. H-SEP, in 2-level, advance nodes die slowly as compared with normal nodes in SEP which help in prolonging the lifetime of the network. H-SEP, nodes die with relatively slow speed as all the sensor nodes are equipped with different energies. It has been observed that the death of the last node is around 3200 round.
image
Figure 5 depicts the number of alive nodes per round. In HSEP, the last node dies around 4000 round. The lifetime of HSEP is better than SEP and LEACH. As the number of advanced is increased the lifetime of the network also increases.

CONCLUSIONS
In this paper, we have introduced the H-SEP protocol for the heterogeneous wireless sensor network. We have discussed the two types of sensor nodes (normal and advanced) possible for the wireless sensor networks. We have evaluated the performance of LEACH, SEP and H-SEP protocol under these energy models using matlab. H-SEP prolongs the network lifetime and it is energy efficient than SEP. It sends more number of packets to the base station. In this, we introduced 2-level heterogeneity in terms of the node energy. It is observed that there is significant improvement in the lifetime in case of H-SEP protocol in comparison with SEP protocol because the number of rounds is maximum with 2- level H-SEP.

References
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