Stable Sensor Network (SSN): A Dynamic Clustering Technique for Maximizing Stability in Wireless Sensor Networks (original) (raw)
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Stability is one of the major concerns in advancement of Wireless Sensor Networks (WSN). A number of applications of WSN require guaranteed sensing, coverage and connectivity throughout its operational period. Death of the first node might cause instability in the network. Therefore, all of the sensor nodes in the network must be alive to achieve the goal during that period. One of the major obstacles to ensure these phenomena is unbalanced energy consumption rate. Different techniques have already been proposed to improve energy consumption rate such as clustering, efficient routing, and data aggregation. However, most of them do not consider the balanced energy consumption rate which is required to improve network stability. In this paper, we present a novel technique, Stable Sensor Network (SSN) to achieve balanced energy consumption rate using dynamic clustering to guarantee stability in WSN. Our technique is based on LEACH (Low-Energy Adaptive Clustering Hierarchy), which is one of the most widely deployed simple and effective clustering solutions for WSN. We present three heuristics to increase the time before the death of first sensor node in the network. We devise the algorithm of SSN based on those heuristics and also formulate its complete mathematical model. We verify the efficiency of SSN and correctness of the mathematical model by simulation results. Our simulation results show that SSN significantly improves network stability period compared to LEACH and its best variant.
A stable energy efficient clustering protocol for wireless sensor networks
Sensor networks comprise of sensor nodes with limited battery power that are deployed at different geographical locations to monitor physical events. Information gathering is a typical but an important operation in many applications of wireless sensor networks (WSNs). It is necessary to operate the sensor network for longer period of time in an energy efficient manner for gathering information. One of the popular WSN protocol, named low energy adaptive clustering hierarchy (LEACH) and its variants, aim to prolong the network lifetime using energy efficient clustering approach. These protocols increase the network lifetime at the expense of reduced stability period (the time span before the first node dies). The reduction in stability period is because of the high energy variance of nodes. Stability period is an essential aspect to preserve coverage properties of the network. Higher is the stability period, more reliable is the network. Higher energy variance of nodes leads to load unbalancing among nodes and therefore lowers the stability period. Hence, it is perpetually attractive to design clustering algorithms that provides higher stability, lower energy variance and are energy efficient. In this paper to overcome the shortcomings of existing clustering protocols, a protocol named stable energy efficient clustering protocol is proposed. It balances the load among nodes using energy-aware heuristics and hence ensures higher stability period. The results demonstrate that the proposed protocol significantly outperforms LEACH and its variants in terms of energy variance and stability period.
Improving the network lifetime of a wireless sensor network using clustering techniques
2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT), 2017
A wireless sensor network (WSN) is a network that consists of spatially distributed autonomous devices that use sensors to monitor the surrounding physical or environmental conditions. As WSNs are generally deployed over large areas or hostile environments, they are difficult to manage and monitor. Furthermore, the batteries cannot be easily recharged or replaced. This is a major drawback of a WSN. Clustering is an important method used for extending the lifetime of a network. It involves a cluster head (CH) which collects data from the cluster members (CMs) present in its cluster, and reports this data to the base station (BS). Thus, energy is conserved by sending data to the CH instead of the sink. An existing clustering technique for WSNs is the Low Adaptive Energy Clustering Hierarchy (LEACH). In this paper, the implementation of LEACH is discussed and an improvement of the LEACH model called Segmented LEACH is proposed. In order to further improve the network lifetime, the appl...
An Intelligent Energy-Efficient Clustering Technique to Maximize Wireless Sensor Network Lifetime
International journal emerging technology and advanced engineering, 2023
A wireless sensor network (WSN) is an environment monitoring network that collects and transmits data wirelessly to the base station. Due to their inability to be recharged or replaced, sensors face battery constraints. Considering how much energy is wasted by sensors in WSN, this is one of the most popular research topics in WSN. Protocols for improving energy efficiency have been developed to improve the network's energy dissipation and, ultimately, its lifetime. An energy-efficient and throughputenhancing clustering technique is presented in this paper, which is superior to existing protocols based on LEACH. A cluster head in LEACH elected from a cluster that includes nodes with small residual energy will lead to an early death of the network, which will adversely affect its efficiency. The proposed clustering technique, on the other hand, uses the remaining energy of the sensor to make the sensor a cluster head. The base station finds the shortest path between the cluster heads. Through this compound, power dissipation is reduced, which contributes to a longer network lifespan and higher throughput. According to simulations performed with the NS3 simulator, the proposed clustering technique achieves higher network lifetime and throughput compared to some recent clustering protocols, i.e. LEACH, BCE-LEACH, and MO-LEACH.
The objective of this paper is to develop a mechanism to increase the lifetime of homogeneous wireless sensor networks (WSNs) through minimizing long range communication, efficient data delivery and energy balancing. Energy efficiency is a very important issue for sensor nodes which affects the lifetime of sensor networks. To achieve energy balancing and maximizing network lifetime we divided the whole network into different clusters. In cluster based architecture, the role of aggregator node is very crucial because of extra processing and long range communication. Once the aggregator node becomes non functional, it affects the whole cluster. We introduced a candidate cluster head node on the basis of node density. We proposed a modified cluster based WSN architecture by introducing a server node (SN) that is rich in terms of resources. This server node (SN) takes the responsibility of transmitting data to the base station over longer distances from the cluster head. We proposed clu...
wireless sensor networking is an emerging technology that promises a wide range of potential applications in both civilian and military areas. A wireless sensor network (WSN) typically consist of a large number of low cost, low power and multi-functional sensor nodes that are deployed in a region of interest. Wireless sensor networks face many challenges caused by communication failures, storage and computational constraints and limited power supply. In WSN, the nodes are battery driven and hence energy saving of sensor nodes is a major design issue. Energy efficient algorithms must be implemented so that network lifetime should be prolonged. Lifetime of a network can be maximized through clustering algorithms, where cluster is responsible for sending the data to the base station and not all the nodes are involved in data transmission .various clustering algorithms are deployed in past few years. In this paper we are proposing an algorithm which is a combination of Bacterial foraging optimization algorithm (BFO) which is a Bio-Inspired algorithm and LEACH and HEED protocols which enhances the lifetime of a network by dissipating minimum amount of energy.
Low Energy Adaptive Clustering Hierarchy in Wireless Sensor Network (LEACH)
2015
– In wireless sensor networks, the power resource of each sensor node is limited.Minimizing energy dissipation and maximizing network lifetime are important issue in the design of routing protocols for sensor networks. This paper proposes a new improved cluster algorithm of LEACH protocol which is intended to balance the energy consumption of the entire network and extend the lifetime of the network.
International Journal of Research and Analytical Reviews (IJRAR), 2018
The field of Wireless sensor networks is the main attraction of various researchers due to its practical applications in daily life. It comprises of sensor nodes geographically distributed over an area, which sense the environmental conditions like temperature, humidity etc and pass this information to the sink .As these nodes are non-rechargeable means energy constrained, so main focus of the researches in this field is to make it energy efficient as par as possible and prolong its network lifetime .Clustering is one of the hierarchical routing technique which is used to make the network energy efficient. It can be further improved by adopting non-uniform cluster size techniques and sub-clustering in farther as well as larger clusters. Cluster heads of distant clusters will need to communicate with only sub-cluster heads which further covers the entire cluster members. This proposed model effectively improves lifetime over LEACH. Keywords-Wireless Sensor Networks, effective lifetime, sub-clustering, cluster head and residual energy. I. INTRODUCTION As sensor nodes have limited and non-rechargeable energy resources, energy is a very scarce resource and has to be managed carefully in order to extend the lifetime of the sensor networks [1]. In recent years, researchers have done a lot of studies and proved that clustering is an effective scheme in increasing the scalability and lifetime of wireless sensor networks [2-5]. In clustering schemes, there are two kinds of nodes in one cluster, one cluster head (CH) and several cluster members (CMs). Cluster members gather data from the environment periodically and send the data to cluster heads. Cluster heads aggregate the data from their cluster members, and send the aggregated data to the base station (BS). There are two kinds of communications between cluster heads and the BS, single-hop communication and multi-hop communication. In multi-hop communication clustering algorithms, the energy consumption of cluster heads consists of the energy for receiving, aggregating and sending the data from their cluster members (intra-cluster energy consumption) and the energy for forwarding data for their neighbor cluster heads (inter-cluster energy consumption) [1]. Cluster-based communication protocols have significant savings in total energy consumption of a sensor network. In these protocols, creation of clusters and assigning special tasks to cluster heads can greatly contribute to overall system scalability, lifetime, and bandwidth efficiency [6].Clustering reduces the energy dissipation in the network by aggregating the messages of cluster members ,thus reducing the number of messages being transferred to the sink. Moreover, the size of the clusters must be optimum as exploiting both small and large clusters would make the sensor networks energy inefficient. When the cluster size is very large (e.g. one cluster of whole network), the nodes have to transmit data very far to the cluster head, consuming more energy. And when the cluster size is very small (e.g. one node in each cluster) the number of messages to be transferred to the sink increases, so the energy saving by aggregation would be reduced, thus resulting in more dissipation of network energy. [6] Clustering is grouping of sensor nodes. Here, each cluster is managed by a special node or leader, called cluster head (CH), which is responsible for coordinating the data transmission activities of all sensors in its group.CH is decided with a different probability [7,8].The selection of cluster head in the clusters contribute a lot to the overall efficiency. In clustering networks, the imbalanced energy consumption among nodes is the key factor affecting the network lifetime. In order to balance the energy consumption among nodes, clustering algorithms for networks with uniform node distribution tend to construct uniformly distributed cluster heads, so that the clusters have the approximate number of members and coverage areas. Thus, the intra-cluster energy consumption of cluster heads is approximate and the energy consumption of cluster heads can be balanced. For cluster members, the maximum communicate distances of cluster members are approximate, because of the uniform cluster sizes. Thus, the energy consumption of cluster members can be balanced too. Therefore, the uniformly distributed cluster head set can balance the energy consumption among nodes and finally prolong the network lifetime [1]. Leach is the very basic protocol used for uniformly distributed nodes. It is simple and does not require a large communication overhead. But its performance in heterogeneous networks is not very well; because it elects cluster heads without considering the residual energy of the nodes .To solve this problem. Researchers improved LEACH and proposed new algorithms [1, 9-11]. Also, LEACH has a disadvantage of non-uniform energy consumption by the cluster heads, so they dissipate their energy quickly. Its proposed solution is non uniform clustering.
To Enhance the Lifetime of Wireless Sensor Network Using a Novel Approach Based on Clustering
2014
Sensor networks are dense wireless networks of small, low-cost sensors, which collect and disseminate environmental data. Wireless sensor networks facilitate monitoring and controlling of physical environments from remote locations with better accuracy. They have applications in a variety of fields such as environmental monitoring, military purposes and gathering sensing information in inhospitable locations. The sensor nodes in Wireless Sensor Network are battery powered devices which consumes energy during data transmission, processing, etc. The critical task in WSN is to deal with optimizing energy consumption. In this our main focus is for enhancing the energy levels in WSN nodes by saving energy using concept of multi sink scenario.
Enery Efficient Clustering Algorithm for Maximizing Network Lifetime in Wireless Sensor Networks
A wireless sensor network is the version of adhoc networks consisting nodes with less energy power fitted with a radio transceiver. The primary constraint of a sensor node is its energy resource limitation in the form of a short battery lifetime. Energy is the critical problem while we design the algorithm for wireless sensor networks to maximize the network lifetime. Hence we have to design the algorithm for bringing down energy use and maximizing network lifetime. In this paper, we proposed energy efficient clustering algorithm for clustering in wireless sensor network to increase the energy power and maximizing the network lifetime of wireless sensor networks. In this algorithm cluster heads are chosen based on the highest residual energy from the home station. In the previous LEACH algorithm cluster heads are selected which node is the highest residual energy from the nearest neighbor nodes. The simulation results demonstrate that minimal energy is consumed compared with the previous LEACH algorithm using the NS-2 simulator.