Application of improved black hole algorithm in prolonging the lifetime of wireless sensor network

Wireless sensor network is an emerging technology capable of having low-cost and low-power and battery-powered sensor node. At this point the protocol concentric clustered power-efficient gathering in sensor information systems and clustered general self organized tree based energy-balance routing protocol energy efficient protocol are used to increase the energy and to extend network lifetime. For these achievement of clustering techniques, optimization technique particle swarm optimization is used for data transmission through base station. If the base station is inaccessible region from the cluster-head, energy consumption will be augmented and it can shrink the lifetime of wireless sensor network. To conquer these, multi-hop gateway node is implemented with both protocol to achieve maximum lifetime and energy efficiency of wireless sensor network. To improve the quality-of-service (QoS) placing more number of gateways is required. So we propose a new algorithm nearer optimal algorithm which recursively computes least possible adequate dominating sets, at the time constantly preserving QoS requirements across iterations. In this paper comparison is done in terms of throughput, packets delivery ratio and number of nodes alive.

Limited energy supply (battery-powered) is a crucial problem in wireless sensor networks (WSNs). Sensor node placement schemes and routing protocols are mostly proposed to address this problem. In this paper, we first present how to place sensor nodes by use of a minimal number of them to maximize the coverage area when the communication radius of the sensor node is different from the sensing radius, which results in the application of regular topology to WSNs deployment. With nodes placed at an equal distance and equipped with an equal power supply, the problem of unbalanced energy consumption in 2-D regular topologies becomes more severe and much more difficult to tackle than that in 1-D chains, though the latter is known as an already quite hard problem. We address this problem and propose an adaptive data collection scheme by employing different communication radii for nodes in different locations to balance the energy consumption in WSNs. In order to achieve the ultimate goal of maximizing network lifetime in grid-based WSNs, we give a mathematical formulation, which shows the problem of maximizing network lifetime is a nonlinear programming problem and NP-hard even in the 1-D case. We discuss several heuristic solutions and show that the halving shift data collection scheme is the best solution among them. We also generalize the maximizing network lifetime problem to the randomly-deployed WSNs, which shows the significance of our mathematical formulation for this crucial problem in WSNs.

Wireless sensor networks (WSNs) are formed using a cluster of sensor nodes (SNs), deployed randomly to perform sensing operations in an area under observation. Due to the unavailability of an external power source, the energy efficiency considered as one of the critical issues in WSNs. Selection of a sensor node (SN) from a wireless sensor network (WSN) cluster to serve as an aggregator or cluster head (CH), considered as an efficient method to increase the lifetime of wireless sensor network (WSN). In this paper, we have proposed an energy efficient CH selection scheme for WSN, to enhance the lifetime and average residual energy of a single WSN cluster. The proposed strategy nominates a group SNs as CHs, based on their channel condition with the base station (BS) and their residual energy. The proposed algorithm is helpful in solving the problem of unbalanced energy consumption in WSNs. Furthermore, the mechanism of using mobile sink during the hand-off stage helps to overcome the delay in data transmission. Moreover, the incorporation of energy harvesting significantly increases the lifetime of WSN. In comparison to a state-of-art technique available in the literature, our scheme shows a 33% increase in lifetime and presents a steady decrease in residual energy for the same rounds of data transmission.

Division of the entire wireless sensor network geographic area into number of equal sized regions by applying virtual grid and strategy to appoint head node of the cluster in each region improves stability, consistency, and lifetime of the wireless sensor network. Applying the same size of grid to the different size of wireless sensor networks will not give consistent performance. In this paper, we are presenting a protocol which will dynamically determine the size of the virtual grid, which will give optimal performance of any geographic sized wireless sensor network. The protocol also allows to place sink node to any location and not at some fixed specific location. Protocol discussed in this paper can also support multiple sink nodes. Protocol dynamically takes decision to transmit the data directly to the sink node or by using multi-hop transmission by considering distances between sensor nodes internally and sink node(s), which will optimize energy efficiency of the sensor nodes and increases the lifetime of wireless sensor network.

One of the major challenges in wireless sensor networks (WSNs) deployment is to decrease sensor node's energy consumption to prolong the lifetime of the finite-capacity batteries. Using multihop has been viewed as one of the main techniques to prolong operational lifetime in wireless sensor networks. In this paper we offer a study on transmission power control (TPC) in multihop WSNs using typical Telosb platform parameters, which is IEEE 802.15.4 standard compliant. We offer a new approach to test TPC in multihop networks at the physical layer and provide energy consumption performance results via simulation and numerical model in multihop WSNs. Our simulation and numerical model results illustrate that energy spent to send packets using short-range multihop path instead of single hop does not necessarily save energy as suggested by some of the earlier research.

We analyze the impact of the structure of the Data Gathering (DG) trees on node lifetime (round of first node failure) and network lifetime (minimum number of rounds by which the network gets either disconnected due to node failures or the fraction of coverage loss reaches a threshold) in wireless sensor networks through extensive simulations. The two categories of DG trees studied are: the Bottleneck Node Weight-Based (BNW-DG) trees and Bottleneck Link Weight-Based (BLW-DG) trees. The BNW-DG trees incur a smaller diameter and a significantly larger fraction of nodes as leaf nodes: thus, protecting a majority of the nodes in the network from simultaneously being exhausted of the energy resources (contributing to a significantly larger network lifetime); nevertheless the nodes that serve as intermediate nodes in the first few instances of the BNW-DG trees are bound to lose their energy more quickly than the other nodes, leading to a smaller node lifetime compared to that of the BLW-DG trees (that incur a larger diameter and a relatively lower fraction of nodes as leaf nodes).

—Wireless sensor networks are composed of a large number of sensor nodes with limited energy resources. One critical issue in wireless sensor networks is how to gather sensed information in an energy efficient way, since their energy is limited. The clustering algorithm is a technique used to reduce energy consumption. It can improve the scalability and lifetime of wireless sensor networks. In this paper, we introduce a clustering protocol with mode selection (CPMS) for wireless sensor networks. Our scheme improves the performance of BCDCP (Base Station Controlled Dynamic Clustering Protocol) and BIDRP (Base Station Initiated Dynamic Routing Protocol) routing protocol. In CPMS, the base station constructs clusters and makes the head node with the highest residual energy send data to the base station. Furthermore, we can save the energy of head nodes by using the modes selection method. The simulation results show that CPMS achieves longer lifetime and more data message transmissions than current important clustering protocols in wireless sensor networks.

Major Wireless Sensor Network designs are focused on improving the network lifetime. The data aggregation process is the simplest way to achieve this. The PEGASIS routing protocol is a promising approach for efficient data aggregation in Wireless Sensor Networks. It is also reported in the literature that the PEGASIS performs better than LEACH and HEED protocol towards improving the network lifetime. However, in PEGASIS, the selection of a leader located far away from the base station still remains exposed to higher energy consumption for sending aggregated data. In this paper, we propose an enhancement to the chain formation process of PEGASIS to further improve its lifetime, and called it PEGASIS with Improved Network Lifetime (PEGASIS-INL). In contrast to original PEGASIS protocol, the PEGASIS-INL selects a node as a leader only if it is within a strong communication range of base station. A multiple overlapped chain formation and the aggregation technique is used for transmission of sensed information to the base station. Experimental results demonstrate that the PEGASIS-INL algorithm outperforms PEGASIS in terms of the product of consumed energy and delay, weighting the overall performance of both the energy consumption and the network lifetime.

Wireless sensor networks offer a lot of potential to improve our ability to see and manage the physical world, but the issue of power consumption in these networks has emerged as a key factor in their dependability and in many use cases for networks. End-to-end quality parameters for wireless sensors must be guaranteed, and these networks' support for quality of service is crucial. The lifespan of each network in wireless sensor networks, which is closely correlated with the energy use of the network sensors, is one of the most crucial challenges. One of the most difficult tasks in these types of networks is to extend the network's lifetime. The most efficient strategy for reducing power consumption in wireless sensor networks is clustering, which is presented in this study. This is the most efficient approach for increasing the scalability and lowering the energy consumption of wireless sensor networks. The simulation results demonstrate that the suggested algorithm may significantly extend the lifetime of the wireless sensor network and decrease its energy consumption.

It is important to prolong the network lifetime in Wireless Sensor Networks. There are two approaches to increase the network lifetime, which are balancing energy consumption and reducing the number of non-working nodes. This paper presents two Cluster head Selection algorithms, one is based on Ensuring target Area and the other is based on Affinity Propagation. We propose a method which makes the energy uniformly distributed throughout the network nodes. In particular, we analyse the effect of the powerful nodes on the network lifetime and cluster characteristics. Simulation results show that the two proposed algorithms distribute non-working nodes evenly, such that the target area is well covered by the remaining nodes. Our proposed algorithms balance the traffic load and energy distributions, and prolong the network lifetime effectively compared with the existing schemes.

Wireless Sensor Networks (WSN) concentrate on the essential problem of increasing the network lifetime of WSN, which are bordered by low capacity batteries1,3 One of the fundamental egresses in WSN is maximizing the network lifetime by mitigating the Hotspot problem. It is the problem of isolation of sink node due to energy diminution of nodes most closelipped to sink1. In WSN nodes which are most adjacent to the Base Station (BS) need to relay many packets while compare with nodes far away from the sink. The outcome of this approach is these nodes deplete their energy very quickly. It results in a network partitioning and reduces the network lifetime. This paper proposes and evaluates a technique for maximizing the lifetime of WSN by preventing sink isolation due to hotspot problem. The clustering mechanism can be used to reduce the energy depletion of node near to the sink node. The cluster is formed based on distance attribute. This mechanism provides the scalability and avoids the redundancy through data collection operation. This paper will analyze the energy consumption of proposed technique using various distance measures. *Author for correspondence Indian Journal of Science and Technology, Vol 7(S4), 92–98, April 2014 ISSN (Print) : 0974-6846 ISSN (Online) : 0974-5645 Increase the Lifetime of WSN by Preventing Sink Isolation using Supercluster Formation R. Devika1 , B. Santhi2 and T. Sivasubramanian3 1,2School of Computing, SASTRA University, Thanjavur, India; srdevika.cse@sastra.edu, b.shanthi@sastra.edu 3 Kings College of Engineering, Punalkulam, Pudhukkotai District, India; shivamiru@gmail.com Keywords: Clustering Mechanism, Data Aggregation Operation, Hotspot Problem, Network Lifetime, Sink

The lifetime of Wireless Sensor Network (WSN) is based on the energy of each sensor. Therefore, numerous routing protocols have been introduced such as SEP (Stable Election Protocol), LEACH (Low energy adaptive clustering hierarchy) and EAMMH (Energy Aware Multi-hop Multi-path Hierarchical routing protocol) to stable the lifetime of WSN by efficient utilization of energy of the sensors. In WSN networks data is collected and forwarded wirelessly to the base stations. Routing protocols in WSN provide an efficient path for multi-hop communication because the transmission range and battery power storage of nodes is limited. As nodes are usually deployed in remote areas so, they face challenges of long lifetime, network architecture, security issues, and network coverage. Many routing protocols have been developed to increase the efficiency of networks. Out of these clustering algorithms are the best choice to increase the lifetime of the nodes. Each protocol has its limitations in different scenarios. In this paper, we discussed and compared the performance of LEACH, EAMMH and SEP. SEP is an efficient algorithm due to its weighted cluster head (CH) selection method. Simulation results are obtained using MATLAB. Design metrics of energy consumption and network lifetime are under consideration in this research work.

In this article, efficient power saving scheme and corresponding algorithm must be developed and designed in order to provide reasonable energy consumption and to improve the network lifetime for wireless sensor network systems. The clusterbased technique is one of the approaches to reduce energy consumption in wireless sensor networks. In this article, we propose a saving energy clustering algorithm to provide efficient energy consumption in such networks. The main idea of this article is to reduce data transmission distance of sensor nodes in wireless sensor networks by using the uniform cluster concepts. In order to make an ideal distribution for sensor node clusters, we calculate the average distance between the sensor nodes and take into account the residual energy for selecting the appropriate cluster head nodes. The lifetime of wireless sensor networks is extended by using the uniform cluster location and balancing the network loading among the clusters. Simulation results indicate the superior performance of our proposed algorithm to strike the appropriate performance in the energy consumption and network lifetime for the wireless sensor networks.

Adequate clustering provides an effective way for prolonging the lifetime of a wireless sensor network (WSN). Most proposed clustering algorithms do not consider the location of the base station. This will lead to the hot spots problem in multi-hop WSNs. In this paper, a fuzzy clustering topology is employed to prolong the lifetime of WSNs. Considering the residual energy, the distances to the base station and influence of neighboring parameters of the sensor nodes, the cluster-head radius are adjusted by fuzzy clustering topology. This helps to decrease the intra-cluster traffic load of sensor nodes closer to the base station or having lower battery level. The uncertainties in the estimation of cluster-head radius are handled by fuzzy logic. Our approach is compared with some popular algorithms in literature, including LEACH, Gupta and CHEF. Our approach performs in various performance metrics, such as First Node Dies (FND), Half of the Nodes Alive (HNA), Last Node Dies (LND) and energy-efficiency metrics. Simulation results show that the proposed method performs better than the other algorithms, up to 54% in certain cases. Therefore, this method is a stable and energy-efficient clustering algorithm can be applied to any real-world WSN applications.

Using the mobile sink for data collection from all sensors is the most highly effective way to prolong the network lifetime of wireless sensor networks(WSNs). Many studies focused on the anchors selection, aiming to reduce the path length of mobile sink and prolong the network lifetime. However, the appropriateness and the number of the selected anchors, which significantly impact the network lifetime of the entire WSNs, still can be improved. This paper proposes a Dynamic Anchor Points Mechanism for data collection, called DAM, aiming to select appropriate anchors under the path length constraint for prolonging the network lifetime. The experimental results show that the proposed DAM outperforms existing data collection mechanisms in term of network lifetime and fairness index.