GREEN ROUTINGSTRATEGY FOR DYNAMICALLY ARRANGED HOMOGENEOUS WSN- MSCT2

Wireless sensor networks (WSN) play a key role in enabling wireless communication technology among several nodes to remotely communicate and exchange information. WSN consists of tiny sensor nodes equipped with battery, scattered in an area to gather information around an environment and send to data collection node known as sink or base station (BS). WSN have been widely used in various applications like agriculture, fire detection, health care and military and has become imperative necessity for future revolutionary area like UAV (unmanned aerial vehicles), IoT (Internet of things) and smart cities which employs large scale sensor nodes. However sensor nodes are limited to battery, memory, low computational power, resource and bandwidth. Continues sensing of events, makes node to drain its battery faster and goes dead fast. For resource constrained WSN, hierarchical cluster based approaches are considered as energy efficient and improves network performance for large scale WSN. Minimizing energy consumption and extending network lifetime are major challenging issues of WSN, clustering methods with optimized routing have offered solution to optimize energy utilization. To balance energy consumption and improve network lifetime many existing hierarchical clustering approaches have been proposed, however existing method does not consider rotation of cluster head (CH) and considers cluster head selection based on residual energy and distance parameter. In this paper we propose an improved energy efficient cluster tree (IEECT) based routing to improve energy efficiency of hierarchical cluster. IEECT considers modification of existing LEACH (Low energy adaptive clustering hierarchy) protocol to improved energy efficient LEACH by considering energy parameters like residual node energy and average network energy. IEECT accounts optimal number of cluster head (CH) and selection of CH is done using threshold value among sensor nodes. Proposed IEECT combines tree based routing and data aggregation scheme to maintain desirable quality of service. Simulation experiments are carried out by using network simulator. Performance of IEECT is evaluated in terms of PDR, delay, energy consumption, network lifetime and overhead.

Node scheduling in wireless sensor networks (WSNs) plays a vital role in conserving energy and lengthening the lifetime of networks, which are considered as prime design challenges. In large-scaled WSNs, especially where sensor nodes are deployed randomly, 100 % coverage is not possible all the times. Additionally, several types of applications of WSNs do not require 100 % coverage. Following these facts, in this paper, we propose a coverage based node scheduling algorithm. The algorithm shows that by sacrificing a little amount of coverage, a huge amount of energy can be saved. This, in turns, helps to increase the lifetime of the network. We provide mathematical analysis, which verifies the correctness of the proposed algorithm. The proposed algorithm ensures balanced energy consumption over the sensor networks. Moreover, simulation results demonstrate that the proposed algorithm almost doubles the lifetime of a wireless sensor network by sacrificing only 5–8 % of coverage.

Sensor devices have been widely applied to variety applications, including internet of things (IoT), cyber physical systems (CPS) and environmental monitoring systems. Because all sensing data in such applications are very important for data analysis and mining in a host machine, sensor devices are equipped with non-volatile memory (NVM) [1] and nonvolatile processor [2], [3] to prevent sensing data in sensor nodes from data loss. As a result, sensing data can be permanently stored in a sensor device without the risk of data loss even if the battery of the sensor device is run out. Based on such observations, the lifetime of a sensor network should be redefined due to non-volatile technologies, such as NVM and NV processor. Conventionally, the lifetime of a sensor network is the time at which the first sensor node uses up its battery due to the consideration of sensor network QoS [4], [5]. However, since sensing data can be permanently stored in a local drive, the lifetime of a sensor network should be redefined as the time at which the first out-of-date data is produced in a sensor node. If the battery of a sensor node is run out but the sensor node does not contain any out-of-date data, the sensor node will be regarded as a moribund node. If all moribund nodes can be rescued by a rechargeable technology, the sensor network will be immortal. Such observations motivate us to design an energy-efficient solution to achieve the goal of immortal sensor network by exploiting the benefits of wireless charging vehicle.

Maximization of lifetime of wireless sensor network (WSN) is an emerging area of research in present scenario. Many authors are performing their research work, so that they could achieve lower energy consumption for the sensor network which leads to increase in lifetime of network. Our work focuses on sink mobility in a fixed trajectory within a wireless sensor network while sensed data are required to be collected. We divide the whole sensor network into two different regions as direct communication area (DCA) and multi-hop communication area (MCA). Sensors node that lies in DCA is at one hop count distance from the sink node trajectory while sensors within MCA are at more than one hop count from the trajectory. We considered all the sensors that are within DCA as subsink nodes. During sink mobility, whenever a subsink is closer to the mobile sink node, then it starts transmitting its data to the sink node. But those sensors that are within MCA needs to search an appropriate sink node for sending its sensed data to the subsink so that on further stage, that subsink could provide those data to the sink node whenever it is in nearest proximity of that subsink. Basically, a sink node is the ultimate destination for the data while a subsink node acts as a relay node for the nodes that are within MCA. So our work is to find out the appropriate subsink node from a given set of subsinks. For doing so, we used location-aided routing on global positioning system (GPS)-enabled sensors and sink node. Our work is validated through simulation experiments using NS-2.

A wireless sensor network (WSN) comprised of a plurality of sensor nodes powered by their internal batteries and one or more base stations. Efficient utilization of the energy resources leads to prolonged network lifetime. In this study, the effects of limiting the total hop count within the network on network lifetime is investigated by using a mixed integer programming (MIP) framework. Our results show that when the hop count of network is limited by minimum hop count, lifetime of network can decrease by %40 of the lifetime obtained without any constraint on hop count. If hop count limit of network is increased by %10, lifetime of network can reach %98 of maximum lifetime obtained without any restrictions on hop count.

A green clustering protocol for mobile sensor network using particle swarm optimization

At present scenario, sensor devices are used in various fields for gathering information so all those data should be secured safely. Securing data is an important role in Wireless Sensor Networks (WSN). WSN is extremely essential for the purpose of reducing the complete redundancy and energy consumption during gathering data among sensor nodes. Optimized data aggregation is needed at cluster head and Base Station (BS) for secured data transmission. Data aggregation is performed in all routers while forwarding data from source to destination node. The complete life time of sensor networks is reducing because of using energy inefficient nodes for the purpose of aggregation. So this paper introduces the optimized methods for securing data (OMSD) which is trust based weights and also completely about the attacks and some methods for secured data transmission.

A large number of sensor nodes are deployed to remote locations and left unattended for a long time in wireless sensor network applications. When a battery-powered sensor node depletes its energy, it is assumed as “dead” and recharging or replacing the battery is not possible in most of the applications. Lifetime of the wireless sensor network depends on the efficient use of available restricted energy. Railway monitoring application of Linear Wireless Sensor Networks (LWSNs) which are a subclass of wireless sensor networks is considered in this paper. The objective of this study is to present the effect of proper node deployment in extending the linear wireless sensor network lifetime. Thanks to proposed deployment scheme, it is shown that the energy consumption of the LWSN is lowered and thus the lifetime of the network is increased.

Nowadays advanced technology of Wireless Sensor Networks used in many applications like health, environment, battle field etc. The sensor nodes equipped with limited power sources. Therefore, efficiently utilizing sensor nodes energy can maintain a prolonged network lifetime . One of the major issues in sensor networks is developing an energy-efficient routing protocol to improve the lifetime of the networks. In this paper, we propose EELBCRP (Energy-Efficient Level Based Clustering Routing Protocol), a protocol for wireless sensor networks. Network partitioned into annular rings by using various power levels at base station and each ring having various sensor nodes. Also consider the residual energy of each node and distance from the BS of nodes as the principle of cluster-head election. The mathematical formulae for election the cluster head is provided. The model developed is simulated in MATLAB. The results are obtained in terms of three metrics- lifetime of the network, number of clusters and energy consumption of clusters heads. From the results of simulation, it is observed that the performance of EELBCRP is better in terms of energy consumption of CH, number of clusters and lifetime of network compared with LEACH.

The sensor network performs gathering, monitoring, and tracking of objects in the given area. The sensor nodes are normally distributed randomly in the network area for collecting the information. The major issues in Wireless Sensor Networks (WSN) are coverage, energy, and limited resources. Sensor Nodes’ (SN) performance depends on so many parameters but normally depends on Residual Energy (RE) and Distance from the base station. The Cluster Head (CH) cooperatively communicates with Base Station (BS) via routing protocols. The proposed Energy Efficient Multilevel Region Based (EEMRB) protocol performs the task by partitioning the entire network area into multiple levels and sub-levels. The sub-levels are partitioned to perform clusters to communicate the sensor via CH (s) using single/multi-hop communication to BS. The proposed protocol is compared with the Stable Election Protocol and shows improvement in network lifetime. Based on the proposed protocol data set, a Multivariate Polynomial Regression (MPR) Model is proposed to predict network lifetime. The model uses packet size and node density as network design parameters. The simulation results show that the size of the packet and network area play a major role in network lifetime. Therefore, the lifetime of the predicted model and EEMRB protocol are close to each other. This prediction model is suitable for the prediction of any network area's lifetime.

Prolonged network lifetime, scalability and efficient load balancing are essential for optimal performance of a wireless sensor network. Clustering provides an effective way of extending the lifetime of a sensor network. Clustering is the process that divides sensor networks into smaller localized group (called clusters) of members with a cluster head. Clustering protocols need to elect optimal number of clusters in hierarchically structured wireless sensor networks. Any clustering scheme that elects clusters uniformly (irrespective of the distance from Base Station) incurs excessive energy usage on clusters proximal and distant to Base Station. In single hop networks a gradual increment in the energy depletion rate is observed as the distance from the cluster head increases[17]. This work focuses on the analysis of wasteful energy consumption within a uniform cluster head election model (EPEM) and provides an analytical solution to reduce the overall consumption of energy usage amongst the clusters elected in a wireless sensor network. A circular model of sensor network is considered, where the sensor nodes are deployed around a centrally located Base Station. The sensor network is divided into several concentric rings centred at the Base Station. A model, Unequal Probability Election Model (UEPEM), which elects cluster heads non-uniformly is proposed. The probability of cluster head election depends on the distance from the Base Station. UEPEM reduces the overall energy usage by about 21% over EPEM. The performance of UEPEM improves as the number of rings is increased.

In this paper, a power-aware routing algorithm with base station assistance for multi-hop wireless sensor networks that increases the operational lifetime of networks is proposed. We consider a practical and feasible network. This network consists of a set of sensor nodes connected by wireless links and only a base station to collect the data from these sensor nodes. In addition, each sensor node has two wireless receiving channels, which one receives messages from other nodes and the other receives assistant messages from the base station that has high transmitting power and is energy-rich. This scheme adequately utilizes the powerful resources of the base station to provide information to sensor nodes, so these nodes can reduce power consumption by using the knowledge to make the reasonable route. In contrast to conventional power-aware algorithms, the proposed algorithm is superiority for large scale sensor networks for maximizing the lifetime of this network.

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.

This paper focuses on enhancement of lifetime in an event driven wireless sensor network (WSN). The network lifetime is enhanced by optimal deployment of sensor nodes in a given region as premature shortening of life takes place leading to uneven consumption of energy. In the proposed scheme, the senor nodes are linearly deployed over the sub-regions and the inter-node distance between the sensor nodes depends on the statistics of events sensed by the sensor nodes in multi hop mode of communication. The performance is measured with respect to the residual energy at each sensor node and total number of days spent by sensor nodes. The lifetime of the sensor network is defined as the survival of some fraction of nodes. For an approximate Poisson distribution for occurrence of events in different sub-regions, the variation of energy consumption in sensor nodes is negligibly small. Further if some nodes are having finite residual energy even after failure of some nodes, then those nodes can continue their communication in single hop mode and hence the lifetime of the network is further extended.

Energy hole refers to the critical issue near the sinks for data collecting, this problem effects the lifetime of wireless sensor network to a great extent. Frequently data forwarding from distributed sensors to the sink will speed up the energy consumption of the sensors near the sink. This circumstance shortens the lifetime of the sensor network. In this paper, an alpha-fraction first strategy was proposed to build a hierarchical model of wireless sensor networks that concerning the energy consumption. The model mixes the so-called relay nodes into the network for transmitting and collecting data from the other sensor nodes. We studied the Farthest First traversal and Harel methods, then combined the proposed alpha-fraction first strategy with the two methods respectively. Three algorithms of FF+Fr(alpha), HD+Fr(alpha), and HL+Fr(alpha) were designed for determining the relay nodes in sensor networks. The algorithms can be used to construct a twotier sensor network with fewer relay nodes than the results of the Farthest First traversal and Harel methods. The proposed strategy also could be used with any other algorithms that regarding for choosing one of many options. The simulation results show that our proposed algorithms perform well. Thus, the network lifetime can be prolonged.