Energy Aware Clustering and Aggregate Node Rotation with Sink Relocation in WSN

As the WSN used in industrial and Environmental monitoring the most critical issues in the WSN is to reduce the energy consumption to extend the lifetime of the wireless sensor network. The intermediate hop nodes are working throughout the data transmission so those nodes drain out their energy which automatically reduces the life time of the wireless sensor network. To overcome these drawbacks the EAC-ASR protocol (Energy Aware Clustering Aggregate Node Rotation) with sink relocation method four important processes which are present in this protocol was Clustering, data aggregation, mobile node rotation by swapping algorithm and sink relocation are applied. In this paper theoretical analysis and the simulation analysis are done and the result shows that the EAC-ASR protocol reduces the energy consumption and increase the energy efficiency. DOI: 10.17762/ijritcc2321-8169.150316

MobileR : Multi-hop energy efficient localised mobile georouting in wireless sensor and actuator networks

International audienceThis paper addresses the usage of actuators (sensors with controlled mobility) for routing in wireless sensor and actuator networks. Different routing protocols have been proposed to improve routing in terms of energy efficiency through the use of controlled mobility enabled sensors . We introduce MobileR. Unlike literature proposals also using actuators, MobileR considers the cost of a full path toward one of its neighbours instead of the cost of the direct edge toward it. To do so, MobileR computes in advance the possible routing paths over the next hops relying on the one-hop neighbours and their possible relocations. Moreover MobileR is fully localised and stateless. We evaluate our solution in terms of cumulative energy consumption with regard to network density. Experiments show that, with sufficient node degree, energy used for routing is significantly reduced and so network lifetime is extended

An improved ant colony optimization-based approach with mobile sink for wireless sensor networks

Traditional wireless sensor networks (WSNs) with one static sink node suffer from the well-known hot spot problem, that of sensor nodes near the static sink bear more traffic load than outlying nodes. Thus, the overall network lifetime is reduced due to the fact some nodes deplete their energy reserves much faster compared to the rest. Recently, adopting sink mobility has been considered as a good strategy to overcome the hot spot problem. Mobile sink(s) physically move within the network and communicate with selected nodes, such as cluster heads (CHs), to perform direct data collection through short-range communications that requires no routing. Finding an optimal mobility trajectory for the mobile sink is critical in order to achieve energy efficiency. Taking hints from nature, the ant colony optimization (ACO) algorithm has been seen as a good solution to finding an optimal traversal path. Whereas the traditional ACO algorithm will guide ants to take a small step to the next node using current information, over time they will deviate from the target. Likewise, a mobile sink may communicate with selected node for a relatively long time making the traditional ACO algorithm delays not suitable for high real-time WSNs applications. In this paper, we propose an improved ACO algorithm approach for WSNs that use mobile sinks by considering CH distances. In this research, the network is divided into several clusters and each cluster has one CH. While the distance between CHs is considered under the traditional ACO algorithm, the mobile sink node finds an optimal mobility trajectory to communicate with CHs under our improved ACO algorithm. Simulation results show that the proposed algorithm can significantly improve wireless sensor network performance compared to other routing algorithms

Study of Challenges in Sensor Node Deployment in Wireless Sensor Network

Wireless Sensor Network is a network which consists of tiny sensors that senses required information from the sorrounding and passes it to the destination for further processing. Deployment of sensor node in wireless sensor network is the way of placing sensors in network for the collection of desired information from environment. Performance of a network in an application depends on the proper deployment of the sensor nodes. Particularly, when it is the case of heterogeneous sensor network, at most focus is required while deploying sensor nodes. Improper deployment reduces the efficiency of the network. It may not be always possible to deploy the sensor nodes easily .Particularly, in harsh environment, it is too difficult to deploy the nodes. In this paper we give a description of the different types of node deployment schemes and challenges developed so far for wireless sensor network

Single Sink Repositioning Technique in Wireless Sensor Networks for Increasing Throughput and Decreasing Delay

Wireless sensor network (WSN) refers to a group of spatially spread and enthusiastic sensors for monitoring and recording the physical conditions of the environment and organizing the collected data at a central location. WSN becomes an energetic subject with the rapid development that is vulnerable to a varied high-quality of attacks due to deployment in the hostile environment. In WSN, throughput is defined as the amount of data transferred from one sensor node to another in a specified amount of time. Delay It refers to the total time taken for a single packet to be transmitted across a network from source to destination. The basic idea of sink relocation is to shorten the distance between sink node and sensor node. So, that significant power savings can be achieved. The problem of distant node energy consumption of wireless sensor node was solved by sink repositioning technique which has capability to move and communicate with all sensor node inside the region. The sink node and sensor node are randomly deployed within the geographic extent of the entire network. In order to test for the impact of repositioning the total power transmission of the sensors for the previous and next sink positions is evaluated and compared. This is result in increasing life time of sensor network by putting sink node at optimum location to decrease the distant node, increases throughput and decrease delay with sink node and analyze the difference. The main aim of the study was to increase throughput and decrease end to end delay. For this study we have used NS-2.35 environment for simulation. Our simulation results show that repositioning the sink achieves significant change on throughput and delay when compared to the static sink approach that have been presented by using network animator(NAM) and Xgraph. Keywords: WSN, Sink node, sensor node, throughput, delay and  sink reposition. DOI: 10.7176/CEIS/11-5-01 Publication date:September 30th 202

Single Sink Repositioning Technique in Wireless Sensor Networks for Increasing Throughput and Decreasing Delay

Wireless sensor network (WSN) refers to a group of spatially spread and enthusiastic sensors for monitoring and recording the physical conditions of the environment and organizing the collected data at a central location. WSN becomes an energetic subject with the rapid development that is vulnerable to a varied high-quality of attacks due to deployment in the hostile environment. In WSN, throughput is defined as the amount of data transferred from one sensor node to another in a specified amount of time. Delay It refers to the total time taken for a single packet to be transmitted across a network from source to destination. The basic idea of sink relocation is to shorten the distance between sink node and sensor node. So, that significant power savings can be achieved. The problem of distant node energy consumption of wireless sensor node was solved by sink repositioning technique which has capability to move and communicate with all sensor node inside the region. The sink node and sensor node are randomly deployed within the geographic extent of the entire network. In order to test for the impact of repositioning the total power transmission of the sensors for the previous and next sink positions is evaluated and compared. This is result in increasing life time of sensor network by putting sink node at optimum location to decrease the distant node, increases throughput and decrease delay with sink node and analyze the difference. The main aim of the study was to increase throughput and decrease end to end delay. For this study we have used NS-2.35 environment for simulation. Our simulation results show that repositioning the sink achieves significant change on throughput and delay when compared to the static sink approach that have been presented by using network animator(NAM) and Xgraph. Keywords:- WSN, Sink node, sensor node, throughput, delay and  sink reposition. DOI: 10.7176/NCS/12-02 Publication date: January 31st 202

SINK REPOSITIONING OPTIMIZATION TECHNIQUE USING PARTICLE SWARM OPTIMIZATION IN WIRELESS SENSOR NETWORKS

In today’s wireless sensor networks mobile sinks plays an important role in data transmission and reception. Therefore it becomes very important to estimate the optimized position of the mobile sinks in order to improve the overall efficiency of the wireless sensor networks. In this paper, the particle swarm optimization technique has been used for the estimation of the position of the mobile sinks and its impact on the various performance factors of the wireless sensor network has been observed. The simulation result showed that finding the optimal location of the sink in the mobile environment improves the various performance parameters of the network thereby extending the overall lifetime of the network

Mobility based energy efficient and multi-sink algorithms for consumer home networks

With the fast development of the Internet, wireless communications and semiconductor devices, home networking has received significant attention. Consumer products can collect and transmit various types of data in the home environment. Typical consumer sensors are often equipped with tiny, irreplaceable batteries and it therefore of the utmost importance to design energy efficient algorithms to prolong the home network lifetime and reduce devices going to landfill. Sink mobility is an important technique to improve home network performance including energy consumption, lifetime and end-to-end delay. Also, it can largely mitigate the hot spots near the sink node. The selection of optimal moving trajectory for sink node(s) is an NP-hard problem jointly optimizing routing algorithms with the mobile sink moving strategy is a significant and challenging research issue. The influence of multiple static sink nodes on energy consumption under different scale networks is first studied and an Energy-efficient Multi-sink Clustering Algorithm (EMCA) is proposed and tested. Then, the influence of mobile sink velocity, position and number on network performance is studied and a Mobile-sink based Energy-efficient Clustering Algorithm (MECA) is proposed. Simulation results validate the performance of the proposed two algorithms which can be deployed in a consumer home network environment

A Hybrid Sink Repositioning Technique for Data Gathering in Wireless Sensor Networks

Wireless sensor network (WSN) is a wireless network that consists of spatially distributed autonomous devices using sensors to cooperatively investigate physical or environmental conditions. WSN has a hundreds or thousands of nodes that can communicate with each other and pass data from one node to another. Energy can be supplied to sensor nodes by batteries only and they are configured in a harsh environment in which the batteries cannot be charged or recharged simply. Sensor nodes can be randomly installed and they autonomously organize themselves into a communication network. The main constraint in wireless sensor networks is limited energy supply at the sensor nodes so it is important to deploy the sink at a position with respect to the specific area which is the area of interest; which would result in minimization of energy consumption. Sink repositioning is very important in modern day wireless sensor network since repositioning the sink at regular interval of time can balance the traffic load thereby decreasing the failure rate of the real time packets. More attention needs to be given on the Sink repositioning methods in order to increase the efficiency of the network. Existing work on sink repositioning techniques in wireless sensor networks consider only static and mobile sink. Not much importance is given to the hybrid sink deployment techniques. Multiple sink deployment and sink mobility can be considered to perform sink repositioning. Precise information of the area being monitored is needed to offer an ideal solution by the sink deployment method but this method is not a realistic often. To reallocate the sink, its odd pattern of energy must be considered. In this chapter a hybrid sink repositioning technique is developed for wireless sensor network where static and mobile sinks are used to gather the data from the sensor nodes. The nodes with low residual energy and high data generation rate are categorized as urgent and the nodes with high residual energy and low data generation rate are categorized as non-urgent. Static sink located within the center of the network collects the data from the urgent nodes. A relay is selected for each urgent sensor based on their residual energy. The urgent sensor sends their data to the static sink through these relay. Mobile sink collects the data from the non-urgent sensors. The performance of the proposed technique is compared with mobile base station placement scheme mainly based on the performance according to the metrics such as average end-to-end delay, drop, average packet delivery ratio and average energy consumption. Through the simulation results it is observed that the proposed hybrid sink repositioning technique reduces the energy hold problem and minimizes the buffer overflow problem thereby elongating the sensor network lifetime