INVESTIGATION ON ENERGY BASED DATA GATHERING APPROACH FOR WSN

Wireless Sensor Networks plays a vital role in all emerging areas of Wireless Platforms like Interne of Things (IoT), WiFi, WiMAX etc. Sensor nodes are communicated with or without the presence of administrator. Data gathering is a major issue in WSN which influences the throughput, energy and data delivery. In previous research, there was not taken efforts to focus on balanced data gathering.  In this research, we propose Reliable Energy Efficient Data Gathering Approach (REEDGA) to balance data gathering and overhead. To achieve this, proposed work consists of three phases. In first phase, estimation of information gathering is implemented through stable paths. Stable paths are found based on link cost. In second phase, data gathering phase is initialized to save energy in the presence of mobile sensor nodes. Overhead is kept low while keeping round trip time of gathered data. From the analytical simulation using NS2, the proposed approach achieves better performance in terms of data delivery rate, data gathering rate, throughput, delay, link availability and control overhead

Spread Spectrum based QoS aware Energy Efficient Clustering Algorithm for Wireless Sensor Networks

Wireless sensor networks (WSNs) are composed of small, resource-constrained sensor nodes that form self-organizing, infrastructure-less, and ad-hoc networks. Many energy-efficient protocols have been developed in the network layer to extend the lifetime and scalability of these networks, but they often do not consider the Quality of Service (QoS) requirements of the data flow, such as delay, data rate, reliability, and throughput. In clustering, the probabilistic and randomized approach for cluster head selection can lead to varying numbers of cluster heads in different rounds of data gathering. This paper presents a new algorithm called "Spread Spectrum based QoS aware Energy Efficient Clustering for Wireless sensor Networks" that uses spread spectrum to limit the formation of clusters and optimize the number of cluster heads in WSNs, improving energy efficiency and QoS for diverse data flows. Simulation results show that the proposed algorithm outperforms classical algorithms in terms of energy efficiency and QoS

Random traveling wave pulse coupled oscillator (RTWPCO) algorithm of energy-efficient wireless sensor networks

Energy-efficient pulse-coupled oscillators have recently gained significant research attention in wireless sensor networks, where the wireless sensor network applications mimic the firefly synchronization for attracting mating partners. As a result, it is more suitable and harder to identify demands in all applications. The pulse-coupled oscillator mechanism causing delay and uncharitable applications needs to reduce energy consumption to the smallest level. To avert this problem, this study proposes a new mechanism called random traveling wave pulse-coupled oscillator algorithm, which is a self-organizing technique for energy-efficient wireless sensor networks using the phase-locking traveling wave pulse-coupled oscillator and random method on anti-phase of the pulse-coupled oscillator model. This technique proposed in order to minimize the high power utilization in the network to get better data gathering of the sensor nodes during data transmission. The simulation results shown that the proposed random traveling wave pulse-coupled oscillator mechanism achieved up to 48% and 55% reduction in energy usage when increase the number of sensor nodes as well as the packet size of the transmitted data compared to traveling wave pulse-coupled oscillator and pulse-coupled oscillator methods. In addition, the mechanism improves the data gathering ratio by up to 70% and 68%, respectively. This is due to the developed technique helps to reduce the high consumed energy in the sensor network and increases the data collection throughout the transmission states in wireless sensor networks

A firefly-inspired scheme for energy-efficient transmission scheduling using a self-organizing method in a wireless sensor network

Various types of natural phenomena are regarded as primary sources of information for artificial occurrences that involve spontaneous synchronization. Among the artificial occurrences that mimic natural phenomena are Wireless Sensor Networks (WSNs) and the Pulse Coupled Oscillator (PCO), which utilizes firefly synchronization for attracting mating partners. However, the PCO model was not appropriate for wireless sensor networks because sensor nodes are typically not capable to collect sensor data packets during transmission (because of packet collision and deafness). To avert these limitations, this study proposed a self-organizing time synchronization algorithm that was adapted from the traditional PCO model of fireflies flashing synchronization. Energy consumption and transmission delay will be reduced by using this method. Using the proposed model, a simulation exercise was performed and a significant improvement in energy efficiency was observed, as reflected by an improved transmission scheduling and a coordinated duty cycling and data gathering ratio. Therefore, the energy-efficient data gathering is enhanced in the proposed model than in the original PCO-based wave-traveling model. The battery lifetime of the Sensor Nodes (SNs) was also extended by using the proposed model

Underwater spray and wait routing technique for mobile ad-hoc networks

1648-1655The underwater mobile ad-hoc networks comprise sensor nodes that are source nodes for gathering underwater-related data. Relay nodes are the mobile nodes for collecting data from sensor nodes and achieving intermittent connectivity among source and destination nodes. Developing an efficient routing protocol for underwater communication is a challenging issue due to limitations of the underwater environment. Underwater mobile ad-hoc networks are intermittent networks where end-to-end path does not exist from source to destination. To overcome these problems a delay and disruption tolerant network (DTN) is a good solution. In the current paper, we consider the Spray and Wait (SaW) routing technique. In SaW, source and relay nodes represents the moving nodes, and they try to send data to destination nodes. Based on this, we propose the replica based underwater SaW (USaW) routing for underwater mobile ad-hoc networks. In USaW, source nodes are fixed to the bottom of the surface. Underwater sensor nodes replicate sensor data and provide maximum copies of data to the relay nodes that they encounter. In generally, relay nodes have high capability of transmitting data as compared to sensor nodes in an underwater environment. We analyze the performance of USaW with respect to delivery ratio, network throughput, energy consumption, end-to-end delay, and packet drop rate comparing with existing SaW and prophet routing protocols

ENERGY-EFFICIENT PROTOCOL DESIGN AND ANALYSIS FOR WIRELESS SENSOR NETWORKS

Wireless sensor networks are an emerging technology which has the promise of revolutionizing the way of collecting, processing and disseminating information. Due to the small sizes of sensor nodes, resources like battery capacity, memory and processing power are very limited. Wireless sensor networks are usually unattended oncedeployed and it is infeasible to replace batteries. Designing energy-efficient protocols to prolong the network life without compromising too much on the network performance is one of the major challenges being faced by researchers.Data generation in wireless sensor networks could be bursty as it is dictated by the presence or absence of events of interest that generate these data. Therefore sensor nodes stay idle for most of the time. However, idle listening consumes as much energy as receiving. To save the unnecessary energy consumption due to idlelistening, sensor nodes are usually put into sleep.MAC protocols coordinate data communications among neighboring nodes. We designed an energy-efficient MAC protocol called PMAC in which sleep-awake schedules are determined through pattern exchange. PMAC also adapts to different traffic conditions.To handle bursty traffic and meanwhile preserve energy, dual radio interfaces with different ranges, capacity and power consumption can be employed on each individual sensor node. We designed a distributed routing-layer switch agent which intelligently directs traffic between the dual radios. The low-power radio will be used for light traffic load to preserve energy. The high-power radio is turned on only when the traffic load becomes heavy or the end-to-end delay exceeds a certain threshold. Each radio has its own routing agent so that a better path can be found when the high-power radio is in use.Data gathering is a typical operation in wireless sensor networks where data flow through a data gathering tree towards a sink node. DMAC is a popular energyefficient MAC protocol specifically designed for data gathering in wireless sensor networks. It employs staggered sleep-awake schedules to enable continuous data forwarding along a data gathering tree, resulting in reduced end-to-end delays and energy consumption. we have analyzed end-to-end delay and energy consumption with respect to the source node for both constant bit rate traffic and stochastic traffic following a Poisson process. The stochastic traffic scenario is modeled as a discrete time Markov chain and expressions for state transition probabilities, the average delay and average energy consumption are developed and are evaluated numerically. Simulations are carried out with various parameters and the results are in line with the analytical results.Lots of work had been done on constructing energy-efficient data gathering trees at the routing layer. We proposed a sleep scheme at the routing layer called DGSS which could be incorporated into different data gathering tree formation algorithms. Unlike DMAC, in which nodes are scanned level by level, DGSS starts scanningfrom the leaf nodes and shrinks inward towards the sink node. Simulation shows that DGSS can achieve better energy efficiency than DMAC at relatively higher data rates

QoS BASED ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORK

A Wireless Sensor Networks (WSN) is composed of a large number of low-powered sensor nodes that are randomly deployed to collect environmental data. In a WSN, because of energy scarceness, energy efficient gathering of sensed information is one of the most critical issues. Thus, most of the WSN routing protocols found in the literature have considered energy awareness as a key design issue. Factors like throughput, latency and delay are not considered as critical issues in these protocols. However, emerging WSN applications that involve multimedia and imagining sensors require end-to-end delay within acceptable limits. Hence, in addition to energy efficiency, the parameters (delay, packet loss ratio, throughput and coverage) have now become issues of primary concern. Such performance metrics are usually referred to as the Quality of Service (QoS) in communication systems. Therefore, to have efficient use of a sensor node’s energy, and the ability to transmit the imaging and multimedia data in a timely manner, requires both a QoS based and energy efficient routing protocol. In this research work, a QoS based energy efficient routing protocol for WSN is proposed. To achieve QoS based energy efficient routing, three protocols are proposed, namely the QoS based Energy Efficient Clustering (QoSEC) for a WSN, the QoS based Energy Efficient Sleep/Wake Scheduling (QoSES) for a WSN, and the QoS based Energy Efficient Mobile Sink (QoSEM) based Routing for a Clustered WSN. Firstly, in the QoSEC, to achieve energy efficiency and to prolong network/coverage lifetime, some nodes with additional energy resources, termed as super-nodes, in addition to normal capability nodes, are deployed. Multi-hierarchy clustering is done by having super-nodes (acting as a local sink) at the top tier, cluster head (normal node) at the middle tier, and cluster member (normal node) at the lowest tier in the hierarchy. Clustering within normal sensor nodes is done by optimizing the network/coverage lifetime through a cluster-head-selection algorithm and a sleep/wake scheduling algorithm. QoSEC resolves the hot spot problem and prolongs network/coverage lifetime. Secondly, the QoSES addressed the delay-minimization problem in sleep/wake scheduling for event-driven sensor networks for delay-sensitive applications. For this purpose, QoSES assigns different sleep/wake intervals (longer wake interval) to potential overloaded nodes, according to their varied traffic load requirement defined a) by node position in the network, b) by node topological importance, and c) by handling burst traffic in the proximity of the event occurrence node. Using these heuristics, QoSES minimizes the congestion at nodes having heavy traffic loads and ultimately reduces end-to-end delay while maximizing the throughput. Lastly, the QoSEM addresses hot spot problem, delay minimization, and QoS assurance. To address hot-spot problem, mobile sink is used, that move in the network to gather data by virtue of which nodes near to the mobile sink changes with each movement, consequently hot spot problem is minimized. To achieve delay minimization, static sink is used in addition to the mobile sink. Delay sensitive data is forwarded to the static sink, while the delay tolerant data is sent through the mobile sink. For QoS assurance, incoming traffic is divided into different traffic classes and each traffic class is assigned different priority based on their QoS requirement (bandwidth, delay) determine by its message type and content. Furthermore, to minimize delay in mobile sink data gathering, the mobile sink is moved throughout the network based on the priority messages at the nodes. Using these heuristics, QoSEM incur less end-to-end delay, is energy efficient, as well as being able to ensure QoS. Simulations are carried out to evaluate the performance of the proposed protocols of QoSEC, QoSES and QoSEM, by comparing their performance with the established contemporary protocols. Simulation results have demonstrated that when compared with contemporary protocols, each of the proposed protocol significantly prolong the network and coverage lifetime, as well as improve the other QoS routing parameters, such as delay, packet loss ratio, and throughput

Optimal coverage multi-path scheduling scheme with multiple mobile sinks for WSNs

Wireless Sensor Networks (WSNs) are usually formed with many tiny sensors which are randomly deployed within sensing field for target monitoring. These sensors can transmit their monitored data to the sink in a multi-hop communication manner. However, the ‘hot spots’ problem will be caused since nodes near sink will consume more energy during forwarding. Recently, mobile sink based technology provides an alternative solution for the long-distance communication and sensor nodes only need to use single hop communication to the mobile sink during data transmission. Even though it is difficult to consider many network metrics such as sensor position, residual energy and coverage rate etc., it is still very important to schedule a reasonable moving trajectory for the mobile sink. In this paper, a novel trajectory scheduling method based on coverage rate for multiple mobile sinks (TSCR-M) is presented especially for large-scale WSNs. An improved particle swarm optimization (PSO) combined with mutation operator is introduced to search the parking positions with optimal coverage rate. Then the genetic algorithm (GA) is adopted to schedule the moving trajectory for multiple mobile sinks. Extensive simulations are performed to validate the performance of our proposed method