With limited battery power of nodes, communication energy consumption is the main factor to affect the lifetime of wireless sensor networks. It is of great significance to design a communication protocol to prolong the lifetime of the networks. In this paper, an energy-efficient LEACH algorithm for wireless sensor networks is proposed, which takes the energy and position factors of each node into account to optimize the cluster head election and data transmission mode. This method introduces the current energy and position factors of the node into the threshold to further reduce the randomness of the cluster head's designation. In the data transmission stage, some of the neighboring cluster heads are dedicated to be selected as the relay nodes to make the communication energy consumption balanced. The simulation results show that the proposed algorithm has higher stability and longer lifetime of the network compared to LEACH and LEACH-C algorithms.

Wireless sensor networks have the potential to become significant subsystems of engineering applications where every each node functions as transmitter, receiver, router and data sink. It is necessary to understand the dynamic behaviour of these systems in simulation environments. It is critical to develop simulation platforms that are useful which can be used to explore both networking and wireless sensor networks issues. A discrete-event simulation is a trusted platform for modeling and simulating a variety of systems. This project emphasize on using new simulator for wireless sensor networks that is based on the discrete event simulation framework called Objective Modular Network Test bed in C++ version 4.1 (OMNeT++4.1) Simulator. This simulator is used to test the performance of sensor nodes within the networking in wireless communication networks based on indoor scenario. The test performances are focussed on aspects such as the time delay and packet utilization of the particular approach. The analysis approach is done through simulation software by the following metrics: packet frames delivery, packet loss and time delay experience within the system.

Wireless sensor networks are engaged in various data gathering applications. The major bottleneck in wireless data gathering systems is the finite energy of sensor nodes. By conserving the on board energy, the life span of wireless sensor network can be well extended. Data communication being the dominant energy consuming activity of wireless sensor network, data reduction can serve better in conserving the nodal energy. Spatial and temporal correlation among the sensor data is exploited to reduce the data communications. Data similar cluster formation is an effective way to exploit spatial correlation among the neighboring sensors. By sending only a subset of data and estimate the rest using this subset is the contemporary way of exploiting temporal correlation. In Distributed Similarity based Clustering and Compressed Forwarding for wireless sensor networks, we construct data similar iso-clusters with minimal communication overhead. The intra-cluster communication is reduced using adaptive-normalized least mean squares based dual prediction framework. The cluster head reduces the inter-cluster data payload using a lossless compressive forwarding technique. The proposed work achieves significant data reduction in both the intra-cluster and the inter-cluster communications, with the optimal data accuracy of collected data.

Wireless sensor networks (WSNs) composed from a lar ge number of sensor node with the ability to sense and process data in the p hysical world in a timely manner. The sensor nodes contain a battery constraint which limit the network lifetime. Due to energy constraints, the deployment of WSNs will required advance techniques to maintain the network lifetime. A clustering based r outing algorithm called LowEnergy Adaptive Clustering Hierarchy (LEACH) was pr o osed as a solution for low power consumption. This document is a study about L EACH algorithm where the implementation was done using OMNeT++ network simul ator to study the performance of this algorithm in term of network li fet me. OMNeT++ was selected as a simulator because it provides some important f eatures for this project like very good scalability unlike other simulators do. During this study, LEACH algorithm shows some drawbacks that need an improvements to o vercome it as to improve the performance. Then, the modified LEACH algorithm was proposed where the improvement was done in cluster head selection base d on LEACH. In cluster head selection, modified LEACH taking into account the r esidual energy of each node for calculation of the threshold value for next round. Meanwhile in LEACH, the cluster head selection was based on distributed algorithm. Both of these protocols was implemented in network simulator to compare the per formance. This study shows that there were a better performance achieved by mo dified LEACH depends on the results obtained.

Wireless sensor networks (WSNs) as an emerging technology face numerous challenges. Sensor nodes are usually resources constrained,also, they are vulnerable to physical attacks or node compromises. Autonomic Computing is a steadily emerging and promising research field. In the domain of simplifying interoperability, it aims to diminish the management complexity in several industries and systems. Self-protection in WSNshasn’t been deeply studied before, because ofthe high rate of fails. The major concern in WSN is to maximize the network’s Lifetime.In this paper,a framework that embeds autonomic capabilities into WSN systems is proposed. The proposed framework provides self-protection features in cases of unauthorized, inadvertent and intentional change in security parameters.

Wireless sensor networks (WSNs) are utilized in various applications and are providing the backbone for the new pervasive Internet, or Internet of Things. The development of a reliable and robust large-scale WSN system requires that the design concepts are checked and optimized before they are implemented and tested for a specific hardware platform. Simulation provides a cost effective and feasible method of examining the correctness and scalability of the system before deployment. In this work, we study the performance of Pymote, a high level Python library for event based simulation of distributed algorithms in wireless ad-hoc networks. We extended the Pymote framework allowing it to simulate packet level performance. The extension includes radio propagation, energy consumption, mobility and other models. The extended framework also provides interactive plotting, data collection and logging facilities for improved analysis and evaluation of the simulated system.

Wireless sensor networks (WSNs) are utilized in various applications and are providing the backbone for the new pervasive Internet, or Internet of Things. The development of a reliable and robust large-scale WSN system requires that the design concepts are checked and optimized before they are implemented and tested for a specific hardware platform. Simulation provides a cost effective and feasible method of examining the correctness and scalability of the system before deployment. In this paper, we study the performance of Pymote, a high level Python library for event-based simulation of distributed algorithms in wireless ad-hoc networks. We extended the Pymote framework allowing it to simulate packet level performance. The extension includes radio propagation, energy consumption, mobility and other models. The extended framework also provides interactive plotting, data collection and logging facilities for improved analysis and evaluation of the simulated system.

Wireless sensor networks (WSNs) are utilized in various applications and are providing the backbone for the new pervasive Internet, or Internet of Things (IoT). Researchers are working on merging other emerging technologies and services such as cloud computing and Big data with IoT to design and build smart cities. Energy consumption is one the important constraint in the design of WSN based system. The sensor nodes typically rely on power sources like batteries which also makes it bulky. Recent advances in ambient energy harvesting technology have made it a potential alternative energy source for WSNs. However, this energy is not available continuously at the desired level and therefore the node need to utilize the sporadic availability of energy to sense and transmit the data efficiently and as quickly as possible. Energy Harvesting-based WSNs (EHWSNs) are the result of granting nodes the capability to extract energy from ambient sources. Due to limited power, it is imperative to optimize every aspect of the WSN including communication protocols. The heart of all this optimization is the medium access control (MAC) layer. In this paper, we study the performance of different MAC schemes for WSNs. Later we proposed a new scheme for better utilization of EHWSN in certain application and provide simulation and experimental results. The cloud services provide the resources to process the information from hundreds of regional IoT systems at a higher level.

Wireless sensor networks (WSN) are widely used in various situations. Energy saving is one of the most important issues because of the limited power. Communication is the mainly energy consuming part of sensor nodes. Reducing the size of transmitted data can conserve the energy of nodes. Spatial and temporal correlation is ubiquitous in wireless sensor networks. By exploiting spatial and temporal correlation, only a subset of data need to be transmitted and the rest of the data can be estimated. Data aware clustering is an effective way to exploit spatial correlation among sensor nodes. In our SC-EEDC framework, fuzzy ART artificial neural network is used to measure the shape similarity among data sequences and the magnitude similarity is estimated by a magnitude similarity model. And two corresponding estimation algorithm are proposed. We propose Weighting based K-means clustering algorithm (WK-means), which considers multiple clustering factors in addition to the data similarity. The K-means algorithm structure is introduced in clustering algorithm to search the more energy-saving clustering topology. Anchor node based data collection strategy is proposed to measure the spatial correlation in real time and suppress the transmission of spatial redundant data at source node. Sleeping scheduling is introduced to dynamically adjust the spatial sampling rate and the temporal redundancy is reduced using Length Encoding. The cluster maintenance scheme keeps the cluster structure’s efficiency over the network lifetime. Simulation results show that our SC-EEDC achieves significant data reduction without affecting the accuracy of collected data, reduces the energy consumption in each round of data collection and effectively prolongs the network lifetime.

Wireless sensor network has revolutionized the way computing and software services are delivered to the clients on demand. Wireless sensor network is very important to the mankind. It consist of number of sensor called nodes and a base station. Nodes collect data and send to the base station. There are number of nodes which send data at a time. So, number of problems are occurred. So, far this nodes are divided into cluster then a cluster head will be formed. WSN is a battery powered system. When the battery is died no data send or received. So when all nodes participate for sending and receiving data then system is died earlier. Our research work proposed a new method for cluster head selection having less computational complexity. It was also found that the modified approach has improved performance to that of the other clustering approaches. The network area is divided into same sized small–small regions. Sensor nodes are randomly deployed in each predefined sub-area. Each region will have its region head (RH) and multiple member nodes. The member nodes in a specific region will send the data to the RH. RH within the region will be elected by distributed mechanism and will be based on fuzzy variables. It was found that the proposed algorithm gives a much improved network lifetime as compared to existing work. Based on our model, transmission tuning algorithm for cluster-based WSNs has been proposed to balance the load among cluster heads that fall in different regions. This algorithm is applied prior to a cluster algorithm to improve the performance of the clustering algorithm without affecting the performance of individual sensor nodes.

Wireless sensor network (WSNs) composed from a large number of sensor node with the ability to sense and process data in the physical world in a timely manner. The sensor nodes contain a battery constraint which limit the network lifetime. Due to energy constraints, the deployment of WSNs will required advance techniques to maintain the network lifetime. A clustering based routing algorithm called Low-Energy Adaptive Clustering Hierarchy (LEACH) was proposed as a solution for power consumption. This paper studies LEACH protocol, but some modification needed because of deficiencies in LEACH protocol. Simulation result shows that modified LEACH algorithm prolong the network lifetime.

Wireless automation is an emerging field of research that aims at significant savings in installation time and costs of cabling in automation systems, while providing a new level of flexibility for system design, reconfiguration, and agility. Wireless sensor networks (WSNs) are a rather new technology, with its origins tracing back to the early 1980s through the Distributed Sensor Networks (DSNs) program at the Defense Advanced Research Project Agency (DARPA) of the US Department of Defense. Industrial Wireless Sensor Network (IWSN) evolved from WSN and are specially designed, keeping in mind the demands and nature of industry. Two common protocols ZigBee and WirelessHART were designed for general commercial use and later adopted for industrial applications. ISA100.11a developed by International Society of Automation, was specially designed for IWSN. These protocols use layer structure which allow secure, fast and reliable data transfer. IEEE 802.15.4 is used at its physical layer with variable data slots. This paper presents the results of the simulation of ZigBee, WirelessHART and ISA100 protocols done using Castalia. This paper compares and discusses the simulated results obtained from all three protocols.

Wireless Sensor Networks (WSNs) technology is one of the building blocks ofthe Internet of Things (IoT). Due to their features of easy deployment and flexibility,they are used in many application domains. Low-Power and Lossy Networks(LLNs) are a special type of WSNs in which nodes are largely resources constrained.For LLNs, convergecast is one of the basic traffic modes, where all traffic in the networkis destined to a predefined destination called the sink. While considering theIoT application domains, convergecast is not the only traffic mode in the network.The sink needs to send commands to certain sensors to perform actions. In this application,anycast is another basic traffic mode. In anycast, the traffic from the sinkis destined to any member of a group of potential receivers in the network.Traditionally LLNs are formed by static sensor nodes and rarely change positions.Due to the strict resource constraints in computation, energy and memory ofLLNs, most routing protocols only support static network. However, mobility hasbecome an important requirement for many emerging applications. In these applications,certain nodes are free to move and organize themselves into a connectednetwork. The topology would continuously change due to the movement of nodesand radio links instability. This is a hard task for most routing protocols of LLNs toadapt rapidly to the movement and to reconstruct topology in a timely manner.The goal of this thesis is to propose an efficient mobility support for routingprotocols in LLNs. We focus on convergecast and anycast, which are the most usedtraffic modes in LLNs, in mobile network scenarios.We propose an enhancement mechanism, named RL (RSSI and Level), to supportrouting protocols in convergecast LLNs in mobility. This mechanism helps routingprotocol make faster decisions for detecting mobility and updating next-hop neighborsbut suffers from high overhead. We propose a dynamic control message managementto enhance the overhead performance of RL and implement it on top ofRouting Protocol for Low-power and Lossy network (RPL) and we named it RRD(RSSI, Rank and Dynamic). After taking into account hysteresis of the coveragezone of the transmission range of nodes, we optimized RRD. This enhanced versionis called RRD+. Based on RRD+, we proposed MRRD+ (Multiple, RSSI, Rankand Dynamic) to support multiple sinks in convergecast LLNs in mobility. ADUP(Adaptive Downward/Upward Protocol) is a routing solution that supports bothconvergecast and anycast in LLNs concurrently.We evaluated the performance of our contributions in both simulation usingCooja simulator and experiment (only for ADUP) on TelosB motes. The resultsobtained in both simulation and experiment confirm the efficiency of our routingprotocols.

Wireless Sensor Networks (WSN) became one of the most important areas of research in the world. The Quality of Services (QoS) is the cornerstone of WSN efficiency due to providing the network with all requirements for efficient sending and receiving of data. Because of WSN different infrastructures, there are different QoS parameters required for this environment. In this paper, a general framework to guarantee the WSN QoS is proposed. The proposed framework aims to produce a standard solution for WSN QoS problems. How to solve the problems of traditional protocols, taking into account the compatibility, which may result from a collection of individual solutions in one general framework, is the paper target. Also, the proposed framework adds new strategies like congestion prediction and network management technologies to outperform the previous solutions. Finally, our framework is simulated using network simulation package (NS2) and compared with individual solutions to make sure that it is more robust and efficient, which leads us to standardization.

Wireless Sensor Network (WSN) has become an important technology that enhances our normal daily life. This research focuses on one of the most important concepts in WSN technologies; the power conservation methods. The main objective of this research is improving the power conservation of a sensor node by dynamically adjusting recharging cycle of the solar-fed batteries based on the geographical areas and radiation levels of the areas and consequently prolonging the battery lifetime. The simulation results show that the proposed scheme improves the battery lifetime within the same geographical area from 0.69 year to 1.39 year; as well as across different areas from 0.69 year to 2.78 year.

Ultrasonic signal attenuator is a component of acoustic logging instruments. It is designed to eliminate the direct wave which arrives at receiving probe directly through drill collar without passing through the formation. Wave function is derived from the model of the sound waves propagating in the one-dimensional discontinuous interfaces. The Ultrasonic signal attenuator consists of three units which are composed by five different materials with big wave impedance difference. These three units have good wave filtering effects on different frequency bands because the thickness of five materials is changed. After stacking the three units, an ultrasonic signal attenuator with better wave filtering effects on the whole frequency band is obtained. The design is verified to be feasible through the MATLAB simulation.

To manage file transfer operation, various tools have been developed so far. However, these tools can not respond adequately for conduct a secure transfer. Also few works have been done using encrypted voice controlled system yet. By regarding this lack, we investigate how to built a useful and secure tool. This work presents a novel improved voice controlled FTP tool (Wb-CFTP) using chaotic system. A chaotic system called as logistic map is associated with Wb-FTP designed on the basis of Asp.Net and C#. Here we depict the prominence of encryption in voice controlled systems.

The recent advancements in the wireless sensor networks (WSNs) are mainly motivated by developing in the micro electromechanical systems technology. One of the major issues in WSNs is to develop an energy efficient routing protocol which has a significant impact on the overall lifetime of sensor networks. In this paper, a novel scheme of an energy-based cluster head selection algorithm (ECHA) to support long-lifetime in WSNs is proposed to improve the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol. In the proposed method, the number of the selection cluster heads (CHs) is optimized based on the effect of the distances from the member nodes to the CH, from the CHs to the base station (BS) and the high energy of each CHs. The simulation results show that the proposed scheme outperforms LEACH and LEACH-C by 35% and 5% in saving power consumption for prolonging network lifetime respectively. The impacts of parameters of density of nodes and weighting probability are verified to find out the best cases for ECHA applications.

The performance of surveillance sensor networks, environmental monitoring sensor networks etc. can be improved with the aid of sensors capable of retrieving multimedia content such as image and video data along with scalar data. The images of same scene of interest from multiple coexisting cameras may have overlapping regions. Transmission of these images individually which have redundant information unnecessarily consumes energy hence to overcome this problem we use prioritized region scheduling. Images from the multiple cameras taken as input can be processed into overlapping and non-overlapping region to get to know about redundant information. Our objective is to provide an efficient way to transmit the image to the sink such that improved image quality is perceived at the sink with the consideration of energy, buffer size, and hop count. The proposed protocol “Energy Efficient Prioritized Region Scheduling based Optimal Image Routing (EE-PRSOIR)” optimally transmit image over wireless sensor network. Multiple paths are built and are scored using path conditions based on availability of resources along the paths. Variant parameters such as free buffer size, energy, hop-count and packet loss. The data is transmitted through highest path score paths. The proposed scheme is compared with non-optimal scheme that it transmits the images without calculating the non-overlapping regions and overlapping regions of the original images that are captured and relevant paths are selected according to hop count for routing the image data to sink. Simulation results have demonstrated the effectiveness of the proposed scheme compared to non-optimal scheme using various metrics. In our previous work we have not calculated packet loss across different region and parameter which gives image quality. In this paper we have included and simulation graph shows better image quality and less packet loss across the image region.

The locations of sensor nodes are essential to Wireless Sensor Networks applications. Researchers have proposed many localization algorithms for Wireless Sensor Network and verified them through simulators. In this paper, a system-level node location model that aims to validate proposed algorithms for wireless sensor networks in Matlab environment is proposed. This model can reflect the reality networks effectively. Using this model, researchers can verify the performance of the localization algorithms including run time, location error, and location node numbers.