Optimized Energy Scheduling Algorithm for Energy Efficient Wireless Sensor Networks

Wireless sensor networks can be tiny, low cost, intelligent sensors connected with advanced communication systems. WSNs have pulled in significant consideration as a matter of fact that, industrial as well as medical solicitations employ these in monitoring targets, conservational observation, obstacle exposure, movement regulator etc. In these applications, sensor hubs are thickly sent in the unattended environment with little non-rechargeable batteries. This constraint requires energy-efficient systems to drag out the system lifetime. There are redundancies in data sent over the network. To overcome this, multiple virtual spine scheduling has been presented. Such networks problems are called Maximum Lifetime Backbone Scheduling (MLBS) problems. Though this sleep wake cycle reduces radio usage, improvement can be made in the path in which the group heads stay selected. Cluster head selection with emphasis on geometrical relation of the system will enhance the load sharing among the nodes. Also the data are analyzed to reduce redundant transmission. Multi-hop communication will facilitate lighter loads on the network.

A Compact Wearable Slot Antenna for LTE and WLAN Applications

In this paper, a compact wide-band, ultra-thin and flexible slot antenna intended for wearable applications is presented. The presented antenna is designed to provide Wireless Local Area Network (WLAN) and Long Term Evolution (LTE) connectivity. The presented design exhibits a relatively wide bandwidth (1600-3500 MHz below -6 dB impedance bandwidth limit). The antenna is positioned on a 33 mm x 30 mm flexible substrate with a thickness of 50 µm. Antenna properties, such as the far-field radiation patterns, scattering parameter S11 are provided. The presented compact, thin and flexible design along with excellent radiation characteristics are deemed suitable for integration into flexible and wearable devices.

Statistical Modeling of Mobile Fading Channels Based on Triply Stochastic Filtered Marked Poisson Point Processes

Understanding the statistics of non-isotropic scattering multipath channels that fade randomly with respect to time, frequency, and space in a mobile environment is very crucial for the accurate detection of received signals in wireless and cellular communication systems. In this paper, we derive stochastic models for the probability density function (PDF) of the shift in the carrier frequency caused by the Doppler Effect on the received illuminating signal in the presence of a dominant line of sight. Our derivation is based on a generalized Clarke’s and a two-wave partially developed scattering models, where the statistical distribution of the frequency shift is shown to be consistent with the power spectral density of the Doppler shifted signal.

Fabrication of Wearable Antennas through Thermal Deposition

Antennas are devices for transmitting and/or receiving signals which make them a necessary component of any wireless system. In this paper, a thermal deposition technique is utilized as a method to fabricate antenna structures on substrates. Thin-film deposition is achieved by evaporating a source material (metals in our case) in a vacuum which allows vapor particles to travel directly to the target substrate which is encased with a mask that outlines the desired structure. The material then condenses back to solid state. This method is used in comparison to screen printing, chemical etching, and ink jet printing to indicate advantages and disadvantages to the method. The antenna created undergoes various testing of frequency ranges, conductivity, and a series of flexing to indicate the effectiveness of the thermal deposition technique. A single band antenna that is operated at 2.45 GHz intended for wearable and flexible applications was successfully fabricated through this method and tested. It is concluded that thermal deposition presents a feasible technique of producing such antennas.

Effects of Incident Angle and Distance on Visible Light Communication

Visible Light Communication (VLC) provides wireless communication features in illumination systems. One of the key applications is to recognize the user location by indoor illuminators such as light emitting diodes. For localization of individual receivers in these systems, we usually assume that receivers and transmitters are placed in parallel. However, it is difficult to satisfy this assumption because the receivers move randomly in real case. It is necessary to analyze the case when transmitter is not placed perfectly parallel to receiver. It is also important to identify changes on optical gain by the tilted angles and distances of them against the illuminators. In this paper, we simulate optical gain for various cases where the tilt of the receiver and the distance change. Then, we identified changing patterns of optical gains according to tilted angles of a receiver and distance. These results can help many VLC applications understand the extent of the location errors with regard to optical gains of the receivers and identify the root cause.

Analysis of Multilayer Neural Network Modeling and Long Short-Term Memory

This paper analyzes fundamental ideas and concepts related to neural networks, which provide the reader a theoretical explanation of Long Short-Term Memory (LSTM) networks operation classified as Deep Learning Systems, and to explicitly present the mathematical development of Backward Pass equations of the LSTM network model. This mathematical modeling associated with software development will provide the necessary tools to develop an intelligent system capable of predicting the behavior of licensed users in wireless cognitive radio networks.

Computing Continuous Skyline Queries without Discriminating between Static and Dynamic Attributes

Although most of the existing skyline queries algorithms focused basically on querying static points through static databases; with the expanding number of sensors, wireless communications and mobile applications, the demand for continuous skyline queries has increased. Unlike traditional skyline queries which only consider static attributes, continuous skyline queries include dynamic attributes, as well as the static ones. However, as skyline queries computation is based on checking the domination of skyline points over all dimensions, considering both the static and dynamic attributes without separation is required. In this paper, we present an efficient algorithm for computing continuous skyline queries without discriminating between static and dynamic attributes. Our algorithm in brief proceeds as follows: First, it excludes the points which will not be in the initial skyline result; this pruning phase reduces the required number of comparisons. Second, the association between the spatial positions of data points is examined; this phase gives an idea of where changes in the result might occur and consequently enables us to efficiently update the skyline result (continuous update) rather than computing the skyline from scratch. Finally, experimental evaluation is provided which demonstrates the accuracy, performance and efficiency of our algorithm over other existing approaches.

Detecting and Secluding Route Modifiers by Neural Network Approach in Wireless Sensor Networks

In a real world scenario, the viability of the sensor networks has been proved by standardizing the technologies. Wireless sensor networks are vulnerable to both electronic and physical security breaches because of their deployment in remote, distributed, and inaccessible locations. The compromised sensor nodes send malicious data to the base station, and thus, the total network effectiveness will possibly be compromised. To detect and seclude the Route modifiers, a neural network based Pattern Learning predictor (PLP) is presented. This algorithm senses data at any node on present and previous patterns obtained from the en-route nodes. The eminence of any node is upgraded by their predicted and reported patterns. This paper propounds a solution not only to detect the route modifiers, but also to seclude the malevolent nodes from the network. The simulation result proves the effective performance of the network by the presented methodology in terms of energy level, routing and various network conditions.

A Car Parking Monitoring System Using a Line-Topology Wireless Sensor Network

This paper presents a car parking monitoring system using a wireless sensor network. The presented sensor network has a line-shaped topology and adopts a TDMA-based protocol for allowing multi-hop communications. Sensor nodes are deployed in the ground of an outdoor parking lot in such a way that a sensor node monitors a parking space. Each sensor node detects the availability of the associated parking space and transmits the detection result to a sink node via intermediate sensor nodes existing between the source sensor node and the sink node. We evaluate the feasibility of the presented sensor network and the TDMA-based communication protocol through experiments using 11 sensor nodes deployed in a real parking lot. The result shows that the presented car parking monitoring system is robust to changes in the communication environments and efficient for monitoring parking spaces of outdoor parking lots.

Fuzzy Based Particle Swarm Optimization Routing Technique for Load Balancing in Wireless Sensor Networks

Network lifetime improvement and uncertainty in multiple systems are the issues of wireless sensor network routing. This paper presents fuzzy based particle swarm optimization routing technique to improve the network scalability. Significantly, in the cluster formation procedure, fuzzy based system is used to solve the uncertainty and network balancing. Cluster heads play an important role to reduce the energy consumption using particle swarm optimization algorithm, the cluster head sends its information along data packets to the heads with link. The simulation results show that the presented routing protocol can perform load balancing effectively and reduce the energy consumption of cluster heads.

Markov Chain Based QoS Support for Wireless Body Area Network Communication in Health Monitoring Services

Wireless Body Area Networks (WBANs) are essential for real-time health monitoring of patients and in diagnosing of many diseases. WBANs comprise many sensors to monitor a large range of ambient conditions. Quality of Service (QoS) is a key challenge in WBAN, because the different state information of the neighboring nodes has to be monitored in an accurate manner. However, energy consumption gets increased while predicting and maintaining the exact information in highly dynamic environments. In order to reduce energy consumption and end to end delay, Markov Chain Based Quality of Service Support (MC-QoSS) method is designed in the health monitoring services of WBAN communication. The energy consumption gets reduced by forming a Markov chain with high energy nodes in the sensor networks communication path. The low energy level sensor nodes are removed using transitional probability in order to reduce end to end delay. High energy nodes are formed in the chain structure of its corresponding path to enhance communication. After choosing the communication path through high energy nodes, the packets are sent to the sink node from the source node with a higher Packet Delivery Ratio. The simulation result shows that MC-QoSS method improves the packet delivery ratio and reduces energy consumption with minimum end to end delay, compared to existing methods.

Reliable Line-of-Sight and Non-Line-of-Sight Propagation Channel Identification in Ultra-Wideband Wireless Networks

The paper addresses the problem of line-of-sight (LOS) vs. non-line-of-sight (NLOS) propagation link identification in ultra-wideband (UWB) wireless networks, which is necessary for improving the accuracy of radiolocation and positioning applications. A LOS/NLOS likelihood hypothesis testing approach is applied based on exploiting distinctive statistical features of the channel impulse response (CIR) using parameters related to the “skewness” of the CIR and its root mean square (RMS) delay spread. A log-normal fit is presented for the probability densities of the CIR parameters. Simulation results show that different environments (residential, office, outdoor, etc.) have measurable differences in their CIR parameters’ statistics, which is then exploited in determining the nature of the propagation channels. Correct LOS/NLOS channel identification rates exceeding 90% are shown to be achievable for most types of environments. Additional improvement is also obtained by combining both CIR skewness and RMS delay statistics.

Algorithm and Software Based on Multilayer Perceptron Neural Networks for Estimating Channel Use in the Spectral Decision Stage in Cognitive Radio Networks

The use of the Multilayer Perceptron Neural Networks (MLPNN) technique is presented to estimate the future state of use of a licensed channel by primary users (PUs); this will be useful at the spectral decision stage in cognitive radio networks (CRN) to determine approximately in which time instants of future may secondary users (SUs) opportunistically use the spectral bandwidth to send data through the primary wireless network. To validate the results, sequences of occupancy data of channel were generated by simulation. The results show that the prediction percentage is greater than 60% in some of the tests carried out.

Bit Error Rate Analysis of Mobile Communication Network in Nakagami Fading Channel: Interference Considerations

Co-channel interference is one of the major problems in wireless systems. The effects of co-channel interference in a Nakagami fading channel on the ABER (Average Bit Error Rate) with static nodes are well analyzed. In this paper, we derive the ABER with the presence of mobile nodes. ABER is also derived for mobile systems in the presence of co-channel interference.

Importance of E-Participation by U-Society in the Development of the U-City

This paper is to reveal developments in the areas of urban technology in Malaysia. Developments occur intend to add value intelligent city development to the ubiquitous city (U-city) or smart city. The phenomenon of change is called the development of post intelligent cities. U-City development discourse is seen from the perspective of the philosophy of the virtuous city organized by al-Farabi. The prosperity and perfection of a city is mainly caused by human personality factors, as well as its relationship with material and technological aspects of the city. The question is, to what extent to which human factors are taken into account in the concept of U-City as an added value to the intelligent city concept to realize the prosperity and perfection of the city? Previously, the intelligent city concept was developed based on global change and ICT movement, while the U-city added value to the development of intelligent cities and focused more on the development of information and communications technology (ICT). Value added is defined as the use of fiber optic technology that is wired to the use of wireless technology, such as wireless broadband. In this discourse, the debate on the concept of U-City is to the symbiosis between the U-City and the importance of local human e-participation (U-Society) for prosperity. In the context of virtuous city philosophy, it supports the thought of symbiosis so the concept of U-City can achieve sustainability, prosperity and perfection of the city.

Enhancing the Performance of Wireless Sensor Networks Using Low Power Design

Wireless sensor networks (WSNs), are constantly in demand to process information more rapidly with less energy and area cost. Presently, processor based solutions have difficult to achieve high processing speed with low-power consumption. This paper presents a simple and accurate data processing scheme for low power wireless sensor node, based on reduced number of processing element (PE). The presented model provides a simple recursive structure (SRS) to process the sampled data in the wireless sensor environment and to reduce the power consumption in wireless sensor node. Based on this model, to process the incoming samples and produce a smaller amount of data sufficient to reconstruct the original signal. The ModelSim simulator used to simulate SRS structure. Functional simulation is carried out for the validation of the presented architecture. Xilinx Power Estimator (XPE) tool is used to measure the power consumption. The experimental results show the average power consumption of 91 mW; this is 42% improvement compared to the folded tree architecture.

Sleep Scheduling Schemes Based on Location of Mobile User in Sensor-Cloud

The mobile cloud computing (MCC) with wireless sensor networks (WSNs) technology gets more attraction by research scholars because its combines the sensors data gathering ability with the cloud data processing capacity. This approach overcomes the limitation of data storage capacity and computational ability of sensor nodes. Finally, the stored data are sent to the mobile users when the user sends the request. The most of the integrated sensor-cloud schemes fail to observe the following criteria: 1) The mobile users request the specific data to the cloud based on their present location. 2) Power consumption since most of them are equipped with non-rechargeable batteries. Mostly, the sensors are deployed in hazardous and remote areas. This paper focuses on above observations and introduces an approach known as collaborative location-based sleep scheduling (CLSS) scheme. Both awake and asleep status of each sensor node is dynamically devised by schedulers and the scheduling is done purely based on the of mobile users’ current location; in this manner, large amount of energy consumption is minimized at WSN. CLSS work depends on two different methods; CLSS1 scheme provides lower energy consumption and CLSS2 provides the scalability and robustness of the integrated WSN.

Condition Monitoring System of Mine Air Compressors Based on Wireless Sensor Network

In the current mine air compressors monitoring system, there are some difficulties in the installation and maintenance because of the wired connection. To solve the problem, this paper introduces a new air compressors monitoring system based on ZigBee in which the monitoring parameters are transmitted wirelessly. The collecting devices are designed to form a cluster network to collect vibration, temperature, and pressure of air cylinders and other parameters. All these devices are battery-powered. Besides, the monitoring software in PC is developed using MFC. Experiments show that the designed wireless sensor network works well in the site environmental condition and the system is very convenient to be installed since the wireless connection. This monitoring system will have a wide application prospect in the upgrade of the old monitoring system of the air compressors.

Wireless Power Transfer Application in GSM Controlled Robot for Home Automation

The aim of this paper is to combine the concept of wireless power transfer and GSM controlled robot for the application of home automation. The wireless power transfer concept can be well utilized to charge battery of the GSM controlled robot. When the robot has completed its task, it can come to the origin where it can charge itself. Robot can be charged wirelessly, when it is not performing any task. Combination of GSM controlled robot and wireless power transfer provides greater advantage such as; no wastage of charge stored in the battery when the robot is not doing any task. This provides greater reliability that at any instant, robot can do its work once it receives a message through GSM module. GSM module of the robot and user mobile phone must be interfaced properly, so that robot can do task when it receives message from same user mobile phone, not from any other phone. This paper approaches a robotic movement control through the smart phone and control of GSM robot is done by programming in Arduino environment. The commands used in controlling the robot movement are also explained.

Proposal of Commutation Protocol in Hybrid Sensors and Vehicular Networks for Intelligent Transport Systems

Hybrid Sensors and Vehicular Networks (HSVN), represent a hybrid network, which uses several generations of Ad-Hoc networks. It is used especially in Intelligent Transport Systems (ITS). The HSVN allows making collaboration between the Wireless Sensors Network (WSN) deployed on the border of the road and the Vehicular Network (VANET). This collaboration is defined by messages exchanged between the two networks for the purpose to inform the drivers about the state of the road, provide road safety information and more information about traffic on the road. Moreover, this collaboration created by HSVN, also allows the use of a network and the advantage of improving another network. For example, the dissemination of information between the sensors quickly decreases its energy, and therefore, we can use vehicles that do not have energy constraint to disseminate the information between sensors. On the other hand, to solve the disconnection problem in VANET, the sensors can be used as gateways that allow sending the messages received by one vehicle to another. However, because of the short communication range of the sensor and its low capacity of storage and processing of data, it is difficult to ensure the exchange of road messages between it and the vehicle, which can be moving at high speed at the time of exchange. This represents the time where the vehicle is in communication range with the sensor. This work is the proposition of a communication protocol between the sensors and the vehicle used in HSVN. The latter has as the purpose to ensure the exchange of road messages in the available time of exchange.