Energy Efficient and QoS Aware Framework for Video Transmission over Wireless Sensor Networks

Wireless Multimedia Sensor Networks (WMSNs), is a network of sensors, which are limited in terms of memory, computing, bandwidth, and battery lifetime. Multimedia transmission over WSN requires certain QoS guarantees such as huge amount of bandwidth, strict delay and lower loss ratio that makes transmitting multimedia is a complicated task. However, adopting cross-layer approach in WMSNs improves quality of service of WSN under different environmental conditions. In this work, an energy efficient and QoS aware framework for transmitting multimedia content over WSN (EQWSN) is presented, where packet, queue and path scheduling were introduced. It adapts the application layer parameter of video encoder to current wireless channel state, and drops less important packets in case of network congestion according to packet type. Finally, the path scheduling differentiates packets types/priority and route them through different paths with different QoS considering network lifetime. Simulation results show that the new scheme EQWSN transmits video quality with QoS guarantees in addition to prolonging network lifetime.

Performance Analysis of an Enhanced Load Balancing Scheme for Wireless Sensor Networks

Research interest in sensor networks routing largely considers minimization of energy consumption as a major performance criterion to provide maximum sensors network lifetime. When considering energy conservation, routing protocols should also be designed to achieve fault tolerance in communications. Moreover, due to dynamic topology and random deployment, incorporating reliability into protocols for WSNs is very important. Hence, we propose an improved scalable clustering-based load balancing scheme (SCLB) in this paper. In SCLB scheme, scalability is achieved by dividing the network into overlapping multihop clusters each with its own cluster head node. Simulation results show that the proposed scheme achieves longer network lifetime with desirable reliability at the initial state compare with the existing multihop load balancing approach.

L3SN: A Level-Based, Large-Scale, Longevous Sensor Network System for Agriculture Information Monitoring

We developed L3SN, a scalable, longevous, adaptive, and internet accessible wireless sensor network system for agriculture information monitoring, which is meticulously designed to meet the requirement of thousands hectares coverage, years of time monitoring and the adverse environment. The system architecture, the agriculture sensor device, the mesh protocol, and the web-based information processing platform are introduced. We also presented some implementation experience. The mesh protocol (LayerMesh) is highlighted, in which “stair scheduling” and “distributed dynamic load-balancing” are proposed to response the scalability, longevity and adaptivity requirements. We believe the design of L3SN is useful to many other large-scale, longevous applications such as hydrologic monitoring, geological monitoring etc.

A Survey on Modeling and Enhancing Reliability of Wireless Sensor Network

Design of reliable wireless sensor network (WSN) needs to address the failure of single or multiple network components and implementation of the techniques to tolerate the faults occurred at various levels. The issues and requirements of reliability improvement mechanism depend on the available resources and application for which the WSN is deployed. This paper discusses the different modeling approaches to evaluate the reliability and classification of the approaches to improve it. Also the paper analyzes reliability enhancement by existing fault tolerant methods in WSN and compares the performance of these techniques with the technique we developed. From the results of the analysis we highlight the challenges and the characteristics of the sensor network affects the reliability and give some scope of future research directions in order to enhance reliability.

Comparison of Correlation Dimension and Fractal Dimension in Estimating BIS index

This paper compares the correlation dimension (D2) and Higuchi fractal dimension (HFD) approaches in estimating BIS index based on of electroencephalogram (EEG). The single-channel EEG data was captured in both ICU and operating room and different anesthetic drugs, including propofol and isoflurane were used. For better analysis, application of adaptive segmentation on EEG signal for estimating BIS index is evaluated and compared to fixed segmentation. Prediction probability (PK) is used as a measure of correlation between the predictors and BIS index to evaluate the proposed methods. The results show the ability of these algorithms (specifically HFD algorithm) in predicting BIS index. Also, evolving fixed and adaptive windowing methods for segmentation of EEG reveals no meaningful difference in estimating BIS index.

Generation of Multiple Weights in the Opportunistic Beamforming Systems

A new scheme to generate multiple weights used in opportunistic beamforming (OBF) system is proposed to deal with the performance degradation due to the fewer active users in the OBF system. In the proposed scheme, only two mini-slots are employed to create effective channels, while more channel candidates can be obtained via linearly combining the two effective channels obtained during the two mini-slots, thus increas-ing the multiuser diversity and the system throughputs. The simulation results verify the effectiveness of the proposed scheme.

Analysis of Geo Positioning System Using RF &DA

Indoor positioning systems (IPSs) have been intended to provide position information of persons and devices. Higher user percentage of handheld devices such as tablets or mobile phones had led to the development of a number of indoor positioning systems. In this research a work on a real time portable RFID indoor positioning device such as on smartphone will be performed. The personal networks will be designed to meet the users’ needs and interconnect users’ devices equipped with different communications technologies in various places to form one network for better result. Radio frequency identification (RFID) with directional antenna has proved its potential for locating objects in indoor environment. Hence, the proposed device idea will be used to exploit various unknown locations in an indoor environment such as college campus;this interpretation will rely on Wireless LAN, Received Signal Strength values from Access Points (AP) in specific mentioned arenas;these APs will be monitored constantly by RFID with directional antenna (DA) and handheld devices. For obtaining the better results from existing devices, algorithms of Range Estimation are proposed, which can be used on various handheld devices for locating indoor objects.

Nanorobotic Agents Communication Using Bee-Inspired Swarm Intelligence

The main goal of this paper is to design nanorobotic agent communication mechanisms which would yield coordinated swarm behavior. Precisely we propose a bee-inspired swarm control algorithm that allows nanorobotic agents communication in order to converge at a specific target. In this paper, we present experiment to test convergence speed and quality in a simulated multi-agent deployment in an environment with a single target. This is done to measure whether the use of our algorithm or random guess improves efficiency in terms of convergence and quality. The results attained from the experiments indicated that the use of our algorithm enhance the coordinated movement of agents towards the target compared to random guess.

Evaluation of Multiusers’ Interference on Radiolocation in CDMA Cellular Networks

Radiolocation has been previously studied for CDMA networks, the effect of Multiple Access Interference has been ignored. In this paper we investigate the problem of Radiolocation in the presence of Multiple Access Interference. An extensive simulation technique was developed, which measures the error in location estimation for different network and user configurations. We include the effects of lognormal shadow and Rayleigh fading. Results that illustrate the effects of varying shadowing losses, number of base stations involved in position location, early-late discriminator offset and cell sizes in conjunction with the varying number of users per cell on the accuracy of radiolocation estimation was presented.

Energy Harvesting Strategy Using Piezoelectric Element Driven by Vibration Method

This study demonstrates a method for harvesting the electrical power by the piezoelectric actuator from vibration energy. This paper presents the energy harvesting technique using the piezoelectric element of a bimorph type driven by a geared motor and a vibrator. The geared motor is a type of PWM controlled device that is a combination of an oval shape cam with five gears and a speed controller. When using the geared motor, the piezoelectric element is size of 36L×13W×0.6H. The output voltage characteristics of the piezoelectric element were investigated in terms of the displacement and vibration. When using the vibrator, the electric power harvesting is based on piezoelectric effect and piezoelectric vibrator consists of a magnetic type oscillator, a cantilever, a bimorph actuator and controllers. Low frequency operating technique using piezoelectric vibrator is very important because normal vibration sources in the environment such as building, human body, windmill and ship have low frequency characteristics. We can know from this study results that there are many energy sources such as vibration, wind power and wave power. Also, these can be used to the energy harvesting system using smart device like piezoelectric element.

Effect of Landslide on Energy Efficiency Chain Based Routing Protocol for Wireless Sensor Network

Wireless sensor network has been used as a landslide monitoring tool for more than one decade. The robustness of the network is important as the systems need to survive in harsh conditions. In this paper, we consider the living time of the sensor network under the influences of the small-scale landslide. We investigate the performance of famous energy-efficient routing protocol PEGASIS in both landslide case and non-landslide case. Genetic Algorithm is also applied to enhance the effectiveness of PEGASIS. The simulation results in this paper showed that the Genetic Algorithm helps to delay the first node death if it is used at the beginning of data transmission while being used every round helps to prolong last node death slightly. The impact of the Genetic Algorithm on energy usage and route length is also examined. Under the effect of landslide, with only 70% of energy are spent, the simulated protocols reduced around 30% equivalent route length while managed to keep the living time up the network up to 90.76%, comparing to cases with no landslide.

A Novel Low-Complexity Low-Latency Power Efficient Collision Detection Algorithm for Wireless Sensor Networks

Collision detection mechanisms in Wireless Sensor Networks (WSNs) have largely been revolving around direct demodulation and decoding of received packets and deciding on a collision based on some form of a frame error detection mechanism, such as a CRC check. The obvious drawback of full detection of a received packet is the need to expend a significant amount of energy and processing complexity in order to fully decode a packet, only to discover the packet is illegible due to a collision. In this paper, we propose a suite of novel, yet simple and power-efficient algorithms to detect a collision without the need for full-decoding of the received packet. Our novel algorithms aim at detecting collision through fast examination of the signal statistics of a short snippet of the received packet via a relatively small number of computations over a small number of received IQ samples. Hence, the proposed algorithms operate directly at the output of the receiver's analog-to-digital converter and eliminate the need to pass the signal through the entire. In addition, we present a complexity and power-saving comparison between our novel algorithms and conventional full-decoding (for select coding schemes) to demonstrate the significant power and complexity saving advantage of our algorithms.

A Distributed Trust Based Secure Communication Framework for Wireless Sensor Network

The wireless sensor network is an emerging technology, which is used to sense and monitor the environment. As the nodes are deployed in an open environment, the security is one of the essential factors. The cryptography techniques can ensure confidentiality, integrity and authentication. However, wireless sensor network also needs to deal with inside and outside attackers. To deal with outside attackers, attacks by compromised or malicious nodes, trust management system is suggested by many researchers in the area of wireless sensor network. Trust management system can be implemented in various applications for security management such as secure data aggregation, secure cluster head selection, trusted routing, access control, etc. Many researchers provide different kind of solutions for these secure applications based on trust management. However, to incorporate, all such applications on a single sensor node in the network, it is essential to design and develop a trust management system, which considers various aspects and applications of wireless sensor network. As a result, in this paper, we would like to propose a parameter and trust factor based secure communication framework and design a trust management system for wireless sensor networks. Our main contribution is to identify various parameters and trust factors which influences on trust in wireless sensor network and developing a framework for a trust management system based on various parameters and trust factors. The working of the proposed model is shown by simulation experiments conducted in MATLAB for the application of secure communication, data aggregation and intrusion detection in wireless sensor networks.

Complexity Results for Wireless Sensor Network Scheduling

We study the problem of scheduling multi sensors to visit and observe a group of sites at discrete time points over a planning horizon of given length. We show that scheduling under a given number of visits for each site and in each period is an NP-complete problem by providing equivalence with a problem in discrete tomography. We also give a polynomial time algorithm to schedule the sensors under a given number of visits in each period.

A Malicious and Malfunctioning Node Detection Scheme for Wireless Sensor Networks

Wireless sensor networks are often used to monitor physical and environmental conditions in various regions where human access is limited. Due to limited resources and deployment in hostile environment, they are vulnerable to faults and malicious attacks. The sensor nodes affected or compromised can send erroneous data or misleading reports to base station. Hence identifying malicious and faulty nodes in an accurate and timely manner is important to provide reliable functioning of the networks. In this paper, we present a malicious and malfunctioning node detection scheme using dual-weighted trust evaluation in a hierarchical sensor network. Malicious nodes are effectively detected in the presence of natural faults and noise without sacrificing fault-free nodes. Simulation results show that the proposed scheme outperforms some existing schemes in terms of mis-detection rate and event detection accuracy, while maintaining comparable performance in malicious node detection rate and false alarm rate.

Compressing Information of Target Tracking in Wireless Sensor Networks

Target tracking is a well studied topic in wireless sensor networks. It is a procedure that nodes in the network collaborate in detecting targets and transmitting their information to the base-station continuously, which leads to data implosion and redundancy. To reduce traffic load of the network, a data compressing based target tracking protocol is proposed in this work. It first incorporates a clustering based data gather method to group sensor nodes into clusters. Then a novel threshold technique with bounded error is proposed to exploit the spatial correlation of sensed data and compress the data in the same cluster. Finally, the compact data presentations are transmitted to the base-station for targets localization. We evaluate our approach with a comprehensive set of simulations. It can be concluded that the proposed method yields excellent performance in energy savings and tracking quality.

Underdetermined Blind Mixing Matrix Estimation Using STWP Analysis for Speech Source Signals

Wavelet packets decompose signals in to broader components using linear spectral bisecting. Mixing matrix is the key issue in the Blind Source Separation (BSS) literature especially in under-determined cases. In this paper, we propose a simple and novel method in Short Time Wavelet Packet (STWP) analysis to estimate blindly the mixing matrix of speech signals from noise free linear mixtures in over-complete cases. In this paper, the Laplacian model is considered in short time-wavelet packets and is applied to each histogram of packets. Expectation Maximization (EM) algorithm is used to train the model and calculate the model parameters. In our simulations, comparison with the other recent results will be computed and it is shown that our results are better than others. It is shown that complexity of computation of model is decreased and consequently the speed of convergence is increased.

Research on DOA Estimation of Multi-Component LFM Signals Based on the FRFT

A novel algorithm for the direction of arrival (DOA) estimation based on the fractional Fourier transform (FRFT) is proposed. Firstly, using the properties of FRFT and mask processing, Multi-component LFM sig-nals are filtered and demodulated into a number of stationary single frequency signals. Then the one-dimensional (1-D) direction estimation of LFM signals can be achieved by combining with the tradi-tional spectrum search method in the fractional Fourier (FRF) domain. As for the multi-component LFM signals, there is no cross-term interference, the mean square error (MSE) and Cramer-Rao bound (CRB) are also analyzed which perfects the method theoretically, simulation results are provided to show the validity of our method. The proposed algorithm is also extended to the uniform circular array (UCA), which realizes the two-dimensional (2-D) estimation. Using the characteristics of time-frequency rotation and demodulation of FRFT, the observed LFM signals are demodulated into a series of single frequency ones;secondly, operate the beam-space mapping to the single frequency signals in FRF domain, which UCA in array space is changed into the virtual uniform circular array (ULA) in mode space;finally, the DOA estimation can be realized by the traditional spectral estimation method. Compared with other method, the complex time-frequency cluster and the parameter matching computation are avoided;meanwhile enhances the esti-mation precision by a certain extent. The proposed algorithm can also be used in the multi-path and Doppler frequency shift complex channel, which expands its application scope. In a word, a demodulated DOA esti-mation algorithm is proposed and is applied to 1-D and 2-D angle estimation by dint of ULA and UCA re-spectively. The detailed theoretical analysis and adequate simulations are given to support our proposed al-gorithm, which enriches the theory of the FRFT.

Problem of Standardization of Configuration Data in Wireless Sensor Networks: The Case of Routing Protocols

The exploitation of Wireless Sensor Networks (WSN) is constrained by limited power, low computing power and storage and short-range radio transmission. Many routing protocols respecting these constraints were developed but, it still lacks formal and standardized solutions being able to help in their configuration. The configuration management that responds to this concern is very important in this type of network. It consists of the definition of data models to configure and is very necessary for the good network performance. Tangible results were obtained in traditional networks with the emergence of NETCONF and YANG standards, but on the best of our humble knowledge there are none yet in WSNs. We propose in this paper wsn-routing-protocol, a YANG data model for routing protocols configuration in WSNs. Following our model, we propose two YANG configuration data models based on the latter: they are respectively aodv for AODV and rpl for RPL.

WEP and WPA Improvement

This paper aims to describe a solution to improve wireless network security protocols WEP and WPA based on a modified RC4 algorithm for encryption, and based on initialization vector (IV) with secret key for a session key exchange, and new mutual authentication mechanism.