Showing papers on "Sensor node published in 2015"

Jamming Attacks on Remote State Estimation in Cyber-Physical Systems: A Game-Theoretic Approach

Abstract: We consider security issues in remote state estimation of Cyber-Physical Systems (CPS). A sensor node communicates with a remote estimator through a wireless channel which may be jammed by an external attacker. With energy constraints for both the sensor and the attacker, the interactive decision making process of when to send and when to attack is studied. We formulate a game-theoretic framework and prove that the optimal strategies for both sides constitute a Nash equilibrium of a zero-sum game. To tackle the computation complexity issues, we present a constraint-relaxed problem and provide corresponding solutions using Markov chain theory.

Event-Based Recursive Distributed Filtering Over Wireless Sensor Networks

Abstract: In this technical note, the distributed filtering problem is investigated for a class of discrete time-varying systems with an event-based communication mechanism. Each intelligent sensor node transmits the data to its neighbors only when the local innovation violates a predetermined Send-on-Delta (SoD) data transmission condition. The aim of the proposed problem is to construct a distributed filter for each sensor node subject to sporadic communications over wireless networks. In terms of an event indicator variable, the triggering information is utilized so as to reduce the conservatism in the filter analysis. An upper bound for the filtering error covariance is obtained in form of Riccati-like difference equations by utilizing the inductive method. Subsequently, such an upper bound is minimized by appropriately designing the filter parameters iteratively, where a novel matrix simplification technique is developed to handle the challenges resulting from the sparseness of the sensor network topology and filter structure preserving issues. The effectiveness of the proposed strategy is illustrated by a numerical simulation.

RF energy harvester-based wake-up receiver

Abstract: Wake-up receivers (WuRxs) can improve the lifetime of a wireless sensor network by reducing energy consumption from undesirable idle listening. The amplitude level of the incoming RF signal is used by a WuRx to generate an interrupt and wake up the radio of a sleeping sensor node. Existing passive WuRx designs are generally based on RFID tags that incur high cost and complexity. Thus, there is a need for cost-effective and low-complexity WuRxs suited for both long-range and directed wake-ups. In this work, we present a WuRx design using an RF energy harvesting circuit (RFHC). Experimental results show that our RFHC-based WuRx can provide a wake-up range sensitivity around 4 cm/mW at low transmit RF powers (< 20 mff), which scales to a long wake-up range at high powers. Our design also obtains accurate selective wake-ups. We finally present simulation-based studies for optimizing the design of RFHCs that enhance decoding efficiency with improved rise and fall times.

Balancing Energy Consumption in Heterogeneous Wireless Sensor Networks Using Genetic Algorithm

Abstract: In a heterogeneous Wireless Sensor Network (WSN), factors such as initial energy, data processing capability, etc greatly influence the network lifespan Despite the success of various clustering strategies of WSN, the numerous possible sensor clusters make searching for an optimal network structure an open challenge In this paper, we propose a Genetic Algorithm based method that optimizes heterogeneous sensor node clustering Compared with five state-of-the-art methods, our proposed method greatly extends the network life, and the average improvement with respect to the second best performance based on the first-node-die and the last-node-die is 338% and 13%, respectively The balanced energy consumption greatly improves the network life and allows the sensor energy to deplete evenly The computational efficiency of our method is comparable to the others and the overall average time across all experiments is 06 seconds with a standard deviation of 006

User authentication schemes for wireless sensor networks

Abstract: Wireless sensor networks (WSNs) are applicable in versatile domains ranging from very common to those which demand crucial security concerns. The deployment of WSNs in unattended environments and the resource-constrained nature of the constituent sensor nodes give rise to an open challenge to ensure that only authorized access to the information is available through the sensor nodes. Many researchers have made considerable efforts to meet this challenge by designing secure and dependable user authentication mechanisms. Every proposed scheme, with its advantages and disadvantages is cryptanalyzed to measure its respective strength and shortcomings. In this study, we first present twenty two features that a reliable user authentication scheme for WSNs should possess. We then evaluate seven of the available schemes against these twenty two features. A common tendency among all the available schemes is their failure to resist gateway node bypass attack, node capture attack and user impersonation attack. There is hardly any scheme that provides user anonymity and reparability in case of smart card loss or theft. Further mutual establishment of a session key between the three participating entities namely user, gateway node and sensor node is achieved in only one scheme; it is an integral characteristic to achieve the confidentiality of messages transmitted over open channels. The mutual authentication between the participating entities is another important aspect which is somewhat fulfilled by only two schemes; only one scheme resists denial of service attack and provides security to gateway node secret parameter. It is time to take halt, ponder upon the acquired objectives and set new goals to equip the contemporary state of art in this field with more viable and promising approaches. We review the state of art in this area; our goal is to explore the course of action for future proposals resulting in protocols with greater potential of usage in industry, military and other purposes. We opine that researchers should develop authentication schemes which take into account the desirable features discussed in this paper. We also discuss future path with some key issues and challenges in the area.

Cooperative and Active Sensing in Mobile Sensor Networks for Scalar Field Mapping

Abstract: Scalar field mapping has many applications including environmental monitoring, search and rescue, etc. In such applications, there is a need to achieve a certain level of confidence regarding the estimates of the scalar field. In this paper, a cooperative and active sensing framework is developed to enable scalar field mapping using multiple mobile sensor nodes. The cooperative and active controller is designed via the real-time feedback of the sensing performance to steer the mobile sensors to new locations in order to improve the sensing quality. During the movement of the mobile sensors, the measurements from each sensor node and its neighbors are fused with the corresponding confidences using distributed consensus filters. As a result, an online map of the scalar field is built while achieving a certain level of confidence of the estimates. We conducted computer simulations to validate and evaluate our proposed algorithms.

Collaborative Mobile Charging

Abstract: The limited battery capacity of sensor nodes has become one of the most critical impediments that stunt the deployment of wireless sensor networks (WSNs). Recent breakthroughs in wireless energy transfer and rechargeable lithium batteries provide a promising alternative to power WSNs: mobile vehicles/robots carrying high volume batteries serve as mobile chargers to periodically deliver energy to sensor nodes. In this paper, we consider how to schedule multiple mobile chargers to optimize energy usage effectiveness, such that every sensor will not run out of energy. We introduce a novel charging paradigm, collaborative mobile charging, where mobile chargers are allowed to intentionally transfer energy between themselves. To provide some intuitive insights into the problem structure, we first consider a scenario that satisfies three conditions, and propose a scheduling algorithm, PushWait, which is proven to be optimal and can cover a one-dimensional WSN of infinite length. Then, we remove the conditions one by one, investigating chargers’ scheduling in a series of scenarios ranging from the most restricted one to a general 2D WSN. Through theoretical analysis and simulations, we demonstrate the advantages of the proposed algorithms in energy usage effectiveness and charging coverage.

Energy Minimization in Multi-Task Software-Defined Sensor Networks

Abstract: After a decade of extensive research on application-specific wireless sensor networks (WSNs), the recent development of information and communication technologies makes it practical to realize the software-defined sensor networks (SDSNs), which are able to adapt to various application requirements and to fully explore the resources of WSNs. A sensor node in SDSN is able to conduct multiple tasks with different sensing targets simultaneously. A given sensing task usually involves multiple sensors to achieve a certain quality-of-sensing, e.g., coverage ratio. It is significant to design an energy-efficient sensor scheduling and management strategy with guaranteed quality-of-sensing for all tasks. To this end, three issues are investigated in this paper: 1) the subset of sensor nodes that shall be activated, i.e., sensor activation, 2) the task that each sensor node shall be assigned, i.e., task mapping, and 3) the sampling rate on a sensor for a target, i.e., sensing scheduling. They are jointly considered and formulated as a mixed-integer with quadratic constraints programming (MIQP) problem, which is then reformulated into a mixed-integer linear programming (MILP) formulation with low computation complexity via linearization. To deal with dynamic events such as sensor node participation and departure, during SDSN operations, an efficient online algorithm using local optimization is developed. Simulation results show that our proposed online algorithm approaches the globally optimized network energy efficiency with much lower rescheduling time and control overhead.

Distributed self fault diagnosis algorithm for large scale wireless sensor networks using modified three sigma edit test

Abstract: Distributed self diagnosis is an important problem in wireless sensor networks (WSNs) where each sensor node needs to learn its own fault status The classical methods for fault finding using mean, median, majority voting and hypothetical test based approaches are not suitable for large scale WSNs due to large deviation in inaccurate data transmission by different faulty sensor nodes In this paper, a modified three sigma edit test based self fault diagnosis algorithm is proposed which diagnose both hard and soft faulty sensor nodes The proposed distribute self fault diagnosis (DSFD) algorithm is simulated in NS3 and the performances are compared with the existing distributed fault detection algorithms The simulation results show that the detection accuracy, false alarm rate and false positive rate performance of the DSFD algorithm is much better in adverse environment where the traditional methods fails to detect the fault The other parameters such as detection latency, energy consumption and the network life time are also determined

Data-Driven Stochastic Models and Policies for Energy Harvesting Sensor Communications

Abstract: Energy harvesting from the surroundings is a promising solution to perpetually power-up wireless sensor communications. This paper presents a data-driven approach of finding optimal transmission policies for a solar-powered sensor node that attempts to maximize net bit rates by adapting its transmission parameters, power levels and modulation types, to the changes of channel fading and battery recharge. We formulate this problem as a discounted Markov decision process (MDP) framework, whereby the energy harvesting process is stochastically quantized into several representative solar states with distinct energy arrivals and is totally driven by historical data records at a sensor node. With the observed solar irradiance at each time epoch, a mixed strategy is developed to compute the belief information of the underlying solar states for the choice of transmission parameters. In addition, a theoretical analysis is conducted for a simple on-off policy, in which a predetermined transmission parameter is utilized whenever a sensor node is active. We prove that such an optimal policy has a threshold structure with respect to battery states and evaluate the performance of an energy harvesting node by analyzing the expected net bit rate. The design framework is exemplified with real solar data records, and the results are useful in characterizing the interplay that occurs between energy harvesting and expenditure under various system configurations. Computer simulations show that the proposed policies significantly outperform other schemes with or without the knowledge of short-term energy harvesting and channel fading patterns.

Collaborative Location-Based Sleep Scheduling for Wireless Sensor Networks Integratedwith Mobile Cloud Computing

Abstract: Recently, much research has proposed to integrate mobile cloud computing (MCC) with wireless sensor networks (WSNs) so that powerful cloud computing can be exploited to process the data gathered by ubiquitous WSNs and share the results with mobile users. However, all current MCC-WSN integration schemes ignore the following two observations: 1) the specific data mobile users request usually depend on the current locations of mobile users 2) most sensors are usually equipped with non-rechargeable batteries with limited energy. In this paper, motivated by these two observations, two novel collaborative location-based sleep scheduling (CLSS) schemes are proposed for WSNs integrated with MCC. Based on the locations of mobile users, CLSS dynamically determines the awake or asleep status of each sensor node to reduce energy consumption of the integrated WSN. Particularly, CLSS1 focuses on maximizing the energy consumption saving of the integrated WSN while CLSS2 considers also the scalability and robustness of the integrated WSN. Theoretical and simulation results show that for WSNs integrated with MCC, both CLSS1 and CLSS2 can prolong the WSN lifetime while still satisfying the data requests of mobile users.

Optimizing power consumption in iot based wireless sensor networks using Bluetooth Low Energy

Abstract: This paper proposes an architecture that uses the ultra-low power Bluetooth Low Energy (BLE) wireless standard and a hybrid topology to reduce power consumption in IOT based wireless sensor networks (IOTWSN). A lot of work has been done in the field of Wireless Sensor Networks (WSN) in recent years. Efforts to make efficient, low cost, scalable and easily deployable WSN have been on going. In order to reduce cost and improve life of a sensor node, it is necessary to optimize battery usage and power consumption. This paper looks at BLE as a potential candidate to reduce power in IOTWSN. BLE based activity detection is also incorporated into the system to avoid power wastage in real-time monitoring. The power consideration of the proposed architecture is compared to existing wireless technologies used in WSN.

Open hardware : a role to play in wireless sensor networks?

Abstract: The concept of the Internet of Things is rapidly becoming a reality, with many applications being deployed within industrial and consumer sectors. At the ‘thing’ level—devices and inter-device network communication—the core technical building blocks are generally the same as those found in wireless sensor network implementations. For the Internet of Things to continue growing, we need more plentiful resources for building intelligent devices and sensor networks. Unfortunately, current commercial devices, e.g., sensor nodes and network gateways, tend to be expensive and proprietary, which presents a barrier to entry and arguably slows down further development. There are, however, an increasing number of open embedded platforms available and also a wide selection of off-the-shelf components that can quickly and easily be built into device and network gateway solutions. The question is whether these solutions measure up to built-for-purpose devices. In the paper, we provide a comparison of existing built-for-purpose devices against open source devices. For comparison, we have also designed and rapidly prototyped a sensor node based on off-the-shelf components. We show that these devices compare favorably to built-for-purpose devices in terms of performance, power and cost. Using open platforms and off-the-shelf components would allow more developers to build intelligent devices and sensor networks, which could result in a better overall development ecosystem, lower barriers to entry and rapid growth in the number of IoT applications.

Wireless sensor networks in agriculture

Abstract: In the paper it is described the multilevel sensor network for data acquisition and processing in precision farming and ecological monitoring. The main aim of the multilevel sensor network is real-time data acquisition of state of plants on large territories, on-line data processing and timely decision making according to specified criteria. Wireless sensor network, which described in article, serves as primary data acquisition system in proposed multilevel sensor network.

A Comprehensive Review of Simulation Tools for Wireless Sensor Networks (WSNs)

Abstract: The trend towards adoption of Wireless Sensor Networks is increasing in recent years because of its diverse use in various fields. Wireless Sensor Network is formed via interconnection of large number of sensor nodes. Each and every sensor node deployed in network monitors various parameters like Temperature, Humidity, Ambient Light, Gas etc. and send the data to the master node. Despite of several applications and diverse uses, sensor networks face various shortcomings like energy, localization, security, self-organization, fault tolerance and many more. So, the area of Wireless Sensor Network is under rigorous research and development by various researchers across the globe to develop new algorithms, protocols and techniques to make WSN network more efficient and reliable. Before live implementation, testing of the developed technique requires rigorous testing. But it is not always possible to have live sensor network environment. So, in that case, Simulation is the only way to test the research before moving towards live implementation. Large numbers of simulation tools are available for WSN network till date, out of which some are dedicated towards wireless sensor networks and some for both wireless and wired networks. The main objective behind this research paper is to do a comprehensive review of various simulation tools of Wireless Sensor Networks to enable researcher to select the most competent tool for simulating wireless sensor networks and testing the research proposed. A comprehensive review of 31 WSN simulators is being presented along with their respective features comparison to assist researchers in advanced WSN based research.

An Efficient Biometric-Based Algorithm Using Heart Rate Variability for Securing Body Sensor Networks

Abstract: Body Sensor Network (BSN) is a network of several associated sensor nodes on, inside or around the human body to monitor vital signals, such as, Electroencephalogram (EEG), Photoplethysmography (PPG), Electrocardiogram (ECG), etc. Each sensor node in BSN delivers major information; therefore, it is very significant to provide data confidentiality and security. All existing approaches to secure BSN are based on complex cryptographic key generation procedures, which not only demands high resource utilization and computation time, but also consumes large amount of energy, power and memory during data transmission. However, it is indispensable to put forward energy efficient and computationally less complex authentication technique for BSN. In this paper, a novel biometric-based algorithm is proposed, which utilizes Heart Rate Variability (HRV) for simple key generation process to secure BSN. Our proposed algorithm is compared with three data authentication techniques, namely Physiological Signal based Key Agreement (PSKA), Data Encryption Standard (DES) and Rivest Shamir Adleman (RSA). Simulation is performed in Matlab and results suggest that proposed algorithm is quite efficient in terms of transmission time utilization, average remaining energy and total power consumption.

Alternative Tuples Based Probabilistic Skyline Query Processing in Wireless Sensor Networks

Abstract: As uncertainty is the inherent character of sensing data, the processing and optimization techniques for Probabilistic Skyline (PS) in wireless sensor networks (WSNs) are investigated. It can be proved that PS is not decomposable after analyzing its properties, so in-network aggregation techniques cannot be used directly to improve the performance. In this paper, an efficient algorithm, called Distributed Processing of Probabilistic Skyline (DPPS) query in WSNs, is proposed. The algorithm divides the sensing data into candidate data (CD), irrelevant data (ID), and relevant data (RD). The ID in each sensor node can be filtered directly to reduce data transmissions cost, since, only according to both CD and RD, PS result can be correctly obtained on the base station. Experimental results show that the proposed algorithm can effectively reduce data transmissions by filtering the unnecessary data and greatly prolong the lifetime of WSNs.

Event-Based Distributed Filtering With Stochastic Measurement Fading

Abstract: In this paper, we investigate the distributed filtering problem over wireless sensor networks (WSNs) with bandwidth and energy constraints. To utilize the limited resources efficiently, a novel event-based mechanism is proposed for the sensor node, such that only selected valuable data are broadcasted to its neighboring sensors via the wireless channel according to whether specific events happen. By resorting to graph theory and utilizing stochastic analysis methods, the filter parameters and the event triggering rules are designed, such that the filtering error converges at an exponential rate in the mean square sense. An adaptive algorithm for determining the triggering threshold is developed, which allows the intelligent sensors to tune the boundary of a local event domain in an online manner, so as to keep the average transmission rate level off a desired value. An illustrative example is given to demonstrate the effectiveness of the proposed strategy.

Cluster Based Multipath Routing Protocol for Wireless Sensor Networks

Abstract: Wireless Sensor Network (WSN) consists of low power sensor nodes. Energy is the main constraint associated with the sensor nodes. In this paper, we propose a cluster based multipath routing protocol, which uses the clustering and multipath techniques to reduce energy consumption and increase the reliability. The basic idea is to reduce the load of the sensor node by giving more responsibility to the base station (sink). We have implemented and compared the protocol with existing protocols and found that it is more energy-efficient and reliable.

An automatic irrigation system using ZigBee in wireless sensor network

Abstract: Wireless Sensing Technology is widely used everywhere in the current scientific world. As the technology is growing and changing rapidly, Wireless sensing Network (WSN) helps to upgrade the technology. In the research field of wireless sensor networks the power efficient time is a major issue. This problem can be overcome by using the ZigBee technology. The main idea of this is to understand how data travels through a wireless medium transmission using wireless sensor network and monitoring system. This paper design an irrigation system which is automated by using controllable parameter such as temperature, soil moisture and air humidity because they are the important factors to be controlled in PA(Precision Agricultures).

A Secure Data Aggregation Scheme Based on Appropriate Cryptographic Primitives in Heterogeneous Wireless Sensor Networks

Abstract: Energy cost of transmitting a single bit of information is approximately the same as that needed for processing a thousand operations in a typical sensor node. Thus, a practical way to prolong a wireless sensor network lifetime is to reduce the sensor energy consumption in data transmissions. Data aggregation is an efficient way to minimize energy consumption on sensors. In this paper, we propose a practical secure data aggregation scheme, Sen-SDA , based on an additive homomorphic encryption scheme, an identity-based signature scheme, and a batch verification technique with an algorithm for filtering injected false data. We then investigate the feasibility of our scheme using low-cost microcontrollers choosing two popular IEEE 802.15.4-compliant wireless sensor network hardware platforms, MICAz and Tmote Sky, used in real-life deployments.

A Mobile Platform for Wireless Charging and Data Collection in Sensor Networks

Abstract: Wireless energy transfer (WET) is a new technology that can be used to charge the batteries of sensor nodes without wires. Although wireless, WET does require a charging station to be brought to within reasonable range of a sensor node so that a good energy transfer efficiency can be achieved. On the other hand, it has been well recognized that data collection with a mobile base station has significant advantages over a static one. Given that a mobile platform is required for WET, a natural approach is to employ the same mobile platform to carry the base station for data collection. In this paper, we study the interesting problem of co-locating a wireless charger (for WET) and a mobile base station on the same mobile platform—the wireless charging vehicle (WCV). The WCV travels along a pre-planned path inside the sensor network. Our goal is to minimize energy consumption of the entire system while ensuring that 1) each sensor node is charged in time so that it will never run out of energy, and 2) all data collected from the sensor nodes are relayed to the mobile base station. We develop a mathematical model for this problem (OPT-t), which is time-dependent. Instead of solving OPT-t directly, we show that it is sufficient to study a special subproblem (OPT-s) which only involves space-dependent variables. Subsequently, we develop a provably near-optimal solution to OPT-s. Our results offer a solution on how to use a single mobile platform to address both WET and data collection in sensor networks.

Dynamic Channel Assignment for Wireless Sensor Networks: A Regret Matching Based Approach

Abstract: Multiple channels in Wireless Sensor Networks (WSNs) are often exploited to support parallel transmission and to reduce interference. However, the extra overhead posed by the multi-channel usage coordination dramatically challenges the energy-constrained WSNs. In this paper, we propose a Regret Matching based Channel Assignment algorithm (RMCA) to address this challenge, in which each sensor node updates its choice of channels according to the historical record of these channels’ performance to reduce interference. The advantage of RMCA is that it is highly distributed and requires very limited information exchange among sensor nodes. It is proved that RMCA converges almost surely to the set of correlated equilibrium. Moreover, RMCA can adapt the channel assignment among sensor nodes to the time-variant flows and network topology. Simulations show that RMCA achieves better network performance in terms of both delivery ratio and packet latency than CONTROL , MMSN and randomized CSMA. In addition, real hardware experiments are conducted to demonstrate that RMCA is easy to be implemented and performs better.