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Node location is of great significance as a supporting technology of wireless sensor network (WSN). The information without position would be greatly devalued. So this paper is about location algorithm for nodes of ship-borne WSN based on research on structure of ship and work environment of ship-borne WSN. The whole location process consists of two steps: one is location algorithm among cabins (LAAC), and the other one is location algorithm in the cabin (LAIC). LAAC refers to location with the topology of ship-borne WSN. We can learn which cabin the node lies in. LAIC refers to location based on received signal strength indication (RSSI), we can get distance relationship between nodes by RSSI, and then obtain the specific location by solving this distance relationship. In the last part, this paper verifies the designed location algorithm by experimenting on "A" ship. Experiments show that the location algorithm designed by this paper is feasible. [ABSTRACT FROM AUTHOR]

This paper presents an efficient data aggregation approach for cluster-based underwater wireless sensor networks in order to prolong network lifetime. In data aggregation, an aggregator collects sensed data fromsurrounding nodes and transmits the aggregated data to a base station. The major goal of data aggregation is to minimize data redundancy, ensuring high data accuracy and reducing the aggregator's energy consumption. Hence, similarity functions could be useful as a part of the data aggregation process for resolving inconsistencies in collected data. Our approach is to determine and apply well-suited similarity functions for clusterbased underwater wireless sensor networks. In this paper, we show the effectiveness of similarity functions, especially the Euclidean distance and cosine distance, in reducing the packet size and minimizing the data redundancy of cluster-based underwater wireless sensor networks. Our results show that the Euclidean distance and cosine distance increase the efficiency of the network both in theory and simulation. [ABSTRACT FROM AUTHOR]

Big data and distributed computing are of great importance in wireless sensor networks (WSNs).They are always bonded together, and the latter one upholds the former one. In distributed computing, mobile agent model is the mainstream technology. With autonomy, communicativeness, mobility, and role, mobile agent model is more suitable for large-scale, resources-restrained WSN to deal with big data. This paper mainly studies migration schemes for mobile agents, determines core factors of migration strategy, and proposes SMLA and DMLA algorithms. And aiming at revealing the characteristics of target tracking, this paper puts forward pid-DMLA algorithm; and considering multiple agents' cooperation, it presents Mpid-DMLA algorithm. Moreover, this paper evaluates and analyzes the advantages and disadvantages of the above-mentioned four algorithms by simulations. [ABSTRACT FROM AUTHOR]

Dynamic service composition provides us with a promising approach to cooperate different sensor nodes in WSN to build complex applications based on their basic functions. Usually multiple nodes located in different regions provide data with different security levels, and it is critical to ensure the security of the information flow in the composite services. However, the energy-limited nature of sensor nodes in WSN poses a significant challenge for the centralized information flow verification with which the verification node needs to consume lots of computation and network resources. In this paper, we specify the security constraints for each service participant to secure the information flow in a service chain based in the lattice model and then present a distributed verification framework that cooperates different service participants to verify their information flow policies distributively The evaluation results show a significant decrease on the verification cost of the single verification node, which provides a better load balance in each sensor node. [ABSTRACT FROM AUTHOR]

With the development of wireless sensor network (WSN) technologies, WSNs have been applied in many areas. In all WSN technologies, localization is a crucial problem. Traditional localization approaches in WSNs mainly focus on calculating the current location of sensor nodes or mobile objects. In this paper, we study the problem of future location prediction in WSNs. We assume the location histories of mobile objects as a rating matrix and then use a random walk based social recommender algorithm to predict the future locations of mobile objects. Experiments show that the proposed algorithm has better prediction accuracy and can solve the rating matrix sparsity problem more effectively than related works. [ABSTRACT FROM AUTHOR]

In designing wireless sensor networks, it is important to reduce energy dissipation and prolong network lifetime. This paper presents research on the existing clustering algorithm applied in heterogeneous sensor networks and then puts forward an energy-efficient prediction clustering algorithm, which is adaptive to sensor networks with energy and objects heterogeneous. This algorithm enables the nodes to select the cluster head according to factors such as energy and communication cost, thus the nodes with higher residual energy have higher probability to become a cluster head than those with lower residual energy, so that the network energy can be dissipated uniformly. In order to reduce energy consumption when broadcasting in clustering phase and prolong network lifetime, an energy consumption prediction model is established for regular data acquisition nodes. Simulation results show that compared with current clustering algorithms, this algorithm can achieve longer sensor network lifetime, higher energy efficiency, and superior network monitoring quality. [ABSTRACT FROM AUTHOR]

Due to the low-cost and low-power requirement in an individual sensor node, the available computing resources turn out to be very limited like small memory footprint and irreplaceable battery power. Sensed data fusion might be needed before being transmitted as a tradeoff between procession and transmission in consideration of saving power consumption. Even worse, the application program needs to be complicated enough to be self-organizing and dynamically reconfigurable because changes in an operating environment continue even after deployment. State-driven operating system platform offers numerous benefits in this challenging situation. It provides a powerful way to accommodate complex reactive systems like diverse wireless sensor network applications. The memory usage can be bounded within a state transition table. The complicated issues like concurrency control and asynchronous event handling capabilities can be easily achieved in a well-defined behavior of state transition diagram. In this paper, we present an efficient and effective design of the state-driven operating system for wireless sensor nodes. We describe that the new platform can operate in an extremely resource constrained situation while providing the desired concurrency, reactivity, and reconfigurability We also compare the executing results after comparing some benchmark test results with those on TinyOS. [ABSTRACT FROM AUTHOR]

In wireless sensor networks, secure data aggregation is very important for reducing the quantity of data transmitted and prolonging the lifetime of wireless sensor networks. When wireless sensor networks are deployed in untrusted and hostile environments, their nodes are often compromised, which reduces the security and reliability of the transmitted data. Compromised nodes can inject erroneous data, selectively forward data to an adversary, impersonate legal nodes to join routing paths, and disrupt data transmission during the data-aggregation operation. Previous researchers have relied on reputation system to find compromised nodes and prevent attacks during the data-aggregation operation. In this paper, we propose an improved reliable, trust-based, and energy-efficient data-aggregation protocol for wireless sensor networks. We call the protocol the iRTEDA protocol, and it combines the reputation system, residual energy, link availability, and a recovery mechanism to improve secure data aggregation and ensure that the network is secure, reliable, and energy-efficient. Simulations have shown that the iRTEDA protocol exceeds the performances of other protocols from the perspectives of the accuracy of the data, the reliability of the routing path, the consumption of energy, and the lifetime of secure data aggregation. [ABSTRACT FROM AUTHOR]

Optimizing the path planning to reduce the time and cost is an essential consideration in modern society, and existing research has mostly concentrated on static path planning and real-time data information in vehicle navigational applications. Using dynamic path planning to adjust and update the path information in time is a challenging approach to reduce road congestion and traffic accidents. In this paper, we present a data analysis algorithmthat determines an efficient dynamic path for vehicle repair-scrap sites and navigates more flexibly to avoid obstacles, where the key idea is to design the sensor wireless network that helps to obtain data fromdifferent devices. Firstly, the data processing scheme for real-time data with regional cluster and node division can be obtained fromdifferent sensor devices through the wireless senor network. Secondly, the search space and the relevant road information are restricted to a strongly connected graph. The most important strategy for an optimal solution to find the shortest path is the search method. Finally, to validate the performance of our design and algorithm, we have conducted a simulation based on necessary traffic variables. The performance simulation results show that real-time dynamic path planning can be significantly optimized using our data processing scheme. [ABSTRACT FROM AUTHOR]

RN and SSR approaches are designed to detect NLOS propagation paths in this paper. When the NLOS propagation paths are detected, an estimation approach for the NLOS range errors is proposed by using residual-error decomposition. The approach can estimate the NLOS range errors quickly and effectively, even if there are multiple NLOS propagation paths. Combining the movement equation with observation position, the position of mobile target node can be tracked precisely with Kalman filter algorithm.Using the estimatedNLOS range errors, we correct the localization result and modify Kalman filter to mitigate the NLOS propagations.The simulations demonstrate the validity withRNand SSR detectionmethods and analyze the impacts of NLOS range errors and number of NLOS anchor nodes. The estimated NLOS range errors are proved to be close to the true especially when the NLOS range errors are much bigger than LOS range errors.The simulation results show that the position of target node can be tracked precisely and effectively, when the NLOS mitigation is used to track the target node position with modified Kalman filter. [ABSTRACT FROM AUTHOR]

Wireless sensor control networks (WSCNs) are important scenarios and trends in mobile wireless sensor networks. Compared with traditional wireless sensor networks,WSCNs have two specific characteristics: entities in networks are extended from passive sensors to active sensors (e.g., actuators and actors) and the transmitting messages are extended from data only to data plus (e.g., data and control instructions).Thus new security problems arises. In this paper, we make the first attempt to specify the security requirements for WSCNs, namely, indistinguishability, reachability, and timeliness. In addition, several new attacks in WSCN, distinguishing risks, dropping attacks, and disordering attacks, are pointed out at the first time. A lightweight scheme LIRT is proposed with tailored design to guarantee the indistinguishability, reachability, and timeliness inWSCNs. Extensive and rigorous analysis on LIRT justifies its security strength and performance measures. [ABSTRACT FROM AUTHOR]

This paper proposes a human motion tracking approach for a daily life surveillance in a distributed wireless sensor network using ultrasonic range sensors. Because the human target often moves with high nonlinearity, the proposed approach applies the unscented Kalman filter (UKF) technique. A novel sensor node selection scheme at each time step considering both the tracking accuracy and the energy cost is presented. Experimental results in a real human motion tracking system show that the proposed approach can perform better tracking accuracy compared to the most recent human motion tracking scheme in the real testbed implementation. [ABSTRACT FROM AUTHOR]

This paper presents a novel data validation algorithm for wireless sensor network. We applied qualitative methods such as heuristic rule, temporal correlation, spatial correlation, Chauvenet's criterion, and modified z-score as algorithms for validating sensor data samples for faults. Performance of the algorithms is evaluated using real data samples of WSNs prototype for environment monitoring injected with different types of data faults such as out-of-range faults, struck-at faults, and outliers and spike faults. Results show heuristic rule, temporal correlation, spatial correlation, chauvenet's criterion, and modified z-score method sit at different point on accuracy, no single method is perfect in detecting different types of data faults and reports false positives when sensor data samples contain different types of data faults. Selected effective methods such as heuristic rule, temporal correlation, and modified z-score are applied successively to data set for detecting different types of data faults but report false positives due to masking effects and increased fault rate. Finally we propose a novel data validation algorithm that uses novel approach in applying heuristic rule, temporal correlation, and modified z-score to data set for detecting different types of data faults. Compared to other methods, the proposed novel data validation algorithm is effective in detecting different types of data faults and reports high fault detection rate by eliminating false positives. [ABSTRACT FROM AUTHOR]

Recently, photovoltaic-supercapacitor-based energy systems have become more and more popular in the design of energy harvesting wireless sensor networks (EH-WSNs) as an alternative to battery power. Existing research on this area mainly focuses on hardware design and the improvement of the charging efficiency However, energy is wasted not only by the inefficient charging process, but also the inefficient discharging process and energy leakage. Therefore, to maximize node lifetime and energy utilization, all the previous energy loss should be considered. In this paper, we develop realistic hardware models of the complete photovoltaic-supercapacitor energy systems and propose the efficiency-aware, a systematic duty cycling framework to maximize energy utilization. We formalize the maximization problem as a nonlinear optimization problem and develop two efficient algorithms for its optimal solutions. The performance of our approaches is evaluated via extensive numeric simulations, and the results show that our efficiency-aware framework can, respectively, achieve 60% and 56% more active time (i.e. energy utilization) than the fixed duty cycle scheme and leakage-aware, a state-of-the-art scheme for photovoltaic-supercapacitor energy systems. [ABSTRACT FROM AUTHOR]

In distributed wireless sensor networks (DWSNs), the data gathered by sink is always massive and consumes a lot of resources. It is suitable for cloud computing platform to apply service in data processing system. In cloud computing, IAAS platform provides services and calculation to the user through the virtual machine. The management of virtual machine images not only consumes a huge amount of storage space but also gives large pressure on network transmission. By using deduplication technology in openstack, this paper designed and implemented, an image management system IM-dedup, which uses static chunking (SC) to divide image file into blocks of data, avoid duplication data blocks transmission on network by using fingerprint pretransmission technology, and reduce storage space by deploying kernel mode file system with deduplication in the image storage server. The experimental results showed that the system not only reduced 80% usage of the virtual machine image storage, but also saved at least 30% of transmission time. Furthermore, the research on virtual machine image format showed that "VMWare Virtual Machine Disk Format" (VMDK), "Virtual Desktop Infrastructure" (VDI), "QEMU Copy On Write2" (QCOW2), and RAW image formats are more suitable for the IM-dedup system. [ABSTRACT FROM AUTHOR]

Energy awareness is a vital design issue in wireless sensor networks. Since the amount of sensing data may be large and sensor nodes are usually battery-powered, it is critical to design energy-efficient routing algorithms to prolong network lifetime. Given a certain sensor deployment, the routing strategy of sensor data would have profound effects on the communication cost. In this paper, based on low-energy adaptive clustering hierarchy (LEACH) series protocols which are low-energy consumption adaptive clustering routing protocols, we propose the OVSF mechanism based routing protocol and EERPP (Energy-Efficient Routing Protocol based on Priority). Simulation results of OVSF mechanism based protocol and EERPP demonstrate a significant improvement on the network metrics such as the lifetime and the end-to-end delay. [ABSTRACT FROM AUTHOR]