• Channel and timeslot co-scheduling with minimal channel switching for data aggregation in MWSNs.

      Yeoum, Sanggil; Kang, Byungseok; Lee, Jinkyu; Choo, Hyunseung; Sungkyunkwan University (MDPI, 2017-05-04)
      Collision-free transmission and efficient data transfer between nodes can be achieved through a set of channels in multichannel wireless sensor networks (MWSNs). While using multiple channels, we have to carefully consider channel interference, channel and time slot (resources) optimization, channel switching delay, and energy consumption. Since sensor nodes operate on low battery power, the energy consumed in channel switching becomes an important challenge. In this paper, we propose channel and time slot scheduling for minimal channel switching in MWSNs, while achieving efficient and collision-free transmission between nodes. The proposed scheme constructs a duty-cycled tree while reducing the amount of channel switching. As a next step, collision-free time slots are assigned to every node based on the minimal data collection delay. The experimental results demonstrate that the validity of our scheme reduces the amount of channel switching by 17.5%, reduces energy consumption for channel switching by 28%, and reduces the schedule length by 46%, as compared to the existing schemes.
    • Data aggregation in wireless sensor networks for lunar exploration

      Zhai, Xiaojun; Vladimirova, Tanya; University of Derby; University of Leicester (IEEE, 2015-09-03)
      This paper presents research work related to the development of Wireless Sensor Networks (WSN) gathering environmental data from the surface of the Moon. Data aggregation algorithms are applied to reduce the amount of the multi-sensor data collected by the WSN, which are to be sent to a Moon orbiter and later to Earth. A particular issue that is of utmost importance to space applications is energy efficiency and a main goal of the research is to optimise the algorithm design so that the WSN energy consumption is reduced. An extensive simulation experiment is carried out, which confirms that the use of the proposed algorithms enhances significantly the network performance in terms of energy consumption compared to routing the raw data. In addition, the proposed data aggregation algorithms are implemented successfully on a System-on-a-chip (SoC) embedded platform using a Xilinx Zynq FPGA device. The data aggregation has two important effects: the WSN life time is extended due to the saved energy and the original data accuracy is preserved. This research could be beneficial for a number of future security related applications, such as monitoring of phenomena that may affect Earth's planetary security/safety as well as monitoring the implementation of Moon treaties preventing establishment of military bases on the lunar surface.
    • Distributed degree-based link scheduling for collision avoidance in wireless sensor networks.

      Kang, Byungseok; Myoung, Sungho; Choo, Hyunseung; Sungkyunkwan University (IEEE, 2016-09-10)
      Wireless sensor networks (WSNs) consist of multiple sensor nodes, which communicate with each other under the constrained energy resources. Retransmissions caused by collision and interference during the communication among sensor nodes increase overall network delay. Since the network delay increases as the node's waiting time increases, the network performance is reduced. Thus, the link scheduling scheme is needed to communicate without collision and interference. In the distributed WSNs environment, a sensor node has limited information about its neighboring nodes. Therefore, a comprehensive link scheduling scheme is required for distributed WSNs. Many schemes in the literature prevent collision and interference through time division multiple access (TDMA) protocol. However, considering the collision and interference in TDMA-based schedule increases the delay time and decreases the communication efficiency. This paper proposes the distributed degree-based link scheduling (DDLS) scheme, based on the TDMA. The DDLS scheme achieves the link scheduling more efficiently than the existing schemes and has the low delay and the duty cycle in the distributed environment. Communication between sensor nodes in the proposed DDLS schemes is based on collision avoidance maximal independent link set, which enables to assign collision-free timeslots to sensor nodes, and meanwhile decreases the number of timeslots needed and has low delay time and the duty cycle. Simulation results show that the proposed DDLS scheme reduces the scheduling length by average 81%, the transmission delay by 82%, and duty cycle by over 85% in comparison with distributed collision-free low-latency scheduling scheme.
    • A distributed delay-efficient data aggregation scheduling for duty-cycled WSNs

      Kang, Byungseok; Nguyen, Phan; Zalyubouskiy, Vyacheslav; Choo, Hyunseung; Sungkyunkwan University (IEEE, 2017-04-07)
      With the growing interest in wireless sensor networks (WSNs), minimizing network delay and maximizing sensor (node) lifetime are important challenges. Since the sensor battery is one of the most precious resources in a WSN, efficient utilization of the energy to prolong the network lifetime has been the focus of much of the research on WSNs. For that reason, many previous research efforts have tried to achieve tradeoffs in terms of network delay and energy cost for such data aggregation tasks. Recently, duty-cycling technique, i.e., periodically switching ON and OFF communication and sensing capabilities, has been considered to significantly reduce the active time of sensor nodes and thus extend network lifetime. However, this technique causes challenges for data aggregation. In this paper, we present a distributed approach, named distributed delay efficient data aggregation scheduling (DEDAS-D) to solve the aggregation-scheduling problem in duty-cycled WSNs. The analysis indicates that our solution is a better approach to solve this problem. We conduct extensive simulations to corroborate our analysis and show that DEDAS-D outperforms other distributed schemes and achieves an asymptotic performance compared with centralized scheme in terms of data aggregation delay.
    • Efficient data-processing algorithms for wireless-sensor-networks-based planetary exploration

      Zhai, Xiaojun; Vladimirova, Tanya; University of Derby; University of Leicester (American Institute of Aeronautics and Astronautics, Inc., 2016-01)
      The Space Wireless Sensor Networks for Planetary Exploration project aims to design a wireless sensor network that consists of small wireless sensor nodes dropped onto the moon surface to collect scientific measurements. Data gathered from the sensors will be processed and aggregated for uploading to a lunar orbiter and subsequent transmission to Earth. In this paper, efficient data-processing/fusion algorithms are proposed, the purpose of which is to integrate the scientific sensor data collected by the wireless sensor network, reducing the data volume without sacrificing the data quality to satisfy energy constraints of wireless-sensor-network nodes operating in the extreme moon environment. The results of an extensive simulation experiment targeted at the Space Wireless Sensor Networks for Planetary Exploration lunar exploration mission are reported, which quantify the performance efficiency of the data-processing scheme. It is shown that the proposed data-processing algorithms can reduce the wireless-sensor-network node energy consumption significantly, decreasing the data transmission energy up to 91%. In addition, it is shown that up to 99% of the accuracy of the original data can be preserved in the final reconstructed data.
    • An energy efficient routing scheme by using GPS information for wireless sensor networks

      Kang, Byungseok; Choo, Hyunseung; Sejong University (Inderscience Enterprises Ltd., 2018-07-02)
      In the process of transmission in wireless sensor networks (WSN), a vital problem is that a centre region close to the sink will form in which sensors have to cost vast amount of energy. To communicate in an energy-efficient manner, compressed sensing (CS) has been employed gradually. However, the performance of plain CS is significantly dependant on the specific data gathering strategy in practice. In this paper, we propose an energy-efficient data gathering scheme based on regionalisation CS. Subsequently, advanced methods for practical applications are considered. Experiments reveal that our scheme outperforms distributed CS, the straight forward and the mixed schemes by comparing different parameters of the data package, and the considered methods also guarantee its feasibility.
    • MLP neural network based gas classification system on Zynq SoC

      Zhai, Xiaojun; Ait Si Ali, Amine; Amira, Abbes; Bensaali, Faycal; University of Derby (IEEE, 2016-10-21)
      Systems based on Wireless Gas Sensor Networks (WGSN) offer a powerful tool to observe and analyse data in complex environments over long monitoring periods. Since the reliability of sensors is very important in those systems, gas classification is a critical process within the gas safety precautions. A gas classification system has to react fast in order to take essential actions in case of fault detection. This paper proposes a low latency real-time gas classification service system, which uses a Multi-Layer Perceptron (MLP) Artificial Neural Network (ANN) to detect and classify the gas sensor data. An accurate MLP is developed to work with the data set obtained from an array of tin oxide (SnO2) gas sensor, based on convex Micro hotplates (MHP). The overall system acquires the gas sensor data through RFID, and processes the sensor data with the proposed MLP classifier implemented on a System on Chip (SoC) platform from Xilinx. Hardware implementation of the classifier is optimized to achieve very low latency for real-time application. The proposed architecture has been implemented on a ZYNQ SoC using fixed-point format and achieved results have shown that an accuracy of 97.4% has been obtained.
    • Multi-sensor data fusion in wireless sensor networks for planetary exploration

      Zhai, Xiaojun; Jing, Hongyuan; Vladimirova, Tanya; University of Derby; University of Leicester (IEEE, 2014-07-14)
      The SWIPE (Space Wireless Sensor Networks for Planetary Exploration) project uses Wireless Sensor Networks (WSN) to characterise the surface of the Moon. The envisaged scenario is that hundreds of small wireless sensor nodes dropped onto the Moon surface will collect scientific measurements. An ad-hoc WSN connecting these nodes will propagate the measurement data to sink nodes for uploading to a lunar orbiter and a subsequent transmission to Earth. The data gathered from the sensors will be processed using state-of-the-art data fusion techniques to overcome the restricted energy and bandwidth resources. In this paper, we first provide a short survey of classical data fusion techniques for WSNs. We then introduce data fusion architectures for the SWIPE project. Building on this, we propose data processing algorithms that enable energy conservation and processing efficiency in the proposed SWIPE architectures. The proposed algorithms are evaluated via a series of simulation models. The results show that the proposed algorithms can efficiently reduce the amount of the transmitted scientific data providing a good level of accuracy in the data reconstruction. Furthermore, they are able to correctly evaluate the node health status.
    • Trail-using ant behavior based energy-efficient routing protocol in wireless sensor networks.

      Jung, Soon-gyo; Kang, Byungseok; Yeoum, Sanggil; Choo, Hyunseung; Sungkyunkwan University (SAGE Publications, 2016-04-06)
      Swarm Intelligence (SI) observes the collective behavior of social insects and other animal societies. Ant Colony Optimization (ACO) algorithm is one of the popular algorithms in SI. In the last decade, several routing protocols based on ACO algorithm have been developed for Wireless Sensor Networks (WSNs). Such routing protocols are very flexible in distributed system but generate a lot of additional traffic and thus increase communication overhead. This paper proposes a new routing protocol reducing the overhead to provide energy efficiency. The proposed protocol adopts not only the foraging behavior of ant colony but also the trail-using behavior which has never been adopted in routing. By employing the behaviors, the protocol establishes and manages the routing trails energy efficiently in the whole network. Simulation results show that the proposed protocol has low communication overhead and reduces up to 55% energy consumption compared to the existing ACO algorithm.