Now showing 1 - 4 of 4
  • Publication
    Extending the Lifetime of Sensor Networks Using Prediction and Scheduling
    Power consumption in wireless sensor networks (WSNs) is a very important issue. Using measured sensor network data, this paper shows that it is possible to conserve a significant amount of energy through the proper use of data prediction and node scheduling without a significant loss in accuracy. Results show that it is possible to increase lifetime by up to 2600% at the cost of increasing average error by 0.5degC for temperature or 1.5% for humidity measurements. The four main design issues tackled are clustering, prediction, scheduling, and spike errors.
      317Scopus© Citations 6
  • Publication
    Trading Sensing Coverage For An Extended Network Lifetime
    One of the main benefits of using Wireless Sensor Networks (WSNs) is that they can be deployed in remote locations without any prior infrastructure. Because of this nodes are normally battery powered. This limits the performance of the network. In this paper, we propose a novel method of scheduling nodes based on a user's sensing coverage requirement. Through the use of our proposed scheduling algorithm (Ncut-GA), it is shown that the duration in which the user's coverage requirement is met can be extended. When compared with a previously published algorithm (Greedy-MSC), the proposed algorithm is able to increase the coverage duration by up to 33%. Furthermore it is also shown that the duration of which the WSN can operate till the first node dies can be improved by up to 125% through the used of Ncut-GA.
      360
  • Publication
    Trading Sensing Coverage for an Extended Network Lifetime
    One of the main benefits of using Wireless Sensor Networks (WSNs) is that they can be deployed in remote locations without any prior infrastructure. Because of this nodes are normally battery powered. This limits the lifetime of the network. In this paper, we propose a novel method of scheduling nodes based on a user’s sensing coverage requirement. Through the use of our proposed scheduling algorithm (Ncut-GA), it is shown that the duration for which the user’s coverage requirement is met can be extended. When compared with a previously published algorithm (Greedy-MSC), the proposed algorithm is able to increase coverage duration by up to 80%. Furthermore it is also shown that the time until the first node dies can be improved by up to 200% through the use of Ncut-GA.
      320Scopus© Citations 4
  • Publication
    Adaptive WSN Scheduling for Lifetime Extension in Environmental Monitoring Applications
    (Hindawi Publishing Corporation, 2012) ;
    Wireless sensor networks (WSNs) are often used for environmental monitoring applications in which nodes periodically measure environmental conditions and immediately send the measurements back to the sink for processing. Since WSN nodes are typically battery powered, network lifetime is a major concern. A key research problem is how to determine the data gathering schedule that will maximize network lifetime while meeting the user's application-specific accuracy requirements. In this work, a novel algorithm for determining efficient sampling schedules for data gathering WSNs is proposed. The algorithm differs from previous work in that it dynamically adapts the sampling schedule based on the observed internode data correlation as well as the temporal correlation. The performance of the algorithm has been assessed using real-world datasets. For two-tier networks, the proposed algorithm outperforms a highly cited previously published algorithm by up to 512% in terms of lifetime and by up to 30% in terms of prediction accuracy. For multihop networks, the proposed algorithm improves on the previously published algorithm by up to 553% and 38% in terms of lifetime and accuracy, respectively.
      544Scopus© Citations 6