Event detection and recognition are important for environmental monitoring in the Internet of things and cyber-physical systems. Low power wide area (LPWA) networks are one of the most powerful wireless sensor networks to support data gathering; however, they do not afford peak wireless access from sensors that detect significant changes in sensing data. Various data gathering schemes for event detection and recognition have been proposed. However, these do not satisfy the requirement for the three functions for the detection of the occurrence of an event, the recognition of the position of an event, and the recognition of spillover of impact from an event. This study proposes a three-stage data gathering scheme for LPWA. In the first stage, the access limitation based on the comparison between the detected sensing data and the high-level threshold is effective in reducing the simultaneous accessing sensors; thus, high-speed recognition of the starting event is achieved. In the second stage, the data centre station designates the sensor to inform the sensing data to achieve high accuracy of the position estimation of the event. In the third stage, all the sensors, except for the accessing sensors in the early stage, access the data centre. Owing to the exhaustive gathering of sensing data, the spillover of impact from the event can be recognised with high accuracy. We implement the proposed data gathering scheme for the actual wireless sensor system of the LPWA. From the computer simulation and experimental evaluation, we show the advantage of the proposed scheme compared to the conventional scheme.

Data aggregation trees in wireless sensor networks (WSNs) are being used for gathering data for various purposes. Especially for the trees within buildings or civil structures, the total amount of energy consumption in a tree must be reduced to save energy. Therefore, the minimum energy-cost aggregation tree (MECAT) and MECAT with relay nodes (MECAT_RN) problems are being discussed to reduce energy consumption in data aggregation trees in WSNs. This paper proposes the tree node switching algorithm (TNSA) that improves on the previous algorithms for the MECAT and MECAT_RN problems in terms of energy efficiency. TNSA repeatedly switches nodes in a tree to reduce the number of packets sent in the tree. Packets are reduced by improving the accommodation efficiency of each packet, in which multiple sensor reports are accommodated. As a result of applying TNSA to MECATs and MECAT-RNs, energy consumption can be reduced significantly with a small burden.

Sensor-data gathering using multi-hop connections in a wireless sensor network is being widely used, and a tree topology for data gathering is considered promising because it eases data aggregation. Therefore, many sensor-tree-creation algorithms have been proposed. The sensors in a tree, however, generally run on batteries, so long tree lifetime is one of the most important factors in collecting sensor data from a tree over a long period. It has been proven that creating the longest-lifetime tree is a non-deterministic-polynomial complete problem; thus, all previously proposed sensor-tree-creation algorithms are heuristic. To evaluate a heuristic algorithm, the time complexity of the algorithm is very important, as well as the quantitative evaluation of the lifetimes of the created trees and algorithm speed. This paper proposes an algorithm called assured switching with accurate graph optimization (ASAGAO) that can create a sensor tree with a much longer lifetime much faster than other sensor-tree-creation algorithms. In addition, it has much smaller time complexity.

We have proposed a fish farm monitoring system for achieving efficient fish farming. In our system, sensor nodes are attached at fish to monitor its health status. In this letter, we propose a method for gathering sensor data from sensor nodes to sink nodes when the transmission range of sensor node is shorter than the size of fish cage. In our proposed method, a part of sensor nodes become leader nodes and they forward gathered sensor data to the sink nodes. Through simulation evaluations, we show that the data gathering performance of our proposed method is higher than that of traditional methods.

We have proposed a fish farm monitoring system for the efficient farming of tuna. In our system, energy efficient and adaptive control of sensor node is highly important. In addition, since a sensor node is attached to the fish, the transmission range of sensor node is not omni-directional. In this paper, we propose a data gathering mechanism for fish farm monitoring by extending a traditional desyncronization mechanism. In our proposed mechanism, by utilizing acknowledgment packets from the sink node, distributed and adaptive timing control of packet transmission is accomplished. In addition, we apply a reassignment mechanism and a sleep mechanism for improving the performance of our proposed mechanism. Through simulation experiments, we show that the performance of our proposed mechanism is higher than that of comparative mechanisms.

In this letter, a distributed TDMA-based data gathering scheme for wireless sensor networks, called DTDGS, is proposed in order to avoid transmission collisions, achieve high levels of power conservation and improve network lifetime. Our study is based on corona-based network division and a distributed TDMA-based scheduling mechanism. Different from a centralized algorithm, DTDGS does not need a centralized gateway to assign the transmission time slots and compute the route for each node. In DTDGS, each node selects its transmission slots and next-hop forwarding node according to the information gathered from neighbor nodes. It aims at avoiding transmission collisions and balancing energy consumption among nodes in the same corona. Compared with previous data gathering schemes, DTDGS is highly scalable and energy efficient. Simulation results show high the energy efficiency of DTDGS.

Many methods have been researched to prolong the lifetime of sensor networks that use mobile technologies. In the mobile sink research, there are the track based methods and the anchor points based methods as representative operation methods for mobile sinks. However, most existing methods decrease the Quality of Service (QoS) and lead to routing hotspots in the vicinity of the mobile sinks. The main reason is that they use static mobile sink movement paths that ignore the network environment such as the query position and the data priority. In this paper, we propose a novel mobile sink operation method that solves the problems of the existing methods. In our method, the probe priority of the mobile sink is determined from data priority to increase the QoS. The mobility of sink used to reduce the routing hotspot. Experiments show that the proposed method reduces the query response time and improves the network lifetime much more than the existing methods.

This paper presents a prototype group modem for a hyper-multipoint data gathering satellite communication system. It can handle arbitrarily and dynamically assigned FDMA signals by employing a novel FFT-type block demultiplexer/multiplexer. We clarify its configuration and operational principle. Experiments show that the developed modem offers excellent performance.

This paper describes a novel channel allocation scheme that enables data to be collected from observation points throughout the ultra-wide area covered by a satellite communication system. Most of the earth stations in the system acquire pre-scheduled type data such as that pertaining to rainfall and temperature measurements, but a few of them acquire event-driven type data such as that pertaining to earthquakes. Therefore, the main issue pertaining to this scheme is how to effectively accommodate demand for the channels by a huge number of earth stations with limited satellite frequency bandwidth regardless of their acquired data types. To tackle this issue, we propose a channel allocation scheme built on a pre-assigned scheme to gather pre-scheduled type data but that also includes an additional procedure to gather event-driven type data reliably. Performance evaluations show that the proposed scheme achieves higher throughput and lower packet loss rate than conventional schemes.

Wireless sensor networks (WSNs) have attracted a significant amount of interest from many researchers because they have great potential as a means of obtaining information of various environments remotely. WSNs have a wide range of applications, such as natural environmental monitoring in forest regions and environmental control in office buildings. In WSNs, hundreds or thousands of micro-sensor nodes with such resource limitations as battery capacity, memory, CPU, and communication capacity are deployed without control in a region and used to monitor and gather sensor information of environments. Therefore, a scalable and efficient network control and/or data gathering scheme for saving energy consumption of each sensor node is needed to prolong WSN lifetime. In this paper, assuming that sensor nodes synchronize to intermittently communicate with each other only when they are active for realizing the long-term employment of WSNs, we propose a new synchronization scheme for gathering sensor information using chaotic pulse-coupled neural networks (CPCNN). We evaluate the proposed scheme using computer simulations and discuss its development potential. In simulation experiments, the proposed scheme is compared with a previous synchronization scheme based on a pulse-coupled oscillator model to verify its effectiveness.

One challenging issue of sensor networks is extension of overall network system lifetimes. In periodic data gathering applications, the typical sensor node spends more time in the idle state than active state. Consequently, it is important to decrease power consumption during idle time. In this study, we propose a scheduling scheme based on the history of RTS/CTS exchange during the setup phase. Scheduling the transmission during transfer phase enables each node to turn off its RF circuit during idle time. By tracing ongoing RTS/CTS exchange during the steady phase, each node knows the progress of the data transfer process. Thereby, it can wait to receive packets for data aggregation. Simulation results show a 160-260% longer system lifetime with the proposed scheduling scheme compared to the existing approaches.

By deploying hundreds or thousands of microsensors and organizing a network of them, one can monitor and obtain information of environments or objects for use by users, applications, or systems. Since sensor nodes are usually powered by batteries, an energy-efficient data gathering scheme is needed to prolong the lifetime of the sensor network. In this paper, we propose a novel scheme for data gathering where sensor information periodically propagates from the edge of a sensor network to a base station as the propagation forms a concentric circle. Since it is unrealistic to assume any type of centralized control in a sensor network whose nodes are deployed in an uncontrolled way, a sensor node independently determines the cycle and the timing at which it emits sensor information in synchrony by observing the radio signals emitted by sensor nodes in its vicinity. For this purpose, we adopt a pulse-coupled oscillator model based on biological mutual synchronization such as that used by flashing fireflies, chirping crickets, and pacemaker cells. We conducted simulation experiments, and verified that our scheme could gather sensor information in a fully-distributed, self-organizing, robust, adaptive, scalable, and energy-efficient manner.

The main contribution of this work is to propose energy-efficient protocols that compute the sum of n numbers over any commutative and associative binary operator stored in n wireless sensor nodes arranged in a two-dimensional grid of size nn. We first present a protocol that computes the sum on a Wireless Sensor Network (WSN) in O(r2+(n/r2)1/3) time slots with no sensor node being awake for more than O(1) time slots, where r is the transmission range of the sensor nodes. We then go on to present a fault-tolerant protocol which computes the sum in the same number of time slots with no sensor node being awake for more than O(log r) time slots. Finally, we show that in a WSN where the sensor nodes are empowered with the ability to dynamically adjust their transmission range r during the execution of the protocol, the sum can be computed in O(log n) time slots and no sensor node needs to awake for more than O(log n) time slots.