• International Journal of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.25-33
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• 2021

Energy-harvesting wireless sensor networks(EH-WSNs) can collect energy from the environment and overcome the technical limitations of existing power. Since the transmission distance in a wireless sensor network is limited, the data are delivered to the destination node through multi-hop routing. In EH-WSNs, the routing protocol should consider the power situations of nodes, which is determined by the remaining power and energy-harvesting rate. In addition, in applications such as environmental monitoring, when there are urgent data, the routing protocol should be able to transmit it stably and quickly. This paper proposes an adaptive routing protocol that satisfies different requirements of normal and urgent data. To extend network lifetime, the proposed routing protocol reduces power imbalance for normal data and also minimizes transmission latency by controlling the transmission power for urgent data. Simulation results show that the proposed adaptive routing can improve network lifetime by mitigating the power imbalance and greatly reduce the transmission delay of urgent data.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.290-292
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• 2009

With advance in technologies for wireless sensor networks(WSNs), 2.4 GHz band has become gradually attractive due to increase in low-power wireless communication devices. Especially ZigBee(IEEE 802.15.4-based) technology whose frequency band includes the 2.4GHz industrial, scientific and medical band providing nearly worldwide availability has been universally applicable to a various remote monitoring system and applications related home network system. However network throughput of these systems is significantly deteriorated due to this ISM band is a license-exemption used in a variety of low-power wireless communication devices. For instance, other IEEE 802 wireless standards such as Bluetooth, WLAN, Wi-Fi and others cause radio interference to ZigBee. The experiments was carried out to analyze radio frequency interference between heterogeneous devices using ISM bands to improve the limited frequency utility factor. Finally this paper suggests a frequency hopping-based adaptive multi-channel methods to decrease interference with empirical results.

• Journal of Communications and Networks
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• v.13 no.1
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• pp.17-25
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• 2011

A convergecast is a popular routing scheme in wireless sensor networks (WSNs) in which every sensor node periodically forwards measured data along configured routing paths to a base station (BS). Prolonging lifetimes in energy-limited WSNs is an important issue because the lifetime of a WSN influences on its quality and price. Low-energy adaptive clustering hierarchy (LEACH) was the first attempt at solving this lifetime problem in convergecast WSNs, and it was followed by other solutions including power efficient gathering in sensor information systems (PEGASIS) and power efficient data gathering and aggregation protocol (PEDAP). Our solution-chain routing with even energy consumption (CREEC)-solves this problem by achieving longer average lifetimes using two strategies: i) Maximizing the fairness of energy distribution at every sensor node and ii) running a feedback mechanism that utilizes a preliminary simulation of energy consumption to save energy for depleted Sensor nodes. Simulation results confirm that CREEC outperforms all previous solutions such as LEACH, PEGASIS, PEDAP, and PEDAP-power aware (PA) with respect to the first node death and the average lifetime. CREEC performs very well at all WSN sizes, BS distances and battery capacities with an increased convergecast delay.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.846-856
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• 2016

Wireless sensor networks (WSNs) are widely applied in monitoring and control of environment parameters. It is sometimes necessary to disseminate data through wireless links after they are deployed in order to adjust configuration parameters of sensors or distribute management commands and queries to sensors. Several approaches have been proposed recently for data dissemination in WSNs. However, none of these approaches achieves both high efficiency and low complexity simultaneously. To address this problem, cluster-tree based network architecture, which divides a WSN into hierarchies and clusters is proposed. Upon this architecture, data is delivered from base station to all sensors in clusters hierarchy by hierarchy. In each cluster, father broadcasts data to all his children with instantly decodable network coding (IDNC), and a novel scheme targeting to maximize total transmission gain (MTTG) is proposed. This scheme employs a new packet scheduling algorithm to select IDNC packets, which uses weight status feedback matrix (WSFM) directly. Analysis and simulation results indicate that the transmission efficiency approximate to the best existing approach maximum weight clique, but with much lower computational overhead. Hence, the energy efficiency achieves both in data transmission and processing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.9
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• pp.820-827
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• 2014

One of the basic problems in Wireless Sensor Networks (WSNs) is the localization of the sensor nodes based on the known location of numerous anchor nodes. WSNs generally consist of a large number of sensor nodes and recording the location of each sensor nodes becomes a difficult task. On the other hand, based on the application environment, the nodes may be subject to mobility and their location changes with time. Therefore, a scheme that will autonomously estimate or calculate the position of the sensor nodes is desirable. This paper presents an intelligent localization scheme, which is an artificial neural network (ANN) based localization scheme used to estimate the position of the unknown nodes. In the proposed method, three anchors nodes are used. The mobile or deployed sensor nodes request a beacon from the anchor nodes and utilizes the received signal strength indicator (RSSI) of the beacons received. The RSSI values vary depending on the distance between the mobile and the anchor nodes. The three RSSI values are used as the input to the ANN in order to estimate the location of the sensor nodes. A feed-forward artificial neural network with back propagation method for training has been employed. An average Euclidian distance error of 0.70 m has been achieved using a ANN having 3 inputs, two hidden layers, and two outputs (x and y coordinates of the position).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4B
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• pp.208-216
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• 2007

Wireless Sensor Networks (WSNs) are characterized by low capacity on each nodes and links. Wireless links have high bit error rate (BER) parameter that changes frequently due to the changes on network topology, interference, etc. To guarantee reliability in an error-prone environment, a retransmission mechanism can be used. In this mechanism, the number of retransmissions is used as a parameter that controls reliability requirement level. In this paper, we propose an Error Adaptive Transport Protocol (EATP) for WSNs that updates the number of retransmissions regularly to guarantee reliability during bit error rate changes as well as to utilize energy effectively. The said algorithm uses local information, thus, it does not create overhead problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.6
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• pp.2644-2657
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• 2018

To utilize the energy of sensor nodes efficiently and extend the network lifetime maximally is one of the primary goals in wireless sensor networks (WSNs). Thus, designing an energy-efficient protocol to optimize the determination of cluster heads (CHs) in WSNs has become increasingly important. In this paper, we propose a novel energy-efficient protocol based on an improved Grey Wolf Optimizer (GWO), which we refer to as Fitness value based Improved GWO (FIGWO). It considers a fitness value to improve the finding of the optimal solution in GWO, which ensures a better distribution of CHs and a more balanced cluster structure. According to the distance to the CHs and the BS, sensor nodes' transmission distance are recalculated to reduce the energy consumption. Simulation results demonstrate that the proposed approach can prolong the stability period of the network in comparison to other algorithms, namely by 31.5% in comparison to SEP, and even by 57.8% when compared with LEACH protocol. The results also show that the proposed protocol performs well over the above comparative protocols in terms of energy consumption and network throughput.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.4 no.1
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• pp.5-24
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• 2010

Data fusion is an attractive technology because it allows various trade-offs related to performance metrics, e.g., energy, latency, accuracy, fault-tolerance and security in wireless sensor networks (WSNs). Under a complicated environment, each sensor node must be equipped with more than one type of sensor module to monitor multi-targets, so that the complexity for the fusion process is increased due to the existence of various physical attributes. In this paper, we first investigate the process and performance of multi-attribute fusion in data gathering of WSNs, and then propose a self-adaptive threshold method to balance the different change rates of each attributive data. Furthermore, we present a method to measure the energy-conservation efficiency of multi-attribute fusion. Based on our proposed methods, we design a novel energy equilibrium routing method for WSNs, viz., multi-attribute fusion tree (MAFT). Simulation results demonstrate that MAFT achieves very good performance in terms of the network lifetime.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.857-869
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• 2016

This paper proposes an X-MAC/BEB protocol that runs a binary exponential backoff (BEB) algorithm on top of an X-MAC protocol to save more energy by reducing collision, especially in densely populated wireless sensor networks (WSNs). X-MAC, a lightweight asynchronous duty cycle medium access control (MAC) protocol, was introduced for spending less energy than its predecessor, B-MAC. One of X-MAC 's conspicuous technique is a mechanism to allow senders to promptly send their data when their receivers wake up. X-MAC, however, has no mechanism to deal with sudden traffic fluctuations that often occur whenever closely located nodes simultaneously diffuse their sense data. To precisely evaluate the impact of the BEB algorithm on X-MAC, this paper builds an analytical model of X-MAC/BEB that integrates the BEB model with the X-MAC model. The analytical and simulation results confirmed that X-MAC/BEB outperformed X-MAC in terms of throughput, delay, and energy consumption, especially in congested WSNs.

• Journal of information and communication convergence engineering
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• v.10 no.3
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• pp.276-283
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• 2012

Nowadays, wireless sensor networks (WSNs) comprise a tremendously growing infrastructure for monitoring the physical or environmental conditions of objects. WSNs pose challenges to mitigating energy dissipation by constructing a reliable and energy saving network. In this paper, we propose a novel network construction and routing method by defining three different duties for sensor nodes, that is, node gateways, cluster heads, and cluster members, and then by applying a hierarchical structure from the sink to the normal sensing nodes. This method provides an efficient rationale to support the maximum coverage, to recover missing data with node mobility, and to reduce overall energy dissipation. All this should lengthen the lifetime of the network significantly.