• Journal of Computing Science and Engineering
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• v.9 no.4
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• pp.163-176
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• 2015

Self-organization of distributed wireless sensor nodes is a critical issue in wireless sensor networks (WSNs), since each sensor node has limited energy, bandwidth, and scalability. These issues prevent sensor nodes from actively collaborating with the other types of sensor nodes deployed in a typical heterogeneous and somewhat hostile environment. The automated self-organization of a WSN becomes more challenging as the number of sensor nodes increases in the network. In this paper, we propose a dynamic self-organized architecture that combines tree topology with a drawn-grid algorithm to automate the self-organization process for WSNs. In order to make our proposed architecture scalable, we assume that all participating active sensor nodes are unaware of their primary locations. In particular, this paper presents two algorithms called active-tree and drawn-grid. The proposed active-tree algorithm uses a tree topology to assign node IDs and define different roles to each participating sensor node. On the other hand, the drawn-grid algorithm divides the sensor nodes into cells with respect to the radio coverage area and the specific roles assigned by the active-tree algorithm. Thus, both proposed algorithms collaborate with each other to automate the self-organizing process for WSNs. The numerical and simulation results demonstrate that the proposed dynamic architecture performs much better than a static architecture in terms of the self-organization of wireless sensor nodes and energy consumption.

• 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).

• IEMEK Journal of Embedded Systems and Applications
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• v.2 no.3
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• pp.138-144
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• 2007

Wireless Sensor Network(WSN) consists of a lot of light-weight sensor nodes with the capability of wireless communication. Studies have been done to improve stability and fault-tolerancy of WSN because the sensor nodes are basically vulnerable to the harsh environment. Specially, the time synchronization among sensor nodes becomes a challenging issue in WSN. All the local times should always keep the same with each other in the sensor field to perform data aggregation and energy-aware communication in WSN. In this paper, a new time synchronization technique is proposed to operate efficiently irrespective of the number of sensor nodes and the number of hops needed to cover all sensor nodes for synchronization. Simulation results show that the proposed technique has the lowest amount of packet traffic among the several time synchronization techniques.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.38-43
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• 2017

Sensor Networks (WSNs) can be defined as a self-configured and infrastructure-less wireless networks to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants and to cooperatively pass their data through the network to a main location or base-station where the data can be observed and analyzed. Typically a wireless sensor network contains hundreds of thousands of sensor nodes. The sensor nodes can communicate among themselves using radio signals. A wireless sensor node is equipped with sensing and computing devices, radio transceivers and power components. The individual nodes in a wireless sensor network (WSN) are inherently resource constrained: they have limited processing speed, storage capacity, communication bandwidth and limited-battery power. At present time, most of the research on WSNs has concentrated on the design of energy- and computationally efficient algorithms and protocols In order to extend the network life-time, in this paper we are looking into a routing protocol, especially LEACH and LEACH-related protocol. LEACH protocol is a representative routing protocol and improves overall network energy efficiency by allowing all nodes to be selected to the cluster head evenly once in a periodic manner. In LEACH, in case of movement of sensor nodes, there is a problem that the data transmission success rate decreases. In order to overcome LEACH's nodes movements, LEACH-Mobile protocol had proposed. But energy consumption increased because it consumes more energy to recognize which nodes moves and re-transfer data. In this paper we propose the new routing protocol considering nodes' mobility. In order to simulate the proposed protocol, we make a scenario, nodes' movements randomly and compared with the LEACH-Mobile protocol.

• Journal of KIISE
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• v.42 no.1
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• pp.114-121
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• 2015

Large-scale wireless sensor networks are constructed by using a large number of sensor nodes that are non-uniformly deployed over a wide area. As a result, the data collected by the sensor nodes are similar to that from one another since a high density of the sensor nodes may cause an overlap. As a result of the characteristics of the traffic, data is collected from a plurality of sensor nodes by a sink node, and when the sensor nodes transmit their collected data to the sink node, the sensor nodes around the sink node have a higher amount of traffic than the sensor nodes far away from the sink node. Thus, the former sensor encounter bottlenecks due to traffic congestion and have an energy hole problem more often than the latter ones, increasing energy consumption. This paper proposes a congestion control scheme that considers traffic flows in order to control traffic congestion of the sensor nodes that are non-uniformly deployed over a large-scale wireless sensor network.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.44 no.1
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• pp.41-48
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• 2007

In this paper, we propose an optimal placement of sensor nodes with 2.4GHz wireless channel characteristics. The proposed method determines optimal transmission range based on log-normal path loss model, and optimal number of sensor nodes calculating the density of sensor nodes. For the lossless data transmission, we search the optimal locations with self-organizing feature maps(SOM) using transmission range, and number of sensor nodes. We demonstrate that optimal transmission range is 20m, and optimal number of sensor nodes is 8. We performed simulations on the searching for optimal locations and confirmed the link condition of sensor nodes.

• Journal of Information Processing Systems
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• v.6 no.3
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• pp.295-306
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• 2010

Network lifetime is a critical issue in Wireless Sensor Networks (WSNs). In which, a large number of sensor nodes communicate together to perform a predetermined sensing task. In such networks, the network life time depends mainly on the lifetime of the sensor nodes constituting the network. Therefore, it is essential to balance the energy consumption among all sensor nodes to ensure the network connectivity. In this paper, we propose an energy-efficient data routing protocol for wireless sensor networks. Contrary to the protocol proposed in [6], that always selects the path with minimum hop count to the base station, our proposed routing protocol may choose a longer path that will provide better distribution of the energy consumption among the sensor nodes. Simulation results indicate clearly that compared to the routing protocol proposed in [6], our proposed protocol evenly distributes the energy consumption among the network nodes thus maximizing the network life time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1224-1248
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• 2022

In various sensor network applications, such as climate observation organizations, sensor nodes need to collect information from time to time and pass it on to the recipient of information through multiple bounces. According to field tests, this information corresponds to most of the energy use of the sensor hub. Decreasing the measurement of information transmission in sensor networks becomes an important issue.Compression sensing (CS) can reduce the amount of information delivered to the network and reduce traffic load. However, the total number of classification of information delivered using pure CS is still enormous. The hybrid technique for utilizing CS was proposed to diminish the quantity of transmissions in sensor networks.Further the energy productivity is a test task for the sensor nodes. However, in previous studies, a clustering approach using hybrid CS for a sensor network and an explanatory model was used to investigate the relationship between beam size and number of transmissions of hybrid CS technology. It uses efficient data integration techniques for large networks, but leads to clone attacks or attacks. Here, a new algorithm called SBEA (Snowball Endurance Algorithm) was proposed and tested with a bow. Thus, you can extend the battery life of your WSN by running effective copy detection. Often, multiple nodes, called observers, are selected to verify the reliability of the nodes within the network. Personal data from the source centre (e.g. personality and geographical data) is provided to the observer at the optional witness stage. The trust and reputation system is used to find the reliability of data aggregation across the cluster head and cluster nodes. It is also possible to obtain a mechanism to perform sleep and standby procedures to improve the life of the sensor node. The sniffers have been implemented to monitor the energy of the sensor nodes periodically in the sink. The proposed algorithm SBEA (Snowball Endurance Algorithm) is a combination of ERCD protocol and a combined mobility and routing algorithm that can identify the cluster head and adjacent cluster head nodes.This algorithm is used to yield the network life time and the performance of the sensor nodes can be increased.

• IEMEK Journal of Embedded Systems and Applications
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• v.6 no.6
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• pp.369-376
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• 2011

Since wireless sensor networks generally have the capability of network recovery, malfunction of a few sensor nodes in a sensor network does not cause a crucial problem paralyzing the sensor network. The malfunction of the sink node, however, is critical. If the sink node of a sensor network stops working, the data collected by sensor nodes cannot be delivered to the gateway because no other sensor nodes can take the place of the sink node. This paper proposes a TDMA-based wireless sensor network equipped with dual sink nodes, with a view to preventing data loss in the case of malfunction of a sink node. A secondary sink node, which synchronizes with a primary sink node and receives data from other sensor nodes in normal situations, takes the role of the primary sink node in the case of malfunction of the primary sink, thereby eliminating the possibility of data loss. The effectiveness of the proposed scheme is demonstrated through experiments.

• Journal of KIISE:Information Networking
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• v.35 no.2
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• pp.120-129
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• 2008

The purpose of sensor network is gathering the information from sensor nodes. If there are selfish node that deliberately avoid packet forwarding to save their own energy, the sensor network has trouble to collect information smoothly. To solve this problem we suggest a mechanism which uses credit payment schema according to the amount of forwarding packets. Sensor nodes use credits to send their own message and they forward packets of other sensor nodes to get credits. To offer authenticity we combined the roles of sink node and server, also we used piggybacking not to send additional report message. The packet trace route is almost fixed because sensor node doesn't have mobility. In this case, it happens that some sensor nodes which don't receive forwarding packets therefore they can't get credit. So, we suggested the way to give more credits to these sensor nodes. Finally, we simulated the suggested mechanism to evaluate performance with ns2(network simulator). As a result, packet transmission rate was kept on a high rate and the number of arrival packets to sink node was increased. Also, we could verify that more sensor nodes live longer due to deceasing the energy consumption of sensor nodes.