• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.766-769
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• 2005

In a ubiquitous environment made up of multiple sensors, most sensors participate in communications with limited battery, and the sensor node isn't able to participate in communications when all the battery is used up. When an existing authentication method is used for the sensor node which has to participate in a long term communication with limited battery, it creates a problem by making the length of network maintenance or sensor node's operation time relatively shorte. Therefore, a network structure where RM (Register Manager) node and AM (Authentication Manager) node are imported to solve the energy consumption problem during a communication process is presented in this thesis. This offers a low power protocol based on safety through a mutual authentication during communications. Through registration and authentication manager nodes, each sensor nodes are ensured of safety and the algorithm of key's generation, encryption/descramble and authentication is processed with faster operation speed. So the amount of electricity used up during the communications between sensor nodes has been evaluated. In case of the amount of electrical usage, an average of $34.783\%$ for the same subnet and 36.855 for communications with two different subnets, are reduced. The proposed method is a protocol which maintains the limited battery for a long time to increase the effectiveness of energy usage in sensor nodes and can also increase the participation rate of communication by sensor nodes.

• ETRI Journal
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• v.39 no.2
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• pp.222-233
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• 2017

Debugging in distributed environments, such as wireless sensor networks (WSNs), which consist of sensor nodes with limited resources, is an iterative and occasionally laborious process for programmers. In sensor networks, it is not easy to find unintended bugs that arise during development and deployment, and that are due to a lack of visibility into the nodes and a dearth of effective debugging tools. Most sensor network debugging tools are not provided with effective facilities such as real-time tracing, remote debugging, or a GUI environment. In this paper, we present a hybrid debugging framework (HDF) that works on WSNs. This framework supports query-based monitoring and real-time tracing on sensor nodes. The monitoring supports commands to manage/control the deployed nodes, and provides new debug commands. To do so, we devised a debugging device called a Docking Debug-Box (D2-Box), and two program agents. In addition, we provide a scalable node monitor to enable all deployed nodes for viewing. To transmit and collect their data or information reliably, all nodes are connected using a scalable node monitor applied through the Internet. Therefore, the suggested framework in theory does not increase the network traffic for debugging on WSNs, and the traffic complexity is nearly O(1).

• Journal of Korea Multimedia Society
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• v.22 no.6
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• pp.676-683
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• 2019

Wireless Sensor Networks (WSNs) consist of multiple tiny and power constrained sensors which use radio frequencies to carry out sensing in a designated sensor area. To effectively design and implement reliable WSN, it is critical to consider models, protocols, and algorithms that can optimize energy consumption of all the sensor nodes with optimal amount of packet delivery. It has been observed that deploying a single sink node comes with numerous challenges especially in a situation with high node density and congestion. Sensor nodes close to a single sink node receive more transmission traffic load compared to other sensors, thus causing quick depletion of energy which finally leads to an energy hole and sink hole problems. In this paper, we proposed the use of multiple energy efficient sink nodes with brute force technique under optimized parameters to improve on the number of packets delivered within a given time. Simulation results not only depict that, deploying N sink nodes in a sensor area has a maximum limit to offer a justifiable improvement in terms of packet delivery ratio but also offers a reduction in End to End delay and reliability in case of failure of a single sink node, and an improvement in the network lifetime rather than deploying a single static sink node.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.1014-1034
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• 2015

Location information of sensor nodes plays a critical role in many wireless sensor network (WSN) applications and protocols. Although many localization algorithms have been proposed in recent years, they usually target at dense networks and perform poorly in sparse networks. In this paper, we propose two component-based localization algorithms that can localize many more nodes in sparse networks than the state-of-the-art solution. We first develop the Basic Common nodes-based Localization Algorithm, namely BCLA, which uses both common nodes and measured distances between adjacent components to merge components. BCLA outperforms CALL, the state-of-the-art component-based localization algorithm that uses only distance measurements to merge components. In order to further improve the performance of BCLA, we further exploit the angular information among nodes to merge components, and propose the Component-based Localization with Angle and Distance information algorithm, namely CLAD. We prove the merging conditions for BCLA and CLAD, and evaluate their performance through extensive simulations. Simulations results show that, CLAD can locate more than 90 percent of nodes in a sparse network with average node degree 7.5, while CALL can locate only 78 percent of nodes in the same scenario.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.1-6
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• 2009

Localization of nodes is a key technology for application of wireless sensor network. Having a GPS receiver on every sensor node is costly. In the past, several approaches, including range-based and range-free, have been proposed to calculate positions for randomly deployed sensor nodes. Most of them use some special nodes, called anchor nodes, which are assumed to know their own locations. Other sensors compute their locations based on the information provided by these anchor nodes. This paper uses a single mobile anchor node to move in the sensing field and broadcast its current position periodically. We provide a weighted centroid localization algorithm that uses coefficients, which are decided by the influence of mobile anchor node to unknown nodes, to prompt localization accuracy. We also suggest a criterion which is used to select mobile anchor node which involve in computing the position of nodes for improving localization accuracy. Weighted centroid localization algorithm is simple, and no communication is needed while locating. The localization accuracy of weighted centroid localization algorithm is better than maximum likelihood estimation which is used very often. It can be applied to many applications.

• Journal of information and communication convergence engineering
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• v.16 no.3
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• pp.135-141
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• 2018

Wireless sensor networks (WSN) are composed of a large number of sensor nodes. Battery-powered sensor nodes have limited coverage; therefore, it is more efficient to transmit data via multi-hop communication. The network lifetime is a crucial issue in WSNs and the multi-hop routing protocol should be designed to prolong the network lifetime. Prolonging the network lifetime can be achieved by minimizing the power consumed by the nodes, as well as by balancing the power consumption among the nodes. A power imbalance can reduce the network lifetime even if several nodes have sufficient (battery) power. In this paper, we propose a routing protocol that prolongs the network lifetime by balancing the power consumption among the nodes. To improve the balance of power consumption and improve the network lifetime, the proposed routing scheme adaptively controls the transmission range using a power control according to the residual power in the nodes. We developed a routing simulator to evaluate the performance of the proposed routing protocol. The simulation results show that the proposed routing scheme increases power balancing and improves the network lifetime.

• Annual Conference of KIPS
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• 2009.11a
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• pp.547-548
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• 2009

The development of USN(Ubiquitous Sensor Network) technology is creating numerous application areas. Although a network configuration with fixed sensors was the norm in the past, the coexistence of mobile and fixed sensor nodes is a new trend. Fixed sensor networks focused on the energy efficiency of nodes, but the latest studies consider guaranteeing the mobility of nodes and maintaining their connectivity, while remaining energy efficient at the same time. This paper proposes a routing protocol for a mobile ad-hoc sensor network that improves the mobility, connectivity and energy efficiency of nodes while allowing for the management and maintenance of a large number of nodes even in a complex communication environment where mobile and fixed nodes coexist. An algorithm for multi-hop multi-paths, a technique for topology reconfiguration by node movement prediction and vibration sensors, path setting for a large number of nodes, and efficient data transfer technology have been introduced to implement the modified LEAHC-AOMDV protocol. Furthermore, the excellence of this protocol was verified through a comparative experiment with the conventional LEACH protocol.

• Journal of KIISE:Information Networking
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• v.37 no.3
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• pp.204-216
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• 2010

Since Sensor nodes around a fixed sink have huge concentrated network traffic, the battery consumption of them is increased extremely. Therefore the lifetime of sensor networks is limited because of huge battery consumption. To address this problem, a mobile sink has been studied for load distribution among sensor nodes. Since a mobile sink changes its location in sensor networks continuously, the mobile sink has time limits to communicate with each sensor node and unstable signal strength from each sensor node. Therefore, a fair and stable data collection method between a mobile sink and sensor nodes is necessary in this environment. When some sensor nodes are not able to send data to the mobile sink, a real-time application in sensor networks cannot be provided. In this paper, the new scheduling method, FQMS (Fair Queuing for Mobile Sink), is proposed for fair and stable data collection for mobile sinks in sensor networks. The FQMS guarantees balanced data collecting between sensor nodes for a mobile sink. In out experiments, the FQMS receives more packets from sensor nodes than legacy scheduling methods and provides fair data collection, because moving speed of a mobile sink, distance between a mobile sink and sensor nodes and the number of sensor nodes are considered.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.91-102
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• 2022

With the evolution of wireless sensor network (WSN) technology, the routing policy has foremost importance in the Internet of Things (IoT). A systematic routing policy is one of the primary mechanics to make certain the precise and robust transmission of wireless sensor networks in an energy-efficient manner. In an IoT environment, WSN is utilized for controlling services concerning data like, data gathering, sensing and transmission. With the advantages of IoT potentialities, the traditional routing in a WSN are augmented with decision-making in an energy efficient manner to concur finer optimization. In this paper, we study how to combine IoT-based deep learning classifier with routing called, Kriging Regressive Deep Belief Neural Learning (KR-DBNL) to propose an efficient data packet routing to cope with scalability issues and therefore ensure robust data packet transmission. The KR-DBNL method includes four layers, namely input layer, two hidden layers and one output layer for performing data transmission between source and destination sensor node. Initially, the KR-DBNL method acquires the patient data from different location. Followed by which, the input layer transmits sensor nodes to first hidden layer where analysis of energy consumption, bandwidth consumption and light intensity are made using kriging regression function to perform classification. According to classified results, sensor nodes are classified into higher performance and lower performance sensor nodes. The higher performance sensor nodes are then transmitted to second hidden layer. Here high performance sensor nodes neighbouring sensor with higher signal strength and frequency are selected and sent to the output layer where the actual data packet transmission is performed. Experimental evaluation is carried out on factors such as energy consumption, packet delivery ratio, packet loss rate and end-to-end delay with respect to number of patient data packets and sensor nodes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.3823-3840
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• 2017

This paper analyzes the nodes deployment optimization problem in energy constrained wireless sensor networks, which multi-hop cooperative beamforming (CB) based cooperative-multi-input-single-output (CMISO) transmission is adopted to reduce the energy consumption. Firstly, we establish the energy consumption models for multi-hop SISO, multi-hop DSTBC based CMISO, multi-hop CB based CMISO transmissions under random nodes deployment. Then, we minimize the energy consumption by searching the optimal nodes deployment for the three transmissions. Furthermore, numerical results present the optimal nodes deployment parameters for the three transmissions. Energy consumption of the three transmissions are compared under optimal nodes deployment, which shows that CB based CMISO transmission consumes less energy than SISO and DSTBC based CMISO transmissions. Meanwhile, under optimal nodes deployment, the superiorities of CB based CMISO transmission over SISO and DSTBC based CMISO transmissions can be more obvious when path-loss-factor becomes low.