• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.17-26
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• 2022

Sensor Nodes play a major role to monitor and sense the variations in physical space in various real-time application scenarios. These nodes are powered by limited battery resources and replacing those resource is highly tedious task along with this it increases implementation cost. Thus, maintaining a good network lifespan is amongst the utmost important challenge in this field of WSN. Currently, energy efficient routing techniques are considered as promising solution to prolong the network lifespan where multi-hop communications are performed by identifying the most energy efficient path. However, the existing scheme suffer from performance related issues. To solve the issues of existing techniques, a novel hybrid technique by merging particle swarm optimization and game theory model is presented. The PSO helps to obtain the efficient number of cluster and Cluster Head selection whereas game theory aids in finding the best optimized path from source to destination by utilizing a path selection probability approach. This probability is obtained by using conditional probability to compute payoff for agents. When compared to current strategies, the experimental study demonstrates that the proposed GTPSO strategy outperforms them.

• Journal of Sensor Science and Technology
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• v.20 no.2
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• pp.137-144
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• 2011

Wireless sensor network(WSN) has the potential to greatly effect many aspects of u-healthcare. By outfitting the potential with WSN, wearable sensor node can collects real-time data on physiological status and transmits through base station to server PC. However, there is a significant gap between WSN and healthcare. WSN has the limited resource about computing capability and data transmission according to bio-sensor sampling rates and channels to apply healthcare system. If a wearable node transmits ECG and accelerometer data of 4 channel sampled at 100 Hz, these data may occur high loss packets for transmitting human activity and ECG to server PC. Therefore current wearable sensor nodes have to solve above mentioned problems to be suited for u-healthcare system. Most WSN based activity and ECG monitoring system have been implemented some algorithms which are applied for signal vector magnitude(SVM) algorithm and ECG noise algorithm in server PC. In this paper, A wearable sensor node using integrated ECG and 3-axial accelerometer based on wireless sensor network is designed and developed. It can form multi-hop network with relay nodes to extend network range in WSN. Our wearable nodes can transmit 1-channel activity data processed activity classification data vector using SVM algorithm to 3-channel accelerometer data. ECG signals are contaminated with high frequency noise such as power line interference and muscle artifact. Our wearable sensor nodes can remove high frequency noise to clear original ECG signal for healthcare monitoring.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.307-312
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• 2007

Wireless Sensor Network(WSN) is considered as a core technology necessary for Ubiquitous computing, with its numerous possible applications in many practical areas, is being researched and studied actively by many around the world. WSN utilizes wireless sensors spatially placed to gather information regarding temperature, light condition, motion and change in speed of the objects within their surrounding environment. This paper implements an environmental information monitoring and indexing system based on spatial indexing technique by constructing a WSN system. This Multi-Query Indexing Technique coupled with wireless sensors provides an output based on the pre-defined built-in data index and new input from the sensors. If environment data is occured, system have to perform a proper action after collecting and analyzing this data. This is the purpose of implementing environment data monitoring system. We constructed environmental application using TinyOS and built tested with MICAz sensor bords. We designed and implemented a monitoring system which detects and multi-indexing process environmental data from distributed sensors.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.10 no.3
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• pp.86-91
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• 2011

Wireless sensor network (WSN) is a distributed self-organizing network which contains a large number of tiny multi-functional sensor nodes. The network life time is an important issue in WSN because every sensor node has a constraint on electric supply. In this paper, an energy consumption model is described and a GA-based algorithm will be used to optimize the energy consumption by analyzing the working model of sensor nodes. The model will provide an effective reference of working pattern for WSN. This algorithm is evaluated through analysis and simulations.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.796-805
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• 2016

In many wireless sensor network (WSN) applications, the information transmitted by an individual entity or node is of limited use without the knowledge of its location. Research in node localization is mostly geared towards multi-hop range-free localization algorithms to achieve accuracy by minimizing localization errors between the node's actual and estimated position. The existing localization algorithms are focused on improving localization accuracy without considering efficiency in terms of energy costs and algorithm convergence time. In this work, we show that our proposed localization scheme, called DV-maxHop, can achieve good accuracy and efficiency. We formulate the multi-objective optimization functions to minimize localization errors as well as the number of transmission during localization phase. We evaluate the performance of our scheme using extensive simulation on several anisotropic and isotropic topologies. Our scheme can achieve dual objective of accuracy and efficiency for various scenarios. Furthermore, the recently proposed algorithms require random uniform distribution of anchors. We also utilized our proposed scheme to compare and study some practical anchor distribution schemes.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.177-185
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• 2008

Research on media access control (MAC) scheme for Wireless Sensor Network (WSN) has been mainly focused on energy efficiency improvement, while interest on latency is relatively weak. However, end-to-end latency could be a critical limitation specifically in the multi-hop network such as wireless multimedia sensor networks. In this paper we propose a media access control scheme with distributed transmission power control to Improve end-to-end transmission latency as well as reduce power consumption in multi-hop wireless sensor networks. According to the simulation results, the proposed scheme is turned out to be an energy efficient scheme with improved end-to-end transmission latency.

• Smart Structures and Systems
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• v.14 no.1
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• pp.39-54
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• 2014

Node layout optimization of structural wireless systems is investigated as a means to prolong the network lifetime without, if possible, compromising information quality of the measurement data. The trade-off between these antagonistic objectives is studied within a multi-objective layout optimization framework. A Genetic Algorithm is adopted to obtain a set of Pareto-optimal solutions from which the end user can select the final layout. The information quality of the measurement data collected from a heterogeneous WSN is quantified from the placement quality indicators of strain and acceleration sensors. The network lifetime or equivalently the network energy consumption is estimated through WSN simulation that provides realistic results by capturing the dynamics of the wireless communication protocols. A layout optimization study of a monitoring system on the Great Belt Bridge is conducted to evaluate the proposed approach. The placement quality of strain gauges and accelerometers is obtained as a ratio of the Modal Clarity Index and Mode Shape Expansion values that are computed from a Finite Element model of the monitored bridge. To estimate the energy consumption of the WSN platform in a realistic scenario, we use a discrete-event simulator with stochastic communication models. Finally, we compare the optimization results with those obtained in a previous work where the network energy consumption is obtained via deterministic communication models.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.11B
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• pp.685-692
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• 2007

Recent advances in wireless communications and electronics have enabled the development of low-cost, low-power, multi-functional sensors. A typical wireless sensor network (WSN) consists of a large number of sensor nodes that can measure and process data while communicating through wireless channels. In this paper, we propose a hybrid query processing (HQP) algorithm for user queries submitted to the WSN. Unlike previous algorithms that consider continuous queries only, HQP supports both continuous queries and ad-hoc queries. Specially. HQP tries to reduce energy consumption of ad-hoc queries by using query results cached at each sensor node which are created during the execution of the previous continuous query. HQP can also exploit a trade-off between energy consumption and data accuracy. We evaluate the performance of HQP under a variety of WSN configurations.

• International journal of advanced smart convergence
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• v.5 no.2
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• pp.24-37
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• 2016

This paper proposes to increase the efficiency of energy in nodes, which rapidly drops during the transmission of the Low Energy Adaptive Clustering Hierarchy (LEACH), through the use of dual-hop layered application in the sensor field. Along with introducing the dual-hop method in the data transmission, the proposed single-hop method for short-range transmission and multi-hop transmission method between the cluster heads for remote transmission were also introduced. Additionally, by introducing a partial multi-hop method in the data transmission, a single-hop method for short range transmission method between the cluster heads for remote transmission was used. In the proposed DL-LEACH, the energy consumption of the cluster head for remote transmission reduced, as well as increased the energy efficiency of the sensor node by reducing the transmission distance and simplifying the transmission route for short-range transmission. As compared the general LEACH, it was adapted to a wider sensor field.

• Journal of Communications and Networks
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• v.18 no.4
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• pp.580-588
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• 2016

Energy efficiency is the main objective in the design of a wireless sensor network (WSN). In many applications, sensing data must be transmitted from sources to a sink in a timely manner. This paper describes an investigation of the trade-off between two objectives in WSN design: minimizing energy consumption and minimizing end-to-end delay. We first propose a new distributed clustering approach to determining the best clusterhead for each cluster by considering both energy consumption and end-to-end delay requirements. Next, we propose a new energy-cost function and a new end-to-end delay function for use in an inter-cluster routing algorithm. We present a multi-hop routing algorithm for use in disseminating sensing data from clusterheads to a sink at the minimum energy cost subject to an end-to-end delay constraint. The results of a simulation are consistent with our theoretical analysis results and show that our proposed performs much better than similar protocols in terms of energy consumption and end-to-end delay.