• Title/Summary/Keyword: wsn

Search Result 891, Processing Time 0.033 seconds

Ad-hoc Query Processing in a Wireless Sensor Network (무선 센서 네트워크에서 순간 질의 처리 방법)

  • Yun, Sang-Hun;Cho, Haeng-Rae
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.32 no.11B
    • /
    • pp.685-692
    • /
    • 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.

Solar Energy Harvesting Wireless Sensor Network Simulator (태양 에너지 기반 무선 센서 네트워크 시뮬레이터)

  • Yi, Jun Min;Kang, Min Jae;Noh, Dong Kun
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.19 no.2
    • /
    • pp.477-485
    • /
    • 2015
  • Most existing simulators for wireless sensor networks(WSNs) are modeling battery-based sensors and providing MAC and routing protocols designed for battery-based WSNs. However, recently, as energy harvesting sensor systems have been studied more extensively, there is an increasing need for appropriate simulators, but few related studies have employed such simulators. Unlike existing simulators, simulators for energy harvesting WSNs require a new energy model that is integrated with the energy-harvesting model, rechargeable battery model, and energy-consuming model. Additionally, it should enable the applications of the well-known MAC and routing protocols designed for energy-harvesting WSNs, as well as a user-friendly interface for convenience. In this work, we design and implement a user-friendly simulator for solar energy-harvesting WSNs.

A Performance Analysis of Distributed Storage Codes for RGG/WSN (RGG/WSN을 위한 분산 저장 부호의 성능 분석)

  • Cheong, Ho-Young
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
    • /
    • v.10 no.5
    • /
    • pp.462-468
    • /
    • 2017
  • In this paper IoT/WSN(Internet of Things/Wireless Sensor Network) has been modeled with a random geometric graph. And a performance of the decentralized code for the efficient storage of data which is generated from WSN has been analyzed. WSN with n=100 or 200 has been modeled as a random geometric graph and has been simulated for their performance analysis. When the number of the total nodes of WSN is n=100 or 200, the successful decoding probability as decoding ratio ${\eta}$ depends more on the number of source nodes k rather than the number of nodes n. Especially, from the simulation results we can see that the successful decoding rate depends greatly on k value than n value and the successful decoding rate was above 70% when $${\eta}{\leq_-}2.0$$. We showed that the number of operations of BP(belief propagation) decoding scheme increased exponentially with k value from the simulation of the number of operations as a ${\eta}$. This is probably because the length of the LT code becomes longer as the number of source nodes increases and thus the decoding computation amount increases greatly.

A Study on Improvement of Energy Efficiency for LEACH Protocol in WSN (WSN에서 LEACH 프로토콜의 에너지 효율 향상에 관한 연구)

  • Lee, Won-Seok;Ahn, Tae-Won;Song, ChangYoung
    • Journal of the Institute of Electronics and Information Engineers
    • /
    • v.52 no.3
    • /
    • pp.213-220
    • /
    • 2015
  • Wireless sensor network(WSN) is made up of a lot of battery operated inexpensive sensors that, once deployed, can not be replaced. Therefore, energy efficiency of WSN is essential. Among the methods for energy efficiency of the network, clustering algorithms, which divide a WSN into multiple smaller clusters and separate all sensors into cluster heads and their associated member nodes, are very energy efficient routing technique. The first cluster-based routing protocol, LEACH, randomly elects the cluster heads in accordance with the probability. However, if the distribution of selected cluster heads is not good, uniform energy consumption of cluster heads is not guaranteed and it is possible to decrease the number of active nodes. Here we propose a new routing scheme that, by comparing the remaining energy of all nodes in a cluster, selects the maximum remaining energy node as a cluster head. Because of decrease in energy gap of nodes, the node that was a cluster head operates as a member node much over. As a result, the network lifespan is increased and more data arrives at base station.

LECSEN : Link Exchanged Chain in SEnsor Networks (링크 교환을 이용한 무선 센서 네트워크용 체인 토폴로지 : LECSEN)

  • Shin, Ji-Soo;Suh, Chang-Jin
    • The KIPS Transactions:PartC
    • /
    • v.15C no.4
    • /
    • pp.273-280
    • /
    • 2008
  • In WSN(Wireless Sensor Network) many routing algorithms such as LEACH, PEGASIS and PEDEP consisting of sensor nodes with limited energy have been proposed to extend WSN lifetime. Under the assumption of perfect fusion, these algorithms used convergecast that periodically collects sensed data from all sensor nodes to a base station. But because these schemes studied less energy consumption for a convergecast as well as fairly energy consumption altogether, the minimum energy consumption for a convergecast was not focused enough nor how topology influences to energy consumption. This paper deals with routing topology and energy consumption for a single convergecast in the following ways. We chose major WSN topology as MSC(Minimum Spanning Chain)s, MSTs, PEGASIS chains and proposed LECSEN chains. We solved the MSC length by Linear Programming(LP) and propose the LECSEN chain to compete with MST and MSC. As a result of simulation by Monte Carlo method for calculation of the topology length and standard deviation of link length, we learned that LECSEN is competitive with MST in terms of total energy consumption and shows the best with the view of even energy consumption at the sensor nodes. Thus, we concluded LECSEN is a very useful routing topology in WSN.

USN과 BcN 연동에 대한 고찰

  • Lee, Jun-Seop;Kim, Eun-Suk;Kim, Hyeong-Jun
    • Information and Communications Magazine
    • /
    • v.24 no.8
    • /
    • pp.33-39
    • /
    • 2007
  • USN은 BcN을 포함하는 포괄적인 서비스의 개념으로 정의되어야 하며, USN과 BcN의 연동은 WSN과 BcN의 연동으로 정의되어야 한다. 이에 따라 BcN과 WSN의 연동에 관해 그 구조 및 각 구성 요소의 기능을 기술한다.

Joint Routing, Scheduling, and Power Control for Wireless Sensor Networks with RF Energy Transfer Considering Fairness (무선 에너지 전송 센서망에서의 공평성을 고려한 라우팅, 스케줄링, 전력 제어)

  • Moon, Seokjae;Roh, Hee-Tae;Lee, Jang-Won
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.41 no.2
    • /
    • pp.206-214
    • /
    • 2016
  • Recently, radio frequency energy transfer (RFET) attracts more and more interests for powering sensor nodes in the wireless sensor network (WSN). In the conventional WSN, reducing energy consumption of sensor nodes is of primary importance. On the contrary, in the WSN with RFET, reducing energy consumption is not an important issue. However, in the WSN with RFET, the energy harvesting rate of each sensor node depends on its location, which causes the unbalanced available energy among sensor nodes. Hence, to improve the performance of the WSN with RFET, it is important to develop network protocols considering this property. In this paper, we study this issue with jointly considering routing, scheduling, and power control in the WSN with RFET. In addition, we study this issue with considering two different objectives: 'Max-min' with which we tries to maximize the performance of a sensor node having the minimum performance and 'Max-min fairness' with which we tries to achieve max-min fairness among sensor nodes. We show that our solutions can improve network performance significantly and we also discuss the differences between 'Max-min' and 'Max-min fairness'.