• Journal of Communications and Networks
• /
• v.5 no.3
• /
• pp.249-257
• /
• 2003

Ring networks are very commonly exploited among local area and metropolitan area networks (LAN/MAN), whereas cells or small fixed-size packets are widely used in synchronized ring networks. In this paper, we present an analytical method for evaluating the delay-throughput performance of a MAC protocol with multiple self-tokens in a slotted ring network under uniform traffic. In our analysis, we introduce the stationary probability, which indicates the number of packets in a node. Also, it is assumed that each node has a sufficiently large amount of self-tokens, and a slotted ring has the symmetry. The analytical results with respect to delay-throughput performance have similar values to computer simulated ones. Furthermore, in order to achieve fair access under non-uniform traffic, we propose an adaptive MAC protocol, where the number of self-tokens in a node dynamically varies, based on the number of packets transmitted within a specified period. In the proposed protocol, when the number of packets transmitted by a node within a specified period is larger than a specified threshold, the node decreases the number of self-tokens in a per-node distributed method. That results in creating free slots in the ring, thus all nodes can obtain an equal opportunity to transmit into the ring. Performance results obtained by computer simulation show that our proposed protocol can maintain throughput fairness under non-uniform traffic.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.37 no.5B
• /
• pp.338-347
• /
• 2012

In this paper, we propose the cooperative transmission scheme (CTS) for system throughput maximization in OFDMA based enterprise femtocell networks. In our scheme, the user equipment (UE) can receive the desired signal from serving femtocell BS (fBS) as well as an adjacent fBS. Thus, UE achieves an improved signal to interference plus and noise ratio (SINR) by the synchronized two signals. The performances of this strategy consider not only the call-level quality of service (QoS) but also the packet-level QoS. We first measure the call blocking probability and utilization for the downlink resources for various offered load in femtocell. Based on that, the outage probability and effective throughput of the system are simulated. Simulation results show that the proposed scheme can reduce the outage probability for enterprise femtocell compared with conventional systems.

• Journal of Positioning, Navigation, and Timing
• /
• v.7 no.2
• /
• pp.53-59
• /
• 2018

This paper proposes a pseudo-random beamforming technique for time-synchronized mobile base stations (BSs) for multi-cell downlink networks which have mobility. The base stations equipped with multi-antennas and mobile stations (MSs) are time-synchronized based on global positioning system (GPS) signals and generate a number of transmit beamforming matrix candidates according to the predetermined pseudo-random pattern. In addition, MSs generate receive beamforming vectors that correspond to the beam index number based on the minimum mean square error (MMSE) using transmit beamforming vectors that make up a number of transmit beamforming matrices and wireless channel matrices from BSs estimated via the reference signals (RS). Afterward, values of received signal-to-interference-plus-noise ratio (SINR) with regard to all transmit beamforming vectors are calculated, and the resulting values are then feedbacked to the BS of the same cells along with the beam index number. Each of the BSs calculates each of the sum-rates of the transmit beamforming matrix candidates based on the feedback information and then transmits the calculated results to the BS coordinator. After this, optimum transmit beamforming matrices, which can maximize a sum-rate of the entire cells, are selected at the BS coordinator and informed to the BSs. Finally, data signals are transmitted using them. The simulation results verified that a sum-rate of the entire cells was improved as the number of transmit beamforming matrix candidates increased. It was also found that if the received SINR values and beam index numbers are feedbacked opportunistically from each of the MSs to the BSs, not only nearly the same performance in sum-rate with that of applying existing feedback techniques could be achieved but also an amount of feedback was significantly reduced.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.4
• /
• pp.1359-1375
• /
• 2015

Energy efficiency is critical for Wireless Sensor Networks (WSNs) since sensor nodes usually have very limited energy supply from battery. Sleep scheduling and nodes cooperation are two of the most efficient methods to achieve energy conservation in WSNs. In this paper, we propose an adaptive energy optimization approach for target tracking applications, called Energy-Efficient Node Coordination (EENC), which is based on the grid structure. EENC provides an unambiguous calculation and analysis for optimal the nodes cooperation theoretically. In EENC, the sleep schedule of sensor nodes is locally synchronized and globally unsynchronized. Locally in each grid, the sleep schedule of all nodes is synchronized by the grid head, while globally the sleep schedule of each grid is independent and is determined by the proposed scheme. For dynamic sleep scheduling in tracking state we propose a multi-level coordination algorithm to find an optimal nodes cooperation of the network to maximize the energy conservation while preserving the tracking performance. Experimental results show that EENC can achieve energy saving of at least 38.2% compared to state-of-the-art approaches.

• International Journal of Computer Science & Network Security
• /
• v.21 no.11
• /
• pp.17-22
• /
• 2021

Recently, image super-resolution techniques used in convolutional neural networks (CNN) have led to remarkable performance in the research area of digital image processing applications and computer vision tasks. Convolutional layers stacked on top of each other can design a more complex network architecture, but they also use more memory in terms of the number of parameters and introduce the vanishing gradient problem during training. Furthermore, earlier approaches of single image super-resolution used interpolation technique as a pre-processing stage to upscale the low-resolution image into HR image. The design of these approaches is simple, but not effective and insert the newer unwanted pixels (noises) in the reconstructed HR image. In this paper, authors are propose a novel single image super-resolution architecture based on synchronized depthwise separable convolution with Dense Skip Connection Block (DSCB). In addition, unlike existing SR methods that only rely on single path, but our proposed method used the synchronizes path for generating the SISR image. Extensive quantitative and qualitative experiments show that our method (SDCN) achieves promising improvements than other state-of-the-art methods.

• International journal of advanced smart convergence
• /
• v.9 no.1
• /
• pp.109-112
• /
• 2020

Many devices are connected on the internet to give functionalities for interconnected services. In 2020', The number of devices connected to the internet will be reached 5.8 billion. Moreover, many connected service provider such as Google and Amazon, suggests edge computing and mesh networks to cope with this situation which the many devices completely connected on their networks. This paper introduces the current state of the introduction of the wireless mesh network and edge cloud in order to efficiently manage a large number of nodes in the exploding Internet of Things (IoT) network and introduces the existing Network Time Protocol (NTP). On the basis of this, we propose a relatively accurate time synchronization method, especially in heterogeneous mesh networks. Using this NTP, multiple time coordinators can be placed in a mesh network to find the delay error using the average delay time and the delay time of the time coordinator. Therefore, accurate time can be synchronized when implementing IoT, remote metering, and real-time media streaming using IoT mesh network.

• Journal of Information Processing Systems
• /
• v.1 no.1 s.1
• /
• pp.70-74
• /
• 2005

Sensor networks have emerged as an interesting and important research area in the last few years. These networks require that time be synchronized more precisely than in traditional Internet applications. In this paper, we compared and analyzed the performance of the RBS and TDP mechanisms in the view of the number of generated messages and the synchronization accuracy. The reason that we chose be RBS ad the TDP mechanism to be compared is because the RES is an innovative method to achieve the high accurate synchronization. And TDP is a new method taking over the NTP method which has been used widely in the Internet. We simulated the performance of two methods assuming the IEEE 802.11 CSMA/CA MAC. As for the number of nodes in the sensor networks, two situations of 25 (for the small size network) and 100 (for the large size network) nodes are used. In the aspect of the number of messages generated for the synchronization, TDP is far better than RBS. But, the synchronization accuracy of RBS is far higher than that of TDP. We cm conclude that in a small size sensor networks requiring very high accuracy, such as an application of very high speed objects tracking in a confined space, the RBS is more proper than TDP even though the RBS may generate more traffic than TDP. But, in a wide range sensor networks with a large number of nodes, TDP is more realistic though the accuracy is somewhat worse than RBS because RBS may make so many synchronization messages, and then consume more energies at each node. So, two mechanisms may be used selectively according to the required environments, without saying that the one method is always better than the other.

• Proceedings of the Korean Vacuum Society Conference
• /
• 2012.02a
• /
• pp.239-240
• /
• 2012

With advancements in semiconductor device technologies, manufacturing processes are getting more complex and it became more difficult to maintain tighter process control. As the number of processing step increased for fabricating complex chip structure, potential fault inducing factors are prevail and their allowable margins are continuously reduced. Therefore, one of the key to success in semiconductor manufacturing is highly accurate and fast fault detection and classification at each stage to reduce any undesired variation and identify the cause of the fault. Sensors in the equipment are used to monitor the state of the process. The idea is that whenever there is a fault in the process, it appears as some variation in the output from any of the sensors monitoring the process. These sensors may refer to information about pressure, RF power or gas flow and etc. in the equipment. By relating the data from these sensors to the process condition, any abnormality in the process can be identified, but it still holds some degree of certainty. Our hypothesis in this research is to capture the features of equipment condition data from healthy process library. We can use the health data as a reference for upcoming processes and this is made possible by mathematically modeling of the acquired data. In this work we demonstrate the use of recurrent neural network (RNN) has been used. RNN is a dynamic neural network that makes the output as a function of previous inputs. In our case we have etch equipment tool set data, consisting of 22 parameters and 9 runs. This data was first synchronized using the Dynamic Time Warping (DTW) algorithm. The synchronized data from the sensors in the form of time series is then provided to RNN which trains and restructures itself according to the input and then predicts a value, one step ahead in time, which depends on the past values of data. Eight runs of process data were used to train the network, while in order to check the performance of the network, one run was used as a test input. Next, a mean squared error based probability generating function was used to assign probability of fault in each parameter by comparing the predicted and actual values of the data. In the future we will make use of the Bayesian Networks to classify the detected faults. Bayesian Networks use directed acyclic graphs that relate different parameters through their conditional dependencies in order to find inference among them. The relationships between parameters from the data will be used to generate the structure of Bayesian Network and then posterior probability of different faults will be calculated using inference algorithms.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.45 no.9
• /
• pp.13-19
• /
• 2008

Time synchronization of nodes in sensor network synchronizes sensor nodes to one time clock. This is very essential in sensor networks so that the information collected and reported from the sensor nodes becomes meaningful. If sensor nodes are not synchronized, disaster report with time information can be wrong analyzed and this may lead to big calamity. With the limitation of battery and computing power, time synchronization algorithm imported in sensor nodes has to be as simple as it doesn't need big complexity, nor generates many synchronization messages. To reduce the synchronization error, hop count should be kept small between reference node to initiate synchronization and sensor nodes to be synchronized. Therefore, multiple reference nodes are used instead of single reference node. The use of multiple reference nodes introduce the requirement of synchronization among reference nodes in the network. Several algorithms have been proposed till now, but the synchronization among reference nodes are not well considered. This paper proposes improved time synchronization for sensor networks by synchronizing multiple reference nodes inside the network. Through simulation, we validated the effects of new algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.3A
• /
• pp.274-281
• /
• 2006

Sensor network applications need synchronized time extremely such as object tracking, consistent state updates, duplicate detection, and temporal order delivery. This paper describes reliable time synchronization protocol (RTSP) for wireless sensor networks. In the proposed method, synchronization error is decreased by creating hierarchical tree with lower depth and reliability is improved by maintaining and updating information of candidate parent nodes. The RTSP reduces recovery time and communication overheads comparing to TPSN when there are topology changes owing to moving of nodes, running out of energy and physical crashes. Simulation results show that RTSP has about 20% better performance than TPSN in synchronization accuracy. And the number of message in the RTSP is $20%{\sim}60%$ lower than that in the TPSN when nodes are failed in the network. In case of different transmission range of nodes, the communication overhead in the RTSP is reduced up to 40% than that in the TPSN at the maximum.