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Cluster-based Energy-aware Data Sharing Scheme to Support a Mobile Sink in Solar-Powered Wireless Sensor Networks
Hong Seob Lee, Jun Min Yi, Jaeung Kim, Dong Kun Noh
In contrast with battery-based wireless sensor networks (WSNs), solar-powered WSNs can operate for a longtime assuming that there is no hardware fault. Meanwhile, a mobile sink can save the energy consumption of WSN, but its ineffective movement may incur so much energy waste of not only itself but also an entire network. To solve this problem, many approaches, in which a mobile sink visits only on clustering-head nodes, have been proposed. But, the clustering scheme also has its own problems such as energy imbalance and data instability. In this study, therefore, a cluster-based energy-aware data-sharing scheme (CE-DSS) is proposed to effectively support a mobile sink in a solar-powered WSN. By utilizing the redundant energy efficiently, CE-DSS shares the gathered data among cluster-heads, while minimizing the unexpected black-out time. The simulation results show that CE-DSS increases the data reliability as well as conserves the energy of the mobile sink.
Message Delivery Techniques using Group Intimacy Information among Nodes in Opportunistic Networks
Seohyang Kim, Hayoung Oh, Chongkwon Kim
In opportunistic networks, each message is delivered to the destination by repeating, storing, carrying, and forwarding the message. Recently, with the vitalization of social networks, a large number of existing articles have shown performance improvement when delivering the message and considering its social relational networks. However, these works only deliver messages when they find nodes, assuming that every node cooperates with each other unconditionally. Moreover, they only consider the number of short-term contacts and local social relations, but have not considered each node’s average relation with the destination node. In this paper, we propose novel message sending techniques for opportunistic networks using nodes’ social network characteristics. In this scheme, each message is delivered to the destination node with fewer copies by delivering it mostly through nodes that have high intimacy with the destination node. We are showing that our proposed scheme presents a 20% performance increase compared to existing schemes.
An Extended DDN based Self-Adaptive System
Misoo Kim, Hohyeon Jeong, Eunseok Lee
In order to solve problems happening in the practical environment of complicated system, the importance of the self-adaptive system has recently begun to emerge. However, since the differences between the model built at the time of system design and the practical environment can lead the system into unpredictable situations, the study into methods of dealing with it is also emerging as an important issue. In this paper, we propose a method for deciding on the adaptation time in an uncertain environment, and reflecting the real-time environment in the system’s model. The proposed method calculates the Bayesian Surprise for the suitable adaptation time by comparing previous and current states, and then reflects the result following the performed policy in the design model to help in deciding the proper policy for the actual environment. The suggested method is applied to a navigation system to confirm its effectiveness.
A Re-configuration Scheme for Social Network Based Large-scale SMS Spam
Sihyun Jeong, Giseop Noh, Hayoung Oh, Chong-Kwon Kim
The Short Message Service (SMS) is one of the most popular communication tools in the world. As the cost of SMS decreases, SMS spam has been growing largely. Even though there are many existing studies on SMS spam detection, researchers commonly have limitation collecting users" private SMS contents. They need to gather the information related to social network as well as personal SMS due to the intelligent spammers being aware of the social networks. Therefore, this paper proposes the Social network Building Scheme for SMS spam detection (SBSS) algorithm that builds synthetic social network dataset realistically, without the collection of private information. Also, we analyze and categorize the attack types of SMS spam to build more complete and realistic social network dataset including SMS spam.
An Energy-Aware Cooperative Communication Scheme for Wireless Multimedia Sensor Networks
Jeong-Oh Kim, Hyunduk Kim, Wonik Choi
Numerous clustering schemes have been proposed to increase energy efficiency in wireless sensor networks. Clustering schemes consist of a hierarchical structure in the sensor network to aggregate and transmit data. However, existing clustering schemes are not suitable for use in wireless multimedia sensor networks because they consume a large quantity of energy and have extremely short lifetime. To address this problem, we propose the Energy-Aware Cooperative Communication (EACC) method which is a novel cooperative clustering method that systematically adapts to various types of multimedia data including images and video. An evaluation of its performance shows that the proposed method is up to 2.5 times more energy-efficient than the existing clustering schemes.
An Improved Depth-Based TDMA Scheduling Algorithm for Industrial WSNs to Reduce End-to-end Delay
Hwakyung Lee, Sang-Hwa Chung, Ik-Joo Jung
Industrial WSNs need great performance and reliable communication. In industrial WSNs, cluster structure reduces the cost to form a network, and the reservation-based MAC is a more powerful and reliable protocol than the contention-based MAC. Depth-based TDMA assigns time slots to each sensor node in a cluster-based network and it works in a distributed manner. DB-TDMA is a type of depth-based TDMA and guarantees scalability and energy efficiency. However, it cannot allocate time slots in parallel and cannot perfectly avoid a collision because each node does not know the total network information. In this paper, we suggest an improved distributed algorithm to reduce the end-to-end delay of DB-TDMA, and the proposed algorithm is compared with DRAND and DB-TDMA.
Analysis of Energy Consumption and Processing Delay of Wireless Sensor Networks according to the Characteristic of Applications
Chong Myung Park, Young Tak Han, Soobin Jeon, Inbum Jung
Wireless sensor networks are used for data collection and processing from the surrounding environment for various applications. Since wireless sensor nodes operate on low computing power, restrictive battery capacity, and low network bandwidth, their architecture model has greatly affected the performance of applications. If applications have high computation complexity or require the real-time processing, the centralized architecture in wireless sensor networks have a delay in data processing. Otherwise, if applications only performed simple data collection for long period, the distributed architecture wasted battery energy in wireless sensors. In this paper, the energy consumption and processing delay were analyzed in centralized and distributed sensor networks. In addition, we proposed a new hybrid architecture for wireless sensor networks. According to the characteristic of applications, the proposed method had the optimal number of wireless sensors in wireless sensor networks.
An Intention-Response Model based on Mirror Neuron and Theory of Mind using Modular Behavior Selection Networks
Although service robots in various fields are being commercialized, most of them have problems that depend on explicit commands by users and have difficulty to generate robust reactions of the robot in the unstable condition using insufficient sensor data. To solve these problems, we modeled mirror neuron and theory of mind systems, and applied them to a robot agent to show the usefulness. In order to implement quick and intuitive response of the mirror neuron, the proposed intention-response model utilized behavior selection networks considering external stimuli and a goal, and in order to perform reactions based on the long-term action plan of theory of mind system, we planned behaviors of the sub-goal unit using a hierarchical task network planning, and controled behavior selection network modules. Experiments with various scenarios revealed that appropriate reactions were generated according to external stimuli.
A Path Prediction-Based Sensor Registry System for Stable Use of Sensor Information
The sensor registry system has been developed for instant use and seamless interpretation of sensor data in a heterogeneous sensor network environment. However, the existing sensor registry system cannot provide information for interpretation of the sensor data in situations in which the network is unstable. This limitation causes several problems such as sensor data loss, inaccuracy of processed results, and low service quality. A method to resolve such problems in the aspect of software is presented herein. In other words, an extended sensor registry system is proposed to enable the stable use of sensor information, even under conditions of unstable network connection, by providing sensor information with a mobile device in advance through the user path prediction. The results of experiments and evaluation are also presented. The extended sensor registry system proposed in this paper enhances the stable usability of sensor information as well as improves the quality of sensor-based services.
A Network Coding Based Green Cognitive Radio Network
With the rapid increase of energy consumption and environmental problems, the need for green techniques is increasing. Network coding can provide a solution by reducing unnecessary data transmission and by estimating traffic patterns. In addition, it can amplify the synergy with the cognitive radio network (CR) since the CR has recognition and optimal decision functionalities. In this paper, we propose a network coding based green cognitive radio network. With the simulations, we show that the proposed scheme is up to 25% better than the previous work.
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