• Proceedings of the Korean Information Science Society Conference
• /
• 2010.11a
• /
• pp.101-106
• /
• 2010

As a part of preparing the sniffing attack, this routing method presented in this thesis decreases the risk rates of the leaking of information through separating valid data and transmitting by a multi-path. then data is transmitted from start node to destination node on distributed sensor network. The level of reduction in leaking of information by the sniffing attack is proved by experimental result thich compare the case described above with the case of transmitting whole data with the single path by simulation, and the algorithm for choosing the routing path is showed by proof of the theorem.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.24 no.2
• /
• pp.86-91
• /
• 2010

We constructed a quasi-distributed fiber-optic sensor network for the safety monitoring in power systems. It is possible to construct many of FBG sensors in a line and to be immune from electromagnetic noise. For demodulation analysis of reflected wavelength from FBG sensor, we proposed a simple and fast system using a InGaAs photo-diode array and a holographic diffraction grating. For accuracy improvement of the proposed demodulation system, we applied a Gaussian line-fitting algorithm. We obtained about 4[pm] of wavelength resolution and stability.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
• /
• v.8 no.3
• /
• pp.122-131
• /
• 2009

Ubiquitous-Transportation sensor network is able to realize a vehicle ad-hoc network. Since there are some problems in an existing ITS system, the new technology and traffic information strategies are requirements in this advanced system, u-TSN. The purposes of this paper is to introduce the components on u-TSN system, establish new traffic strategies for this system, and then evaluate these strategies by making a comparative study of ITS and using micro traffic simulator, AIMSUN. The strategy evaluated by AIMSUN is position-based multicast strategy which provides traffic information to vehicles using V2I (vehicle to Infrastructure) communication. This paper focuses on the providing real-time route guidance information when congestion is occurred by the incidents. This study estimates total travel time on each route by API modules. Result from simulation experiments suggests that position-based multicast strategy can achieve more optimal network performance and increased driver satisfaction since the total accumulated travel times of both the major road and the total system on position-based multicast strategy are less than those on VMS.

• Journal of Information Processing Systems
• /
• v.11 no.1
• /
• pp.148-164
• /
• 2015

The use of mobile agents for collaborative processing in wireless sensor network has gained considerable attention. This is when mobile agents are used for data aggregation to exploit redundant and correlated data. The efficiency of agent-based data aggregation depends on the agent migration scheme. However, in general, most of the proposed schemes are centralized approach-based schemes where the sink node determines the migration paths for the agents before dispatching them in the sensor network. The main limitations with such schemes are that they need global network topology information for deriving the migration paths of the agents, which incurs additional communication overhead, since each node has a very limited communication range. In addition, a centralized approach does not provide fault tolerant and adaptive migration paths. In order to solve such problems, we have proposed a distributed approach-based scheme for determining the migration path of the agents where at each hop, the local information is used to decide the migration of the agents. In addition, we also propose a local repair mechanism for dealing with the faulty nodes. The simulation results show that the proposed scheme performs better than existing schemes in the presence of faulty nodes within the networks, and manages to report the aggregated data to the sink faster.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.1
• /
• pp.193-214
• /
• 2017

In this paper, we study the problem of network utility maximization in a CSMA based multi-hop wireless network. Existing work in this aspect typically adopted continuous time Markov model for performance modelling, which fails to consider the channel conflict impact in actual CSMA networks. To maximize the utility of a CSMA based wireless network with channel conflict, in this paper, we first model its weighted network capacity (i.e., network capacity weighted by link queue length) and then propose a distributed link scheduling algorithm, called CSMA based Maximal-Weight Scheduling (C-MWS), to maximize the weighted network capacity. We derive the upper and lower bounds of network utility based on C-MWS. The derived bounds can help us to tune the C-MWS parameters for C-MWS to work in a distributed wireless network. Simulation results show that the joint optimization based on C-MWS can achieve near-optimal network utility when appropriate algorithm parameters are chosen and also show that the derived utility upper bound is very tight.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.12
• /
• pp.4372-4388
• /
• 2014

Robotic sensor network (RSN) contains mobile sensors and robots providing feasible solution for many multi-agent applications. One of the most critical issues in RSN and its application is how to effectively assign tasks. This paper presents a novel connectivity preserving hybrid task allocation strategy to answer the question particularly for RSN. Firstly, we model the task allocation in RSN to distinguish the discovering and allocating processes. Secondly, a fully distributed simple Task-oriented Unoccupied Neighbor Algorithm, named TUNA, is developed to allocate tasks with only partial view of the network topology. A connectivity controller is finally developed and integrated into the strategy to guarantee the global connectivity of entire RSN, which is critical to most RSN applications. The correctness, efficiency and scalability of TUNA are proved with both theoretical analysis and experimental simulations. The evaluation results show that TUNA can effectively assign tasks to mobile robots with the requirements of only a few messages and small movements of mobile agents.

• Smart Structures and Systems
• /
• v.5 no.2
• /
• pp.119-137
• /
• 2009

Smart sensors densely distributed over structures can use their computational and wireless communication capabilities to provide rich information for structural health monitoring (SHM). Though smart sensor technology has seen substantial advances during recent years, implementation of smart sensors on full-scale structures has been limited. Hardware resources available on smart sensors restrict data acquisition capabilities; intrinsic to these wireless systems are packet loss, data synchronization errors, and relatively slow communication speeds. This paper addresses these issues under the hardware limitation by developing corresponding middleware services. The reliable communication service requires only a few acknowledgement packets to compensate for packet loss. The synchronized sensing service employs a resampling approach leaving the need for strict control of sensing timing. The data aggregation service makes use of application specific knowledge and distributed computing to suppress data transfer requirements. These middleware services are implemented on the Imote2 smart sensor platform, and their efficacy demonstrated experimentally.

• ETRI Journal
• /
• v.34 no.3
• /
• pp.330-340
• /
• 2012

In many applications of wireless sensor actor networks (WSANs) that often run in harsh environments, the reduction of completion times of tasks is highly desired. We present a new time-aware, energy-aware, and starvation-free algorithm called Scate for assigning tasks to actors while satisfying the scalability and distribution requirements of WSANs with semi-automated architecture. The proposed algorithm allows concurrent executions of any mix of small and large tasks and yet prevents probable starvation of tasks. To achieve this, it estimates the completion times of tasks on each available actor and then takes the remaining energies and the current workloads of these actors into account during task assignment to actors. The results of our experiments with a prototyped implementation of Scate show longer network lifetime, shorter makespan of resulting schedules, and more balanced loads on actors compared to when one of the three well-known task-scheduling algorithms, namely, the max-min, min-min, and opportunistic load balancing algorithms, is used.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.13 no.7
• /
• pp.3671-3689
• /
• 2019

Software defined networking brings unique security risks such as control plane saturation attack while enhancing the performance of wireless sensor networks. The attack is a new type of distributed denial of service (DDoS) attack, which is easy to launch. However, it is difficult to detect and hard to defend. In response to this, the attack threat model is discussed firstly, and then a DDoS attack prevention extension, called FuzzyGuard, is proposed. In FuzzyGuard, a control network with both the protection of data flow and the convergence of attack flow is constructed in the data plane by using the idea of independent routing control flow. Then, the attack detection is implemented by fuzzy inference method to output the current security state of the network. Different probabilistic suppression modes are adopted subsequently to deal with the attack flow to cost-effectively reduce the impact of the attack on the network. The prototype is implemented on SDN-WISE and the simulation experiment is carried out. The evaluation results show that FuzzyGuard could effectively protect the normal forwarding of data flow in the attacked state and has a good defensive effect on the control plane saturation attack with lower resource requirements.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.9
• /
• pp.3120-3137
• /
• 2021

Small-sized IoT wireless sensing devices can be deployed with small aircraft such as drones, and the deployment of mobile IoT devices can be relocated to suit data collection with efficient relocation algorithms. However, the terrain may not be able to predict its shape. Mobile IoT devices suitable for these terrains are hopping devices that can move with jumps. So far, most hopping sensor relocation studies have made the unrealistic assumption that all hopping devices know the overall state of the entire network and each device's current state. Recent work has proposed the most realistic distributed network environment-based relocation algorithms that do not require sharing all information simultaneously. However, since the shortest path-based algorithm performs communication and movement requests with terminals, it is not suitable for an area where the distribution of obstacles is uneven. The proposed scheme applies a simple Monte Carlo method based on relay nodes selection random variables that reflect the obstacle distribution's characteristics to choose the best relay node as reinforcement learning, not specific relay nodes. Using the relay node selection random variable could significantly reduce the generation of additional messages that occur to select the shortest path. This paper's additional contribution is that the world's first distributed environment-based relocation protocol is proposed reflecting real-world physical devices' characteristics through the OMNeT++ simulator. We also reconstruct the three days-long disaster environment, and performance evaluation has been performed by applying the proposed protocol to the simulated real-world environment.