• Journal of KIISE:Information Networking
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• v.35 no.1
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• pp.76-90
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• 2008

Wireless sensor networks are expected to play a vital role in the upcoming age of ubiquitous computing such as home environmental, industrial, and military applications. Compared with the vivid utilization of the sensor networks, however, security and privacy issues of the sensor networks are still in their infancy because unique challenges of the sensor networks make it difficult to adopt conventional security policies. Especially, node compromise is a critical threat because a compromised node can drain out the finite amount of energy resources in battery-powered sensor networks by launching various insider attacks such as a false data injection. Even cryptographic authentication mechanisms and key management schemes cannot suggest solutions for the real root of the insider attack from a compromised node. In this paper, we propose a novel trust-based secure aggregation scheme which identifies trustworthiness of sensor nodes and filters out false data of compromised nodes to make resilient sensor networks. The proposed scheme suggests a defensible approach against the insider attack beyond conventional cryptographic solutions. The analysis and simulation results show that our aggregation scheme using trust evaluation is more resilient alternative to median.

• Journal of Korea Multimedia Society
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• v.13 no.10
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• pp.1423-1435
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• 2010

Building wireless sensor networks requires a constituting sensor node to consider the following limited hardware resources: a small battery lifetime limiting available power supply for the sensor node, a low-power microprocessor with a low-performance computing capability, and scarce memory resources. Despite such limited hardware resources of the sensor node, the sensor node platform needs to activate real-time sensing, guarantee the real-time processing of sensing data, and exchange data between individual sensor nodes concurrently. Therefore, in this paper, we propose an energy-efficient real-time task scheduling technique for battery-powered wireless sensor nodes. The proposed energy-efficient task scheduling technique controls the microprocessor's operating frequency and reduces the power consumption of a task by exploiting the slack time of the task when the actual execution time of the task can be less than its worst case execution time. The outcomes from experiments showed that the proposed scheduling technique yielded efficient performance in terms of guaranteeing the completion of real-time tasks within their deadlines and aiming to provide low power consumption.

• Journal of the Korea Society of Computer and Information
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• v.25 no.2
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• pp.105-111
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• 2020

In this paper, we propose a scheme that minimizes the energy imbalance problem of solar-powered wireless sensor network (SP-WSN) using both a mobile sink capable of wireless power transfer and an efficient clustering scheme (including cluster head election). The proposed scheme charges the cluster head using wireless power transfer from a mobile sink and mitigates the energy hotspot of the nodes nearby the head. SP-WSNs can continuously harvest energy, alleviating the energy constraints of battery-based WSN. However, if a fixed sink is used, the energy imbalance problem, which is energy consumption rate of nodes located near the sink is relatively increased, cannot be solved. Thus, recent research approaches the energy imbalance problem by using a mobile sink in SP-WSN. Meanwhile, with the development of wireless power transmission technology, a mobile sink may play a role of energy charging through wireless power transmission as well as data gathering in a WSN. Simulation results demonstrate that increase the amount of collected data by the sink using the proposed scheme.

• ETRI Journal
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• v.43 no.2
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• pp.221-231
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• 2021

To resolve energy depletion issues in massive Internet of Things sensor networks, we developed a set of distributed energy beamforming methods with one-bit feedback and clustering for multi-node wireless energy transfer, where multiple singleantenna distributed energy transmitters (Txs) transfer their energy to multiple nodes wirelessly. Unlike previous works focusing on distributed information beamforming using a single energy receiver (Rx) node, we developed a distributed energy beamforming method for multiple Rx nodes. Additionally, we propose two clustering methods in which each Tx node chooses a suitable Rx node. Furthermore, we propose a fast distributed beamforming method based on Tx sub-clustering. Through computer simulations, we demonstrate that the proposed distributed beamforming method makes it possible to transfer wireless energy to massive numbers of sensors effectively and rapidly with small implementation complexity. We also analyze the energy harvesting outage probability of the proposed beamforming method, which provides insights into the design of wireless energy transfer networks with distributed beamforming.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.3
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• pp.608-614
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• 2009

In wireless sensor networks, there are hundreds to thousands of small battery powered devices which are called sensors. As sensors have a limited energy resources, there is a need to use it effectively. A clustering based routing protocol forms clusters by distributed algorithm. Member nodes send their data to their cluster heads then cluster heads integrate data and send to sink node. In this paper we propose an energy efficient cluster-head selection algorithm. We have used some factors(a previous cluster head experience, a existence of data to transmit and an information that neighbors have data or not) to select optimum cluster-head and eventually improve network lifetime. Our simulation results show its effectiveness in balancing energy consumption and prolonging the network lifetime compared with LEACH and HEED algorithms.

• Journal of KIISE
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• v.42 no.12
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• pp.1495-1502
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• 2015

Data compression involves a trade-off between delay time and data size. Greater delay times require smaller data sizes and vice versa. There have been many studies performed in the field of wireless sensor networks on increasing network life cycle durations by reducing data size to minimize energy consumption; however, reductions in data size result in increases of delay time due to the added processing time required for data compression. Meanwhile, as energy generation occurs periodically in solar energy-based wireless sensor networks, redundant energy is often generated in amounts sufficient to run a node. In this study, this excess energy is used to reduce the delay time between nodes in a sensor network consisting of solar energy-based nodes. The energy threshold value is determined by a formula based on the residual energy and charging speed. Nodes with residual energy below the threshold transfer data compressed to reduce energy consumption, and nodes with residual energy above the threshold transfer data without compression to reduce the delay time between nodes. Simulation based performance verifications show that the technique proposed in this study exhibits optimal performance in terms of both energy and delay time compared with traditional methods.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.1
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• pp.55-59
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• 2010

Most applications for solar-powered wireless sensor networks are usually deployed in remote areas without a continuous connection to the external networks and a regular maintenance by an administrator. In this case, sensory data has to be stored in the network as much as possible until it is uploaded by the data mule. For this purpose, a balanced data distribution over the network should be performed, and this can be achieved efficiently by taking the amount of available energy and storage into account, in the system layer of each node. In this paper, we introduce a simple but very efficient data distribution algorithm, by which each solar-powered node utilizes the harvested energy and the storage space maximally. This scheme running on each node determines the amount of energy which can be used for a data distribution as well as the amount of data which should be transferred to each neighbor, by using the local information of energy and storage status.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.4
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• pp.83-88
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• 2020

In Solar-powered wireless sensor networks(SP-WSN), the battery is periodically charged, so the best use of harvested energy is more important, rather than minimizing energy consumption. Meanwhile, as is well known, the reliability of communication between sensor nodes is very limited due to the resource-constraint of sensor nodes. In this paper, we propose an advanced FEC (forward error correction) scheme which can give SP-WSN more reliability for communication. Firstly, the proposed scheme uses energy modeling to calculate the amount of surplus energy which can be utilized for extra operations, and then determines the number of additional parity bits according to this amount of surplus energy. At the same time, link quality modeling calculates the optimal parity bits for error recovery in the current data communication environment. Finally, by considering these two parity sizes, it is possible to determine the optimal parity size that can maximize the data reliability without affecting the node black out. Performance verification was performed by comparing the amount of data collected at the sink and the number of outage nodes with other schemes.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.5
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• pp.360-370
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• 2009

Using solar power in wireless sensor networks requires a different approach to energy optimization from networks with battery-based nodes. Solar energy is an inexhaustible supply which can potentially allow a system to run forever, but there are several issues to be considered such as the uncertainty of energy supply and the constraint of rechargeable battery capacity. In this paper, we present SolarSS: a reliable storage system for solar-powered sensor networks, which provides a set of functions, in separate layers, such as sensory data collection, replication to prevent failure-induced data loss, and storage balancing to prevent depletion-induced data loss. SolarSS adapts the level of layers activated dynamically depending on solar energy availability, and provides an efficient resource allocation and data distribution scheme to minimize data loss.

• Journal of the Korea Society for Simulation
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• v.17 no.3
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• pp.27-34
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• 2008

Wireless sensor networks are comprised of sensor nodes with resource-constrained hardware. Nodes in the sensor network without adequate protection may be compromised by adversaries. Such compromised nodes are vulnerable to the attacks like false reports injection attacks and false data injection attacks on legitimate reports. In false report injection attacks, an adversary injects false report into the network with the goal of deceiving the sink or the depletion of the finite amount of energy in a battery powered network. In false data injection attacks on legitimate reports, the attacker may inject a false data for every legitimate report. To address such attacks, the probabilistic voting-based filtering scheme (PVFS) has been proposed by Li and Wu. However, each cluster head in PVFS needs additional transmission device. Therefore, this paper proposes a fuzzy logic-based false report detection method (FRD) to mitigate the threat of these attacks. FRD employs the statistical en-route filtering scheme as a basis and improves upon it. We demonstrate that FRD is efficient with respect to the security it provides, and allows a tradeoff between security and energy consumption, as shown in the simulation.