• Journal of information and communication convergence engineering
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• 제6권3호
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• pp.343-347
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• 2008

Wakeup schemes that turn off sensors' radio when communication is not necessary have great potential in energy saving. At the start of each beacon interval in the IEEE 802.11 power saving mode specified for DCF, each node periodically wakes up for duration called the ATIM Window. However, in the power saving mechanism specified in IEEE 802.11, all nodes use the same ATIM window size. Since the ATIM window size critically affects throughput and energy consumption, a fixed ATIM window does not perform well in all situations. This paper proposes an adaptive mechanism to dynamically choose an ATIM window size according to network condition. Simulation results show that the proposed scheme outperforms the IEEE 802.11 power saving mechanism in terms of the amount of power consumed and the packet delivery ratio.

• 정보보호학회논문지
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• 제34권3호
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• pp.393-401
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• 2024

최근 사물인터넷(Internet of Things, IoT)이 인간의 안전, 생명, 자산과 직결되는 산업과 일상생활에 널리 활용되고 있다. 그러나 저가, 경량, 저전력 요건을 충족해야 하는 IoT 장치는 배터리 소모 공격과 간섭 때문에 배터리 라이프타임이 심각하게 단축되는 문제가 있다. 이러한 문제를 해결하기 위해 웨이크업 리시버(Wake-up Receiver, WuR)를 위한 802.11ba 표준이 등장했고, 이 기능은 와이파이 기반 IoT의 에너지 소비를 최소화하는데 중요한 역할을 하고 있다. 그러나 WuR 프로토콜은 지연시간과 오버헤드를 단축하기 위해서 보안 메커니즘을 고려하지 않았다. 따라서 본 연구에서는 배터리 소모 공격에 대응하기 위해서 저전력 웨이크업 리시버를 위한 적응형 파워 세이빙 메커니즘(Adaptive Power Saving Mechanism, APSM)을 제안한다. APSM은 공격이 잦은 환경에서 파워 세이빙 시간을 기하급수적으로 증가시킴으로써 비정상적으로 발생하는 파워 소모량을 최소화할 수 있다. 실험 결과에 따르면, APSM은 전체 트래픽 중 공격 비중이 10% 이상일 때 종래의 파워 세이빙 메커니즘(Legacy Power Saving Mechanism, LPSM)보다 13.77% 이상의 에너지 소비 효율을 개선할 수 있었다.

• Journal of Communications and Networks
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• 제13권1호
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• pp.17-25
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• 2011

A convergecast is a popular routing scheme in wireless sensor networks (WSNs) in which every sensor node periodically forwards measured data along configured routing paths to a base station (BS). Prolonging lifetimes in energy-limited WSNs is an important issue because the lifetime of a WSN influences on its quality and price. Low-energy adaptive clustering hierarchy (LEACH) was the first attempt at solving this lifetime problem in convergecast WSNs, and it was followed by other solutions including power efficient gathering in sensor information systems (PEGASIS) and power efficient data gathering and aggregation protocol (PEDAP). Our solution-chain routing with even energy consumption (CREEC)-solves this problem by achieving longer average lifetimes using two strategies: i) Maximizing the fairness of energy distribution at every sensor node and ii) running a feedback mechanism that utilizes a preliminary simulation of energy consumption to save energy for depleted Sensor nodes. Simulation results confirm that CREEC outperforms all previous solutions such as LEACH, PEGASIS, PEDAP, and PEDAP-power aware (PA) with respect to the first node death and the average lifetime. CREEC performs very well at all WSN sizes, BS distances and battery capacities with an increased convergecast delay.

• Journal of Information Processing Systems
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• 제15권3호
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• pp.593-603
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• 2019

In wearable healthcare systems, sensor devices can be deployed in places around the human body such as the stomach, back, arms, and legs. The sensors use tiny batteries, which have limited resources, and old sensor batteries must be replaced with new batteries. It is difficult to deploy sensor devices directly into the human body. Therefore, instead of replacing sensor batteries, increasing the lifetime of sensor devices is more efficient. A transmission power control (TPC) algorithm is a representative technique to increase the lifetime of sensor devices. Sensor devices using a TPC algorithm control their transmission power level (TPL) to reduce battery energy consumption. The TPC algorithm operates on a closed-loop mechanism that consists of two parts, such as sensor and sink devices. Most previous research considered only the sink part of devices in the closed-loop. If we consider both the sensor and sink parts of a closed-loop mechanism, sensor devices reduce energy consumption more than previous systems that only consider the sensor part. In this paper, we propose a new approach to consider both the sensor and sink as part of a closed-loop mechanism for efficient energy management of sensor devices. Our proposed approach judges the current channel condition based on the values of various body sensors. If the current channel is not optimal, sensor devices maintain their current TPL without communication to save the sensor's batteries. Otherwise, they find an optimal TPL. To compare performance with other TPC algorithms, we implemented a TPC algorithm and embedded it into sensor devices. Our experimental results show that our new algorithm is better than other TPC algorithms, such as linear, binary, hybrid, and ATPC.