Earticle

Wireless body area network (WBAN) is a communication standard optimized for low power devices and operation on, in or around the human body but not limited to humans used to serve a variety of applications including medical, consumer electronics, entertainment and other[1]. The challenge of WBAN is that the energy of the sensors is limited by the battery life that’s why the transmitting of data is not continuous for long time. This leads to poor efficiency of the WBAN because the continuous power decreasing is due to network operations. An algorithms such as MAC zigbee802.15.4 and adaptive reliable MAC are important to reduce the replacement of batteries many times and to save power consumption. In this paper we concentrated our study on some type of sensors, they are telosB, mica2, micaz, and imote2 depends on power consumption calculations using mat lab program and based on adaptive reliable MAC. We analyzed the sensors with several nodes and packet sizes, and calculate the lifetimes for all the sensors in WBAN. The results we obtained show a good performance of using Adaptive reliable MAC in Wireless Body Area Networks.

In this paper, we simulate and comparatively analyze the sensor network protocols with additional aggregate queue and transmit duplicate layers on MICA and MICAz platform with different radio models using PROWLER and RMASE. The simulation results show that the MICAz motes give low latency, high throughput, high energy consumption, low efficiency but better lifetime while the MICA motes give high success rate and low loss rate. It has been, thus, concluded that in case of all the radio models the MICA is preferably better than MICAz in applications where energy is a constraint otherwise MICAz is better as it gives greater lifetime.

본 논문에서는 "작은 워드 크기를 사용하는 센서모트에서는 GF$(2^m)$상의 partial XOR 곱셈연산이 저전력 마이크로프로세서에 의하여 효율적으로 지원되지 않기 때문에 GF$(2^m)$에 기반을 둔 타원곡선 암호시스템의 소프트웨어 구현은 비효율적이다"라는 일반적으로 인정된 의견을 검증한다. 비록 센서모트에서 GF$(2^m)$에 기반을 둔 몇 가지의 소프트웨어 구현은 있지만, 이것들의 성능은 센서네트워크에서 사용할 만큼 충분하지 못하다. 기존 구현들의 성능 저하는 유한체 곱셈과 감산 연산에서 발생하는 중복된 메모리 접근에서 기인한다. 따라서 본 논문에서는 유한체 곱셈과 감산과정에서 발생하는 불필요한 메모리 접근을 줄일 수 있는 몇 가지 방법을 제안한다. 제안한 방법을 통하여, GF$(2^{163})$상의 유한체 곱셈과 감산의 수행시간을 각각 21.1%와 24.7% 줄일 수 있으며 이것은 Elliptic Curve Digital Signature Algorithm (ECDSA)의 sign과 verify 연산 시간을 약 $15{\sim}19%$ 단축시킬 수 있다.

In this paper, we revisit a generally accepted opinion: implementing Elliptic Curve Cryptosystem (ECC) over GF$(2^m)$ on sensor motes using small word size is not appropriate because partial XOR multiplication over GF$(2^m)$ is not efficiently supported by current low-powered microprocessors. Although there are some implementations over GF$(2^m)$ on sensor motes, their performances are not satisfactory enough due to the redundant memory accesses that result in inefficient field multiplication and reduction. Therefore, we propose some techniques for reducing unnecessary memory access instructions. With the proposed strategies, the running time of field multiplication and reduction over GF$(2^{163})$ can be decreased by 21.1% and 24.7%, respectively. These savings noticeably decrease execution times spent in Elliptic Curve Digital Signature Algorithm (ECDSA) operations (Signing and verification) by around $15{\sim}19%$.

본 논문에서는 "작은 워드 크기를 사용하는 센서모트에서는 GF$(2^m)$상의 partial XOR 곱셈연산이 저전력 마이크로프로세서에 의하여 효율적으로 지원되지 않기 때문에 GF$(2^m)$에 기반을 둔 타원곡선 암호시스템의 소프트웨어 구현은 비효율적이다"라는 일반적으로 인정된 의견을 검증한다. 비록 센서모트에서 GF$(2^m)$에 기반을 둔 몇 가지의 소프트웨어 구현은 있지만, 이것들의 성능은 센서네트워크에서 사용할 만큼 충분하지 못하다. 기존 구현들의 성능 저하는 유한체 곱셈과 감산 연산에서 발생하는 중복된 메모리 접근에서 기인한다. 따라서 본 논문에서는 유한체 곱셈과 감산과정에서 발생하는 불필요한 메모리 접근을 줄일 수 있는 몇 가지 방법을 제안한다. 제안한 방법을 통하여, GF$(2^{163})$상의 유한체 곱셈과 감산의 수행시간을 각각 21.1%와 24.7% 줄일 수 있으며 이것은 Elliptic Curve Digital Signature Algorithm (ECDSA)의 sign과 verify 연산 시간을 약 $15{\sim}19%$ 단축시킬 수 있다.

In this paper, we revisit a generally accepted opinion: implementing Elliptic Curve Cryptosystem (ECC) over GF$(2^m)$ on sensor motes using small word size is not appropriate because partial XOR multiplication over GF$(2^m)$ is not efficiently supported by current low-powered microprocessors. Although there are some implementations over GF$(2^m)$ on sensor motes, their performances are not satisfactory enough due to the redundant memory accesses that result in inefficient field multiplication and reduction. Therefore, we propose some techniques for reducing unnecessary memory access instructions. With the proposed strategies, the running time of field multiplication and reduction over GF$(2^{163})$ can be decreased by 21.1% and 24.7%, respectively. These savings noticeably decrease execution times spent in Elliptic Curve Digital Signature Algorithm (ECDSA) operations (Signing and verification) by around $15{\sim}19%$.