software
Fatemeh SalarKaleji; Parvin Shavandi; Alireza Omranian; Oveys Kazemi; Farzad Emami; shahrokh jalilian; Alireza Khani; Abolfazl Dayyani; Mohammad Sayanjali
Abstract
PARS1 Satellite is a Remote Sensing satellite with a 3-years mission. The main mission of this satellite is imaging the earth by three cameras named MS, SWIR and TIR. PARS1 OnBoard Software (OBSW) is developed as a performance platform, satellite components control, manage their data, algorithm management ...
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PARS1 Satellite is a Remote Sensing satellite with a 3-years mission. The main mission of this satellite is imaging the earth by three cameras named MS, SWIR and TIR. PARS1 OnBoard Software (OBSW) is developed as a performance platform, satellite components control, manage their data, algorithm management included normal status control and event handling. OBSW is more important than other satellite subsystems due to its complexity and different features. So, the design, development and test of the PARS1 satellite OBSW is a useful platform to gain valuable experiences in the field of satellite onboard software which is very wide and complicated in its field. Therefore, in this paper decided to present experiences which gained in this field, in the form of summary of achievements and lessons learned. These experiences is gained from development and test phase of the satellite and using of these experiences will be very useful and effective in smoothing of test and development path in future projects of the Satellite Research Institute
Computer
Athena Abdi; shahrokh jalilian
Abstract
In this paper, a task scheduling and mapping method based on multi-objective particle swarm optimization (MOPSO) algorithm is presented to improve lifetime reliability of multiprocessors systems on chip. This method considers power consumption temperature and performance along with the lifetime reliability ...
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In this paper, a task scheduling and mapping method based on multi-objective particle swarm optimization (MOPSO) algorithm is presented to improve lifetime reliability of multiprocessors systems on chip. This method considers power consumption temperature and performance along with the lifetime reliability due to the antagonistic relations of these parameters. These antagonistic and dependent relations make the design space exploration and optimization processes complex. The proposed method is based on MOPSO algorithm and starts with an initial population of candidate solutions which are generated randomly and represents valid task scheduling and mapping solutions. By changing the scheduling and mapping parameters during the MOPSO algorithm, new solutions are produced and the design space is explored based on the objective of the target problem of this method. Several experiments on random and real-life benchmarks are performed to verify the effectiveness of our proposed method. The results demonstrate the capability of the proposed method in effective design space exploration and generating the Pareto front. Moreover, comparisons to the related research show 35%, 23%, 19% and 3% improvements in performance, lifetime reliability, temperature, and power consumption on average.
