Bonjour, je m’appelle Abdusy SYARIF. Je travaille Ă CESI Strasbourg, en collaboration avec ABA et JFDR dans le cadre d’un projet de recherche international. (more…)
Archive for the ‘Wireless Sensor Networks’ Category
CESI Recherche International
February 21, 2019IJR Project UMB-UHA-CESI
February 21, 2019Since October 2017, I have been involving as a member of International Joint Research (IJR) project between 3 institutions (2 France, 1 Indonesian). Currently I’m an associate professor at UMB (maybe until [month] 20[xx] 🙂 ) and a PostDoc fellow at CESI Starsbourg, France, as a part of joint research between UMB-UHA-CESI. We have started our project on December 2017. (more…)
Protokol Routing RPL
January 23, 2018Internet of Things (IoT) bukan lagi sebagai fantasi sains-fiksi. Dengan kemajuan teknologi yang sangat pesat memungkinkan terhubungnya semua objek sehari-hari ke Internet. Namun, diperlukan sebuah solusi yang interoperabel untuk memastikan optimal komunikasi antar objek-objek tersebut. Protokol routing adalah salah satu elemen kunci pada IoT. Karena protokol routing memungkinkan setiap objek menentukan bagaimana mencapai objek lain. Beberapa kendala pada protokol routing antara lain saluran komunikasi yang tidak stabil dan energi daya rendah yang harus diperhitungkan dalam pengembangan protokol routing yang sesuai untuk IoT. Pada artikel kali ini, saya akan menyajikan sekilas tentang protokol RPL yang dirancang khusus untuk jaringan berdaya rendah dan lossy (Low-power and Lossy Network disingkat LLN).
MATLAB : WSN SIMULATION
November 13, 2017The instruction is valid for Matlab version R2007b.
First dowload and save grTheory toolobox (save it in Tools): http://www.mathworks.com/matlabcentral/fileexchange/4266. Open the Matlab and go to the File/Set Path and click on the Add Folder. Insert the path to your grTheory toolbox. (more…)
Optimisasi Penyebaran Jaringan Sensor Pemantauan Maritim Menggunakan Algoritma Genetik
November 8, 2017Abstrak
Sebagai negara kepulauan terbesar di dunia, Indonesia memiliki potensi besar menjadi poros maritim dunia. Poros maritim merupakan sebuah gagasan strategis yang diwujudkan untuk menjamin konektifitas antar pulau, pengembangan industri perkapalan dan perikanan, perbaikan transportasi laut serta fokus pada keamanan maritim. Maka diperlukan pemantauan maritim untuk mencegah terjadinya hal-hal yang negatif seperti pencemaran laut, pencurian ikan, pelanggaran kedaulatan, sengketa wilayah, dan perompakan. Pemantauan maritim telah menjadi isu yang sangat menarik selama beberapa tahun belakangan ini. Dengan adanya kemajuan teknologi dan Internet yang sangat pesat, teknologi jaringan sensor nirkabel telah menjadi hal yang sangat penting pada pemantauan lingkungan perairan. Penelitian ini mengusulkan sebuah metode optimasi penyebaran jaringan sensor untuk pemantauan lingkungan maritim. Dengan menggunakan pendekatan algoritma genetik multi-obyektif evolusioner untuk mendapatkan solusi topologi jaringan sensor optimal dengan jumlah sensor seminimum mungkin, namun maksimum dalam hal jangkauan dan konektifitas.
Operator calculus approach for route optimizing and enhancing wireless sensor network
October 1, 2017This is the abstract of my paper which accepted and published at Journal of Network and Computer Applications,Vol 97, pp. 1-10. 2017. DOI: 10.1016/j.jnca.2017.08.007.
Abstract
Route optimization is one of important feature in wireless sensor networks in order to enhancing the life time of WSNs. Since Centrality is one of the greatest challenges in computing and estimating the important node metrics of a structural graph, it is necessary to calculate and determine the importance of a node in a network. This paper proposes an alternative way to optimizing the route problems which is based on multi-constrained optimal path (MCOP) and operator calculus approach. A novel routing protocol called Path Operator Calculus Centrality (POCC) is proposed as a new method to determine the main path which contains high centrality nodes in a wireless sensor network deployment. The estimation of centrality is using the operator calculus approach based on network topology which provides optimal paths for each source node to base station. Some constraints such as energy level and bit error rate (BER) of node are considered to define the path centrality in this approach. The simulation evaluation shows improved performance in terms of energy consumption and network lifetime.
Keywords
Wireless Sensor Network, Multi-constrained Optimal Path Centrality, Path Centrality, Operator Calculus
NS-2: WSN with obstacles
May 29, 2017
This is the tcl script for simulating a Wireless Sensor Network with some obstacles in the target area.
Kuliah Umum di Program Pasca Sarjana Universitas Mercu Buana – Jakarta
March 27, 2016
Hari minggu, 27 Maret 2016, saya diberikan kesempatan yang baik oleh Prof. Mudrik Alaydrus untuk memberikan Kuliah Umum kepada teman-teman sivitas akademis Program Sarjana Teknik Elektro, Magister Manajemen Telekomunikasi, Universitas Mercu Buana, Jakarta.
Pada kesempatan kali ini, saya berbagi pengalaman dan ilmu pengetahuan mengenai riset yang telah saya lakukan selama di Perancis. Topiknya adalah mengenai “Optimizing and Enhancing the lifetime of WSN Deployment” dengan menggunakan pendekatan MOP (Multi-objective Optimisation Problem) dan Operator Calculus untuk mendefinisikan sebuah Path Centrality dari sebuah WSN.
Senang dan bahagia sekali melihat antusias teman-teman/adik-adik mahasiswa yang penuh semangat untuk melanjutkan studi ke jenjang yang lebih tinggi. Bon courage…!
Anda bisa mengunduh file presentasi dalam file pdf ini.
Search Based Software Engineering on Evolutionary Multi-Objective Approach
March 15, 2016
Here is the abstract of our paper entitle “Search Based Software Engineering on Evolutionary Multi-Objective Approach” which is accepted in IEEE International Converence on Communications 2016 and will be presented at Kuala Lumpur, Malaysia, on 23 May 2016.
The works on Search Based Software Engineering (SBSE) have been a big increase in the last decade. An approach to software engineering in which search based optimisation algorithms are applied to address problems in software engineering. SBSE has been applied to problems throughout the software engineering lifecycle, from requirements and project planning to maintenance and re-engineering. This paper provides a modification and an implementation of SBSE on evolutionary multi-objective based ap-proach for deployment of wireless sensor network (WSN) with the presence of fixed obstacle. In this work a multi-objective evolutionary algorithms based on elitist non-dominated sorting genetic algorithm (NSGA-II) is proposed to address the deployment problem. Two functions namely ranking function and fitness function are used to select the best optimal solution from Pareto optimal fronts.
Performance Analysis of Evolutionary Multi-Objective Based Approach for Deployment of Wireless Sensor Network with The Presence of Fixed Obstacles
November 11, 2014
Here is the abstract from our paper that already accepted and will be presented on Globecom 2014 that will be held in Austin, Texas, USA from 8 – 12 December 2014.
Abstract — In this paper, a study about wireless sensor network (WSN) deployment strategy is demonstrated and made workable for the use of multi-objective approach. The development of sensor nodes by considering multiple objectives and existence of fixed obstacles is an important optimization problem. There are two objectives in this study, connectivity and coverage as two fundamental issues in wireless sensor networks deployment. In this work a multi-objective evolutionary algorithms based on elitist non-dominated sorting genetic algorithm (NSGA-II) is proposed to address this problem. Two proposed functions, ranking function and fitness function, are used to determine the best optimal solution from Pareto optimal fronts. Further we presented simulation and analysis to verify and validate the deployment of wireless sensor network in area with the presence of permanent obstacles.
Keywords — Multi-objective optimization, Wireless Sensor Network, Deployment, Genetic Algorithm, Obstacle.
