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2nd EAI International Conference on Nature of Computation and Communication

March 17–18, 2016 | Rach Gia, Vietnam

Keynote speech 1: Application of Genetic Algorithms for MANETS and Wireless Mesh Networks

Prof.Leonard Barolli at Fukuoka Institute of Technology (FIT) in Japan will give a talk at ICTCC 2016 on a hot topic of genetic algorithm with the title of "Application of Genetic Algorithms for MANETS and Wireless Mesh Networks"

Keynote speech 2: Algebraically Autonomic Computing

Prof.Phan Cong Vinh at Nguyen Tat Thanh University in Vietnam will give a talk at ICTCC 2016 on a hot topic of autonomic computing with the title of "Algebraically Autonomic Computing"

Keynote speech 3: Computational Intelligence (CI) and Its Application in Engineering and Computer Science

Pandian Vasant at Universiti Teknologi PETRONAS in Malaysia will give a talk at ICTCC 2016 on a hot topic of computational intelligence with the title of "Computational Intelligence (CI) and Its Application in Engineering and Computer Science"


Leonard Barolli

BIO

Leonard Barolli received BE and PhD degrees from Tirana University and Yamagata University in 1989 and 1997, respectively. From April 1997 to March 1999, he was a JSPS Post Doctor Fellow Researcher at Department of Electrical and Information Engineering, Yamagata University. From April 1999 to March 2002, he was as a Research Associate at the Department of Public Policy and Social Studies, Yamagata University. From April 2002 to March 2003, he was an Assistant Professor at Department of Computer Science, Saitama Institute of Technology (SIT). From April 2003 to March 2005, he was an Associate Professor and presently is a Full Professor, at Department of Information and Communication Engineering, Fukuoka Institute of Technology (FIT). Prof. Barolli has published more 700 papers in referred Journals, Books and International Conference proceedings. He was an Editor of the IPSJ Journal and has served as a Guest Editor for many International Journals. Dr. Barolli has been a PC Chair and General Chair of many International Conferences. Prof. Barolli is the Steering Committee Chair of CISIS and BWCCA International Conferences and Steering Committee Co-Chair of AINA, NBiS, 3PGCIC, EIDWT, INCoS and IMIS. He is organizers of many International Workshops. Prof. Barolli has won many Awards for his scientific work and has received many research funds. He got the “Doctor Honoris Causa” Award from Polytechnic University of Tirana in 2009. His research interests include network traffic control, fuzzy control, genetic algorithms, agent-based systems, ad-hoc networks, sensor networks, sensor-actor networks, P2P systems, vehicular networks, cellular networks, Web applications and medical applications. He is a member of SOFT, IPSJ, IEEE and IEEE CS.

 

ABSTRACT

'Application of Genetic Algorithms for MANETS and Wireless Mesh Networks'

 

In this talk, I will present the application of Genetic Algorithms (GAs) for QoS Routing in Mobile Ad-hoc Networks (MANETs) and node placement in Wireless Mesh Networks (WMNs).

In general, most of routing solutions in MANETs deal with the best effort data traffic. Connections with Quality of Service (QoS) requirements, such as voice channels with delay and bandwidth constraints, are not supported. The QoS routing has been receiving increasingly intensive attention, but searching for the shortest path with many metrics is an NP-complete problem. For this reason, approximated solutions and heuristic algorithms should be developed for multi-path constraints QoS routing. Also, the routing methods should be adaptive, flexible, and intelligent. Therefore, we use Genetic Algorithms (GAs) and Multi-objective Optimization for QoS routing in MANETs.

In WMNs, several optimization problems are appearing. Such problems are related to optimizing network connectivity, coverage and stability. The solution of these problems turns out to be crucial for optimized network performance. In the case of WMNs, such problems include computing placement of mesh router nodes so that network performance is optimized. However, as these optimization problems are known to be computationally hard to solve, GAs have been recently investigated as effective resolution methods.

In this research, we implement two simulation systems: one for MANETs (called GAMAN) and another one for WMNs (called WMN-GA). Both simulation systems are based on GAs. We evaluate both approaches by computer simulations. In this study, we give a comparison study between GA-based routing algorithms: GAMAN and GLBR. The performance evaluation via simulations shows that the GAMAN algorithm has better behavior than previous GAMAN-1 and GLBR algorithms and is a promising algorithm for QoS routing in MANETs.

 We evaluate the performance of WMN-GA for different settings in order to judge the suitability of solving mesh router nodes problem. We consider a bi-objective optimization consisting in the maximization of the size of the giant component in the mesh routers network (for measuring network connectivity) and that of user coverage. We have used a benchmark of instances (varying from small to large size) generated using different distributions of mesh node clients. In order to evaluate the performance of the proposed genetic operators, we use different distributions of client and mesh routers (Uniform, Normal, Exponential and Weibull). We have shown by simulations that both systems have a very good behavior and they successfully can be used for MANETs QoS routing and node placement problem in WMNs.

 

Phan Cong Vinh

BIO

Phan Cong Vinh received a PhD in computer science from London South Bank  University (LSBU) in the United Kingdom. He finished his PhD dissertation with the title of “Formal Aspects of Dynamic Reconfigurability in Reconfigurable Computing Systems” at LSBU where he was affiliated with the Center for Applied Formal Methods (CAFM) at the Institute for Computing Research (ICR). At present, he is an Associate Professor of Nguyen Tat Thanh University (NTTU) to take on the responsibility of a senior research scientist. He has been author or co-author of many refereed contributions published in prestigious journals, conference proceedings or edited books. He is editor of two books titled, “Autonomic Networking-on-Chip: Bio-Inspired Specification, Development and Verification” (CRC Press, 2012) and “Formal and Practical Aspects of Autonomic Computing and Networking: Specification, Development and Verification” (IGI Global, 2011). He has served on many conference program committees and has been general or technical (co)chair and (co)organizer of several international conferences such as a series of ICCASA and ICTCC. His research interests center on all aspects of formal methods, nature of computation and communication, and applied categorical structures in computer science.

 

ABSTRACT

'Algebraically Autonomic Computing

 

Autonomic computing (AC) is characterized by self-* such as self-configuration, self-healing, selfoptimization, self-protection and more which run simultaneously in autonomic systems (ASs). Hence, self-* is a set of self- ’s. Each self- in self-* is called self-* action. Our way to interpret self-* is to say that self-* actions are running on ASs. In this paper, algebraic objects called monoids
are tasked with encoding the self-* action’s perspective in all this, i.e. what the self-* action can do, and what happens when different self-* actions are done in succession.
 
 

Pandian Vasant

BIO

Pandian Vasant is a senior lecturer at Department of Fundamental and Applied Sciences, Universiti Teknologi PETRONAS in Malaysia. His research interest includes Soft Computing, Hybrid Optimization, Holistic Optimization and Applications. He has co-authored research papers and articles in national journals, international journals, conference proceedings, conference paper presentation, and special issues lead guest editor, lead guest editor for book chapters’ project, conference abstracts, edited books and book chapters. In the year 2009, P. Vasant was awarded top reviewer for the journal Applied Soft Computing (Elsevier). Currently he’s member of editorial board of International Journal of Computing and Optimization (IJCO), International Journal of Energy Optimization and Engineering (IJEOE), and Global Journal of Technology and Optimization (GJTO).

Website References:

http://www.igi-global.com/affiliate/pandian-vasant/182010

https://scholar.google.com.my/citations?hl=en&user=cOKj9goAAAAJ

https://my.linkedin.com/in/vasant

 

ABSTRACT

‘Computational Intelligence (CI) and Its Application in Engineering and Computer Science’

 

Computational Intelligent techniques have been successfully applied to many aspects of Engineering and Computer Science. For example, as reported in the literature, Gravitational search algorithm (GSA), Genetic algorithm (GA), Particle swarm optimization (PSO), Ant colony optimization (ACO), Bat Algorithm (BA), Fire Fly (FF), Evolutionary algorithm (EA)and several hybrid swarm evolutionary algorithms have been adopted to handle complex and uncertain real world optimization problems. On the other hand, advances in hybrid optimization techniques, an important section in Computational Intelligence and Soft Computing, also assist optimization algorithm experts to develop better methods. For instance, hybrid algorithm has been utilized for finding the relationship among decision variables for optimizers. In order to bridge the concepts and methodologies from the two ends, this talk focus on the related topics of integrating and utilizing algorithms in computational intelligent techniques and their applications in Engineering and Computer Science. It provides the opportunity for practitioners handling their complicated real world issues by using Computational Intelligent optimization methodologies and for researchers to realize the significant contribution to the body of the knowledge to share findings and look into future directions.

This talk aims at providing holistic state-of-the-art Computational Intelligent optimization techniques in Engineering and Computer Science, developing the cutting hedge optimization techniques by using modern and classical approaches, as well as exchanging of related ideas and discussing the future directions [1-4].

References

[1] Vasant, P., Weber, G., & Dieu, V. N. (2016). Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics (pp. 1-684). Hershey, PA: IGI Global. doi:10.4018/978-1-4666-9644-0

[2]Vasant, P. M. (2013). Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance (pp. 1-734). Hershey, PA: IGI Global.doi:10.4018/978-1-4666-2086-5

[3]Vasant, P. M. (2014). Handbook of Research on Novel Soft Computing Intelligent Algorithms: Theory and Practical Applications (2 Volumes) (pp. 1-1018). Hershey, PA: IGI Global. doi:10.4018/978-1-4666-4450-2

[4]Vasant, P. (2015). Handbook of Research on Artificial Intelligence Techniques and Algorithms (2 Volumes) (pp. 1-873). Hershey, PA: IGI Global. doi:10.4018/978-1-4666-7258-1