Performance evaluation of two-fuzzy based cluster head selection systems for wireless sensor networks

Sensor networks supported by recent technological advances in low power wireless communications along with silicon integration of various functionalities are emerging as a critically important computer class that enable novel and low cost applications. There are many fundamental problems that sensor networks research will have to address in order to ensure a reasonable degree of cost and system quality. Cluster formation and cluster head selection are important problems in sensor network applications and can drastically affect the network’s communication energy dissipation. However, selecting of the cluster head is not easy in different environments which may have different characteristics. In this paper, in order to deal with this problem, we propose two fuzzy-based systems for cluster head selection in sensor networks. We call these systems: FCHS System1 and FCHS System2. We evaluate the proposed systems by simulations and have shown that FCHS System2 make a good selection of the cluster head compared with FCHS System1 and another previous system.Peer ReviewedPostprint (published version

Guest editors’ preface to the special issue devoted to the 2nd International Conference “Numerical Computations: Theory and Algorithms”, June 19–25, 2016, Pizzo Calabro, Italy

This special issue of the Journal of Global Optimization contains twelve high-quality research papers devoted to different aspects of global optimization such as theory, numerical methods and real-life applications. The papers included in this special issue are based on the presentations carefully selected by the guest editors among the talks delivered at the 2nd International Conference “Numerical Computations: Theory and Algorithms (NUMTA)” held in June 19–25, 2016 in Pizzo Calabro, Italy (the first NUMTA conference took place in Falerna, Italy in 2013). The NUMTA 2016 has been organized by the University of Calabria, Rende (CS), Italy, in cooperation with the Society for Industrial and Applied Mathematics, USA. The guest editors actively participated in the organization of the conference: the Program Committee of the NUMTA 2016 was chaired by Yaroslav D. Sergeyev, in their turn, Renato De Leone and Anatoly Zhigljavsky took part in the Program Committee. The goal of the NUMTA 2016 was creation of a multidisciplinary round table for an open discussion on numerical modeling nature by using traditional and emerging computational paradigms. Participants of this conference discussed several aspects of numerical computations and modeling from foundations of mathematics and computer science to advanced numerical techniques. A large part of presentations has been dedicated to optimization. Selected papers presented at the conference in the field of numerical analysis and respective applications have been published in the special issue of the international journal Applied Mathematics and Computation, Volume 318 (2018). In its turn, the present special issue contains articles dealing with global optimization. Let us give a brief description of the papers included in this special issue

From the Guest Editors: Special issue dedicated to Carlos Castillo-Chavez on his 60th birthday

Carlos Castilo-Chavez is a Regents Professor, a Joaquin Bustoz Jr. Professor of Mathematical Biology, and a Distinguished Sustainability Scientist at Arizona State University. His research program is at the interface of the mathematical and natural and social sciences with emphasis on (i) the role of dynamic social landscapes on disease dispersal; (ii) the role of environmental and social structures on the dynamics of addiction and disease evolution, and (iii) Dynamics of complex systems at the interphase of ecology, epidemiology and the social sciences. Castillo-Chavez has co-authored over two hundred publications (see goggle scholar citations) that include journal articles and edited research volumes. Specifically, he co-authored a textbook in Mathematical Biology in 2001 (second edition in 2012); a volume (with Harvey Thomas Banks) on the use of mathematical models in homeland security published in SIAM\u27s Frontiers in Applied Mathematics Series (2003); and co-edited volumes in the Series Contemporary Mathematics entitled ``Mathematical Studies on Human Disease Dynamics: Emerging Paradigms and Challenges\u27\u27 (American Mathematical Society, 2006) and Mathematical and Statistical Estimation Approaches in Epidemiology (Springer-Verlag, 2009) highlighting his interests in the applications of mathematics in emerging and re-emerging diseases. Castillo-Chavez is a member of the Santa Fe Institute\u27s external faculty, adjunct professor at Cornell University, and contributor, as a member of the Steering Committee of the ``Committee for the Review of the Evaluation Data on the Effectiveness of NSF-Supported and Commercially Generated Mathematics Curriculum Materials,\u27\u27 to a 2004 NRC report. The CBMS workshop ``Mathematical Epidemiology with Applications\u27\u27 lectures delivered by C. Castillo-Chavez and F. Brauer in 2011 have been published by SIAM in 2013

IEEE Access Special Section Editorial: Big Data Technology and Applications in Intelligent Transportation

During the last few years, information technology and transportation industries, along with automotive manufacturers and academia, are focusing on leveraging intelligent transportation systems (ITS) to improve services related to driver experience, connected cars, Internet data plans for vehicles, traffic infrastructure, urban transportation systems, traffic collaborative management, road traffic accidents analysis, road traffic flow prediction, public transportation service plan, personal travel route plans, and the development of an effective ecosystem for vehicles, drivers, traffic controllers, city planners, and transportation applications. Moreover, the emerging technologies of the Internet of Things (IoT) and cloud computing have provided unprecedented opportunities for the development and realization of innovative intelligent transportation systems where sensors and mobile devices can gather information and cloud computing, allowing knowledge discovery, information sharing, and supported decision making. However, the development of such data-driven ITS requires the integration, processing, and analysis of plentiful information obtained from millions of vehicles, traffic infrastructures, smartphones, and other collaborative systems like weather stations and road safety and early warning systems. The huge amount of data generated by ITS devices is only of value if utilized in data analytics for decision-making such as accident prevention and detection, controlling road risks, reducing traffic carbon emissions, and other applications which bring big data analytics into the picture

New and Emerging Topics in Computing

This installment of Computer’s series highlighting the work published in IEEE Computer Society journals comes from IEEE Transactions on Emerging Topics in Computing

How to Create an Innovation Accelerator

Too many policy failures are fundamentally failures of knowledge. This has become particularly apparent during the recent financial and economic crisis, which is questioning the validity of mainstream scholarly paradigms. We propose to pursue a multi-disciplinary approach and to establish new institutional settings which remove or reduce obstacles impeding efficient knowledge creation. We provided suggestions on (i) how to modernize and improve the academic publication system, and (ii) how to support scientific coordination, communication, and co-creation in large-scale multi-disciplinary projects. Both constitute important elements of what we envision to be a novel ICT infrastructure called "Innovation Accelerator" or "Knowledge Accelerator".Comment: 32 pages, Visioneer White Paper, see http://www.visioneer.ethz.c