Real-world engineering design problems with complex objective functions under some constraints are relatively difficult problems to solve. Such design problems are widely experienced in many engineering fields, such as industry, automotive, construction, machinery, and interdisciplinary research. However, there are established optimization techniques that have shown effectiveness in addressing these types of issues. This research paper gives a comparative study of the implementation of seventeen new metaheuristic methods in order to optimize twelve distinct engineering design issues. The algorithms used in the study are listed as: transient search optimization (TSO), equilibrium optimizer (EO), grey wolf optimizer (GWO), moth-flame optimization (MFO), whale optimization algorithm (WOA), slime mould algorithm (SMA), harris hawks optimization (HHO), chimp optimization algorithm (COA), coot optimization algorithm (COOT), multi-verse optimization (MVO), arithmetic optimization algorithm (AOA), aquila optimizer (AO), sine cosine algorithm (SCA), smell agent optimization (SAO), and seagull optimization algorithm (SOA), pelican optimization algorithm (POA), and coati optimization algorithm (CA). As far as we know, there is no comparative analysis of recent and popular methods against the concrete conditions of real-world engineering problems. Hence, a remarkable research guideline is presented in the study for researchers working in the fields of engineering and artificial intelligence, especially when applying the optimization methods that have emerged recently. Future research can rely on this work for a literature search on comparisons of metaheuristic optimization methods in real-world problems under similar conditions.

In this demo, we provide a Mininet-based Software-Defined Network (SDN) simulation environment that improves the total flow throughput and scalability of the overall network. Mininet is a suitable and manageable tool to implement the proposed SDN based flow admission control module in order to configure the entire topology since it has already built in Open-Flow switches and virtual controllers. This open-source platform is also easily configurable via its drag and drop capabilities. In this Demo, for the Control Plane, OpenDaylight controller is used in order to simulate flow admission control module that fairly admits flows into the OpenFlow switches. OpenFlow version, 1.3. for communication between separated Data and Control plane and Linux based operating system to build Mininet 2.1.0 are deployed in the simulator environment.

The tremendous increase in the mobile data traffic has led the network operators to use offloading solutions in Radio Access Technologies (RATs) such as WiFi or smallcells. However, these solutions are not efficient since none of them controls the offloading from a centralized global network view. Current offloading methods are mostly user-based and they do not completely consider the user satisfaction, and more significantly they do not consider the Quality of Service (QoS) of the whole network system. These aforementioned motivations have led us to design a software based orchestration model for Heterogeneous Networks (HetNets) which is provided by our SDoff framework in a Software-Defined Network (SDN) fashion. This paper presents a novel SDN-based control of smallcell offloading in order to enhance the satisfaction of users and QoS of the overall system by considering a dissatisfaction parameter (ψ). The proposed framework analyzes the distance of each user to the all HetNet base stations in the topology by considering different type of users. After that, the offloading decision algorithm resolves which user must be offloaded to which base station by identifying the most dissatisfied user in the topology according to (ψ), by evaluating the QoS matrix and user types. Moreover, a new beacon format is proposed in order to maintain a standardized communication between the SDoff plane and virtual representatives (Avatars) of the Data Plane elements. We showed the overall system dissatisfaction difference between SDoff controlled offloading and on-the-spot offloading in the evaluation.

Otonom sürüş için önerilen çeşitli yaklaşımlar temelde bir görüntü işleme ve bir makine öğrenmesi sürecini içermektedir. Bu süreçlerin başarıya ulaşması için uygun görüntü işleme tekniklerinin ve kapsamlı bir veri setinin kullanılması son derece önemlidir. Bununla birlikte, gerçek dünyada uygulanabilir bir model ortaya koymak adına, önerilen modelin gerçek zamanlı çalışması gerekir. Öte yandan, bir otonom araç modelinin tasarlanması, imalatı ve test süreçleri ciddi donanım maliyetleri ile sonuçlanmaktadır. Ayrıca, yeni yaklaşımların geliştirilmesi ve uygulanması için ciddi donanım değişikliklerine ihtiyaç duyulması durumunda, tasarım ve imalat süreçlerinin tekrarlanması gerekmektedir. Bu bağlamda, gerçek zamanlı bir benzetim mimarisinden faydalanmak, modelin daha az maliyetle bir ön doğrulaması için uygun bir yaklaşımdır. Bu yüzden, bu çalışmada, bir otonom sürüş modelini sınamak üzere, Unity kütüphanesi ve gerekli diğer bileşenler ile gerçek zamanlı bir benzetim ortamı mimarisi önerilmektedir. Ayrıca, şerit takip ve nesne tanıma yaklaşımlarının uygun bir bileşimin içeren bir otonom sürüş modeli tanıtılarak, önerilen benzetim mimarisinde hazırlanan bir parkur üzerinde, bir otonom araç benzetimi oluşturulmaktadır. Son olarak, literatürde yer alan bir veri seti üzerinde, evrişimsel sinir ağları tabanlı YOLO algoritması versiyonları ile önerilen benzetim mimarisinin uygulanabilirliği sınanmaktadır. Çalışmadan elde edilen bulgular göz önüne alındığında, otonom sürüş modeline sahip bir araç benzetiminin, önerilen sistem mimarisinde başarılı bir şekilde sınandığı savunulmaktadır.