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Renewable Energies (RE) are considered as an important alternative sources of energy for the generation of electricity such as hydrogen and photovoltaic energies. To ensure an efficient photovoltaic energy conversion several Maximum Power Point Tracking (MPPT) algorithms have been developed to incite the PV field to deliver maximum power. This paper presents a comprehensive comparative study of two...
Most of IoT applications include large number of distributed sensors which are interesting in specific geographical area. A large number of IoT entities have multiple relations and dynamic connections with each other. And there are many group communication requirements. Flexible multicast mechanism will be essential in such environments but it is difficult to satisfy verious requirements by means...
This paper presents an algorithm for Distributed Generation (DG) allocation planning, using fuzzy set theory and fuzzy multi criteria decision making based on the Bellman-Zadeh method. The proposed model considers power losses and investment deferral values on one side (goals) and line currents, node voltages and short circuit power values on the other (constraints). The objective of this work is...
Standard called MPEG Dynamic Adaptive Streaming over HTTP (MPEG DASH) was developed in order to ensure that the end user shall be given the best possible quality of requested content under certain network conditions. DASH is used to notify the user that there are several transmission streams with different quality levels available. Bitrate adaptation algorithms used in DASH-based system have developed...
This paper gives a brief overview of the current state in the ant colony optimization (ACO) field of study. Furthermore, it introduces an alternative pheromone laying strategy for the ACO algorithm. In the paper, the newly introduced strategy is implemented, tested on a model problem and compared with the classical approach. A parameterized problem space generator has been introduced. The generator...
Network virtualization provides a flexible solution to reduce costs, share network resources and improve recovery time upon failure. An important part of virtual network management consists in migrating them in order to optimize resource allocation and react to link failures. However, the migration process might entail the loss of security properties in the virtual network, such as confidentiality...
Power electronics converters are essential and critical components of the new power-systems paradigm where renewable energy sources are expected to play a significant role in the future worldwide energy portfolio. In this paper, the flexibility of PV converters is exploited, proposing a novel method for tracking an external power-reference in real-time which generally differs from the maximum power...
Mobile edge computing (MEC) has recently emerged as an important paradigm to bring computation and cache resources to the edge of core networks. However, the resources of edge network are relatively limited, so it is necessary to cooperate with data center (DC) which has sufficient computational resources. In this paper, we aim at designing a computation offloading and data caching model under the...
Virtual Network Embedding (VNE) is widely considered as a longstanding challenge in Network Virtualization: how to efficiently embed multiple virtual networks (VNs), with node-link resource requirements, onto the shared substrate network (SN), having finite underlying resources. Most heuristic VNE algorithms in the literature, only considering single network topology attribute and local network resources,...
A lot of research has been proposed to improve network performance in the data center. However, with the development of distributed applications, these applications face a new performance bottleneck since existing solutions almost ignore the application level optimization. The concept of coflow has been proposed which provides a chance for us to optimize network in application level rather than individual...
In this paper, we investigate the quality of information (QoI) maximization problem by jointly optimizing the sampling rate, packet-dropped rate, and transmit power in wireless sensor networks (WSNs). We consider a complicated but practical scenario, where various tasks with heterogeneous traffic are supported by one WSN simultaneously. Accordingly, the QoI maximization problem is formulated as a...
The performance of fingerprint based indoor localization techniques is significantly degraded by environmental dynamics especially when devices such as Wi-Fi access points (APs), which are used to build fingerprint database, are densely deployed. The primary reason is that the plug-and-play feature of these devices would render the fingerprints in the database invalid. Worsestill, the time-varying...
There has been a significant increase in the number of sensors deployed to accomplish military missions. These sensors might be on manned or unmanned resources, and might collect quantitative and/or qualitative information important for mission success. Of critical importance for mission success is ensuring that the collected information is routed to the people/systems that need the information for...
This paper presents the joint design of network coding and backpressure algorithm for cognitive radio networks and its implementation with software-defined radios (SDRs) in a high fidelity network emulation testbed. The backpressure algorithm is known to provide throughput optimal solutions to joint routing and scheduling for dynamic packet traffic. This solution applies to cognitive radio networks...
Cognition involves dynamic reconfiguration of functional brain networks at sub-second time scale. A precise tracking of these reconfigurations to categorize visual objects remains elusive. Here, we use dense electroencephalography (EEG) data recorded during naming meaningful (tools, animals…) and scrambled objects from 20 healthy subjects. We combine technique for identifying functional brain networks...
How to reduce the energy consumption of urban rail transit system is always the focus of attention. The automatic train operation(ATO) system operates trains between successive stations by controlling the speed automatically, which is very important for the train energy saving operation. The traditional ATO recommended speed curve optimization research is based on line information, train information...
In this paper, a new strategy combining the MDPSO (multimodal delayed particle swarm optimization) and continuous Bezier curve is developed for the global smooth path planning of mobile robots. Firstly, the preliminaries on Bezier curve and the MDPSO are briefly introduced. Secondly, the environment modeling is presented and the smooth path planning problem is mathematically formulated. Then, the...
Research results in neurophysiology show the predictive nature of vergence eye movement, vergence eye movement can persistently track a moving target which shifts in distance relative to the head. Few models have attempted to consider prediction of target motion in vergence models. Most models only considered static targets, their input are frozen driving signals. In this paper, a model with estimator...
In this paper, we focus on the basic form of autonomous follow driving problem with one leader and one follower. A reinforcement learning based throttle and brake control approach is developed for the follower vehicle. Near optimal control law is directly learned by “trial and error” with the neural dynamic programming algorithm. According to the timely updated following state, the learned control...
ID3 is a classical algorithm of decision tree of classification with fast speed and easily understandable classification results. ID3 based on information gain tend to select test attribute with a variety of values, thus unable to deal with continuous attributes. In order to solve the above problems, this paper introduces the support in rough sets to discretize the continuous attributes dynamically,...
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