Wide area measurement system in the IEEE-14 bus system using multiobjective shortest path algorithm for fault analysis

In a large-scale interconnected power system network, few challenges exist in evaluating and maintaining the overall system stability. The power system's ability to supply all types of loads during natural disasters or faults has yet to be addressed. This work focuses on developing a wide-area measurement system to manage and control the power system under all operating conditions. The IEEE-14 bus system was modeled in PSCAD software for simulating nineteen types of fault based on multi-objective shortest path algorithm. To manage the wide area measurement, the research must comprehend the working principle of the multi-objective shortest path algorithm, whereby the proposed method will determine the new path for the IEEE-14 bus system. To evaluate the performance of the multi-objective shortest path algorithm, all sections of the IEEE-14 bus system were simulated with faults. The distances of the normal path (without simulated fault) and the new path (with simulated fault) were recorded. Based on the recorded data, it was found that the location of the fault has significant influence on the shortest path of the buses connected to each other

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

Data-Centric Multiobjective QoS-Aware Routing Protocol for Body Sensor Networks

In this paper, we address Quality-of-Service (QoS)-aware routing issue for Body Sensor Networks (BSNs) in delay and reliability domains. We propose a data-centric multiobjective QoS-Aware routing protocol, called DMQoS, which facilitates the system to achieve customized QoS services for each traffic category differentiated according to the generated data types. It uses modular design architecture wherein different units operate in coordination to provide multiple QoS services. Their operation exploits geographic locations and QoS performance of the neighbor nodes and implements a localized hop-by-hop routing. Moreover, the protocol ensures (almost) a homogeneous energy dissipation rate for all routing nodes in the network through a multiobjective Lexicographic Optimization-based geographic forwarding. We have performed extensive simulations of the proposed protocol, and the results show that DMQoS has significant performance improvements over several state-of-the-art approaches

Topology Control and Pointing in Free Space Optical Networks

Free space optical (FSO) communication provides functionalities that are different from fiber optic networks and omnidirectional RF wireless communications in that FSO is optical wireless (no infrastructure installation cost involving fibers) and is highly directional (no frequency interference). Moreover, its high-speed data transmission capability is an attractive solution to the first or last mile problem to bridge to current fiber optic network and is a preferable alternative to the low data rate directional point-to-point RF communications for inter-building wireless local area networks. FSO networking depends critically on pointing, acquisition and tracking techniques for rapidly and precisely establishing and maintaining optical wireless links between network nodes (physical reconfiguration), and uses topology reconfiguration algorithms for optimizing network performance in terms of network cost and congestion (logical reconfiguration). The physical and logical reconfiguration process is called Topology Control and can allow FSO networks to offer quality of service by quickly responding to various traffic demands of network users and by efficiently managing network connectivity. The overall objective of this thesis research is to develop a methodology for self-organized pointing along with the associated autonomous and precise pointing technique as well as heuristic optimization methods for Topology Control in bi-connected FSO ring networks, in which each network node has two FSO transceivers. This research provides a unique, autonomous, and precise pointing method using GPS and local angular sensors, which is applicable to both mobile and static nodes in FSO networking and directional point-to-point RF communications with precise tracking. Through medium (264 meter) and short (40 meter) range pointing experiments using an outdoor testbed on the University of Maryland campus in College Park, sub-milliradian pointing accuracy is presented. In addition, this research develops fast and accurate heuristic methods for autonomous logical reconfiguration of bi-connected ring network topologies as well as a formal optimality gap measure tested on an extensive set of problems. The heuristics are polynomial time algorithms for a congestion minimization problem at the network layer and for a multiobjective stochastic optimization of network cost and congestion at both the physical and network layers

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing