Planning Support Systems: Progress, Predictions, and Speculations on the Shape of Things to Come

In this paper, we review the brief history of planning support systems, sketching the way both the fields of planning and the software that supports and informs various planning tasks have fragmented and diversified. This is due to many forces which range from changing conceptions of what planning is for and who should be involved, to the rapid dissemination of computers and their software, set against the general quest to build ever more generalized software products applicable to as many activities as possible. We identify two main drivers – the move to visualization which dominates our very interaction with the computer and the move to disseminate and share software data and ideas across the web. We attempt a brief and somewhat unsatisfactory classification of tools for PSS in terms of the planning process and the software that has evolved, but this does serve to point up the state-ofthe- art and to focus our attention on the near and medium term future. We illustrate many of these issues with three exemplars: first a land usetransportation model (LUTM) as part of a concern for climate change, second a visualization of cities in their third dimension which is driving an interest in what places look like and in London, a concern for high buildings, and finally various web-based services we are developing to share spatial data which in turn suggests ways in which stakeholders can begin to define urban issues collaboratively. All these are elements in the larger scheme of things – in the development of online collaboratories for planning support. Our review far from comprehensive and our examples are simply indicative, not definitive. We conclude with some brief suggestions for the future

DFQIoV: Design of a Dynamic Fan-Shaped-Clustering Model for QoS-aware Routing in IoV Networks

Internet of Vehicles (IoV) is a steadily growing field of research that deals with highly ad-hoc wireless networks. These networks require design of high-speed & high-efficiency routing models, that can be applied to dynamically changing network scenarios. Existing models that perform this task are highly complex and require larger delays for estimation of dynamic routes. While, models that have faster performance, do not consider comprehensive parameters, which limits their applicability when used for large-scale network scenarios. To overcome these limitations, this text proposes design of a novel dynamic fan-shaped clustering model for QoS-aware routing in IoV networks. The model initially collects network information sets including node positions, & energy levels, and combines them with their temporal packet delivery & throughput performance levels. These aggregated information sets are processed via a hybrid bioinspired fan shaped clustering model, that aims at optimization of routing performance via deployment of dynamic clustering process. The model performs destination-aware routing process which assists in reducing communication redundances. This is done via a combination of Elephant Herding Optimization (EHO) with Particle Swarm Optimization (PSO), which integrates continuous learning for router level operations. The integrated model is able to reduce communication delays by 5.9%, while improving energy efficiency by 8.3%, throughput by 4.5%, and packet delivery performance by 1.4% under different network scenarios. Due to which the proposed model is capable of deployment for a wide variety of dynamic network scenarios

UAV-assisted data dissemination based on network coding in vehicular networks

Efficient and emergency data dissemination service in vehicular networks (VN) is very important in some situations, such as earthquakes, maritime rescue, and serious traffic accidents. Data loss frequently occurs in the data transition due to the unreliability of the wireless channel and there are no enough available UAVs providing data dissemination service for the large disaster areas. UAV with an adjustable active antenna can be used in light of the situation. However, data dissemination assisted by UAV with the adjustable active antenna needs corresponding effective data dissemination framework. A UAV-assisted data dissemination method based on network coding is proposed. First, the graph theory to model the state of the data loss of the vehicles is used; the data dissemination problem is transformed as the maximum clique problem of the graph. With the coverage of the directional antenna being limited, a parallel method to find the maximum clique based on the region division is proposed. Lastly, the method\u27s effectiveness is demonstrated by the simulation; the results show that the solution proposed can accelerate the solving process of finding the maximum clique and reduce the number of UAV broadcasts. This manuscript designs a novel scheme for the UAV-assisted data dissemination in vehicular networks based on network coding. The graph theory is used to model the state of the data loss of the vehicles. With the coverage of the directional antenna being limited, then a parallel method is proposed to find the maximum clique of the graph based on the region division. The effectiveness of the method is demonstrated by the simulation