Planning of Electric Vehicle Charging Facilities on Highways Based on Chaos Cat Swarm Simulated Annealing Algorithm

Aiming at the layout planning of electric vehicle (EV) charging facilities on highways, this study builds a multi-objective optimization model with the minimum construction cost of charging facilities, minimum access cost to the grid, minimum operation and maintenance cost, and maximum carbon emission reduction benefit by combining the state of charge (SOC) variation characteristics and charging demand characteristics of EVs. A chaos cat swarm simulated annealing (CCSSA) algorithm is proposed. In this algorithm, chaotic logistic mapping is introduced into the cat swarm optimization (CSO) algorithm to satisfy the planning demand of EV charging facilities. The location information of the cat swarm is changed during iteration, the search mode and tracking mode are improved accordingly. The simulated annealing method is adopted for global optimization search to balance the whole swarm in terms of local and global search ability, thus obtaining the optimal distribution strategy of charging facilities. The case of the Xi’an highway network in Shanxi Province, China, shows that the optimization model considering carbon emission reduction benefits can minimize the comprehensive cost and balance economic and environmental benefits. The facility spacing of the obtained layout scheme can meet the daily charging demand of the target road network area

Topological Embedding Feature Based Resource Allocation in Network Virtualization

Virtualization provides a powerful way to run multiple virtual networks on a shared substrate network, which needs accurate and efficient mathematical models. Virtual network embedding is a challenge in network virtualization. In this paper, considering the degree of convergence when mapping a virtual network onto substrate network, we propose a new embedding algorithm based on topology mapping convergence-degree. Convergence-degree means the adjacent degree of virtual network's nodes when they are mapped onto a substrate network. The contributions of our method are as below. Firstly, we map virtual nodes onto the substrate nodes with the maximum convergence-degree. The simulation results show that our proposed algorithm largely enhances the network utilization efficiency and decreases the complexity of the embedding problem. Secondly, we define the load balance rate to reflect the load balance of substrate links. The simulation results show our proposed algorithm achieves better load balance. Finally, based on the feature of star topology, we further improve our embedding algorithm and make it suitable for application in the star topology. The test result shows it gets better performance than previous works

A QoS-based Resource Selection Approach for Virtual Networks

The Internet has gained an outstanding success in a short amount of time and it became a critical infrastructure for accessing information and global commerce. With the help of the Internet and its new channels for connecting people a new way of communication has been established. Meanwhile, its great success leads to new limitations. The Internet consists of various network infrastructure providers with different objectives which makes emerging of new technologies or major architectural changes that require cooperative agreements, relatively impractical. While the current Internet architecture is not suitable for supporting many types of applications, network virtualization is considered as promising, yet challenging solution of these limitations. Network virtualization separates the role of traditional internet service providers (ISPs) into physical infrastructure providers (PIPs) responsible for deploying the physical infrastructure and service providers (SPs) offering end-to-end services to end users. Another motivation for network virtualization is the possibility to add value in the virtualization layer aiming to make use of new technologies (e.g. QoS schemes) and customizing existing technologies to adapt specific services (i.e. customizable networks). This provides the means to run multiple virtual networks on a shared substrate network simultaneously while each virtual network is customized for a specific use. The key challenge in virtual networks is the problem of assigning virtual nodes and links to physical resources. Virtual network mapping/embedding consists in finding the most suitable physical nodes and links in the physical network in order to map virtual network requests with certain constraints on virtual nodes and links. The goal of this thesis is to design and implement substrate network resource selection scheme to increase the overall efficiency of the virtual network embedding process and satisfy the set of predefined resource constraints. This work assumes the existence of a virtual infrastructure provider requesting virtual networks from physical infrastructure providers and proposes a selection algorithm based on service-oriented architecture. Our proposed virtual network embedding algorithm is a heuristic algorithm that considers static attributes along with dynamic attributes of nodes and links as well as end-to-end QoS constraints