Search Results (29)

In V2G service operations, highly efficient data sharing among participants is useful in grid load balancing and renewable energy integration. However, the data quality and sharing efficiency greatly rely on entities’ willingness to share. Moreover, there is no rational assessment framework for the privacy sensitivity of sharing data, which highly affects data sharing willingness. Existing privacy sensitivity assessment methods rely on static privacy attributes and fail to rationally assess privacy threats within V2G service scenarios. To address these limitations, this paper proposes Dyn-Pri, a novel multi-dimensional privacy sensitivity assessment framework for large-scale V2G interactive service scenarios. Dyn-Pri features an adaptive comprehensive multi-dimensional quantification model that integrates both the three privacy elements’ intrinsic effects and the dynamic, intertwining influences among them. The experimental validations in three typical V2G scenarios demonstrate that Dyn-Pri has significant advantages in the precision of sensitivity assessments, and balancing data utilization and privacy protection enhances renewable energy integration efficiency while ensuring cross-domain data security. Full article

A demand response (DR) aggregator is a specialized entity designed to collaborate with electricity producers, facilitating the exchange of energy for numerous stakeholders. This application is a pivotal development within the Russian Energy System as it transitions to a Smart Grid. Its successful operation relies on the advancement and implementation of more efficient strategies to manage emerging energy assets and structures. The holonic approach is a distributed management model used to handle systems characterized by random and dynamic changes. This paper analyzes the specific aspects of the electricity demand management mechanism in Russia, primarily aimed at reducing peak load in the energy system by engaging active consumers who are outside the wholesale market. The DR-Aggregator is considered both a cyber-physical system (CPS) with a cluster structure and a business process. The DR-Aggregator exhibits essential holonic properties, enabling the application of a holonic approach to enhance the efficiency of the DR-Aggregator mechanism. This approach will facilitate greater flexibility in managing the load schedules of individual holon consumers, bolster the reliability of power supply by aligning load schedules among holon consumers within the super-holon cluster, and improve the fault tolerance of the DR-Aggregator structure, providing greater adaptability of demand management services. Full article

This study is aimed at addressing the problem of optimizing microgrid operations to improve local renewable energy consumption and ensure the stability of multi-energy systems. Microgrids are localized power systems that integrate distributed energy sources, storage, and controllable loads to enhance energy efficiency and reliability. The proposed approach introduces a novel microgrid optimization method that leverages the parameterized Dueling Deep Q-Network (Dueling DQN) and Deep Deterministic Policy Gradient (DDPG) algorithms. The method employs a parametric hybrid action-space reinforcement learning technique, where the DDPG is utilized to convert discrete actions into continuous action values corresponding to each discrete action, while the Dueling DQN uses the current observation states and these continuous action values to predict the discrete actions that maximize Q-values. This integrated strategy is designed to tackle the co-scheduling challenge in microgrids, enabling them to dynamically select the most favorable control strategies based on their specific states and the actions of other intelligent entities. The ultimate objective is to minimize the overall operational costs of microgrids while ensuring the efficient local consumption of renewable energy and maintaining the stability of multi-energy systems. Simulation experiments were conducted to validate the efficacy and superiority of the proposed method in achieving the optimal microgrid operation, showcasing its potential to improve service quality and reduce operational expenses. Average rewards increased by 30% and 15% compared to the use of the Dueling DQN or DDPG only. Full article

With the booming development of the electricity market, market factors such as electricity trading varieties are growing rapidly. The frequency of transactions has become increasingly real-time, and transaction clearing and settlement tasks have become more complex. The increasing demands for concurrent access and carrying capacity in trading systems have made it increasingly difficult for existing systems to support business. This article proposes a transaction support system for large-scale electricity trading market entities, which solves the problems of high concurrency access and massive access data calculation while ensuring system security through business isolation measures. The system uses microservices to treat various functional modules as independent service modules, thus making service segmentation and composition more flexible. By using read–write separation, caching mechanisms, and several data reliability assurance measures, data can be stored and accessed quickly and securely. The use of a three-layer load balancing module consisting of an OpenResty access entry layer, a gateway routing gateway layer, and a WebClient service inter-resource invocation layer can effectively improve the system’s ability to handle concurrent access. Full article

We face a decentralized renewable energy production scenario, where a large number of small energy producers, i.e., prosumers, contribute to a common distributor entity, who resells energy directly to end-users. A major challenge for the distributor is to ensure power stability, constantly balancing produced vs consumed energy flows. In this context, being able to provide quick restore actions in response to unpredictable unbalancing events is a must, as fluctuations are the norm for renewable energy sources. To this aim, the high scalability and diversity of sources are crucial requirements for the said balancing to be actually manageable. In this study, we explored the challenges and benefits of adopting a blockchain-based software architecture as a scalable, trustless interaction platform between prosumers’ smart energy meters and the distributor. Our developed prototype accomplishes the energy load balancing service via smart contracts deployed in a real blockchain network with an increasing number of simulated prosumers. We show that the blockchain-based application managed to react in a timely manner to energy unbalances for up to a few hundred prosumers. Full article

The growing penetration of electric vehicles (EVs) introduces both opportunities and challenges for power grid operators. Incentivization is considered a viable option to tempt EV owners to participate in supporting the grid during peak load intervals while receiving compensation for their services. Therefore, this study proposes a two-step incentive mechanism to reduce the peak load of the grid by enabling power trading among the microgrid, EVs and the utility grid. In the first step, an incentive price is determined for EVs considering the grid-loading conditions during different hours of the day. In the second step, a multi-objective optimization problem is formulated to optimize trading among different entities, such as EVs, the microgrid and the utility grid. The two objectives considered in this study are the operation cost of the microgrid and the revenue of EVs. Monte Carlo simulations are used to deal with uncertainties associated with EVs. Simulations are conducted to analyze the impact of different weight parameters on the energy-trading amount and operation cost of EVs and MG. In addition, a sensitivity analysis is conducted to analyze the impact of changes in the EV fleet size on the energy-trading amount and operation cost. Full article

The Internet of Things (IoT) is one of the key components of the ICT infrastructure of smart cities due to its great potential for intelligent management of infrastructures and facilities and the enhanced delivery of services in support of sustainable cities. Smart cities typically rely on IoT, where a wide variety of devices communicate with each other and collaborate across heterogeneous and distributed computing environments to provide information and services to urban entities and urbanites. However, leveraging the IoT within software applications raises tremendous challenges, such as data acquisition, device heterogeneity, service management, security and privacy, interoperability, scalability, flexibility, data processing, and visualization. Middleware for IoT has been recognized as the system that can provide the necessary infrastructure of services and has become increasingly important for IoT over the last few years. This study aims to review and synthesize the relevant literature to identify and discuss the core challenges of existing IoT middleware. Furthermore, it augments the information landscape of IoT middleware with big data applications to achieve the required level of services supporting sustainable cities. In doing so, it proposes a novel IoT middleware for smart city applications, namely Generic Middleware for Smart City Applications (GMSCA), which brings together many studies to further capture and invigorate the application demand for sustainable solutions which IoT and big data can offer. The proposed middleware is implemented, and its feasibility is assessed by developing three applications addressing various scenarios. Finally, the GMSCA is tested by conducting load balance and performance tests. The results prove the excellent functioning and usability of the GMSCA. Full article

The performance of vehicular communication technologies changes dynamically according to the application requirements considering data rate, communication ranges, latency, etc. These applications are evolving rapidly and should enhance intelligent transport systems (ITS) such as road safety and automated driving. However, to reach the required quality, these applications need many radio resources to carry the potential traffic load resulting from the environmental perception and data exchanged between the different entities. Therefore, an assessment of vehicular communication technologies’ reliability and resilience under these conditions is required to address the multiple challenges of the ITS services. The paper’s main contribution is to propose a comprehensive analysis model able to evaluate and compare the performances of ITS technologies according to different constraints related to environment-changing situations. This analysis examines the channel occupancy and provides simulation results which allow the identification of the suitable configurations and the most appropriate technology for a given use case. We also propose a coexistence solution between these technologies based on density-sharing according to the use case requirements and the availability of the technology. Finally, we present the challenge of adaptive configuration in vehicular networks, which helps to provide the optimal structure through road profiles and environment variability (infrastructure, data, etc.). Results show different trade offs and limitations between the considered ITS technologies, which are essential to understand their behaviour in a realistic environment. Full article

Network infrastructure sharing and mobile traffic offloading are promising technologies for Heterogeneous Networks (HetNets) to provide energy and cost effective services. In order to decrease the energy requirements and the capital and operational expenditures, Mobile Network Operators (MNOs) and third parties cooperate dynamically with changing roles leading to a novel market model, where innovative challenges are introduced. In this paper, a novel resource sharing and offloading algorithm is introduced based on a double auction mechanism where MNOs and third parties buy and sell capacity and roam their traffic among each other. For low traffic periods, Base Stations (BSs) and Small Cells (SCs) can even be switched off in order to gain even more in energy and cost. Due to the complexity of the scenario, we adopt the multi-objective optimization theory to capture the conflicting interests of the participating entities and we design an iterative double auction algorithm that ensures the efficient operation of the market. Additionally, the selection of the appropriate time periods to apply the proposed algorithm is of great importance. Thus, we propose a machine learning technique for traffic load prediction and for the selection of the most effective time periods to offload traffic and switch off the Base Stations. Analytical and experimental results are presented to assess the performance of the algorithm. Full article

Mobile operators must increase investments in network infrastructures due to the emergent growth of the internet and technological advancements. Mobile operators consider cloud-RAN and software defined networking to be developing technologies that can reduce costs and increase scalability for fifth-generation mobile communication networks (5G). A base station consists of two important components, namely baseband (BBU) and remote radio head (RRH) units. Unbalanced data traffic can arise, leading to call dropping and call blocking. When network traffic conditions start to vary, the performance of the system becomes suboptimal. Self-optimization of the network is necessary to reduce the load of overloaded eNode’s with more call blocking, that increase the load of underloaded eNode’s with less utilization of resources. The main objective of a self-organizing network is to reduce call blocking and optimize an unbalanced network. The proposed algorithm is an enhanced version of the cat swarm optimization algorithm performed by the host manager entity to select the best BBU-RRH combination after analyzing the quality-of-service (QoS) information from the remaining BBU-RRH configurations. Optimization is carried out on each user after a QoS analysis for every new BBU-RRH combination. The proposed algorithm is implemented in Matlab R2020a and evaluation is conducted in terms of blocking probability, response time, and throughput. The simulation results show that the proposed ECSO optimization algorithm reduces blocking probability by 10%, throughput is increased by 8%, and response time is reduced by 7% as compared with the existing PSO and CSO algorithms. Full article

The growth of smart cities is fueled by the vast rise in wireless smart gadgets and uninterrupted connectivity. WiFi is the dominant wireless technology, enabling Internet-of-Things (IoT) connectivity in smart cities due to its ubiquitous access points and low deployment cost. However, smart city applications offer a wide range of services with different quality-of-service (QoS) demands. This paper addresses packet delivery latency as one of the QoS metrics affecting many time-sensitive smart city services. Thus, the paper proposes employing software-defined networking (SDN) to control the traffic load of WiFi access points (APs), preserving its symmetry in a city-wide coverage of WiFi-connected IoT gateways or fog nodes. These gateways receive data packets from smart city/IoT devices via wireless links and forward them over a city-deployed WiFi network to their management entities or servers. Three SDN-based algorithms are devised to reduce the gateways’ packet-forwarding delay and keep a symmetric traffic load at the WiFi network APs. The algorithms are developed and tested using a real hardware setup constituting WiFi devices without additional requirements on the IoT gateways (WiFi clients) or the APs, such as support for a specific roaming protocol or bandwidth-consuming signaling such as sending probe packets. Extensive hardware experimentation shows that the SDN controller, via the proposed algorithms, can effectively reduce the packet forwarding latency of IoT gateways by carefully selecting the IoT gateway with the highest packet latency and seamlessly handing it over to the least-loaded covering AP. Full article

Background: An increasing number of container and chassis staging, “dray-off”, drop yard, and depot facilities are being established outside of North American marine container terminals. The increased use of these “second-tier” facilities implies that there must be some capacity, delivery time, service, or reliability benefit that offset the additional cost and complexity. Methods: This paper builds on the previously developed integrated drayage scheduling model to determine the impact of second-tier port facilities on drayage operation. It modifies the previously developed model by incorporating the following features: (1) trucks do not have to wait at customers’ locations during the import unloading and export loading operations; (2) drayage operations can include a drop yard (i.e., second-tier facility) for picking up or/and dropping off loaded containers outside the marine container terminal; and (3) a customer is allowed to request any of the following jobs: pick up an empty container, pick up a loaded container, drop off an empty container, and drop off a loaded container. Results: The results indicated that by moving the location of import pickup and export delivery from inside the marine container terminal to a location outside the terminal, the efficiency of drayage operation could increase. Additionally, when import pickup and export delivery take place inside the marine container terminal, the most efficient location for the chassis yard and empty container depot is inside the terminal. However, when the location of import pickup and/or export delivery are outside the terminal, the most efficient location for the chassis yard and empty container depot is also outside the terminal. Conclusions: The modeling results suggest that in addition to adding reserved capacity for marine terminals or as buffers to reconcile the preferred delivery times of importers, the second-tier facilities could also yield operational savings. However, the potential drayage efficiencies depend heavily on shorter queuing and turn time at these less-complex facilities compared to marine container terminals. Lastly, the modeling results suggest that the observed evolution of North American marine container terminals from self-contained entities into multi-tier systems is likely to continue to add additional capacities to accommodate container trade growth. This finding has important implications for regions and communities concerned over the impact of growing container ports. Full article

Fog computing is an extension of cloud computing that provides computing services closer to user end-devices at the network edge. One of the challenging topics in fog networks is the placement of tasks on fog nodes to obtain the best performance and resource usage. The process of mapping tasks for resource-constrained devices is known as the service or fog application placement problem (SPP, FAPP). The highly dynamic fog infrastructures with mobile user end-devices and constantly changing fog nodes resources (e.g., battery life, security level) require distributed/decentralized service placement (orchestration) algorithms to ensure better resilience, scalability, and optimal real-time performance. However, recently proposed service placement algorithms rarely support user end-device mobility, constantly changing the resource availability of fog nodes and the ability to recover from fog node failures at the same time. In this article, we propose a distributed agent-based orchestrator model capable of flexible service provisioning in a dynamic fog computing environment by considering the constraints on the central processing unit (CPU), memory, battery level, and security level of fog nodes. Distributing the decision-making to multiple orchestrator fog nodes instead of relying on the mapping of a single central entity helps to spread the load and increase scalability and, most importantly, resilience. The prototype system based on the proposed orchestrator model was implemented and tested with real hardware. The results show that the proposed model is efficient in terms of response latency and computational overhead, which are minimal compared to the placement algorithm itself. The research confirms that the proposed orchestrator approach is suitable for various fog network applications when scalability, mobility, and fault tolerance must be guaranteed. Full article

Dynamic wireless charging (DWC) is a promising technology to charge Electric Vehicles (EV) using on-road charging segments (CS), also known as DWC pads. In order to ensure effective utilization of this on-the-road charging service, communication and coordination need to be established between the EVs and the different network entities, thereby forming an Internet of Electric Vehicles (IoEV). In an IoEV, EVs can utilize different V2X communication modes to enable charging scheduling, load management, and reliable authentication and billing services. Yet, designing an authentication scheme for dynamic EV charging presents significant challenges given the mobility of the EVs and the short contact time between the EVs and the charging segments. Accordingly, this work proposes a fast, secure and lightweight authentication scheme that allows only authentic EVs with valid credentials to charge their batteries while ensuring secure and fair payments. The presented scheme starts with a key pre-distribution phase between the charging service company (CSC) and the charging pad owner (PO), followed by a hash chain and digital signature-based registration and authentication phase between the EV and the CSC, before the EV reaches the beginning of the charging lane. These preliminary authentication phases allow the authentication between the EVs and the charging segments to be performed using simple hash key verification operations prior to charging activation, which reduces the computational cost of the EVs and the CS. Symmetric and asymmetric key cryptography are utilized to secure the communication between the different network entities. Analysis of the computational and transmission time requirements of the proposed authentication scheme shows that, for an EV traveling at 60 km/h to start charging at the beginning of the charging lane, the authentication process must be initiated at least $1.35$ m ahead of the starting point of the lane as it requires ≃81 ms to be completed. Full article

Woody plant encroachment in North American rangelands has led to calls for greater use of prescribed fire to reduce fuel loads and restore grazing productivity and grassland biodiversity. However, the use of prescribed fire during periods when woody plant mortality is maximized has often been limited by temporary restrictions on outdoor burning enacted by regional or local governmental entities. This study reports the results of a survey assessing the familiarity with and attitudes toward prescribed fire in Texas and Oklahoma, USA, of officials tasked with implementing restrictions on outdoor burning and how these attitudes influence their decisions. Most responding officials considered prescribed fire to be a safe and beneficial land management tool that should be used more frequently. Self-reported familiarity with prescribed fire was the most significant explanatory variable for this attitude. Further, familiarity with prescribed fire was influenced by respondent participation in or being invited to participate in a prescribed fire. Such invitations came mostly from private landowners. Landowners wishing to use prescribed fire may benefit from building trust with local officials by demonstrating they are qualified to conduct such fires safely. This could help reduce the frequency of burn restrictions and may increase the likelihood that officials will grant burn ban exemptions to qualified burn managers. Additionally, because officials’ primary sources of prescribed fire information were reported to be local fire departments and emergency services, educating those entities about the benefits of prescribed fire for reducing wildfire risks could help reduce pressure on officials to enact or maintain burning restrictions. These findings highlight opportunities for reducing the frequency of burning restrictions, increasing opportunities for land managers to effectively halt or reverse woody plant encroachment. Full article