Risk Prediction of Digital Human Resource Management Based on Artificial Intelligence

The latest information technologies have greatly accelerated the digitalization progress of Human Resource Management (HRM) and many useful techniques and tools have been developed for that purpose. However, in terms of risk management, effective enough tools and methods are still insufficient. Existing studies generally fail to give a turnkey solution to the operational risks in digital HRM system, and the macro measurement models are not suitable for dealing with the risks in the digital HRM system of each single enterprise. In view of these defects, this paper studied the prediction of risks in digital HRM systems based on Artificial Intelligence (AI). Firstly, the paper outlined the functions of a digital HRM system, defined the risk management mechanism of a HRM system, and built a conceptual model for it. Then, this paper proposed a novel method for predicting the risks in the digital HRM system, which innovatively integrates the digital HRM risk event chains with the risk event graph. After that, the paper elaborated on the structures and building principles of the risk event representation layer, risk event chain module, risk event graph module, and attention fusion module. At last, experimental results verified that the proposed model has obvious advantages in digital HRM risk prediction in terms of both stability and accuracy

WirePlanner: Fast, Secure and Cost-Efficient Route Configuration for SD-WAN

As enterprises increasingly migrate their applications to the cloud, the demand for secure and cost-effective Wide Area Networking (WAN) solutions for data transmission between branches and data centers grows. Among these solutions, Software-Defined Wide Area Networking (SD-WAN) has emerged as a promising approach. However, existing SD-WAN implementations largely rely on IPSec tunnels for data encryption between edge routers, resulting in drawbacks such as extended setup times and limited throughput. Additionally, the SD-WAN control plane rarely takes both latency and monetary cost into consideration when determining routes between nodes, resulting in unsatisfactory Quality of Service (QoS). We propose WirePlanner, an SD-WAN solution that employs a novel algorithm for path discovery, optimizing both latency and cost, and configures WireGuard tunnels for secure and efficient data transmission. WirePlanner considers two payment methods: Pay-As-You-Go, where users pay for a fixed amount of bandwidth over a certain duration, and Pay-For-Data-Transfer, where users pay for the volume of transmitted data. Given an underlay topology of edge routers and a user-defined budget constraint, WirePlanner identifies a path between nodes that minimizes latency and remains within the budget, while utilizing WireGuard for secure data transmission

Analyzing the Impact of Roadmap and Vehicle Features on Electric Vehicles Energy Consumption

Electric Vehicles (EVs) market penetration rate is continuously increasing due to several aspects such as pollution reduction initiatives, government incentives, cost reduction, and fuel cost increase, among others. In the vehicular field, researchers frequently use simulators to validate their proposals before implementing them in real world, while reducing costs and time. In this work, we use our ns-3 network simulator enhanced version to demonstrate the influence of the map layout and the vehicle features on the EVs consumption. In particular, we analyze the estimated consumption of EVs simulating two different scenarios: (i) a segment of the E313 highway, located in the north of Antwerp, Belgium and (ii) the downtown of the city of Antwerp with real vehicle models. According to the results obtained, we demonstrate that the mass of the vehicle is a key factor for energy consumption in urban scenarios, while in contrast, the Air Drag Coefficient (C-d) and the Front Surface Area (FSA) play a critical role in highway environments. The most popular and powerful simulations tools do no present combined features for mobility, realistic map-layouts and electric vehicles consumption. As ns-3 is one of the most used open source based simulators in research, we have enhanced it with a realistic energy consumption feature for electric vehicles, while maintaining its original design and structure, as well as its coding style guides. Our approach allows researchers to perform comprehensive studies including EVs mobility, energy consumption, and communications, while adding a negligible overhead

Efficient and coordinated vertical takeoff of UAV swarms

[EN] As we witness the unrelenting growth of the UAV sector, novel and more sophisticated applications keep emerging every year, with many more in the horizon. Among these, applications that require the adoption of UAV swarms are among the most complex, as deploying swarms requires the interaction and cooperation of all the UAVs involved, which can become quite challenging. In this work we specifically focus on the swarm takeoff procedure for UAVs of the Vertical Take-Off and Landing (VTOL) type, proposing a heuristic that achieves reduced computing overhead while introducing near-optimal assignments of UAV positions in the swarm formation selected. Such heuristic is complemented by an efficient and collision-free takeoff approach that relies on adequate ordering and inter- UAV communications to achieve a sequential phased takeoff. A large number of experiments using our own ArduSim emulation platform, which is totally compatible with real drone code, evidence the improvements achieved in terms of time overhead and safety when compared to both ideal and agnostic approaches.This work was partially supported by the Ministerio de Ciencia, Innovacion y Universidades, Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a los Retos de la Sociedad, Proyectos I+D+I 2018, Spain, under Grant RTI2018-096384-B-I00.Fabra Collado, FJ.; Wubben, J.; Tavares De Araujo Cesariny Calafate, CM.; Cano, J.; Manzoni, P. (2020). Efficient and coordinated vertical takeoff of UAV swarms. IEEE. 1-5. https://doi.org/10.1109/VTC2020-Spring48590.2020.9128488S1

Internet of Unmanned Aerial Vehicles: QoS Provisioning in Aerial Ad-Hoc Networks

Aerial ad-hoc networks have the potential to enable smart services while maintaining communication between the ground system and unmanned aerial vehicles (UAV). Previous research has focused on enabling aerial data-centric smart services while integrating the benefits of aerial objects such as UAVs in hostile and non-hostile environments. Quality of service (QoS) provisioning in UAV-assisted communication is a challenging research theme in aerial ad-hoc networks environments. Literature on aerial ad hoc networks lacks cooperative service-oriented modeling for distributed network environments, relying on costly static base station-oriented centralized network environments. Towards this end, this paper proposes a quality of service provisioning framework for a UAV-assisted aerial ad hoc network environment (QSPU) focusing on reliable aerial communication. The UAV’s aerial mobility and service parameters are modelled considering highly dynamic aerial ad-hoc environments. UAV-centric mobility models are utilized to develop a complete aerial routing framework. A comparative performance evaluation demonstrates the benefits of the proposed aerial communication framework. It is evident that QSPU outperforms the state-of-the-art techniques in terms of a number of service-oriented performance metrics in a UAV-assisted aerial ad-hoc network environment

Providing resilience to UAV swarms following planned missions

As we experience an unprecedented growth in the field of Unmanned Aerial Vehicles (UAVs), more and more applications keep arising due to the combination of low cost and flexibility provided by these flying devices, especially those of the multirrotor type. Within this field, solutions where several UAVs team-up to create a swarm are gaining momentum as they enable to perform more sophisticated tasks, or accelerate task execution compared to the single-UAV alternative. However, advanced solutions based on UAV swarms still lack significant advancements and validation in real environments to facilitate their adoption and deployment. In this paper we take a step ahead in this direction by proposing a solution that improves the resilience of swarm flights, focusing on handling the loss of the swarm leader, which is typically the most critical condition to be faced. Experiments using our UAV emulation tool (ArduSim) evidence the correctness of the protocol under adverse circumstances, and highlight that swarm members are able to seamlessly switch to an alternative leader when necessary, introducing a negligible delay in the process in most cases, while keeping this delay within a few seconds even in worst-case conditions

Unmanned aerial vehicles optimal airtime estimation for energy aware deployment in IoT-enabled fifth generation cellular networks

[EN] Cellular networks based on new generation standards are the major enabler for Internet of things (IoT) communication. Narrowband-IoT and Long Term Evolution for Machines are the newest wide area network-based cellular technologies for IoT applications. The deployment of unmanned aerial vehicles (UAVs) has gained the popularity in cellular networks by using temporary ubiquitous coverage in the areas where the infrastructure-based networks are either not available or have vanished due to some disasters. The major challenge in such networks is the efficient UAVs deployment that covers maximum users and area with the minimum number of UAVs. The performance and sustainability of UAVs is largely dependent upon the available residual energy especially in mission planning. Although energy harvesting techniques and efficient storage units are available, but these have their own constraints and the limited onboard energy still severely hinders the practical realization of UAVs. This paper employs neglected parameters of UAVs energy consumption in order to get actual status of available energy and proposed a solution that more accurately estimates the UAVs operational airtime. The proposed model is evaluated in test bed and simulation environment where the results show the consideration of such explicit usage parameters achieves significant improvement in airtime estimation.The research is funded by the Department of Computer Science, Iqra University, Islamabad Campus, PakistanMajeed, S.; Sohail, A.; Qureshi, KN.; Kumar, A.; Iqbal, S.; Lloret, J. (2020). Unmanned aerial vehicles optimal airtime estimation for energy aware deployment in IoT-enabled fifth generation cellular networks. EURASIP Journal on Wireless Communications and Networking. 2020(1):1-14. https://doi.org/10.1186/s13638-020-01877-01142020

Engineering Semantic Self-composition of Services Through Tuple-Based Coordination

Service self-composition is a well-understood research area focusing on service-based applications providing new services by automatically combining pre-existing ones. In this paper we focus on tuple-based coordination, and propose a solution leveraging logic tuples and tuple spaces to support semantic self-composition for services. A full-stack description of the solution is provided, ranging from a theoretical formalisation to a technologically valuable design and implementation

Designing security-aware service requests for NFV-enabled networks

International audienceNetwork Function Virtualization (NFV) is a new concept where virtualization is used to shift "network functions" (e.g., routers, switches, load-balancers, proxies) from specialized hardware appliances to software images running on high volume servers. The resource allocation problem in the NFV environment has received considerable attention in the past years. However, little attention was paid to the security aspects of the problem in spite of the increasing number of vulnerabilities faced by cloud-based applications. Securing the services is an urgent need to completely benefit from the advantages offered by NFV. In this paper, we show how a network service request, composed of a set of service function chains (SFC) should be modified and enriched to take into consideration the security requirements of the supported service. We examine the well-known security best practices and propose a two-step algorithm that extends the initial SFC requests to a more complex chaining model that includes the security requirements of the service

Three Dimensional UAV Positioning for Dynamic UAV-to-Car Communications

[EN] In areas with limited infrastructure, Unmanned Aerial Vehicles (UAVs) can come in handy as relays for car-to-car communications. Since UAVs are able to fully explore a three-dimensional environment while flying, communications that involve them can be affected by the irregularity of the terrains, that in turn can cause path loss by acting as obstacles. Accounting for this phenomenon, we propose a UAV positioning technique that relies on optimization algorithms to improve the support for vehicular communications. Simulation results show that the best position of the UAV can be timely determined considering the dynamic movement of the cars. Our technique takes into account the current flight altitude, the position of the cars on the ground, and the existing flight restrictions.This work was partially supported by the Ministerio de Ciencia, Innovación y Universidades, Programa Estatal de Investigación, Desarrollo e Innovación Orientada a los Retos de la Sociedad, Proyectos I+D+I 2018 , Spain, under Grant RTI2018-096384-B-I00, and grant BES-2015-075988, Ayudas para contratos predoctorales 2015.Hadiwardoyo, SA.; Tavares De Araujo Cesariny Calafate, CM.; Cano, J.; Krinkin, K.; Klionskiy, D.; Hernández-Orallo, E.; Manzoni, P. (2020). Three Dimensional UAV Positioning for Dynamic UAV-to-Car Communications. Sensors. 20(2):1-18. https://doi.org/10.3390/s20020356S11820