Internet of Things-aided Smart Grid: Technologies, Architectures, Applications, Prototypes, and Future Research Directions

Traditional power grids are being transformed into Smart Grids (SGs) to address the issues in existing power system due to uni-directional information flow, energy wastage, growing energy demand, reliability and security. SGs offer bi-directional energy flow between service providers and consumers, involving power generation, transmission, distribution and utilization systems. SGs employ various devices for the monitoring, analysis and control of the grid, deployed at power plants, distribution centers and in consumers' premises in a very large number. Hence, an SG requires connectivity, automation and the tracking of such devices. This is achieved with the help of Internet of Things (IoT). IoT helps SG systems to support various network functions throughout the generation, transmission, distribution and consumption of energy by incorporating IoT devices (such as sensors, actuators and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, we provide a comprehensive survey on IoT-aided SG systems, which includes the existing architectures, applications and prototypes of IoT-aided SG systems. This survey also highlights the open issues, challenges and future research directions for IoT-aided SG systems

Career Development an Imperative of Job Satisfaction and Career Commitment: Empirical Evidence from Pakistani Employees in Banking Sector

The idea of strengthening human capital to beginning creativeness, business soul, and advancement through preparing the careers of institutional members using HRM policies and methods to develop different skills, mindsets and expertise with the ultimate aim to provide a range of innovative goods and services is gaining attention. The overall perspective for the research study was to discover the effects and outcomes of profession growth initiatives on companies and employees. The survey is conducted to collect data from the Banking sector in Islamabad and sample selected is of five major private banks. The data is analyzed by using SPSS and Amos to authenticate the model and propositions made by the researcher. Organizations invest resources in profession growth kinds of actions for recruiting, there tends to be less investment in similar kinds of actions for worker retention. This paper examines the link between profession preparing and profession control as antecedents of profession growth and job fulfillment, and profession dedication as its outcome. There is a significant link between the factors of profession preparing and profession control, and profession growth, and in turn, with job fulfillment and profession dedication. The paper converses about the significances of these conclusions for career development

Lamento antecipado e norma moral na intenção dos consumidores de selecionar restaurantes de trabalho infantil: aumentando a teoria do comportamento planejado

Child labor is very severe social obstacle of the world of under develop nations like Pakistan. Still most of the young children are working in different sectors for the livelihood of their homes. This study explore the anticipated regret and moral norm in consumers’ intention to select child labor restaurants with the uses of augmenting the theory of planned behavior. Present study carried out in the five districts of south Punjab, Pakistan. There are three hundred questionnaires is filled from the owners of the restaurants from the selected regions. SPSS is used for the analysis of the data and multiple regression is used for testing the hypothesis. The results showed that theory of planned behavior constructs are significantly influence the intention of the child. Many owners took child as a labor because its cheap. While augmenting version of the planned behavior theory also good predictor of the child labor intentions. Government and NGOs take some actions to eliminate the child labor and sent into the schools.El trabajo infantil es un obstáculo social muy severo en el mundo de las naciones subdesarrolladas como Pakistán. Aún así, la mayoría de los niños pequeños están trabajando en diferentes sectores para el sustento de sus hogares. Este estudio explora el arrepentimiento anticipado y la norma moral en la intención de los consumidores de seleccionar restaurantes de trabajo infantil con el fin de aumentar la teoría del comportamiento planificado. Estudio actual realizado en los cinco distritos del sur de Punjab, Pakistán. Hay trescientos cuestionarios llenados por los propietarios de los restaurantes de las regiones seleccionadas. SPSS se utiliza para el análisis de los datos y la regresión múltiple se utiliza para probar la hipótesis. Los resultados mostraron que la teoría de los comportamientos planificados influye significativamente en la intención del niño. Muchos dueños tomaron al niño como mano de obra porque es barato. Si bien la versión aumentada de la teoría de la conducta planificada también es un buen predictor de las intenciones del trabajo infantil. El gobierno y las ONG toman algunas medidas para eliminar el trabajo infantil y las envían a las escuelas.O trabalho infantil é um obstáculo social muito grave do mundo dos países em desenvolvimento, como o Paquistão. Ainda a maioria das crianças jovens estão trabalhando em diferentes setores para o sustento de suas casas. Este estudo explora o lamento antecipado e a norma moral na intenção dos consumidores de selecionar restaurantes de trabalho infantil com o objetivo de aumentar a teoria do comportamento planejado. Presente estudo realizado nos cinco distritos do sul de Punjab, Paquistão. Existem trezentos questionários preenchidos pelos proprietários dos restaurantes das regiões selecionadas. O SPSS é usado para a análise dos dados e a regressão múltipla é usada para testar a hipótese. Os resultados mostraram que a teoria dos construtos de comportamento planejados influencia significativamente a intenção da criança. Muitos proprietários levaram criança como um trabalho de parto porque é barato. Enquanto aumenta a versão da teoria do comportamento planejado também bom preditor das intenções de trabalho infantil. O governo e as ONGs tomam algumas medidas para eliminar o trabalho infantil e enviá-las para as escolas

Flow-Based Rules Generation for Intrusion Detection System using Machine Learning Approach

Rapid increase in internet users also brought new ways of privacy and security exploitation. Intrusion is one of such attacks in which an authorized user can access system resources and is major concern for cyber security community. Although AV and firewall companies work hard to cope with this kind of attacks and generate signatures for such exploits but still, they are lagging behind badly in this race. This research proposes an approach to ease the task of rules generationby making use of machine learning for this purpose. We used 17 network features to train a random forest classifier and this trained classifier is then translated into rules which can easily be integrated with most commonly used firewalls like snort and suricata etc. This work targets five kind of attacks: brute force, denial of service, HTTP DoS, infiltrate from inside and SSH brute force. Separate rules are generated for each kind of attack. As not every generated rule contributes toward detection that's why an evaluation mechanism is also used which selects the best rule on the basis of precision and f-measure values. Generated rules for some attacks have 100% precision with detection rate of more than 99% which represents effectiveness of this approach on traditional firewalls. As our proposed system translates trained classifier model into set of rules for firewalls so it is not only effective for rules generation but also give machine learning characteristics to traditional firewall to some extent.&nbsp

QoS-aware Data Offloading for Vehicular Networks

International audienceLes réseaux véhiculaireséchangent divers types de données qui doiventêtre transmises vers les Road Side Units (RSU) depuis directement depuis les véhiculesà portée de communication. Les RSU n'étant pas déployés partout, on observe une connectivité intermittente des véhicules avec les RSU. Dans cet article, nous proposons un schéma d'envoi des données pour les réseaux de véhicules avec QoS (DOVEQ), qui permetà un véhicule de transmettre ses données vers un RSU directement ou via des communications inter véhicules (V2V). DOVEQ prend en compte le temps de connexion d'un véhicule avec le RSU et les autres véhicules se dirigeant dans la même direction ou la direction opposée, la capacité d'envoi et le temps prévu pour atteindre la zone de couverture d'un RSU. De plus, la qualité de service (QoS) est une considération importante pour la transmission de données dans les réseaux de véhicules en raison de l'existence de données urgentes (par exemple, des données d'accident ou d'urgence). Par conséquent, pour respecter un niveau de qualité de service, DOVEQ utilise trois fonctions de qualité de service : classification du trafic, contrôle de surcharge et contrôle d'admission. L'évaluation des performances dans le simulateur de réseau OMNeT++ avec les frameworks Veins et SUMO montre l'efficacité de DOVEQ

A QoS-Aware Hybrid V2I and V2V Data Offloading for Vehicular Networks

International audienceIn vehicular networks, RoadSide Units (RSUs) are not available everywhere, therefore, it is not possible for vehicles to stay connected with RSUs all the time and to send their data directly to RSUs anytime using Vehicle-to-Infrastructure (V2I) data offloading. Hence, in these cases, Vehicle-to-Vehicle (V2V) communications are used to offload data to RSUs through other vehicles. Data to offload could be urgent (e.g., accident data), therefore, it is important to consider the Quality of Service (QoS) provisioning. In this paper, we propose a QoS-aware data offloading scheme for vehicular networks with QoS provisioning (DOVEQ) that considers both V2I and V2V data offloading. DOVEQ models the connectivity of vehicles with RSUs and vehicles, offloading capacity and estimation of reaching RSUs. It provides QoS using traffic classification, overload control and admission control. The performance evaluation of DOVEQ shows that DOVEQ outperforms other schemes by offloading more amount of important data with lesser offloading delay and running time

DIVINE: Data Offloading In Vehicular Networks with QoS Provisioning

International audienceIn vehicular networks, vehicles may carry various types of data that need to be offloaded to the RoadSide Units (RSUs) through Vehicle-to-Infrastructure (V2I) communications when vehicles come into their coverage. RSUs are not widely deployed everywhere, which causes intermittent connectivity between vehicles and RSUs. In this paper, we propose DIVINE, a Data offloading In VehIcular NEtworks scheme with QoS provisioning, which enables a vehicle to offload its data to RSU directly through V2I communications or using other neighboring vehicles through Vehicle-to-Vehicle (V2V) communications. DIVINE considers the connectivity time of an offloading vehicle with the RSU, with other vehicles heading either on the same or opposite direction, offloading capacity, expected time to reach RSU and contact duration with neighboring vehicles. Additionally, the Quality of Service (QoS) is an important consideration for data offloading in vehicular networks due to the coexistence of urgent data to offload (e.g., accident or emergency data). Therefore, for QoS provisioning, DIVINE uses three QoS functions: traffic classification, overload control and admission control. DIVINE is presented with algorithms and procedures, as well as with illustrative examples. The performance evaluation in network simulator OMNeT++ with Veins and SUMO frameworks shows that DIVINE outperforms other schemes in terms of average offloading delay, maximum offloading delay and running time for a varying number of vehicles, maximum speed values, number of RSUs and RSUs' capacity. It also best behaves in terms of amount of offloaded important data

A Vehicle-to-Infrastructure Data Offloading Scheme for Vehicular Networks with QoS Provisioning

International audienceIn vehicular networks, vehicles carry various types of data that need to be offloaded to the RoadSide Units (RSUs) through Vehicle-to-Infrastructure (V2I) communications when vehicles come into their coverage. Since, RSUs are not widely deployed, vehicles have intermittent connectivity with RSUs. The data that vehicles carry to offload could be urgent data (such as accident data of nearby incident or emergency health data) that needs to be offloaded to the RSUs as soon as possible. Therefore, the consideration of Quality of Service (QoS) provisioning is imperative for data offloading in vehicular networks. In this paper, we propose V2I-Q, a V2I data offloading scheme with QoS provisioning by using three QoS functions: traffic classification, overload control and admission control. Traffic classification organizes the data into three priorities: high, medium and low. Overload control avoids overloading the RSUs to enable it to receive high priority data as soon as possible. Admission control allows RSUs to stop servicing existing vehicles offloading low priority data in order to receive high priority data from other vehicles. The performance evaluation shows that V2I-Q is able to offload more high priority data by incurring lower maximum offloading delay as compared to the traditional V2I data offloading schemes

Development of a Powerful Product: Evidence from Pakistan

The development of a powerful product and the deliverance of recognized support quality are premised by staff's capability to provide on client objectives. No concern has been given, however, to knowing the ‘added value’ exemplified in an organization’s product due to the operant sources (skills and knowledge) provided by the organization’s individual investment. This research, therefore, examines the differential impact that internal focused projects have on an organization’s individual investment and its following impact on the organization’s product, from the worker's viewpoint. In-depth discussions were performed with workers across a variety of support sectors and the results provide a knowing into the development of worker product dedication. Furthermore, this empirical research provides a powerful foundation for upcoming research in this region. Keywords: employees, brand commitment, internal brandin

SMART: A SpectruM-Aware clusteR-based rouTing scheme for distributed cognitive radio networks

Cognitive radio (CR) is the next-generation wireless communication system that allows unlicensed users (or secondary users, SUs) to exploit the underutilized spectrum (or white spaces) in licensed spectrum while minimizing interference to licensed users (or primary users, PUs). This article proposes a SpectruM-Aware clusteR-based rouTing (SMART) scheme that enables SUs to form clusters in a cognitive radio network (CRN) and enables each SU source node to search for a route to its destination node on the clustered network. An intrinsic characteristic of CRNs is the dynamicity of operating environment in which network conditions (i.e., PUs’ activities) change as time goes by. Based on the network conditions, SMART enables SUs to adjust the number of common channels in a cluster through cluster merging and splitting, and searches for a route on the clustered network using an artificial intelligence approach called reinforcement learning. Simulation results show that SMART selects stable routes and significantly reduces interference to PUs, as well as routing overhead in terms of route discovery frequency, without significant degradation of throughput and end-to-end delay