Future Internet, Volume 11, Issue 6 (June 2019) – 20 articles

The emerging connected and autonomous vehicles (CAVs) challenge ad hoc wireless multi-hop communications by mobility, large-scale, new data acquisition and computing patterns. The Named Data Networking (NDN) is suitable for such vehicle ad hoc networks due to its information centric networking approach. However, flooding interest packets in ad-hoc NDN can lead to broadcast storm issue. Existing solutions will either increase the number of redundant interest packets or need a global knowledge about data producers. In this paper, a Location-Based Deferred Broadcast (LBDB) scheme is introduced to improve the efficiency and performance of interest broadcast in ad-hoc NDN. The scheme takes advantage of location information to set up timers when rebroadcasting an interest. The LBDB is implemented in V-NDN network architecture using ndnSIM simulator. Comparisons with several existing protocols are conducted in simulation. The results show that LBDB improves the overhead, the average number of hops and delay while maintaining an average satisfaction ratio when compared with several other broadcast schemes. The improvement can help offer timely data acquisition for quick responses in emergent CAV application situations. Full article

Set-valued database publication has been increasing its importance recently due to its benefit for various applications such as marketing analysis and advertising. However, publishing a raw set-valued database may cause individual privacy breach such as the leakage of sensitive information like personal tendencies when data recipients perform data analysis. Even though imposing data anonymization methods such as suppression-based methods and random data swapping methods to such a database can successfully hide personal tendency, it induces item loss from records and causes significant distortion in record structure that degrades database utility. To avoid the problems, we proposed a method based on swapping technique where an individual’s items in a record are swapped to items of the other record. Our swapping technique is distinct from existing one called random data swapping which yields much structure distortion. Even though the technique results in inaccuracy at a record level, it can preserve every single item in a database from loss. Thus, data recipients may obtain all the item information in an anonymized database. In addition, by carefully selecting a pair of records for item swapping, we can avoid excessive record structure distortion that leads to alter database content immensely. More importantly, such a strategy allows one to successfully hide personal tendency without sacrificing a lot of database utility. Full article

Social network service (SNS) information has benefited many individuals. However, as such information has increased exponentially, the number of SNS users has increased dramatically and negative effects of SNSs on users have emerged. Many SNS users experience negative psychological conditions such as fatigue, burnout, and stress. Thus, in this study, we investigated the SNS and user characteristics that affect SNS fatigue, living disorder, and reduced SNS use intention. We developed a research model to examine the impact of two SNS characteristics (irrelevant information overload and open reachability) and two user characteristics (engagement and maintaining self-reputation) on SNS fatigue. We also examined the role of the experience of privacy violations in the relationship between living disorder and reduced SNS use intention. We collected data from 579 SNS users and created a partial least squares structural equation model to test the hypotheses. The results of the analysis showed that three factors, other than open reachability, positively affected SNS fatigue. Furthermore, we found that SNS fatigue significantly affected living disorder and reduced SNS use intention, and that experience of privacy violations significantly affected the relationship between living disorder and reduced SNS use intention. These results expand our understanding of SNS fatigue and users’ negative behaviors. Full article

Electronic purchasing or e-procurement saves millions of dollars yearly in transaction costs. E-procurement helps to cut down the supplier base, promotes paperless transactions, and increases transparency and accountability in the procurement process. Nonetheless, studies report that around 80% of e-procurement initiatives have met with failure and failed to achieve the desired results. Although studies to better understand the Critical Success Factors (CSFs) of e-procurement implementation involving various industries have been on the rise, little is known about architecture engineering and construction (AEC) practices, which has led to limited development of pragmatic frameworks to uncover the factors. Thus, this study aims to identify those CSFs (predicting variables) which significantly contribute to e-procurement implementation success in the construction sector and to put forward for better implementation. Results from multiple regression analysis revealed five factors to be statistically significant predictors of success. Three factors were determined to be predictors of user satisfaction. Finally, internet online procurement frameworks were developed for the success of e-procurement implementation in the construction sector. Full article

This is a study of the way in which YouTubers’ media metrics influence the effect of their one-sided messages (1SMs) and two-sided messages (2SMs), providing theoretical explanations based on the elaboration likelihood model. Its main objective is the proposition and testing of: (i) the interaction effect between type of message and media metrics of the YouTuber on customers’ responses, and (ii) the moderation of individuals’ conformity intention for the interaction effect between type of message and media metrics on customers’ responses. The results of an experiment showed that high YouTubers’ media metrics have more effect for 1SMs and less effect for 2SMs. Additionally, conformity intention moderates the effect of the interaction type of message X media metrics. A high level of conformity intention neutralizes the interaction effect between YouTubers’ media metrics and message sidedness. This study makes a theoretical contribution to research into online content and information use, providing explanations of how media metrics of a vlog influence the effect of two types of messages. Full article

This study develops a contingent mediation model to investigate whether user perception enhances customer stickiness through emotional connection and further assess such mediating effect varies with different adaptivity. A moderated mediation approach is adopted to test the hypotheses. Findings reveal the mediating role of emotional connection on the link between perceived usefulness and customer stickiness, but not moderated by adaptivity. On the other hand, the results showed that the relationship between perceived ease of use and customer stickiness is not mediated by emotional connection; however, after considering the moderating effect, our results show that moderated mediation exists. Full article

Software-defined networking (SDN) is an innovative architecture that designs a logical controller to manage and program the network based on the global view, providing more efficient management, better performance, and higher flexibility for the network. Therefore, applying the SDN concept in a multi-hop wireless network (MWN) has been proposed and extensively studied to overcome the challenges of MWN. In this paper, we propose an energy-efficient global routing algorithm for a software-defined multi-hop wireless network (SDMWN), which is able to get transmission paths for several users at the same time to minimize the global energy consumption with the premise of satisfying the QoS required by users. To this end, we firstly propose a Lagrange relaxation-based aggregated cost (LARAC) and K-Dijkstra combined algorithm to get the top K energy-minimum paths that satisfy the QoS in polynomial time. Then, we combine the alternative paths of each user obtained by K-LARAC and propose an improved genetic algorithm to solve the global routing strategy. The simulation results show that the proposed K-LARAC and genetic algorithm combined method has the ability to obtain an approximate optimal solution with lower time cost. Full article

Next Generation Internet (NGI) is the European initiative launched to identify the future internet technologies, designed to serve the needs of the digitalized society while ensuring privacy, trust, decentralization, openness, inclusion, and business cooperation. NGI provides efficient support to promote diversity, decentralization and the growth of disruptive innovation envisioned by smart cities. After the earthquake of 6 April 2009, the city of L’Aquila is facing a massive and innovative reconstruction process. As a consequence, nowadays, the L’Aquila city can be considered as a living laboratory model for applications within the context of smart cities. This paper describes and evaluates the realization of a Collaborative Road Mobility System (CRMS) for L’Aquila city by using our CHOReVOLUTION approach for the automated choreography production. The CRMS allows vehicles and transport infrastructure to interconnect, share information and use it to coordinate their actions. Full article

Next generation 5G networks generate a need for broadband, low latency and power efficient backhauling and data-relay services. In this paper, optical satellite communications links, as an integrated component of 5G networks, are studied. More specifically, the Geostationary (GEO) satellite-to-ground optical communication link is investigated. Long-term irradiance statistics based on experimental measurements from the ARTEMIS program are presented and a new time series generator related to the received irradiance/power fluctuations due to atmospheric turbulence is reported. The proposed synthesizer takes into consideration the turbulence-induced scintillation effects that deteriorate the laser beam propagation, on the assumption of the Kolmogorov spectrum. The modeling is based on Rytov theory regarding weak turbulence conditions with the incorporation of first order stochastic differential equations. Summing up, the time series synthesizer is validated in terms of first and second order statistics with experimental results from the European Space Agency‘s ARTEMIS experimental optical downlink and simulated received power statistics for various weather conditions are presented using the proposed validated methodology. Some important conclusions are drawn. Full article

Currently, the digital economy contributes decisively to an increase in competitiveness, especially as a digital transformation involves migrating to new technological models where digital marketing is a key part of growth and user loyalty strategies. Internet and Digital Marketing have become important factors in campaigns, which attract and retain Internet users. This study aims to identify the main ways in which users can be gained and retained by using Digital Marketing. The Delphi method with in-depth interviews was the methodology used in this study. The results of the research show the most important actions for achieving user recruitment and loyalty with Digital Marketing from the opinions of consulted experts. The limitations of this study are those related to the number of experts included in the study, and the number of research papers consulted in the literature review. The literature review and the results of this research are used to propose new solid research with a consolidated critical methodology. This research deals with a new approach that will optimize web technologies for the evolution of user trends, and therefore, will be of academic and professional use for marketing managers and web solution developers. The conclusions of the investigation show the key factors, discarding others that do not affect the optimization of conversions in B2C businesses such as the duration of the session and the rebound percentage. Likewise, the results of the research identify the specific actions that must be carried out to attract and retain users in B2C companies that use the Digital Marketing ecosystem on the Internet. The requirements for companies that wish to implement a model to optimize conversions using the current digital economy are also shown. Full article

Internet of Things (IoT) systems have seen recent growth in popularity for city and home environments. We report on the design, deployment, and use of the IoT infrastructure for environmental monitoring and management. Working closely with hydrologists, soil scientists, and animal behaviour scientists, we successfully deployed and utilised a system to deliver integrated information across these two fields in the first such example of real-time multidimensional environmental science. We describe the design of this system; its requirements and operational effectiveness for hydrological, soil, and ethological scientists; and our experiences from building, maintaining, and using the deployment at a remote site in difficult conditions. Based on this experience, we discuss key future work for the IoT community when working in these kinds of environmental deployments. Full article

Vehicular ad hoc networks (VANETs) are a recent class of peer-to-peer wireless networks that are used to organize the communication and interaction between cars (V2V), between cars and infrastructure (V2I), and between cars and other types of nodes (V2X). These networks are based on the dedicated short-range communication (DSRC) IEEE 802.11 standards and are mainly intended to organize the exchange of various types of messages, mainly emergency ones, to prevent road accidents, alert when a road accident occurs, or control the priority of the roadway. Initially, it was assumed that cars would only interact with each other, but later, with the advent of the concept of the Internet of things (IoT), interactions with surrounding devices became a demand. However, there are many challenges associated with the interaction of vehicles and the interaction with the road infrastructure. Among the main challenge is the high density and the dramatic increase of the vehicles’ traffic. To this end, this work provides a novel system based on mobile edge computing (MEC) to solve the problem of high traffic density and provides and offloading path to vehicle’s traffic. The proposed system also reduces the total latency of data communicated between vehicles and stationary roadside units (RSUs). Moreover, a latency-aware offloading algorithm is developed for managing and controlling data offloading from vehicles to edge servers. The system was simulated over a reliable environment for performance evaluation, and a real experiment was conducted to validate the proposed system and the developed offloading method. Full article

The Internet of Things (IoT) is rapidly changing our society to a world where every “thing” is connected to the Internet, making computing pervasive like never before. This tsunami of connectivity and data collection relies more and more on the Cloud, where data analytics and intelligence actually reside. Cloud computing has indeed revolutionized the way computational resources and services can be used and accessed, implementing the concept of utility computing whose advantages are undeniable for every business. However, despite the benefits in terms of flexibility, economic savings, and support of new services, its widespread adoption is hindered by the security issues arising with its usage. From a security perspective, the technological revolution introduced by IoT and Cloud computing can represent a disaster, as each object might become inherently remotely hackable and, as a consequence, controllable by malicious actors. While the literature mostly focuses on the security of IoT and Cloud computing as separate entities, in this article we provide an up-to-date and well-structured survey of the security issues of cloud computing in the IoT era. We give a clear picture of where security issues occur and what their potential impact is. As a result, we claim that it is not enough to secure IoT devices, as cyber-storms come from Clouds. Full article

Industrial Automation and Control Systems (IACS) are broadly utilized in critical infrastructures for monitoring and controlling the industrial processes remotely. The real-time transmissions in such systems provoke security breaches. Many security breaches have been reported impacting society severely. Hence, it is essential to achieve secure communication between the devices for creating a secure environment. For this to be effective, the keys used for secure communication must be protected against unauthorized disclosure, misuse, alteration or loss, which can be taken care of by a Key Management Infrastructure. In this paper, by considering the generic industrial automation network, a comprehensive key management infrastructure (CKMI) is designed for IACS. To design such an infrastructure, the proposed scheme employs ECDH, matrix method, and polynomial crypto mechanisms. The proposed design handles all the standard key management operations, viz. key generation, device registration, key establishment, key storage, device addition, key revocation, key update, key recovery, key archival, and key de-registration and destruction. The design supports secure communication between the same and different levels of IACS devices. The proposed design can be applied for major industrial automation networks to handle the key management operations. The performance analysis and implementation results highlight the benefits of the proposed design. Full article

Telco content delivery networks (CDNs) have envisioned building highly distributed and cloudified sites to provide a high-quality CDN service in the 5G era. However, there are still two open problems to be addressed. First, telco CDNs are operated upon the underlay network evolving towards information-centric networking (ICN). Different from CDNs that perform on the application layer, ICN enables information-centric forwarding to the network layer. Thus, it is challenging to take advantage of the benefits of both ICN and CDN to provide a high-quality content delivery service in the context of ICN-based telco CDNs. Second, bandwidth pricing and request mapping issues in ICN-based telco CDNs have not been thoroughly studied. In this paper, we first propose an ICN-based telco CDN framework that integrates the information-centric forwarding enabled by ICN and the powerful edge caching enabled by telco CDNs. Then, we propose a location-dependent pricing (LDP) strategy, taking into consideration the congestion level of different sites. Furthermore, on the basis of LDP, we formulate a price-aware request mapping (PARM) problem, which can be solved by existing linear programming solvers. Finally, we conduct extensive simulations to evaluate the effectiveness of our design. Full article

One of the main drawbacks of Global Navigation Satellite Sytems (GNSS) is that they do not work indoors. When inside, there is often no direct line from the satellite signals to the device and the ultra high frequency (UHF) used is blocked by thick, solid materials such as brick, metal, stone or wood. In this paper, we describe a solution based on the Long Range Wide Area Network (LoRaWAN) technology to geolocalise vehicles indoors. Through estimation of the behaviour of a LoRaWAN channel and using trilateration, the localisation of a vehicle can be obtained within a 20–30 m range. Indoor geolocation for Intelligent Transporation Systems (ITS) can be used to locate vehicles of any type in underground parkings, keep a platoon of trucks in formation or create geo-fences, that is, sending an alert if an object moves outside a defined area, like a bicycle being stolen. Routing of heavy vehicles within an industrial setting is another possibility. Full article

Vehicle speed estimation is an important problem in traffic surveillance. Many existing approaches to this problem are based on camera calibration. Two shortcomings exist for camera calibration-based methods. First, camera calibration methods are sensitive to the environment, which means the accuracy of the results are compromised in some situations where the environmental condition is not satisfied. Furthermore, camera calibration-based methods rely on vehicle trajectories acquired by a two-stage tracking and detection process. In an effort to overcome these shortcomings, we propose an alternate end-to-end method based on 3-dimensional convolutional networks (3D ConvNets). The proposed method bases average vehicle speed estimation on information from video footage. Our methods are characterized by the following three features. First, we use non-local blocks in our model to better capture spatial–temporal long-range dependency. Second, we use optical flow as an input in the model. Optical flow includes the information on the speed and direction of pixel motion in an image. Third, we construct a multi-scale convolutional network. This network extracts information on various characteristics of vehicles in motion. The proposed method showcases promising experimental results on commonly used dataset with mean absolute error (MAE) as $2.71$ km/h and mean square error (MSE) as $14.62$ . Full article

The revolution of cooperative connected and automated vehicles is about to begin and a key milestone is the introduction of short range wireless communications between cars. Given the tremendous expected market growth, two different technologies have been standardized by international companies and consortia, namely IEEE 802.11p, out for nearly a decade, and short range cellular-vehicle-to-anything (C-V2X), of recent definition. In both cases, evolutions are under discussion. The former is only decentralized and based on a sensing before transmitting access, while the latter is based on orthogonal resources that can be also managed by an infrastructure. Although studies have been conducted to highlight advantages and drawbacks of both, doubts still remain. In this work, with a reference to the literature and the aid of large scale simulations in realistic urban and highway scenarios, we provide an insight in such a comparison, also trying to isolate the contribution of the physical and medium access control layers. Full article

Volunteer computing (VC) is a distributed computing paradigm, which provides unlimited computing resources in the form of donated idle resources for many large-scale scientific computing applications. Task scheduling is one of the most challenging problems in VC. Although, dynamic scheduling problem with deadline constraint has been extensively studied in prior studies in the heterogeneous system, such as cloud computing and clusters, these algorithms can’t be fully applied to VC. This is because volunteer nodes can get offline whenever they want without taking any responsibility, which is different from other distributed computing. For this situation, this paper proposes a dynamic task scheduling algorithm for heterogeneous VC with deadline constraint, called deadline preference dispatch scheduling (DPDS). The DPDS algorithm selects tasks with the nearest deadline each time and assigns them to volunteer nodes (VN), which solves the dynamic task scheduling problem with deadline constraint. To make full use of resources and maximize the number of completed tasks before the deadline constraint, on the basis of the DPDS algorithm, improved dispatch constraint scheduling (IDCS) is further proposed. To verify our algorithms, we conducted experiments, and the results show that the proposed algorithms can effectively solve the dynamic task assignment problem with deadline constraint in VC. Full article