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Currently, the use of biosensor-enabled mobile healthcare workflow applications in mobile edge-cloud-enabled systems is increasing progressively. These applications are heavyweight and divided between a thin client mobile device and a thick server edge cloud for execution. Application partitioning is a mechanism in which applications are divided based on resource and energy parameters. However, existing application-partitioning schemes widely ignore security aspects for healthcare applications. This study devises a dynamic application-partitioning workload task-scheduling-secure (DAPWTS) algorithm framework that consists of different schemes, such as min-cut algorithm, searching node, energy-enabled scheduling, failure scheduling, and security schemes. The goal is to minimize the energy consumption of nodes and divide the application between local nodes and edge nodes by applying the secure min-cut algorithm. Furthermore, the study devises the secure-min-cut algorithm, which aims to migrate data between nodes in a secure form during application partitioning in the system. After partitioning the applications, the node-search algorithm searches optimally to run applications under their deadlines. The energy and failure schemes maintain the energy consumption of the nodes and the failure of the system. Simulation results show that DAPWTS outperforms existing baseline approaches by 30% in terms of energy consumption, deadline, and failure of applications in the system., This work is financially supported by the Research grant of PIFI 2020 (2020VBC0002), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences (SIAT,CAS), Shenzhen, China. Also, this work is partially supported by Chiang Mai University and the college of arts, mediaand technology.

These days, with the emerging developments in wireless communication technologies, such as 6G and 5G and the Internet of Things (IoT) sensors, the usage of E-Transport applications has been increasing progressively. These applications are E-Bus, E-Taxi, self-autonomous car, E-Train and E-Ambulance, and latency-sensitive workloads executed in the distributed cloud network. Nonetheless, many delays present in cloudlet-based cloud networks, such as communication delay, round-trip delay and migration during the workload in the cloudlet-based cloud network. However, the distributed execution of workloads at different computing nodes during the assignment is a challenging task. This paper proposes a novel Multi-layer Latency (e.g., communication delay, round-trip delay and migration delay) Aware Workload Assignment Strategy (MLAWAS) to allocate the workload of E-Transport applications into optimal computing nodes. MLAWAS consists of different components, such as the Q-Learning aware assignment and the Iterative method, which distribute workload in a dynamic environment where runtime changes of overloading and overheating remain controlled. The migration of workload and VM migration are also part of MLAWAS. The goal is to minimize the average response time of applications. Simulation results demonstrate that MLAWAS earns the minimum average response time as compared with the two other existing strategies.

These days, the Industrial Internet of Healthcare Things (IIT) enabled applications have been growing progressively in practice. These applications are ubiquitous and run onto the different computing nodes for healthcare goals. The applications have these tasks such as online healthcare monitoring, live heartbeat streaming, and blood pressure monitoring and need a lot of resources for execution. In IIoHT, remote procedure call (RPC) mechanism-based applications have been widely designed with the network and computational delay constraints to run healthcare applications. However, there are many requirements of IIoHT applications such as security, network and computation, and failure efficient RPC with optimizing the quality of services of applications. In this study, the work devised the lightweight RPC mechanism for IIoHT applications and considered the hybrid constraints in the system. The study suggests the secure hybrid delay scheme (SHDS), which schedules all healthcare workloads under their deadlines. For the scheduling problem, the study formulated this problem based on linear integer programming, where all constraints are integer, as shown in the mathematical model. Simulation results show that the proposed SHDS scheme and lightweight RPC outperformed the hybrid for IIoHT applications and minimized 50% delays compared to existing RPC and their schemes., This work is financially supported by the Research grant of PIFI 2020 (2020VBC0002), Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences (SIAT,CAS), Shenzhen, China.

With the development of ubiquitous technologies that support the digitization of money, research is needed on how individuals’ private life practices are affected by new technological financial systems and how cash-based practices can inform their design. In this paper, we report the cash-based monetary practices of one Ethiopian rural community and identify their implications for the design of new financial technology. Particularly, we focus on addressing the question: What characteristic features should go into the design of mobile money application(s) to embody a rural Ethiopian community’s money practices in social (marriage and death) and religious contexts? Primary data on everyday practices of the community was collected. Analysis of our data reveals that new financial technology design should support lived experiences such as: embedded social meaning, segregated and aggregate money control, restricted money use, identity extension and hiding, refusal and acceptance of donations, disclosed and secret money practices, and assigning aesthetics to money. The paper concludes by discussing possible ways of mapping these concepts into financial system design, thus contributing towards the development of cashless transactions and a cashless society.

In this paper we demonstrate the feasibility of IoT deployment for noise level measurement to time-limited and high-intense, high-volume data, events. Through an iterative process, a prototype solution were designed and implemented in a real-time, privacy-compliant IoT sensor system under tight constraints concerning budget and development time. Our sensor system enables festival management to easily track, document and further, by applying real time big data analytics to the harvested information, have fact-full insights generated for decision making in terms of resolving noise disturbances. The whole approach was demonstrated by the use of lightweight Internet of Things architecture demonstrating how web technologies can be used throughout the technology stack in and IoT big data analytics case.

Semantics is still a challenge to automation and to the improvement of the relationship between humans and machines. Content management systems have a lot of improvement possibilities using semantics. A news writing process incorporating a content management system that provides semantic search, semantic relationships between articles and communication with external semantic systems can improve the productivity of the writers and make the reader's task easier. This work presents a functional prototype of a content management system which focuses on the construction of semantic annotations based on domain ontology, reuse annotations in search and on relationship construction between stored texts, providing a semantic interface for external systems. We present in this paper the annotation algorithm, the use cases of annotation, article creation and editing, as well as an approach for doing a semantic search and creating semantic relationships between texts. The system enables users to create semantic annotations quickly and allows them to remove and add annotations, including those suggested by the annotation algorithm. The two approaches for semantic relationships between texts are accurate and useful, while the search tool is versatile because it allows users to search in semantic and non semantic fields at the same time and it also uses logic operators in all fields.

Virtual Reality (VR) offers new opportunities to marketers. Considering the fact that the primary role of marketing is to engrave a product or service to potential users and that VR arouses emotional responses and can influence the behavior of users, the applicability of VR to marketing cannot be underestimated. Accordingly, in this paper, we explore Critical Success Factors (CSFs) of VR in marketing ecosystems. Moreover, by adopting the means-end chain model, this paper focuses on the conditions that lead to a successful VR marketing campaign rather than any barriers associated with it. Results highlight the presence of 17 success factors for VR-based marketing campaign and provide insights to stakeholders who are considering whether or not to utilize VR technology in marketing their service or product.

This paper describes the use of Internet of Things as a solution for personal training, based on NFC wearable sensors mounted on garment like gym t-shirts and smart training units. Instead of sowing in wearable technology to every possible body part in motion, our solution builds on a sensory system applied to the object in training — such as a training mat, a barbell or a rod. The described study is underpinned by a research gap of-which a prototype solution (SmartPT) is developed to fill. Furthermore, the planning-, design-and development processes are described. Lastly, novel lessons learned and challenges faced when developing SmartPT are discussed, as well as possibilities for future research.