Several virtual machine (VM) placement algorithms have been proposed and studied in the literature with various scopes such as server consolidation or network cost minimization. In most cases, decisions on VM migrations are taken without factoring in directly the data access cost by VMs. In this paper, we investigate the use of data replication in conjunction with the VM assignment problem and target on developing algorithms that decide both on which data should be replicated where and which VM must be migrated so as to minimize the network overhead among traditional cloud and mobile cloud systems. We discuss both the un-capacitated case and the more realistic case whereby datacenters (for the traditional cloud case) and micro-datacenters (for the mobile cloud case) have limited storage and computing capacity. We propose an algorithm based on hyper-graph partitioning to solve the aforementioned problem in an optimal way regarding the unconstrained case and extend it to capture storage and computing capacity constraints. Experimental evaluation shows that the proposed algorithm yields up to 53 percent network overhead reduction when compared to state-of-the-art algorithms found in the literature.

Internet of Things offers the infrastructure for smooth functioning of autonomous context-aware devices being connected towards the Cloud. Edge Computing (EC) relies between the IoT and Cloud providing significant advantages. One advantage is to perform local data processing (limited latency, bandwidth preservation) with real time communication among IoT devices, while multiple nodes become hosts of the collected data (reported by IoT devices). In this work, we provide a mechanism for the exchange of data synopses (summaries of extracted knowledge) among EC nodes that are necessary to give the knowledge on the data present in EC environments. The overarching aim is to intelligently decide on when nodes should exchange data synopses in light of efficient execution of tasks. We enhance such a decision with a stochastic optimization model based on the Theory of Optimal Stopping. We provide the fundamentals of our model and the relevant formulations on the optimal time to disseminate data synopses to network edge nodes. We report a comprehensive experimental evaluation and comparative assessment related to the optimality achieved by our model and the positive effects on EC.

Computer programming can help children develop problem solving and analytical skills. Thus, many countries have included computer science in the curriculum of primary school. Given differences in culture, available infrastructures, as well as the age pupils are introduced to computer science, forming a computer science curriculum still remains a challenge. Towards this end, this study focuses on ex-ploring the potential merits of introducing concurrent programming concepts ear-ly in the learning process. The basic premise is that although concurrent pro-gramming at its full details is a rather advanced topic even at university level, it is everyday practice to perform two or more tasks simultaneously that might need (or not) some sort of synchronization. Therefore, the tutor can capitalize on eve-ryday experience to explain basic concepts on concurrency. Such correlation be-tween life experience and concurrent programming challenges may expand the cognitive functions of the pupils and provide them with further background to improve analytical thinking. The proposed curriculum for fifth and sixth grade primary school was adopted in seven classes in Greece. Results indicate that un-initiated to programming pupils at the age of ten (fifth grade) were able to com-prehend basic concurrency topics, while pupils at the age of eleven (sixth grade) with some programming familiarity were able to understand more advanced concepts.

Torque calculation is essential for selecting the appropriate motor to achieve the required torque at each joint of a hybrid exoskeleton. In recent years, the combined use of functional electrical stimulation (FES) and robotic devices, called hybrid robotic rehabilitation systems, has emerged as a promising approach for the rehabilitating of lower limb motor functions. Specifically, the implementation strategy of functional electrical stimulation walking aid combined with the design of the exoskeleton part is the main focus of our research team. This work copes with issues of the design process of a robotic exoskeleton. The importance of robotic exoskeletons for providing walking aid to people with mobility disorders or the elderly is discussed. Furthermore, the approaches to calculating the joint torques are investigated, and the mathematical models and parameters of interest are identified. This further includes the comparative data for servo motors: robotic exoskeleton characteristics and actuator analysis in the robotic exoskeleton. The aforementioned is used to propose a mathematical model based on previous models (Zatsiorsky BSP and Dempster BSP body segment parameters models, forward kinematics models), which was extended to include added adjustable parameters such as length, area, volume, mass, density, the centre of mass, human body characteristics, and considering both static and dynamic parameter extraction. Then, an analytic method is presented, exploiting the results from the mathematical model to select the appropriate motor for each joint of the lower extremities. The detailed description of the method is followed by examples, experimental measurements, and statistical analysis of qualitative and quantitative characteristics. The results showed deviations from typical calculation methods, offering a better understanding of the motor requirements for each joint of the exoskeleton and avoiding selections of marginal functionality features of the motors. In addition, researchers are offered a tool for replicating the results of this work, allowing them to configure the parameters associated with the servo motor features. The researcher can either use the embedded library developed for this work or enter new data into it, affecting the calculated torques of the model joints. The extracted results assist the researcher in choosing the appropriate motor among commercially available brushed and brushless motors based on the torques applied at each joint in robotic articulated systems.