scholarly journals ДОСЯГНЕННЯ ЕФЕКТИВНОГО РОЗПОДІЛЕНОГО ПЛАНУВАННЯ ЗА ДОПОМОГОЮ ЧЕРГ ПОВІДОМЛЕНЬ У ХМАРІ ДЛЯ БАГАТОЗАДАЧНИХ ОБЧИСЛЕНЬ ТА ВИСОКОПРОДУКТИВНИХ ОБЧИСЛЕНЬ

Author(s):  
Старовойтенко Олексій Володимирович

Due to the growth of data and the number of computational tasks, it is necessary to ensure the required level of system performance. Performance can be achieved by scaling the system horizontally / vertically, but even increasing the amount of computing resources does not solve all the problems. For example, a complex computational problem should be decomposed into smaller subtasks, the computation time of which is much shorter. However, the number of such tasks may be constantly increasing, due to which the processing on the services is delayed or even certain messages will not be processed. In many cases, message processing should be coordinated, for example, message A should be processed only after messages B and C. Given the problems of processing a large number of subtasks, we aim in this work - to design a mechanism for effective distributed scheduling through message queues. As services we will choose cloud services Amazon Webservices such as Amazon EC2, SQS and DynamoDB. Our FlexQueue solution can compete with state-of-the-art systems such as Sparrow and MATRIX. Distributed systems are quite complex and require complex algorithms and control units, so the solution of this problem requires detailed research.

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 515
Author(s):  
Michele La Manna ◽  
Luigi Treccozzi ◽  
Pericle Perazzo ◽  
Sergio Saponara ◽  
Gianluca Dini

This paper aims to show that it is possible to improve security for over the air update functionalities in an automotive scenario through the use of a cryptographic scheme, called “Attribute-Based-Encryption” (ABE), which grants confidentiality to the software/firmware update done Over The Air (OTA). We demonstrate that ABE is seamlessly integrable into the state of the art solutions regarding the OTA update by showing that the overhead of the ABE integration in terms of computation time and its storage is negligible w.r.t. the other overheads that are introduced by the OTA process, also proving that security can be enhanced with a minimum cost. In order to support our claim, we report the experimental results of an implementation of the proposed ABE OTA technique on a Xilinx ZCU102 evaluation board, which is an automotive-oriented HW/SW platform that is equipped with a Zynq UltraScale+ MPSoC chip that is representative of the computing capability of real automotive Electronic Control Units (ECUs).


2021 ◽  
Vol 37 (1-4) ◽  
pp. 1-30
Author(s):  
Vincenzo Agate ◽  
Alessandra De Paola ◽  
Giuseppe Lo Re ◽  
Marco Morana

Multi-agent distributed systems are characterized by autonomous entities that interact with each other to provide, and/or request, different kinds of services. In several contexts, especially when a reward is offered according to the quality of service, individual agents (or coordinated groups) may act in a selfish way. To prevent such behaviours, distributed Reputation Management Systems (RMSs) provide every agent with the capability of computing the reputation of the others according to direct past interactions, as well as indirect opinions reported by their neighbourhood. This last point introduces a weakness on gossiped information that makes RMSs vulnerable to malicious agents’ intent on disseminating false reputation values. Given the variety of application scenarios in which RMSs can be adopted, as well as the multitude of behaviours that agents can implement, designers need RMS evaluation tools that allow them to predict the robustness of the system to security attacks, before its actual deployment. To this aim, we present a simulation software for the vulnerability evaluation of RMSs and illustrate three case studies in which this tool was effectively used to model and assess state-of-the-art RMSs.


Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 400 ◽  
Author(s):  
Zelin Nie ◽  
Feng Gao ◽  
Chao-Bo Yan

Reducing the energy consumption of the heating, ventilation, and air conditioning (HVAC) systems while ensuring users’ comfort is of both academic and practical significance. However, the-state-of-the-art of the optimization model of the HVAC system is that either the thermal dynamic model is simplified as a linear model, or the optimization model of the HVAC system is single-timescale, which leads to heavy computation burden. To balance the practicality and the overhead of computation, in this paper, a multi-timescale bilinear model of HVAC systems is proposed. To guarantee the consistency of models in different timescales, the fast timescale model is built first with a bilinear form, and then the slow timescale model is induced from the fast one, specifically, with a bilinear-like form. After a simplified replacement made for the bilinear-like part, this problem can be solved by a convexification method. Extensive numerical experiments have been conducted to validate the effectiveness of this model.


Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 999
Author(s):  
Ahmad Taher Azar ◽  
Anis Koubaa ◽  
Nada Ali Mohamed ◽  
Habiba A. Ibrahim ◽  
Zahra Fathy Ibrahim ◽  
...  

Unmanned Aerial Vehicles (UAVs) are increasingly being used in many challenging and diversified applications. These applications belong to the civilian and the military fields. To name a few; infrastructure inspection, traffic patrolling, remote sensing, mapping, surveillance, rescuing humans and animals, environment monitoring, and Intelligence, Surveillance, Target Acquisition, and Reconnaissance (ISTAR) operations. However, the use of UAVs in these applications needs a substantial level of autonomy. In other words, UAVs should have the ability to accomplish planned missions in unexpected situations without requiring human intervention. To ensure this level of autonomy, many artificial intelligence algorithms were designed. These algorithms targeted the guidance, navigation, and control (GNC) of UAVs. In this paper, we described the state of the art of one subset of these algorithms: the deep reinforcement learning (DRL) techniques. We made a detailed description of them, and we deduced the current limitations in this area. We noted that most of these DRL methods were designed to ensure stable and smooth UAV navigation by training computer-simulated environments. We realized that further research efforts are needed to address the challenges that restrain their deployment in real-life scenarios.


Author(s):  
Rocco De Nicola ◽  
Michele Loreti

A new area of research, known as Global Computing, is by now well established. It aims at defining new models of computation based on code and data mobility over wide-area networks with highly dynamic topologies, and at providing infrastructures to support coordination and control of components originating from different, possibly untrusted, fault-prone, malicious or selfish sources. In this paper, we present our contribution to the field of Global Computing that is centred on Kernel Language for Agents Interaction and Mobility ( Klaim ). Klaim is an experimental language specifically designed to programme distributed systems consisting of several mobile components that interact through multiple distributed tuple spaces. We present some of the key notions of the language and discuss how its formal semantics can be exploited to reason about qualitative and quantitative aspects of the specified systems.


1995 ◽  
Vol 117 (B) ◽  
pp. 80-86 ◽  
Author(s):  
Lung-Wen Tsai

This paper presents an overview of the current state-of-the-art in the design of tendon-driven manipulators. A special characteristic associated with tendon-driven manipulators is that tendons can only exert tension but not compression. Based on this unique characteristic, the fundamental mechanics associated with the design of tendon-driven manipulators are reviewed. The review includes structure classification, kinematics, statics, dynamics and control.


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