In today’s world, the Internet of Things has become an integral part of our lives. The increasing number of intelligent devices and their pervasiveness has made it challenging for developers and system architects to plan and implement systems of Internet of Things and Industrial Internet of Things effectively. The primary objective of this work is to automate the design process of Industrial Internet of Things systems while optimizing the quality of service parameters, battery life, and cost. To achieve this goal, a general four-layer fog-computing model based on mathematical sets, constraints, and objective functions is introduced. This model takes into consideration the various parameters that affect the performance of the system, such as network latency, bandwidth, and power consumption. The Non-dominated Sorting Genetic Algorithm II is employed to find Pareto optimal solutions, while the Technique for Order of Preference by Similarity to Ideal Solution is used to identify compromise solutions on the Pareto front. The optimal solutions generated by this approach represent servers, communication links, and gateways whose information is stored in a database. These resources are chosen based on their ability to enhance the overall performance of the system. The proposed strategy follows a three-stage approach to minimize the dimensionality and reduce dependencies while exploring the search space. Additionally, the convergence of optimization algorithms is improved by using a biased initial population that exploits existing knowledge about how the solution should look. The algorithms used to generate this initial biased population are described in detail. To illustrate the effectiveness of this automated design strategy, an example of its application is presented.
Active attraction of information technologies when conducting modern business puts forward a number of requirements to safety of information resources uses thus. In this regard the majority of experts in information security is engaged in development of various methods of protection of information systems from technical attacks. Recently more and more the staff of departments of information security starts paying attention to problems of secutrity of users of the information systems. About sociotechnical (socio-engineering) attacks tell the majority of authors of conssdered articles, but in one of them there are no data on the solution of problems of the automated assessment of degree of security of the personnel of information systems or problems of an assesment of efficiency of the actions directed on prevention os such attacks. The purpose of this article is the short state-of-the-art rewiew of scientific literature on subject of information security which will allow to list as existing needs for the analysis of security of users of information systems, and the preconditions revealed by the author to development of new approaches of such analysis.
The Smart-M3 platform allows constructing software applications consisting of agents that interact by sharing information in a smart space. An important problem is dependability of the application in case of failures, which is a common place for existing networked environments. In this paper, we consider a generic software infrastructure for Smart-M3 applications and propose two solutions to support the application fault tolerance. Our first solution is introduction of a content service, which provides safety of volumetric data and their integrity due to delegation of storage functions to a separate element of the application infrastructure. The second solution is mechanisms for network connections recovery. For experimental case study, we use an existing Smart-M3 application — the SmartRoom system. Based on this case we show effectiveness of the proposed solutions.
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