Hardware Reliability Analysis of a Coal Mine Gas Monitoring System Based on Fuzzy-FTA

The hardware reliability of a gas monitoring system was investigated using the fuzzy fault tree analysis method. A fault tree was developed considering the hardware failure of the gas monitoring system as a top event. Two minimum path sets were achieved through qualitative analysis using the ascending method. The concept of fuzzy number of the fuzzy set theory was applied to describe the probability of basic event occurrence in the fault tree, and the fuzzy failure probabilities of the middle and top events were calculated using fuzzy AND and OR operators. The results show that the proposed fuzzy fault tree is an effective method of reliability analysis for gas monitoring systems. Results of calculations using this method are more reasonable than those obtained with the conventional fault tree method.

A Light Weight Multi-Objective Task Offloading Optimization for Vehicular Fog Computing

Most Internet of Vehicles (IoV) applications are delay-sensitive and require resources for data storage and tasks processing, which is very difficult to afford by vehicles. Such tasks are often offloaded to more powerful entities, like cloud and fog servers. Fog computing is decentralized infrastructure located between data source and cloud, supplies several benefits that make it a non-frivolous extension of the cloud. The high volume data which is generated by vehicles’ sensors and also the limited computation capabilities of vehicles have imposed several challenges on VANETs systems. Therefore, VANETs is integrated with fog computing to form a paradigm namely Vehicular Fog Computing (VFC) which provide low-latency services to mobile vehicles. Several studies have tackled the task offloading problem in the VFC field. However, recent studies have not carefully addressed the transmission path to the destination node and did not consider the energy consumption of vehicles. This paper aims to optimize the task offloading process in the VFC system in terms of latency and energy objectives under deadline constraint by adopting a Multi-Objective Evolutionary Algorithm (MOEA). Road Side Units (RSUs) x-Vehicles Mutli-Objective Computation offloading method (RxV-MOC) is proposed, where an elite of vehicles are utilized as fog nodes for tasks execution and all vehicles in the system are utilized for tasks transmission. The well-known Dijkstra's algorithm is adopted to find the minimum path between each two nodes. The simulation results show that the RxV-MOC has reduced significantly the energy consumption and latency for the VFC system in comparison with First-Fit algorithm, Best-Fit algorithm, and the MOC method.

A Method of Fast Evaluation of an MC Placement for Network-on-Chip

On-chip Memory-Controllers (MCs) placement is a key issue in designing Network-on-Chip (NoC) with multiple MCs. A good MC placement can efficiently decrease NoC memory-access latency. However, it is difficult to search an optimal MC placement within a feasible time period due to huge design space of MC placements and much time spent on evaluating whether an MC placement is better or not. This paper focuses on how to evaluate an MC placement quickly. As a common manner of evaluating an MC placement, network simulation manners often cost too much time. In this paper, we propose a method of fast evaluation of an MC placement. There are two contributions in this paper: the first one is to use an indicator “path-load” to approximately represent memory-access-flow transmission latency; the second one is to propose a highly-efficient method of calculating path-load to evaluate an MC placement to take the place of traditional simulation manner. To verify this method, we embed it into a traversal method to find out optimal MCs placements. Experiments show that almost all MCs placements with the minimum path load value are those placements that are of the best network performance in the same network scenarios. In a word, our proposed method can efficiently evaluate MCs placements rather than simulation manners. It can be embedded into searching algorithm to accelerate achieving optimal solutions.

Medians are Below Joins in Semimodular Lattices of Breadth 2

Let L be a lattice of finite length and let d denote the minimum path length metric on the covering graph of L. For any $\xi =(x_{1},\dots ,x_{k})\in L^{k}$ ξ = ( x 1 , … , x k ) ∈ L k , an element y belonging to L is called a median of ξ if the sum d(y,x1) + ⋯ + d(y,xk) is minimal. The lattice L satisfies the c1-median property if, for any $\xi =(x_{1},\dots ,x_{k})\in L^{k}$ ξ = ( x 1 , … , x k ) ∈ L k and for any median y of ξ, $y\leq x_{1}\vee \dots \vee x_{k}$ y ≤ x 1 ∨ ⋯ ∨ x k . Our main theorem asserts that if L is an upper semimodular lattice of finite length and the breadth of L is less than or equal to 2, then L satisfies the c1-median property. Also, we give a construction that yields semimodular lattices, and we use a particular case of this construction to prove that our theorem is sharp in the sense that 2 cannot be replaced by 3.

Distributed Algorithm for Base Station Assignment in 4G/5G Machine-Type Communication Scenarios with Backhaul Limited Conditions

A progressive paradigm shift from centralized to distributed network architectures has been consolidated since the 4G communication standard, calling for novel decision-making mechanisms with distributed control to operate at the network edge. This situation implies that each base station (BS) must manage resources independently to meet the quality of service (QoS) of existing human-type communication devices (HTC), as well as the emerging machine type communication (MTC) devices from the internet of things (IoT). In this paper, we address the BS assignment problem, whose aim is to determine the most appropriate serving BS to each mobile device. This problem is formulated as an optimization problem for maximizing the system throughput and imposing constraints on the air interface and backhaul resources. The assignment problem is challenging to solve, so we present a simple yet valid reformulation of the original problem while using dual decomposition theory. Subsequently, we propose a distributed price-based BS assignment algorithm that performs at each BS the assignment process, where a novel pricing update scheme is presented. The simulation results show that our proposed solution outperforms traditional maximum signal to interference plus noise ratio (Max-SINR) and minimum path-loss (Min-PL) approaches in terms of system throughput.

Cultural Identity Distance Computation through Artificial Intelligence as an Analysis Tool of the Amazon Indigenous People. A Case Study in the Waorani Community

Cultural identity is a complex concept that includes subjective factors such as ideology, family knowledge, customs, language, and acquired skills, among others. Measuring culture involves a significant level of difficulty, since its study and scope differ from the point of view, the time and the place where the studies are carried out. In the Amazon, indigenous communities are in an accelerated process of acculturation that results in a loss of cultural identity that is not easy to quantify. This paper presents a method to measure the cultural distance between individuals or between groups of people using Artificial Intelligence techniques. The distance between individuals is calculated as the distance of the minimum path in the self-organizing map using Dijkstra’s algorithm. The experiments have been carried out to measure the cultural identity of indigenous people in the Waorani Amazon community and compares them with people living in cities who have a modern identity. The results showed that the communities are still distant in terms of identity from the westernised cities around them, although there are already factors where the distances are minimal concerning these cities. In any case, the method makes it possible to quantify the state of acculturation. This quantification can help the authorities to monitor these communities and take political decisions that will enable them to preserve their cultural identity.

Development of the Authors' Method for Arranging Routes for Elimination of Unauthorized Dumps

Purpose of research is to develop a method for arraging routes for elimination of spontaneously formed unauthorized dumps on the territory of a municipal formation of a constituent entity of the Russian Federation.Methods. The development of a method for arraging routes for elimination of unauthorized dumps is based on the theory of graphs, which includes algorithms for finding the shortest path: Dijkstra's algorithm, Floyd-Warshall algorithm, Ford-Bellman algorithm, Hamiltonian cycle, etc. Having analyzed the peculiarities of using the listed algorithms, the authors have developed a method for arranging a route for the elimination of unauthorized dumps based on the Hamiltonian cycle.Results. The task of arranging a route is reduced to choosing those unauthorized dumps from the detected ones, which will be accepted as the vertices of the graph, between which it is necessary to find the shortest path. The authors' approach to the formation of a set of vertices of the graph is as follows. At the first stage, the initial and boundary conditions are set. The parking of special equipment (garbage trucks) is selected as the zero vertex of the graph, and the SMW polygon is selected as the last (nth) vertex. In this case, it should be taken in the account that after transporting waste from dumps to the place of their burial (landfill), the garbage truck must return back to the parking place. The limits taken into consideration are the maximum distance that the garbage truck can travel without refueling and the volume of the garbage truck body. Then, the closest to the starting point unauthorized dump which represents the greatest danger to the environment is chosen as the first vertex of the graph. An unauthorized dump closest to the first peak is chosen as the second, etc.. The search for vertices continues until the inequalities that take into account the given constraints are satisfied. Next, a graph, an adjacency matrix, and a route are formed. With this approach, for arranging a route, it is optimal to use the Hamiltonian cycle, which ensures finding the minimum path between all the vertices of the graph and returns to the starting point.Conclusion. Application of the authors' method for arranging routes for elimination of unauthorized dumps will make it possible to promptly clean up unauthorized dumps found in the city, which will significantly reduce the environmental load.