scholarly journals A kommunikációs gráfok és a fekete-fehér SAT probléma közti összefüggések vizsgálata

2021 ◽  
Author(s):  
Franciska Rajna
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Normal Form ◽  
Directed Graphs ◽  
Conjunctive Normal Form ◽  
Wireless Sensor ◽  
Sat Problem ◽  
Black And White ◽  
Communication Graphs ◽  
The Relationship

Ebben a cikkben a kommunikációs gráfok és a fekete-fehér SAT probléma közötti összefüggéseket vizsgálom. A kommunikációs gráfok olyan speciális hurokélmentes irányított gráfok, amelyeknek csúcsai logikai változók, az élei pedig a kommunikációt reprezentálják. Ilyen típusú gráfokkal lehet többek között vezeték nélküli szenzorhálózatokat is modellezni. A cikkben bemutatom a fekete-fehér SAT problémát. A fekete-fehér SAT problémák olyan logikai formulák, amelyek majdnem kielégíthetetlenek, csak két megoldásuk van, az úgynevezett fehér hozzárendelés, ahol minden változó igaz, és a fekete hozzárendelés, amelyben minden változó hamis. A fekete-fehér SAT problémák ekvivalensek az olyan konjunktív normálformában lévő logikai formulákkal, amelyekben minden klózban pozitív és negatív literálok vegyesen szerepelnek (például ilyen 3SAT klózok a -++, --+), de sem a fehér klóz, amelyben minden literál pozitív, sem a fekete klóz, amelyben minden literál negatív, nem vezethető le. Továbbá ismertetem, és hatékonyság szempontjából elemzem a kommunikációs gráfok különböző logikai modelljeit (Erős modell, Balatonboglár modell, Egyszerűsített BB modell, Gyenge modell). ----- Investigation of the relationship between communication graphs and the black and white sat ----- In this article, I examine the relationships between communication graphs and the black-andwhite SAT problem. Communication graphs are special loop-free directed graphs whose vertices are logical variables and whose edges represent communication. These types of graphs can be used to model wireless sensor networks (WSNs), among other things. I present the black-and-white SAT problem. Black-and-white SAT problems are logical formulas that are almost unsatisfiable, they have only two solutions, the so-called white assignment, where all variables are true, and the black assignment, in which all variables are false. Black-and-white SAT problems are equivalent to logical formulas in a conjunctive normal form in which positive and negative literals are mixed in each clause (e.g., such 3-SAT clauses are - ++, - +), but not the white clause in which all literals are positive, nor the black clause in which all literals are negative cannot be deduced. I also describe and analyze the different logical models of communication graphs (Strong model, Balatonboglár model, Simplified BB model, Weak model) in terms of efficiency.

scholarly journals Convert a Strongly Connected Directed Graph to a Black-and-White 3-SAT Problem by the Balatonboglár Model

2020 ◽  
Author(s):  
Gábor Kusper ◽  
Csaba Biró
Keyword(s):  
Directed Graph ◽  
Directed Graphs ◽  
Deep Insight ◽  
Communication Graph ◽  
Sat Problem ◽  
Weak Model ◽  
Know How ◽  
Black And White ◽  
Communication Graphs ◽  
Strongly Connected

In a previous paper we defined the Black-and-White SAT problem which has exactly two solutions, where each variable is either true or false. We showed that Black-and-White $2$-SAT problems represent strongly connected directed graphs. We presented also the strong model of communication graphs. In this work we introduce two new models, the weak model, and the Balatonbogl\'{a}r model of communication graphs. A communication graph is a directed graph, where no self loops are allowed. In this work we show that the weak model of a strongly connected communication graph is a Black-and-White SAT problem. We prove a powerful theorem, the so called Transitions Theorem. This theorem states that for any model which is between the strong and the weak model, we have that this model represents strongly connected communication graphs as Blask-and-White SAT problems. We show that the Balatonbogl\'{a}r model is between the strong and the weak model, and it generates $3$-SAT problems, so the Balatonbogl\'{a}r model represents strongly connected communication graphs as Black-and-White $3$-SAT problems. Our motivation to study these models is the following: The strong model generates a $2$-SAT problem from the input directed graph, so it does not give us a deep insight how to convert a general SAT problem into a directed graph. The weak model generates huge models, because it represents all cycles, even non-simple cycles, of the input directed graph. We need something between them to gain more experience. From the Balatonbogl\'{a}r model we learned that it is enough to have a subset of a clause, which represents a cycle in the weak model, to make the Balatonbogl\'{a}r model more compact. We still do not know how to represent a SAT problem as a directed graph, but this work gives a strong link between two prominent fields of formal methods: SAT problem and directed graphs.

Wireless Sensor Networks to Predict the Range Covered by the Priority Scheduling Algorithm for Multi-Target Tracking

2014 ◽  
Vol 687-691 ◽  
pp. 1071-1075
Author(s):  
Yong Long Zhuang ◽  
Xiao Lan Weng ◽  
Xiang He Wei
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Target Tracking ◽  
Scheduling Algorithm ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Tracking Accuracy ◽  
Detection Range ◽  
Multi Target Tracking ◽  
The Relationship

Research on multi-target tracking wireless sensor networks, the main problem is how to improve tracking accuracy and reduce energy consumption. Proposed use of forecasting methods to predict the target state, the selection of target detection range forecast based on the relationship between states and between sensor nodes deployed. And in accordance with the selected detection range, to wake up and form a cluster to track the target. In multi-target tracking will use to adjust the detection range, time to time to separate the conflict node of conflict, in order to achieve a successful track multiple targets. Simulation results show that the proposed method can indeed improve the chances of success of the track.

scholarly journals Strip-based deployment with cooperative communication to achieve connectivity and information coverage in wireless sensor networks

2019 ◽  
Vol 15 (10) ◽  
pp. 155014771988488
Author(s):  
Wei Cheng ◽  
Xiaolin Lu ◽  
Yong Li ◽  
Hui Wang ◽  
Lei Zhong
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Cooperative Communication ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
New Strategy ◽  
Optimal Deployment ◽  
Coverage And Connectivity ◽  
The Relationship ◽  
Information Coverage

Coverage and connectivity in wireless sensor network have been studied extensively in existing research works with physical and information coverage. The optimal deployment to achieve both information coverage and connectivity, on arbitrary values of the ratio of rc and rs, has been studied in previous work; meanwhile, the extended strip-based deployment based on information coverage is also studied. Either information coverage or cooperative communication could exploit collaboration of sensor nodes to improve the efficiency of deployment, while how good is strip-based deployment with both information coverage and cooperative communication is worth to be measured when the value of rc/ rs is varied. In this article, the relationship between the density of sensors needed to achieve physical or information coverage and connectivity and the variety of rc/ rs is derived in closed form for strip-based deployment of wireless sensor networks with cooperative communication. Then, a summary of different combinations of coverage and connectivity is provided, that physical or information coverage with or without cooperative communication could be employed to achieve full coverage and connectivity for strip-based deployment. Finally, some new strategy could be proposed based on the fusion of physical and information coverage to improve strip-based deployment. Some numerical results are provided to show the efficiency of all schemes to help researchers design more effective deployment schemes.

scholarly journals Convert a Strongly Connected Directed Graph to a Black-and-White 3-SAT Problem by the Balatonboglár Model

Algorithms ◽  
2020 ◽  
Vol 13 (12) ◽  
pp. 321
Author(s):  
Gábor Kusper ◽  
Csaba Biró
Keyword(s):  
Directed Graph ◽  
Directed Graphs ◽  
Deep Insight ◽  
Communication Graph ◽  
Sat Problem ◽  
Weak Model ◽  
Know How ◽  
Black And White ◽  
Communication Graphs ◽  
Strongly Connected

In a previous paper we defined the black and white SAT problem which has exactly two solutions, where each variable is either true or false. We showed that black and white 2-SAT problems represent strongly connected directed graphs. We presented also the strong model of communication graphs. In this work we introduce two new models, the weak model, and the Balatonboglár model of communication graphs. A communication graph is a directed graph, where no self loops are allowed. In this work we show that the weak model of a strongly connected communication graph is a black and white SAT problem. We prove a powerful theorem, the so called transitions theorem. This theorem states that for any model which is between the strong and the weak model, we have that this model represents strongly connected communication graphs as black and white SAT problems. We show that the Balatonboglár model is between the strong and the weak model, and it generates 3-SAT problems, so the Balatonboglár model represents strongly connected communication graphs as black and white 3-SAT problems. Our motivation to study these models is the following: The strong model generates a 2-SAT problem from the input directed graph, so it does not give us a deep insight how to convert a general SAT problem into a directed graph. The weak model generates huge models, because it represents all cycles, even non-simple cycles, of the input directed graph. We need something between them to gain more experience. From the Balatonboglár model we learned that it is enough to have a subset of a clause, which represents a cycle in the weak model, to make the Balatonboglár model more compact. We still do not know how to represent a SAT problem as a directed graph, but this work gives a strong link between two prominent fields of formal methods: the SAT problem and directed graphs.

scholarly journals A Participation Degree-Based Fault Detection Method for Wireless Sensor Networks

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1522
Author(s):  
Wei Zhang ◽  
Gongxuan Zhang ◽  
Xiaohui Chen ◽  
Xiumin Zhou ◽  
Yueqi Liu ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Fault Detection ◽  
Detection Method ◽  
Wireless Sensor ◽  
Support Vector ◽  
Local Cluster ◽  
Real World Datasets ◽  
The Relationship ◽  
Isolation Forest

In wireless sensor networks (WSNs), there are many challenges for outlier detection, such as fault detection, fraud detection, intrusion detection, and so on. In this paper, the participation degree of instances in the hierarchical clustering process infers the relationship between instances. However, most of the existing algorithms ignore such information. Thus, we propose a novel fault detection technique based on the participation degree, called fault detection based on participation degree (FDP). Our algorithm has the following advantages. First, it does not need data training in labeled datasets; in fact, it uses the participation degree to measure the differences between fault points and normal points without setting distance or density parameters. Second, FDP can detect global outliers without local cluster influence. Experimental results demonstrate the performance of our approach by applying it to synthetic and real-world datasets and contrasting it with four well-known techniques: isolation forest (IF), local outlier factor (LOF), one-class support vector machine (OCS), and robust covariance (RC).

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