Node Replacement Research Articles

Graph topology resulting from addition and deletion of nodes determined by random walk

How the power-law form of the degree distribution of networks can survive in the equilibrium state of number of nodes is an open question, since the deletion of nodes seriously affects the degree distribution. In this paper, we introduce a network evolution rule based on a random walk to describe the replacement of nodes in networks. Numerical results show that model assumptions support the power-law form of degree distribution even when the replacement of vertices achieves an equilibrium state of the number of vertices, and the distribution is described by the distribution of the maximum degree that each node experiences in its life. We showed additionally that the reduction of the addition probability of nodes causes an edge condensation to hub nodes. A novel feature of the model is that the visit frequency and recurrence property of the walker to a vertex determines the degree and lifetime of the vertex in an equilibrium state of the number of vertices.

Working position with recomposed production systems: devices

The article presents the current trends in the recomposed work stand and the terminology used. Technical solutions were considered in order to optimize the use of this system type. Intermodular element of locating and fixing - multi-tiered was proposed. This device contains automatic plug-in units, layout - multi-tiered. Tiered layout does not always meet the requirements of the technical process. Industrial robot for automatic replacement of nodes was proposed.

Evaluating Local Disaster Recovery Strategies

It is of vital importance to maintain at least some network functionality after a disaster, for example by temporarily replacing damaged nodes by emergency nodes. We propose a framework to evaluate different node replacement strategies, based on a large set of representative disasters. We prove that computing the optimal choice of nodes to replace is an NP-hard problem and propose several simple strategies. We evaluate these strategies on two U.S. topologies and show that a simple greedy strategy can perform close to optimal.

Principles of Formation of a Vehicle’s Remote Diagnostics

Complex of remote diagnostics and control of an automobile’s nodes enables to remotely control the state of vehicle’s nodes and diagnose malfunctions; control ecological norms and compliance with traffic regulations. Its implementation will allow diagnostics of intermittent malfunctions due to application of the proposed methods of remote diagnostics of an automobile’s nodes as well as to reduce terms of diagnostics significantly due to application of intellectual system of malfunctions detection and due to possibility to control parameters in real time mode. Implementation of the complex will cut unforeseen idle time of vehicles due to preventive control of the tendencies in nodes parameters changes, and due to executing modern repair or replacement of nodes and units. The complex grants safe local and remote access to data and reports by using WebPortal and VPN technologies with possibility to appoint personal right to every user. Due to application of the elaborated methods and the complex that implements it, one can achieve high rate of economic efficiency due to collection of statistic information under conditions of actual exploitation, diagnostics of emerging malfunctions of various difficulty degrees, and making necessary corrections in the structure of an automobile’s nodes prior to serial production launch.

Food Safety Supervision System Based on Hierarchical Multi-Domain Blockchain Network

The traditional food supervision system has problems such as lack of industry chain and data fragmentation, which has caused the phenomenon of field regulation to be uncomprehensive in the existing regulatory system and the disposal of response lag. Combining the characteristics of blockchain such as distribution, transparent, and collegiality with the actual needs of regional autonomy, we propose the hierarchical multi-domain blockchain (HMDBC) network structure and the secondary-check mechanism, which can support timely correction and replacement of the malicious supervision nodes by regional nodes co-governance, auxiliary verification of supervision nodes, and arbitration of superior regions. In order to optimize the supervision nodes election, we proposed fuzzy comprehensive evaluation model of credibility, which can be used to objectively and fairly evaluate the comprehensive reputation of each node in that region by considering various influencing factors of node performance indicators. Furthermore, we designed the data block structure model, which can support the supervisor node replacement. Our system can perform automatic food quality detection and warning of substandard food in the entire industrial chain, with the use of smart contracts combined with the food industry standards. Finally, comparing the complexity of the traditional blockchain system with PBFT consortium, our system is more secure, with lower broadcast complexity.

Context-free graph P system

Graph grammar is a rewriting system generating graph languages. Context-free graph grammars are studied developing a theory similar to that of context-free string languages. In this paper we define context-free node replacement graph P system with conditional communication and context-free node replacement graph rewriting P system. Results on the notions such as the minimum number of membranes required to generate a family of context-free graph languages are discussed.

Intelligent On‐Demand Connectivity Restoration for Wireless Sensor Networks

Wireless sensor networks are envisioned to play a very important role in the Internet of Things in near future and therefore the challenges associated with wireless sensor networks have attracted researchers from all around the globe. A common issue which is well studied is how to restore network connectivity in case of failure of single or multiple nodes. Energy being a scarce resource in sensor networks drives all the proposed solutions to connectivity restoration to be energy efficient. In this paper we introduce an intelligent on‐demand connectivity restoration technique for wireless sensor networks to address the connectivity restoration problem, where nodes utilize their transmission range to ensure the connectivity and the replacement of failed nodes with their redundant nodes. The proposed technique helps us to keep track of system topology and can respond to node failures effectively. Thus our system can better handle the issue of node failure by introducing less overhead on sensor node, more efficient energy utilization, better coverage, and connectivity without moving the sensor nodes.

Network lifetime-aware data collection in Underwater Sensor Networks for delay-tolerant applications

Development of energy-efficient data collection and routing schemes for Underwater Wireless Sensor Networks (UWSNs) is a challenging issue due to the peculiarities of the underlying physical layer technology. Since the recharging or replacement of sensor nodes is almost impossible after deployment, the critical issue of network lifetime maximization must be considered right from the beginning of designing the routing schemes. We propose a mobile sink (MS)-based data collection scheme that can extend network lifetime, taking into account power-constrained sensor nodes, partitioned networks with geographically distant data collection points and periodic monitoring applications with delay-tolerance. Lifetime extension is achieved by mitigating the ‘sink neighbourhood problem’ and by deferring the data transmissions until the MS is at the most favourable location for data transfer. Unlike the models available for terrestrial WSNs, we consider non-zero travel time of the MS between data collection points, thus making our model more realistic for UWSNs, both connected and partitioned. The performance of the proposed mobility-assisted data collection scheme is thoroughly investigated using both analytical and simulation models. The analytical results are compared to those of existing models to assess their effectiveness and to investigate the trade-offs. Results show that, with a network size of 60 nodes, the network lifetime achieved by the proposed model is 188% higher than that of static sink model and 91% higher than that of mobile sink model (MSM). The proposed maximum lifetime routing scheme is implemented in the network simulation platform OMNET++, for validating the analytical results as well as for evaluating other performance metrics that are not tractable via analytical methods. Both analytical and simulation results demonstrate the superiority of the proposed model in capturing realistic network conditions and providing useful performance indicators prior to network deployment.

Influential Node Tracking on Dynamic Social Network: An Interchange Greedy Approach

As both social network structure and strength of influence between individuals evolve constantly, it requires tracking the influential nodes under a dynamic setting. To address this problem, we explore the Influential Node Tracking (INT) problem as an extension to the traditional Influence Maximization problem (IM) under dynamic social networks. While the Influence Maximization problem aims at identifying a set of $k$ nodes to maximize the joint influence under one static network, the INT problem focuses on tracking a set of influential nodes that keeps maximizing the influence as the network evolves. Utilizing the smoothness of the evolution of the network structure, we propose an efficient algorithm, Upper Bound Interchange Greedy (UBI) and a variant, UBI+. Instead of constructing the seed set from the ground, we start from the influential seed set we found previously and implement node replacement to improve the influence coverage. Furthermore, by using a fast update method by calculating the marginal gain of nodes, our algorithm can scale to dynamic social networks with millions of nodes. Empirical experiments on three real large-scale dynamic social networks show that our UBI and its variants, UBI+ achieves better performance in terms of both influence coverage and running time.

Dynamic performance of an attacker replacement algorithm for wireless sensor networks

In the recent years Wireless Sensor Networks (WSN) has become the very interesting and challenging area for the effective rapid data transmission. The efficiency and the throughput of the wireless network should be high. Sometime it is necessary to select the best/correct adjacent node to transmit the data without any loss. To disrupt communication between the nodes various types of attackers are available in the networks. Here proposed a new approach called Attacker Replacement Algorithm (ARA) to detect the attacker in the network and to replace the attacker node by a new substitute node with the help of nearby base stations. After the replacement of the node, the effective communication takes place through the replaced node. Then several parameters are analyzed with and without the replacement of attacker node. And found it to be better after the replacement of node by using Attacker Replacement Algorithm (ARA).

Novel approach for replacement of a failure node in wireless sensor network

In the recent years, there has been a growing interest in wireless sensor networks (WSN). Network's lifetime depends on energy efficiency and load balancing where connectivity is a very important factor. However, such connectivity can be lost due to the failure of some sensor nodes which creates disruptions to the network operations, lead to a reconfiguration of the network by generating energy losses, or in another case, the network mission fails. Energy conservation is a very important problem in WSN. In this paper, we propose a new solution for the connectivity problem when failure nodes are considered. The replacement of failed nodes is done in two phases: the first one is the search of redundant nodes using the clusterheads; the second phase is a restoration of connectivity. Performance evaluation of the proposed replacement approach shows that the results are globally satisfactory.

A Simple Algorithm For Replacement Paths Problem

Let G=(V,E) (|V|=n and |E|=m) be an undirected graph with positive edge weights. Let PG(s,t) be a shortest s−t path in G. Let l be the number of edges in PG(s,t). The Edge Replacement Path problem is to compute a shortest s−t path in G\\{e}, for every edge e in PG(s,t). The Node Replacement Path problem is to compute a shortest s−t path in G\\{v}, for every vertex v in PG(s,t).In this paper we present an O(TSPT(G)+m+l2) time and O(m+l2) space algorithm for both the problems. Where, TSPT(G) is the asymptotic time to compute a single source shortest path tree in G. The proposed algorithm is simple and easy to implement.

On Maximizing Sensor Network Lifetime by Energy Balancing

Many physical systems, such as water/electricity distribution networks, are monitored by battery-powered Wireless Sensor Networks (WSNs). Since battery replacement of sensor nodes is generally difficult, long-term monitoring can be only achieved if the operation of the WSN nodes contributes to a long WSN lifetime. Two prominent techniques to long WSN lifetime are i) optimal sensor activation and ii) efficient data gathering and forwarding based on compressive sensing. These techniques are feasible only if the activated sensor nodes establish a connected communication network (connectivity constraint), and satisfy a compressive sensing decoding constraint (cardinality constraint). These two constraints make the problem of maximizing network lifetime via sensor node activation and compressive sensing NP-hard. To overcome this difficulty, an alternative approach that iteratively solves energy balancing problems is proposed. However, understanding whether maximizing network lifetime and energy balancing problems are aligned objectives is a fundamental open issue. The analysis reveals that the two optimization problems give different solutions, but the difference between the lifetime achieved by the energy balancing approach and the maximum lifetime is small when the initial energy at sensor nodes is significantly larger than the energy consumed for a single transmission. The lifetime achieved by the energy balancing is asymptotically optimal, and that the achievable network lifetime is at least $50$\% of the optimum. Analysis and numerical simulations quantify the efficiency of the proposed energy balancing approach.

An Energy Efficient Routing Algorithm for Wireless Body Area Network

Wireless body area networks (WBANs) are emerging as one of the newest forms of Wireless Sensor Networks. In WBANs, sensor nodes accumulate human physiological data and transmit it to the sink node. However, transmission of physiological data to the sink node over a mobile route becomes a very daunting task for sensors due to their limited battery power. Moreover, replacement of critical sensor nodes is a major challenge in such scenarios. In order to increase network lifetime, some routing protocols have been proposed in the literature, but the majority of them are focused on coverage distance and residual energy of sensor nodes. In this work, we will propose an energy efficient routing algorithm for WBANs that will take into consideration two additional attributes (node criticality and communication count) along with the above stated attributes. These four parameters in the proposed algorithm will result in enhancement of working lifetime of the network via less energy consumption in comparison to existing routing protocols.

Transmission of Secured Image using DWT-SVD Technique for Applications in Wireless Sensor Network

Wireless sensor networks hold the promise of facilitating large-scale and real-time data processing in complex environments. These networks are used in a variety of applications including military, surveillance, industry and health systems. Sensors used in these applications can be susceptible to various types of attacks such as data modification, data insertion and deletion, or even physical capture and sensor node replacement. Therefore, security is a critical issue that must be resolved. This paper presents the transmission of secured image using DWT-SVD image hiding technique. Initially, both the carrier image and the secret image are decomposed according to DWT (Discrete Wavelet Transform) and then the secret image is embedded in singular values of the carrier image by applying SVD (Singular Value Decomposition). An Energy saving greedy algorithm is applied for routing the resultant secured image in the form of packets. Experimental results and performance analysis demonstrate that the proposed scheme can protect the sensitive information without affecting the transmission and usability of the ordinary data.

A Python-based Interface for Wide Coverage Lexicalized Tree-adjoining Grammars

Abstract This paper describes the design and implementation of a Python-based interface for wide coverage Lexicalized Tree-adjoining Grammars. The grammars are part of the XTAG Grammar project at the University of Pennsylvania, which were hand-written and semi-automatically curated to parse real-world corpora. We provide an interface to the wide coverage English and Korean XTAG grammars. Each XTAG grammar is lexicalized, which means at least one word selects a tree fragment (called an elementary tree or etree). Derivations for sentences are built by combining etrees using substitution (replacement of a tree node with an etree at the frontier of another etree) and adjunction (replacement of an internal tree node in an etree by another etree). Each etree is associated with a feature structure representing constraints on substitution and adjunction. Feature structures are combined using unification during the combination of etrees. We plan to integrate our toolkit for XTAG grammars into the Python-based Natural Language Toolkit (NLTK: nltk.org). We have provided an API capable of searching the lexicalized etrees for a given word or multiple words, searching for a etree by name or function, display the lexicalized etrees to the user using a graphical view, display the feature structure associated with each tree node in an etree, hide or highlight features based on a regular expression, and browsing the entire tree database for each XTAG grammar.

Node replacement graph grammars with dynamic node relabeling

The paper introduces node replacement graph grammars with dynamic node relabeling as an extension of the eNCE families of graph grammars. Initiated by NLC grammars in which graph embedding is based on node labels only, node distinction of the embedded graph extended NLC grammars to NCE grammars and dynamic edge relabeling further extended NCE grammars to eNCE grammars. Now, dynamic node relabeling, the node counterpart of the dynamic edge relabeling, is introduced as the next extension, which we call neNCE. The paper analyzes basic language-theoretical properties of the neNCE system.

Energy Efficient Sensor Activation for Water Distribution Networks Based on Compressive Sensing

The recent development of low cost wireless sensors enables novel internet-of-things (IoT) applications, such as the monitoring of water distribution networks. In such scenarios, the lifetime of the wireless sensor network (WSN) is a major concern, given that sensor node replacement is generally inconvenient and costly. In this paper, a compressive sensing-based scheduling scheme is proposed that conserves energy by activating only a small subset of sensor nodes in each timeslot to sense and transmit. Compressive sensing introduces a cardinality constraint that makes the scheduling optimization problem particularly challenging. Taking advantage of the network topology imposed by the IoT water monitoring scenario, the scheduling problem is decomposed into simpler subproblems, and a dynamic-programming-based solution method is proposed. Based on the proposed method, a solution algorithm is derived, whose complexity and energy-wise performance are investigated. The complexity of the proposed algorithm is characterized and its performance is evaluated numerically via an IoT emulator of water distribution networks. The analytical and numerical results show that the proposed algorithm outperforms state-of-the-art approaches in terms of energy consumption, network lifetime, and robustness to sensor node failures. It is argued that the derived solution approach is general and it can be potentially applied to more IoT scenarios such as WSN scheduling in smart cities and intelligent transport systems.

Performance Evaluation of Least Disruptive Topology Repair Algorithm (Ledir) Using Ns-2

In wireless sensor networks, sensor nodes fail either when some critical event occurs at the node or when the battery of the nodes is completely drained. If the remaining nodes in the sensor network are not aware of the node failure, the network might under undergo significant broadcast delay and path loss. An alarm packet has to be broadcast throughout the network when any critical event occurs and the transmission path must be recovered to achieve better quality of service in the sensor network. This paper utilizes least disruptive topology repair (LeDir) algorithm to minimize the power consumption and to handle such critical events. LeDir algorithm is used to recover the transmission path and to ensure that the quality of service issues in the network is met. The variations in the throughput, roundtrip time, broadcast delays and packet delivery ratio of the network are observed by performing multiple NS-2 simulations. It is observed that the throughput of the network could be quickly regained when the transmission path is recovered by node replacement.

Energy efficient fast predictor for WSN-based target tracking

Power source replacement of the sensor nodes, which are once deployed in the network area, is generally difficult. So, energy saving is one of the most important issues for object tracking in wireless sensor networks. To reduce the consumed energy and prolong the network lifetime, the nodes surrounding the mobile object should be responsible for sensing the target. The number of participant nodes in target tracking can be reduced by an accurate prediction of the object location. In this paper, we present a fast energy efficient with high-accuracy target tracking scheme which is based on location prediction. The missing rate of proposed predictor is very low in comparison with other predictors especially in a random waypoint mobility model in which after pause time, the three main parameters direction, velocity and, acceleration would be changed. The accuracy of predictor has a direct effect on missing rate and so strongly reduces the consumed energy. Additionally, a new node selection criterion is proposed in which minimum nodes surrounding the object are wakened and track the object. Simulation results show that our proposed predictor has low consumed energy and complexity in comparison with Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) predictors.