Active Network Nodes Research Articles

Multi-Objective Reactive Power Optimization for Distribution Networks Based on the Modified Golden Eagle Algorithm

The Golden Eagle algorithm was proposed in 2020 by Abdolkarim et al. and has been applied in several fields. In this paper, we introduce the proposed algorithm to the reactive power optimization problem for distribution networks and develop a dual-objective reactive power optimization model with active network loss and node voltage bias. Logistic chaotic mapping and Levy flights are introduced to improve the original algorithm, which is prone to local optima and slow convergence. Finally, the IEEE30 node system is used for testing, which verifies the feasibility of the proposed algorithm in the reactive power optimization problem, and the improved algorithm has faster convergence and higher solution accuracy.

Estimating Traffic Rates in CSMA/CA Networks: A Feasibility Analysis for a Class of Eavesdroppers

Estimation of transmission rates by a malicious user can serve as a stepping stone to further attacks on the network. In this paper, we aim to investigate the general problem of estimating traffic transmission rates in a CSMA/CA network using a class of passive eavesdropping methods. We consider the case where a single eavesdropper passively monitors all active network nodes but cannot observe all packet transmissions due to spatial-reuse collisions. To enable tractable analysis, we first propose an approximate statistical model that can help the eavesdropper estimate transmission rates with partial measurements under spatial reuse. We next consider a class of eavesdroppers that become increasingly more capable, and develop a framework to demonstrate that two classes of eavesdropper capabilities are sufficient to achieve a consistent transmission rate estimator. We provide numerical tests of our proposed estimators under practical network cases using the NS-3 simulator that validate the theoretical results.

The Partition Bridge (PB) tree: Efficient nearest neighbor query processing on road networks

With the rapid development of location-based services, many types of applications in urban areas such as transportation planning, traffic management, and deployment of infrastructure depend on spatial objects that are distributed along the road network. As current place datasets include millions of spatial objects and human mobility datasets capture billions of locations, it is an important challenge to answer k-nearest neighbor queries efficiently. However, shortest-path distance calculations are the computational bottleneck for a k-nearest neighbor queries on road networks. Existing query algorithms partition the network to mitigate this bottleneck, but they do not take the data distribution into account, which leads to inefficiencies in dense areas and sparse areas. In this paper, an efficient and scalable indexing method called the Partition Bridge tree (PB-tree), is proposed based on hierarchical network partitions that consider network connectivity and data distribution. The structure of the PB-tree mainly includes distance matrices, union-bridges, bridges, and active network nodes component. Based on the PB-tree, a k nearest neighbor query processing algorithm is proposed by combining “bottom-up”, “top-down”, and adjacent extension methods. By using different road networks and datasets, the effectiveness and practicability of PB-tree are evaluated; the experimental results show that PB-tree outperforms the state-of-the-art methods and the classical approach.

Revisiting the System Energy Footprint and Power Efficiency on the Way to Sustainable 6G Systems

It is expected that the 6G architecture will bring much better network economics and energy efficiency through a heterogeneous architecture that natively blurs the boundary between dedicated network infrastructure and devices. In this context, we foresee that 6G devices will not only be communication endpoints, but they will also be able to act as active network nodes in a data path. As the impetus of climate change calls for a sustainable 6G system design approach toward carbon neutrality, it is time to revisit the power management strategies across devices and networks in cellular systems in a fundamental and holistic manner.

A graph neural network method for distributed anomaly detection in IoT

Recent IoT proliferation has undeniably affected the way organizational activities and business procedures take place within several IoT domains such as smart manufacturing, food supply chain, intelligent transportation systems, medical care infrastructures etc. The number of the interconnected edge devices has dramatically increased, creating a huge volume of transferred data susceptible to leakage, modification or disruption, ultimately affecting the security level, robustness and QoS of the attacked IoT ecosystem. In an attempt to prevent or mitigate network abnormalities while accommodating the cohesiveness among the involved entities, modeling their interrelations and incorporating their structural, content and temporal attributes, graph-based anomaly detection solutions have been repeatedly adopted. In this article we propose, a multi-agent system, with each agent implementing a Graph Neural Network, in order to exploit the collaborative and cooperative nature of intelligent agents for anomaly detection. To this end, against the propagating nature of cyber-attacks such as the Distributed Denial-of-Service (DDoS), we propose a distributed detection scheme, which aims to monitor efficiently the entire network infrastructure. To fulfill this task, we consider employing monitors on active network nodes such as IoT devices, SDN forwarders, Fog Nodes, achieving localization of anomaly detection, distribution of allocated resources such as the bandwidth and power consumption and higher accuracy results. In order to facilitate the training, testing and evaluation activities of the Graph Neural Network algorithm, we create simulated datasets of network flows of various normal and abnormal distributions, out of which we extract essential structural and content features to be passed to neighbouring agents.

Improving sensitivity of self-powered room temperature NO2 sensor by triboelectric-photoelectric coupling effect

Nitrogen dioxide sensors with high sensitivity and low energy consumption are demanded for atmosphere sensing networks. Here, a self-powered room temperature NO2 sensor has been developed based on the conjugation between the triboelectric and photoelectric effect. By converting the mechanical motions into electricity, a triboelectric nanogenerator (TENG) serves as a power source to simultaneously drive chemoresistive gas sensing and UV illumination. Under a 5 Hz external impact, the output voltage drop across interdigital electrodes has a proportional relationship with the NO2 concentration. A self-powered optomechatronic gas sensor (OGS) with hydrothermal ZnO nanowires synthesized at a concentration of 0.035 mol/l exhibits a superior response (∼14.8) and sensitivity (0.302 ppm−1) than those synthesized at other concentrations. Furthermore, the influence of the external force frequency and rectification on the gas sensing properties was systematically investigated. It is found that the TENG induced built-in electric field can effectively modulate the internal quantum efficiency and thus the sensing performance of OGSs. This work not only paves the way for constructing self-powered optomechatronic devices and systems but also pushes forward the active multifunctional network node for environmental monitoring.

Dynamic analysis of rumor spreading model for considering active network nodes and nonlinear spreading rate

Rumor spreading is an important form of social communication, and it will cause unnecessary panic and conflict to society. This paper aims to investigate the combined impact of the internal and external factors on the efficiency of rumor spreading over the social networks. In this paper, firstly, a modified ISR rumor spreading model on heterogeneous networks by taking into account the activity and infectivity of nodes and propagation environment was introduced. Then, through theoretical analysis, we derive the mean field equations with considering nonlinear spreading rate and active network nodes. Next, we calculate the basic reproduction number ℜ0 based on the next generation matrix method whose results reveal that if ℜ0<1, the rumor-free equilibrium is global asymptotically stable, the rumors will disappear. If ℜ0>1, the rumor-endemic equilibrium is global attractivity, then the number of spreaders will remain stable and the rumors will become endemic. Further, some numerical simulations are performed, which is consistent with the deterministic mean-field approach. Our results show that it is very important to consider the internal and external factors to control the spread of the rumors.

Approaches to detecting active network nodes in IPv6 address space

Approaches to detecting active network nodes in the IPv6 address space have been considered. Two principal families of approaches have been considered, i.e., with and without the initial sample.

The comparison of network congestion avoidance algorithms in data exchange networks.

Effective congestion control strategies allow in maintaining low delay and high throughput in data exchange networks. These requirements seem to be the most desired by network environment participants. Wide range of algorithms are proposed in the literature to approximate to these ideal parameters. All of these approaches are focused on alleviating the results of sudden, unexpected network state changes. This paper discuss a comparison of four control strategies, focused on congestion avoidance. All of them are in charge of queue length control in active network nodes. For research purpose, non-stationary, discrete, dynamical model of communication channel has been used. Research results are presented in table and chart form.

Belousov-Zhabotinsky autonomic hydrogel composites: Regulating waves via asymmetry.

Belousov-Zhabotinsky (BZ) autonomic hydrogel composites contain active nodes of immobilized catalyst (Ru) encased within a nonactive matrix. Designing functional hierarchies of chemical and mechanical communication between these nodes enables applications ranging from encryption, sensors, and mechanochemical actuators to artificial skin. However, robust design rules and verification of computational models are challenged by insufficient understanding of the relative importance of local (molecular) heterogeneities, active node shape, and embedment geometry on transient and steady-state behavior. We demonstrate the predominance of asymmetric embedment and node shape in low-strain, BZ-gelatin composites and correlate behavior with gradients in BZ reactants. Asymmetric embedment of square and rectangular nodes results in directional steady-state waves that initiate at the embedded edge and propagate toward the free edge. In contrast, symmetric embedment does not produce preferential wave propagation because of a lack of diffusion gradient across the catalyzed region. The initiation at the embedded edge is correlated with bromide absorption by the inactive matrix, which locally elevates the bromate concentration required for catalyst oxidation. The competition between embedment asymmetry and node geometry was used to demonstrate a repeatable switch in wave direction that functions as a signal delay. Furthermore, signal propagation in or out of the composite was demonstrated via embedment asymmetry and relative dimensions of a T-shaped active network node. Overall, structural asymmetry provides a robust approach to controlling initiation and orientation of chemical-mechanical communication within composite BZ gels.

Congestion Management in Modern Power System Containing Active Distribution Network Nodes

This article presents a novel methodology to determine a transmission congestion management strategy for a power system containing active distribution network nodes. Constrained scheduling, used in traditional pools, has been utilized. A bi-level optimization model is proposed to obtain the optimal congestion management strategy by rescheduling the distributed generators inside active distribution network nodes. The upper-level optimization model determines the generation rescheduling in the main grid and the load adjustment of each active distribution network node to relieve the congestion. The lower-level optimization model aims at minimizing load adjustment cost in the upper level by rescheduling the distributed generators. The proposed bi-level optimization model is transformed into an equivalent single-level optimization model through application of Karush–Kuhn–Tucker optimality conditions. Three heuristic algorithms—particle swarm optimization, cat swarm optimization, and clonal selection algorithm—have been applied to solve the equivalent single-level optimization problem. The effectiveness of the proposed methodology has been tested on a modified system using the IEEE 30-bus system as the main network and the IEEE 14-bus system as the active distribution network node. The results obtained by the particle swarm optimization algorithm have been compared with those obtained by cat swarm optimization and clonal selection algorithms.

Ensembles of dynamic systems in active wireless networks

Generalized wireless sensor network (active sensor networks) are considered as a multicomponent processor platform whereby the behavior of interacting dynamic systems is simulated. During the simulation process, each node of the sensor network is represented as a dynamic system. The equations of the system are solved using a specialized computing device (microcontroller) located in each network node. The interaction between dynamic systems is performed so that system state data are transmitted over radio channels between active network nodes. The simulation scheme is investigated by the example of an ensemble of coupled logistic maps. This ensemble is experimentally implemented in the network comprising PPS-43 direct chaotic transceivers equipped with actuator boards, which include microcontroller to iterate maps and a display unit to visualize information (colored light-emitting diode). The simulation technique is described, experimental results are presented, and their analysis is accomplished.

Adaptive Mobility Management Framework Using Active Proxy Node

In mobile computing, mobility management is a fundamental issue. The substance of mobility management are proxy and forwarding based model to achieve, the difference of a variety of technologies are the choice which proxy and forwarding entity is chosen and what strategy to implement proxy and forwarding services. The paper propose a basic framework based on mobile agent technology forwarding proxy migration, combined with a mechanism for automatic proxy service deployment for mobile environments by using active network nodes, collaborative support to complete the optimization proxy services, which has a unique advantage of dynamic execution, reducing the switching overhead, improving efficiency of the system and showing good applied characteristics.

Relocation routing for energy balancing in mobile sensor networks

AbstractWireless sensor networks (WSNs) have been widely investigated in the past decades because of its applicability in various extreme environments. As sensors use battery, most works on WSNs focus on energy efficiency issues (e.g., local energy balancing problems) in statically deployed WSNs. Few works have paid attention to the global energy balancing problem for the scenario that mobile sensor nodes can move freely. In this paper, we propose a new routing protocol called global energy balancing routing protocol (GEBRP) based on an active network framework and node relocation in mobile sensor networks. This protocol achieves global energy efficiency by repairing coverage holes and replacing invalid nodes dynamically. Simulation and experiment results demonstrate that the proposed GEBRP achieves superior performance over the existing scheme. In addition, we analyze the delay performance of GEBRP and study how the delay performance is affected by various system parameters.Copyright © 2013 John Wiley &amp; Sons, Ltd.

Extended Mobile IPv6 Route Optimization for Mobile Networks in Local and Global Mobility Domain

Network mobility (NEMO) route optimization support is strongly demanded in next generation networks; without route optimization the mobile network (e.g., a vehicle) tunnels all traffic to its Home Agent (HA). The mobility may cause the HA to be geographically distant from the mobile network, and the tunneling causes increased delay and overhead in the network. It becomes peculiar in the event of nesting of mobile networks due to pinball routing, for example, a Personal Area Network (PAN) inside a vehicle. The authors propose an Extended Mobile IPv6 route optimization (EMIP) scheme to enhance the performance of nested mobile networks in local and global mobility domain. The EMIP scheme is based on MIPv6 route optimization and the root Mobile Router (MR) performs all the route optimization tasks on behalf of all active Mobile Network Nodes (MNNs). Thus, the network movement remains transparent to sub MRs and MNNs and modifies only MRs and MNNs leaving other entities untouched and is more efficient than the Network Mobility Basic Support protocol (NEMO BS). The authors carried out an extensive simulation study to evaluate the performance of EMIP.

Deployment and management of component-based services in active networks

This paper describes an integrated architecture for deployment and management of component-based services on heterogeneous programmable and active network nodes. The approach allows for flexible handling of active services on a fine-grained level thanks to the full component orientation and the application of mature concepts commonly used in enterprise software systems. The main features of the proposed solution are: a hierarchical component service model, two-tiered service deployment architecture with separated network-level and node-level deployment requirement resolution engines, out-of-band node-level-controlled code distribution on demand, as well as deployment and management support for heterogeneous multi-plane distributed active services. The architecture has been implemented and experimentally evaluated within the FAIN project.

Lightweight thread tunnelling in network applications

Active Network nodes allow for non-trivial processing of data streams. These complex network applications typically benefit from protection between their components for fault-tolerance or security. However, fine-grained memory protection introduces bottlenecks in communication among components. This paper describes memory protection in Expert, an OS for programmable network elements which re-examines thread tunnelling as a way of allowing these complex applications to be split over multiple protection domains. We argue that previous problems with tunnelling are symptoms of overly general designs, and we demonstrate a minimal domain-crossing primitive which nevertheless achieves the majority of benefits possible from tunnelling.

An introduction to active network node operating systems

article Share on An introduction to active network node operating systems Author: Parveen Patel View Profile Authors Info & Claims XRDS: Crossroads, The ACM Magazine for StudentsVolume 9Issue 2December 2002 pp 21–26https://doi.org/10.1145/904067.904072Published:01 December 2002Publication History 0citation291DownloadsMetricsTotal Citations0Total Downloads291Last 12 Months5Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

The price of safety in an active network

Security is a major challenge for “Active Networking,” as accessible programmability creates numerous opportunities for mischief. The point at which programmability is exposed, e.g., through the loading and execution of code in network elements, must therefore be carefully crafted to ensure security. The SwitchWare active networking research project has studied the architectural implications of various tradeoffs between performance and security. Namespace protection and type safety were achieved with a module loader for active networks, ALIEN, which carefully delineated boundaries for privilege and dynamic updates. ALIEN supports two extensions, the Secure Active Network Environment (SANE), and the Resource Controlled Active Network Environment (RCANE). SANE extends ALIEN's node protection model into a distributed setting, and uses a secure bootstrap to guarantee integrity of the namespace protection system. RCANE provides resource isolation between active network node users, including separate heaps and robust time-division multiplexing of the node. The SANE and RCANE systems show that convincing active network security can be achieved. This paper contributes a measurement-based analysis of the costs of such security with an analysis of each system based on both execution traces and end-to-end behavior.

Janos: a Java-oriented OS for active network nodes

Janos is an operating system (OS) for active network nodes whose primary focus is strong resource management and control of untrusted active applications written in Java. Janos includes the three major components of a Java-based active network operating system: the low-level NodeOS, a resource-aware Java virtual machine, and an active network protocol execution environment. Each of these components is separately usable. This article lays out the Janos design and its rationale.