Address Assignment Research Articles

Exploiting Spatial Ionic Dynamics in Solid-State Organic Electrochemical Transistors for Multi-Tactile Sensing and Processing.

The human nervous system inspires the next generation of sensory and communication systems for robotics, human-machine interfaces (HMIs), biomedical applications, and artificial intelligence. Neuromorphic approaches address processing challenges; however, the vast number of sensors and their large-scale distribution complicate analog data manipulation. Conventional digital multiplexers are limited by complex circuit architecture and high supply voltage. Large sensory arrays further complicate wiring. An 'in-electrolyte computing' platform is presented by integrating organic electrochemical transistors (OECTs) with a solid-state polymer electrolyte. These devices use synapse-like signal transport and spatially dependent bulk ionic doping, achieving over 400 times modulation in channel conductance, allowing discrimination of locally random-access events without peripheral circuitry or address assignment. It demonstrates information processing from 12 tactile sensors with a single OECT output, showing clear advantages in circuit simplicity over existing all-electronic, all-digital implementations. This self-multiplexer platform offers exciting prospects for circuit-free integration with sensory arrays for high-quality, large-volume analog signal processing.

The Comprehensive Review: Internet Protocol (IP) Address a Primer for Digital Connectivity

The Internet Protocol (IP) is the rule book that governs how data is addressed and routed across networks on the internet. Think of it as the postal system for the digital world. This addressing system allows routers, the digital mail carriers, to efficiently transfer packets between devices and networks until they reach their destination. It ensures data reaches the right place by assigning addresses and enabling efficient routing. IP also encompasses various protocols and services, such as ICMP (Internet Control Message Protocol) for error reporting and diagnostics, and DHCP (Dynamic Host Configuration Protocol) for automatic IP address assignment. Additionally, IP can be configured to support different transmission modes, including uni-cast, multicast, and broadcast, catering to diverse communication requirements. Adopting technology that has been researched and developed commercially offers the military a cost-effective method of implementation. IP systems enable the forces to share a common network that supports voice, video, and data sharing. This systematic review article initially highlighted the basics on IP and lastly the brief discussion regards data gram format, NAT, IPv4, IPV6 IP fragmentation, CIDR, TCP and UDP individually.

Analytical Subnetwork and IP Alias Resolution for Network Tomography Using Path Traces

Mapping of link-level network topologies requires the processing of collected raw traces, including the resolution of alias IPs of router interfaces and underlying subnetworks. There have been several probing techniques for IP alias resolution along with an analytical resolution approach which relies on the IP address assignment practices. The analysis of IP address assignments can also reveal the underlying subnetworks, i.e., the link-level connectivity among the routers. In this paper, we present a comprehensive Analytical Subnetwork and Alias IP Resolution (ASIAR) method that relies on the analytical analysis of path traces to infer underlying subnetworks and router interfaces. While ASIAR increases the efficiency of the analytical resolution method, it integrates additional sanity checks and performs parameter adjustment based on the topology sampling characteristics to improve the resolution accuracy. We explore how different network sampling issues affect the analytical resolution, and analyze the accuracy of the ASIAR on synthetic and genuine networks. Compared with the state-of-the-art analytical resolution method, ASIAR is able to increase both precision and recall by fine-tuning the parameters of sanity checks used for analytical subnetwork and IP alias resolution.

Fault detection and identification in induction motor using weightless neural network.

This paper presents a novel multiclass, multiparameter real-valued weightless neural network-based classifier for fault detection and identification. In contrast to primitive variants of weightless neural nets, the proposed method is capable of multiclass identification with real-valued input features and has improved recognition and generalization capabilities. The major accomplishments of the proposed method include an improved input-to-address mapping strategy that is suitable for address assignment within discriminator units and an effective memory expansion scheme based on similarity metric-based membership value. The developed classifier is utilized for fault detection and identification in single-phase and three-phase induction motors. The sensitivity analysis of the method is investigated for design parameter variation and the fault diagnosis is performed for multiple faults of the motor. The proposed method achieves the highest accuracy of 99.6% and 89.25% for single-phase and three-phase induction motor fault identification, respectively.

Efficient dynamic IP datacasting mobility management based on LRS in mobile IP networks

IP mobility support is based on terminal behavior, recognizing mobility and maintaining a continuous communication session. The existing mobile IP location registration sends a message to one or more routers during a handoff within a domain by using a multicast address to process messages continuously. This implementation requires persistent message processing among all routers to determine new multicast address assignments. To solve this problem, we propose a method that enables the mobile user to obtain a QoS guarantee when the mobile device moves to an overlapping area under the mobile IP. Therefore, dynamic mobility management includes location updates under the mobile IP, and transmission of packets from the expected access points. When a handoff occurs while the mobile device is connected, the mobile host dynamically adapts to the mobility characteristics of the mobile node and transmits missed packets. In addition, by first using a location router, handoff latency reduction and packet loss requirements between domains in the overlapping mobile network environment are resolved. Second, the proposed algorithm has low-control traffic in the mobile network, allowing quick handoffs. Although instantaneous throughput is reduced during handoffs, tunneling is reduced by 10-30%, even after a handoff, by retransmitting packets missed by the mobile host, while location-registration-update times are reduced by 20-80%.

Machine Learning Based Resilience Testing of an Address Randomization Cyber Defense

Moving target defenses (MTDs) are widely used as an active defense strategy for thwarting cyberattacks on cyber-physical systems by increasing diversity of software and network paths. Recently, machine Learning (ML) and deep Learning (DL) models have been demonstrated to defeat some of the cyber defenses by learning attack detection patterns and defense strategies. It raises concerns about the susceptibility of MTD to ML and DL methods. In this paper, we analyze the effectiveness of ML and DL models when it comes to deciphering MTD methods and ultimately evade MTD-based protections in real-time systems. Specifically, we consider a MTD algorithm that periodically randomizes address assignments within the MIL-STD-1553 protocol—a military standard serial data bus. Two ML and DL-based tasks are performed on MIL-STD-1553 protocol to measure the effectiveness of the learning models in deciphering the MTD algorithm: 1) determining whether there is an address assignments change i.e. whether the given system employs a MTD protocol and if it does 2) predicting the future address assignments. The supervised learning models (random forest and k-nearest neighbors) effectively detected the address assignment changes and classified whether the given system is equipped with a specified MTD protocol. On the other hand, the unsupervised learning model (K-means) was significantly less effective. The DL model (long short-term memory) was able to predict the future addresses with varied effectiveness based on MTD algorithm's settings.

Probability without Tears

This article is about teaching probability to students of philosophy who don’t aim to do primarily formal work in their research. These students are unlikely to seek out classes about probability or formal epistemology for various reasons, for example because they don’t realize that this knowledge would be useful for them or because they are intimidated by the material. However, most areas of philosophy now contain debates that incorporate probability, and basic knowledge of it is essential even for philosophers whose work isn’t primarily formal. In this article, I explain how to teach probability to students who are not already enthusiastic about formal philosophy, taking into account the common phenomena of math anxiety and the lack of reading skills for formal texts. I address course design, lesson design, and assignment design. Most of my recommendations also apply to teaching formal methods other than probability theory.

THE IMPACT OF COMBINING FOLLOW-UP QUESTIONS AND WORKED EXAMPLES IN PROGRAM VISUALIZATION TOOL ON IMPROVING STUDENTS’ HELD MENTAL MODELS OF POINTERS’ VALUE AND ADDRESS ASSIGNMENT

Previous studies have shown that the lack of a useful mental model of pointers is one of the reasons why many novice programmers fail the data structures course. This study had two main objectives: to analyze the status of mental models of pointers (focusing on value and address assignment); and to evaluate the impact of combining worked-examples and follow-up questions in CeliotM program visualization (PV) tool in the learning of pointers. The subjects of the study were sixty-two second-year undergraduate students taking a course on data structures (PMT 221) at the College of Natural and Mathematical Sciences (CNMS) of the University of Dodoma. Data were collected using pretest and posttest questionnaires. The collected data were analyzed using descriptive statistics. The results showed that 56.5% of the students had incorrect mental models of pointers. The results also showed that using the proposed strategy improved the students’ mental models of pointers from 56.5% to 87.1%. These results contribute to our understanding of the most common misconceptions that novice students may have when learning pointers. The findings of this study confirm previous studies that when the new innovative teaching strategies are used in combination with PV tools in teaching and learning programming can help improve students’ programming comprehension.

An Intelligent Caching Strategy Considering Time-Space Characteristics in Vehicular Named Data Networks

In the Internet of Vehicles (IoV), the classic TCP/IP still plays an important role for data transmission, traffic control and address assignment. However, with increasing requirements on content retrieve efficiency in IoV, the drawbacks of traditional TCP/IP stacks, such as weak scalability in large networks, low efficiency in dense environment and unreliable addressing in high mobility circumstance, have incurred significant performance degradations in vehicular environments. Fortunately, the emerging Named Data Network (NDN) technology provides a good choice to address above issues in vehicular environment by proving content caching capability with introduced content store module, and boosts the research activity of Vehicular Named Data Network (VNDN) in the last few years. In this paper, to improve the service performance, e.g., reducing the delay of data acquisition, a data caching scheme is proposed by taking the spatial-temporal characteristics of data into account. At first, we divided the data in a VNDN into emergency safety message, traffic efficiency message and service message, according to the application requirements. Then, we analyze the spatial-temporal characteristics of these three message categories and design the caching strategy according to these characteristics. Experimental results from NDNSim platform show that our designed scheme has an approximately 50% performance enhancement compared with Leave Copy Everywhere (LCE), Pro(0.7), and Pro(0.2) data caching protocols in terms of average hit rate, average hop count and average cache replacement times, which verifies the reliability and effectiveness of our proposed data caching scheme.

Sinusoidal Current Signal-Based Fire Detection System with Automatic Address Assignment

In this paper, a novel sinusoidal current signal-based fire detection system is proposed with automatic address assignment. The system model employs a conventional power line to embed fire information, i.e., the address, rather than using an additional communication line. At the transmitter, different frequencies of the sinusoidal current signal are combined and transmitted through a power line. At the receiver, fast Fourier transform (FFT) is applied to distinguish the frequency bins, which can represent the addresses of fire detectors. The proposed system model is implemented and the numerical results are presented in terms of measurements.

Design and Implementation of ID Based MANET Autoconfiguration Protocol

Auto-configuration protocols are used for assignment of unique IP addresses to nodes in Mobile ad hoc networks. Without the assignment of unique IP addresses, service provisioning between the nodes is not possible. Such protocols use various heuristics to ensure the uniqueness in IP address assignment; such aspects increase the overall complexity in MANET system design. Moreover the overriding role of IP address as an ID in Application layer and Locator in routing space is a bottleneck in future wireless network (FWN) design. Contemporary FWN research is focusing on ID/Locator split concept designs. In this paper we propose an ID/Locator based architecture for MANETs which also solves auto-configuration requirements for MANETs. Our proposed architecture is an adaptation from available ID/Locator split concepts for infrastructure oriented networks for usage in MANET context. The designed protocol uses identifiers for node identification, node discovery and traffic flow between end points. The protocol support provision for running contemporary IP oriented services. We have also verified various use cases of our proposed protocol through Linux based implementation.

DETERMINATION OF OPTIMISED PICK-UP AND DROP-OFF LOCATIONS IN TRANSPORT ROUTING – A COST DISTANCE APPROACH

With the emergence of dynamic passenger transport systems, such as demand-responsive transport (DRT) and ride-sharing without predetermined stop locations as used for static bus routes, accurate routing for these flexible door-to-door transport services is needed. Routing between two addresses requires the assignment of addresses to suitable, so-called snapping points as reference points on the road network. Therefore, many conventional routing machines use perpendicular distance to identify the nearest point on the road network. However, this technique tends to produce inaccurate results if the access to a building is not reachable from the road segment with the shortest perpendicular distance. We provide a novel approach to identify the access to buildings (paths) based on remote sensing data to obtain more reasonable stop locations for passenger transport. Multispectral images, OpenStreetMap data, and light detection and ranging (LiDAR) data were used to perform a cost distance analysis based on vegetation cover, building footprints, and the slope of the terrain to identify such optimised stop locations. We assumed that the access to buildings on the shortest route to the building’s entrance consists of little vegetation cover and minimal slope of the terrain; furthermore, the calculated path should not cross building footprints. Thus, snapping points on the road network can be determined based on the most likely path between a building and the road network. We validated our results based on a predetermined ideal snapping area considering different weightings for the parameters slope, vegetation, and building footprints. The results were compared with a conventional routing machine that uses perpendicular distance. This routing machine shows a validation rate of 81.4%, whereas the validation rate of our presented approach is as high as 90.3%. This new approach provides increased accuracy and better comfort for flexible passenger transport systems.

An efficient mechanism to detect and mitigate an ARP spoofing attack in software-defined networks

The work focuses on software-defined network security, as it was always one of these foremost critical concerns due to the centralized nature in SDN architecture where many serious attacks in traditional networks still appear in SDN networks such as ARP spoofing attack despite many existing security algorithms, methods and systems. In this work, we proposed a new approach to secure SDN from an ARP poisoning attack. The new solution extends the controller with a new module that uses a new algorithm to detect and mitigate the ARP spoofing attacks according to three states of each host in the network. The new mechanism involves the DHCP and manual assignment of IP addresses using three classes to classify the hosts according to their situations in the network. The CHT helps to set the host in an intermediate state between verifying and banning and detect the attack according to the next step of the host. The proposed mechanism was tested successfully in a simulated environment using Mininet and POX controller. The solution was effectively able to accomplish the objective for which it was built, with a limited overhead on the network. This proposed solution neither has an extra overload in the network, nor requires any changes in the infrastructure or additional hardware to install. According to the experiment results of this solution, the average time to detect the ARP spoofing attack is about 11 ms, with minor overhead on the controller CPU.

An Iontronic Multiplexer Based on Spatiotemporal Dynamics of Multiterminal Organic Electrochemical Transistors

AbstractThe seamless integration of electronics with biology requires new bio‐inspired approaches that, analogously to nature, rely on the presence of electrolytes for signal multiplexing. On the contrary, conventional multiplexing schemes mostly rely on electronic carriers and require peripheral circuitry for their implementation, which imposes severe limitations toward their adoption in bio‐applications. Here, a bio‐inspired iontronic multiplexer based on spatiotemporal dynamics of organic electrochemical transistors (OECTs), with an electrolyte as the shared medium of communication, is shown. The iontronic system discriminates locally random‐access events with no need of peripheral circuitry or address assignment, thus deceasing significantly the integration complexity. The form factors of OECTs that allow for intimate biointerfacing as well as the electrochemical nature of the communication medium, open new avenues for unconventional multiplexing in the emerging fields of bioelectronics, wearables, and neuromorphic computing or sensing.

Design of Remote Environmental Monitoring Network Based on Intelligent Sensor Network Address Allocation and Addressing

Based on the wireless sensor network, this paper combines node monitoring data with intelligent network address management. Users can view real‐time environmental data through a computer or mobile phone and can manually remotely manage the environmental adjustment equipment of the network address through the mobile phone. This article first discusses the research background of the subject, introduces the current domestic and foreign research status of WSN in environmental detection, and analyzes the reasons for choosing ZigBee network as the wireless transmission environment of the intelligent monitoring system. Secondly, the structure, layered model, and key technologies of wireless sensor networks are introduced, and it is pointed out that ZigBee technology, which has the characteristics of low power consumption, reliable communication, self‐organization of the network, strong self‐healing ability, and low cost, is very suitable for application in the environment. Then, it analyzes TI’s protocol stack Z‐Stack based on the ZigBee2006 standard and analyzes the network address assignment and addressing in Z‐Stack, the process and steps of node binding, the routing mechanism and routing maintenance, and channel configuration. The realization of other functions was discussed in depth. During the simulation experiment, in the hardware design of the intelligent monitoring system, the network node was divided into two parts: the core board and the backplane. The crystal oscillator, power supply, antenna, and I/O port circuits of the core board were designed, and the data acquisition, relay, and power supply of the backplane were designed. Finally, this paper studies the data security issues in the environmental monitoring network and proposes two solutions to control network access and data encryption. Experimental results show that in terms of low‐power design, the energy of the entire system is calculated to determine the factors that affect the power consumption of the system and methods such as increasing the node sleep time to ensure that the system can work for a long time.

Space‐address decoupled scratchpad memory management for neural network accelerators

SummaryDeep neural networks have been demonstrated to be useful in varieties of intelligent tasks, and various specialized NN accelerators have been proposed recently to improve the hardware efficiency, which are typically equipped with software‐managed scratchpad memory (SPM) for high performance and energy efficiency. However, traditional SPM management techniques cause memory fragmentation for NN accelerators, and thus lead to low utilization of precious SPM. The main reason is that traditional techniques are originally designed for managing fixed‐length registers rather than variable‐length memory blocks. In this article, we propose a novel SPM management approach for NN accelerators. The basic intuition is that NN computation/memory behaviors are predictable and relatively regular compared with traditional applications, and thus most information can be determined at compile time. In addition, by exploiting the variable‐length feature of SPM, we propose to divide the allocation process into two passes: the space assignment and the address assignment pass, which are simultaneously (and implicitly) performed in traditional one‐pass allocation techniques. Experimental results on the memory requests of a representative NN accelerator demonstrate that the proposed approach can significantly reduce the memory consumption by 30% at most compared with state‐of‐the‐art SPM management techniques, and the memory usage is only 2% larger than that of the theoretical optimal allocation.

IPoE based campus network IPv4/IPv6 dual-stack admission control design and implementation

With the expansion of the campus network, various security risks have appeared. Most campus networks have implemented AAA, but seldom implemented admission control, which decreases the efficiency of dynamic allocation of IP addresses and makes it possible for users to avoid traffic billing. In order to realize the admission control of IPv4/IPv6 dual-stack network in large-scale campus network, we design and implement IPoE-based dual-stack admission control for the campus network in Tsinghua University. In IPoE, users can obtain IP address by DHCP with Ethernet physical link access. Authentication is achieved through a variety of user authentication methods. IP packets are encapsulated in Ethernet and pass through the access network to BRAS devices. BRAS devices find the user's address assignment information based on the client hardware address and the current Vlan ID after receiving the client's DHCP confirmation request message. Our main contributions include: for the various application scenarios under unified IPv4/IPv6 network, session-level IPoE technology is proposed; with the application of different configuration template in different protocol stack, various account control policy is submitted to AAA servers to achieve multi-type, multi-scenario requirements; to deal with the risk in large scale campus network, BRAS, AAA server, DHCP server can cooperate to realize that only authorized users are permitted to obtain addresses, thus avoid the security threats from unauthorized users; to cope with the high load pressure under large-scale deployment, the whitelist of webportal configured on the BRAS side reduces the load on webportal servers. The actual deployment shows that the dual-stack access authentication system has achieved the design objectives and runs smoothly.

Toward Resilient Wireless Sensor Networks: A Virtualized Perspective.

The Internet of Things (IoT) has been one of the main focus areas of the research community in recent years, the requirements of which help network administrators to design and ensure the functionalities and resources of each device. Generally, two types of devices—constrained and unconstrained devices—are typical in the IoT environment. Devices with limited resources—for example, sensors and actuators—are known as constrained devices. Unconstrained devices includes gateways or border routers. Such devices are challenging in terms of their deployment because of their connectivity, channel selection, multiple interfaces, local and global address assignment, address resolution, remote access, mobility, routing, border router scope and security. To deal with these services, the availability of the IoT system ensures that the desired network services are available even in the presence of denial-of-service attacks, and the use of the system has become a difficult but mandatory task for network designers. To this end, we present a novel design for wireless sensor networks (WSNs) to address these challenges by shifting mandatory functionalities from unreliable to reliable and stable domains. The main contribution of our work consists in addressing the core network requirements for IoT systems and pointing out several guidelines for the design of standard virtualized protocols and functions. In addition, we propose a novel architecture which improves IoT systems, lending them more resilience and robustness, together with highlighting and some important open research topics.

Unregulated Open Enrollment and Inequitable Access to Schools of Choice

ABSTRACT In severing the link between residential address and school assignment, school choice policies have the potential to decrease school segregation and increase educational equity. Yet this promise is undermined when school choice creates greater opportunity for those who are already privileged while limiting access to students from historically marginalized groups. This study combines data from a new survey of local open enrollment policies in Metro Detroit, student-level administrative records, and geographic data to critically analyze the local discretion provided in Michigan’s interdistrict school choice policy in relation to the goals of access to schools of choice, desegregation, and educational equity. I found that local school districts implement provisions of state policy in ways that restrict access to Black and economically disadvantaged students while creating pathways of opportunity for others. Districts are incentivized to implement these restrictions because of the inequities built into the state school funding formula and the racialized geography of Metro Detroit that is mechanized in district and county boundaries to restrict access. This study has implications for the regulation of local school choice markets and the role they play in increasing equitable public school opportunities.

Overall-transparent dynamic identifier-mapping mechanism against scanning and worm propagation in the SINET

Static assignment of IP addresses or identifiers can be exploited by an adversary to attack a network. However, existing dynamic IP address assignment approaches suffer from two limitations, namely: participation of terminals in the assignment and inadequate network server management. Thus, in this paper, we propose an Overall-transparent Dynamic Identifier-mapping Mechanism (ODIM) to manage the identifier of network nodes to defend against scanning and worm propagation in the Smart Identifier NETwork (SINET). We establish the selection and allocation constraints, and present selection and allocation algorithms to determine the constraints. The non-repetition probability and cover cycle allow us to evaluate the defense efficiency against scanning. We propose the probability for routing identifiers and derive the defense efficiency of ODIM against worm propagation. Simulation results and theoretical analysis show that the proposed method effectively reduces the detection probability of Routing IDentifiers (RIDs) and thus improves defense capabilities against worm propagation.