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Topic Review
Routing Protocols for Mobile IoT
IoT (Internet of Things) is the connection of devices to the Internet where devices are able to communicate with each other and their users, such as cameras, medical sensors, light-bulbs, and smoke alarms. IoT allows devices to assist daily routines, such as cars can be synced with calendars for appointment or meeting tracking to plan the best routes. According to the research done by IDC, there are already 13 billion connected devices in use worldwide in 2017 and the number could reach over 40 billion by 2025.
  • 726
  • 15 Oct 2021
Topic Review
Routing Protocol for Wireless Sensor Networks
Wireless sensor networks (WSNs), constrained by limited resources, demand routing strategies that prioritize energy efficiency. The tactic of cooperative routing, which leverages the broadcast nature of wireless channels, has garnered attention for its capability to amplify routing efficacy.
  • 360
  • 18 Dec 2023
Topic Review
Routing Protocol for Low Power and Lossy Network
The IETF Routing Over Low power and Lossy network (ROLL) working group defined IPv6 Routing Protocol for Low Power and Lossy Network (RPL) to facilitate efficient routing in IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN). Limited resources of 6LoWPAN nodes make it challenging to secure the environment, leaving it vulnerable to threats and security attacks. Machine Learning (ML) and Deep Learning (DL) approaches have shown promise as effective and efficient mechanisms for detecting anomalous behaviors in RPL-based 6LoWPAN.
  • 3.9K
  • 19 May 2022
Topic Review
Routing in the Data Center
To have adequate routing and forwarding, it is imperative to fully exploit the topological characteristics of fat trees. Some basic requirements should be satisfied: forwarding loops avoidance, rapid failure detection, efficient network utilization (e.g., spanning-tree solutions are not acceptable), routing scalability (in addition to physical scalability). In principle, being the data center a single administrative domain, the candidates to fulfill the routing role are popular link-state IGPs. However, as they have been designed for arbitrary topologies, the flood of link-state advertisements may suffer from scalability issues. Therefore, the possible solutions should entail reducing the message flooding, exploiting the topology knowledge, or using other routing algorithms. In this regard, the following routing protocols will be considered in this work: BGP with a specific configuration for the data center, link-state algorithms with flooding reduction, and ongoing Internet Engineering Task Force (IETF) efforts, namely Routing in Fat Trees (RIFT) and Link State Vector Routing (LSVR), which are leveraging link-state and distance-vector advantages to design specific routing algorithms for data centers.This entry only consider distributed control plane solutions, i.e., routing protocols. Consequently, logically centralized Software-Defined Networking (SDN) solutions are not analyzed.
  • 777
  • 27 Jan 2022
Topic Review
Rosetta Stone
Rosetta Stone Language Learning is proprietary, computer-assisted language learning (CALL) software published by Rosetta Stone Inc, part of the IXL Learning family of products. The software uses images, text, and sound to teach words and grammar by spaced repetition, without translation. Rosetta Stone calls its approach Dynamic Immersion. The software's name and logo allude to the ancient stone slab of the same name on which the Decree of Memphis is inscribed in three writing systems. IXL Learning acquired Rosetta Stone in March 2021.
  • 681
  • 24 Oct 2022
Topic Review
Root-Finding Algorithm
In mathematics and computing, a root-finding algorithm is an algorithm for finding zeroes, also called "roots", of continuous functions. A zero of a function f, from the real numbers to real numbers or from the complex numbers to the complex numbers, is a number x such that f(x) = 0. As, generally, the zeroes of a function cannot be computed exactly nor expressed in closed form, root-finding algorithms provide approximations to zeroes, expressed either as floating point numbers or as small isolating intervals, or disks for complex roots (an interval or disk output being equivalent to an approximate output together with an error bound). Solving an equation f(x) = g(x) is the same as finding the roots of the function h(x) = f(x) – g(x). Thus root-finding algorithms allow solving any equation defined by continuous functions. However, most root-finding algorithms do not guarantee that they will find all the roots; in particular, if such an algorithm does not find any root, that does not mean that no root exists. Most numerical root-finding methods use iteration, producing a sequence of numbers that hopefully converge towards the root as a limit. They require one or more initial guesses of the root as starting values, then each iteration of the algorithm produces a successively more accurate approximation to the root. Since the iteration must be stopped at some point these methods produce an approximation to the root, not an exact solution. Many methods compute subsequent values by evaluating an auxiliary function on the preceding values. The limit is thus a fixed point of the auxiliary function, which is chosen for having the roots of the original equation as fixed points, and for converging rapidly to these fixed points. The behaviour of general root-finding algorithms is studied in numerical analysis. However, for polynomials, root-finding study belongs generally to computer algebra, since algebraic properties of polynomials are fundamental for the most efficient algorithms. The efficiency of an algorithm may depend dramatically on the characteristics of the given functions. For example, many algorithms use the derivative of the input function, while others work on every continuous function. In general, numerical algorithms are not guaranteed to find all the roots of a function, so failing to find a root does not prove that there is no root. However, for polynomials, there are specific algorithms that use algebraic properties for certifying that no root is missed, and locating the roots in separate intervals (or disks for complex roots) that are small enough to ensure the convergence of numerical methods (typically Newton's method) to the unique root so located.
  • 10.3K
  • 14 Oct 2022
Topic Review
Root System of a Semi-simple Lie Algebra
In mathematics, there is a one-to-one correspondence between reduced crystallographic root systems and semisimple Lie algebras. Here the construction of a root system of a semisimple Lie algebra – and, conversely, the construction of a semisimple Lie algebra from a reduced crystallographic root system – are shown.
  • 503
  • 17 Nov 2022
Topic Review
Root Name Server
A root name server is a name server for the root zone of the Domain Name System (DNS) of the Internet. It directly answers requests for records in the root zone and answers other requests by returning a list of the authoritative name servers for the appropriate top-level domain (TLD). The root name servers are a critical part of the Internet infrastructure because they are the first step in translating (resolving) human readable host names into IP addresses that are used in communication between Internet hosts. A combination of limits in the DNS and certain protocols, namely the practical size of unfragmented User Datagram Protocol (UDP) packets, resulted in a decision to limit the number of root servers to thirteen server addresses. The use of anycast addressing permits the actual number of root server instances to be much larger, and is 1,086 (As of July 2020).
  • 1.7K
  • 03 Nov 2022
Topic Review
Rooftop Solar Photovoltaic Systems
Rooftop solar photovoltaic (PV) retrofitting can greatly reduce the emissions of greenhouse gases, thus contributing to carbon neutrality. Retrofitting distributed rooftops with solar PV is an effective means of promoting “carbon peaking” and “carbon neutral” strategies. Rooftop solar PV is geographically unrestricted. The PV cells can be closely integrated into buildings without taking up additional land resources, not only saving land resources but also improving their utilization rate.
  • 581
  • 12 Jul 2022
Topic Review
Role of Visual Tools in Understanding Mathematical Culture
The term mathematical culture’ cannot be naturally defined; we will understand it in the same way as ‘good mathematics’ is understood by, i.e., good ways of solving mathematical issues, good mathematical techniques, good mathematical applications and cultivating of mathematical insight, creativity and beauty of mathematics. Cultivation of a mathematical culture means teaching how to see the roots of mathematics in reality (in nature, in society, but also in mathematics itself), getting to know the world of mathematical concepts, understanding this world and being able to apply it in a cultivated and correct way when solving various problems.
  • 213
  • 25 Jul 2023
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