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Computer Science

Demystifying Kubernetes: A Comprehensive Guide to Container Orchestration

Demystifying Kubernetes A Comprehensive Guide to Container Orchestration

What is Kubernetes?

Kubernetes (K8s) is an open-source platform that facilitates the execution of containerized applications in a virtual environment via Application Program Interfaces (APIs). Containerized applications are programs that are executed in containers. Containers are the virtual entities that hold the primary code for the execution of an application, its dependencies of that application and the configuration files of that application. Containerized applications are widely adapted because they facilitate the execution of multiple applications in a single host by isolating them from the core Operating System. This makes Kubernetes a go-to for users/developers to test, assess, and deploy their applications.

Kubernetes Architecture

Kubernetes employs a Master-Slave architecture. Kubernetes Cluster is divided into two separate planes:

i. Control Plane: Also known as the Master Node, the Control plane can be interpreted as the brains of Kubernetes. It is the policy maker that applications executed in Kubernetes clusters have to follow. It consists of:

a. API server: The API server is the entity that authenticates and authorizes a developer and allows interaction between the developer and Kubernetes Cluster. The API server configures and manipulates entities in the data plane via Kubernetes Controller-Manager, Kubernetes Scheduler, and Key-Value Store (Etcd).
b. Kubernetes Controller-Manager: It is the entity in the Control Plane that is responsible for keeping the system in a desired state, as per the instructions obtained from the API server. It constantly monitors the containers, Pods, and Nodes and tweaks them to bring them to the desired state.
c. Kubernetes Scheduler: It is the entity in the Control plane responsible for deploying applications in Worker Nodes received through the API server. It schedules the applications as per their requirements of resources, like memory, identifies suitable Pods, and places them in suitable Worker Nodes in the Kubernetes Clusters.
d. Key-Value Store (Etcd): It is a storage that can be placed within the control plane or independent of it. Key-value Store, as the name suggests, stores all the data of the Kubernetes Cluster, i.e., it provides a restore point to the whole of the Kubernetes Cluster.

ii. Data Plane: The Data Plane is a cluster of Kubernetes Worker Nodes that executes the policies made by the Control plane for the smooth operation of applications within the Kubernetes Cluster. Worker nodes are the machines that run containerized applications and provide the necessary resources for the applications to run smoothly. Each Worker Node consists of:
a. Kubelet: Kubelet is the entity within the Worker Node that is responsible for connecting that node with the API server in the Control Plane and reporting the status of Pods and containers within the node. This facilitates the resources assigned to that node to become a part of the Kubernetes Cluster. It is also responsible for the execution of works received from the API server to keep the node in a desired state by making the necessary changes as per API server instructions.
b. Kube-proxy: It is responsible for routing traffic from the users through the Internet to the correct applications within a node by creating/altering traffic routing policies for that node.
c. Pods:  Pods are the entities in the Worker Node that have containers within them. Although it is possible to host multiple application instances in a Pod, running one application instance in one Pod is recommended. Pods are capable of horizontal scaling, i.e., they are created according to the application instance needs. If assigned node resources are available, Pods can utilize more resources than assigned to them- if needed. Pods, along with containers, are capable of running on multiple machines. The resources of the Pods are shared among the containers it hosts.

HBM Layout: Deploying an Application in Kubernetes

HBM Layout (Source: Medium)

Deploying an Application in Kubernetes:

i. The developer should have a Service account. This account is needed to authenticate and authorize a developer. Also, this service account is used for authentication against the API server when the application needs access to protected resources.

Kubernetes Service Account Requirement

Service Account Requirement (Source: Medium)

ii. Create a new Node or select an existing node according to the application requirement (memory, RAM, etc).

iii. The intended application should be packed in a Docker image or similar container format. A Docker image is a software package that has all the necessary programs, dependencies, runtimes, libraries, and configuration files for an application to run smoothly.

iv. The developer should define Kubernetes Manifest as a YAML or JASON file. The Kubernetes Manifest defines the desired state for the application to be deployed. It consists of:
a. Configmaps: As the name suggests, Configmaps have configuration data of the application to be deployed. It has supporting configurations, like environment variables for the intended application. The total size of this data is less than 1MB.
b. Secrets: Kubernetes secrets are similar to Configmaps, but hold secure information. They hold supporting files, like passwords, for the application that is to be deployed.
c. Deployments: Deployments define the procedure of creating and updating application instances for the application to be deployed.
d. Kubernetes Service: It is the entity that assigns an IP address or hostname to the application that is to be deployed. When the assigned name is matched to a user’s search string, the application is presented to the user through the internet via Kube Proxy.

v. The developer places the Docker image through the Kubernetes API server. The API server pulls the Docker image to create the containers in the Pods, to deploy the intended application.

vi. Once the intended application is deployed in the pods, the developer can monitor, update, change, and edit the application as per the requirement through Kubectl from the developers’ service account through the API server in the control panel.

Kubernetes Deployment Flow

Deployment Flow (Source: Polarsquad)

Categories
Automotive

LiDAR Technology in Autonomous Vehicles

LiDAR Technology in Autonomous Vehicles

Introduction:

LiDAR, an acronym for “light detection and ranging” or “laser imaging, detection, and ranging” is a sensor used for determining ranges by targeting an object or a surface with a laser and measuring the time for the reflected light to return to the receiver. With the functionality of scanning its environment, it is also sometimes called 3D laser scanning. Particularly, LiDAR image registration (LIR) is a critical task that focuses on techniques of aligning or registering lidar point cloud data with corresponding images. It involves two types of data that have different properties and may be acquired from different sensors at different times or under different conditions. With an accurate alignment of LiDAR point clouds and captured 2D images, the registration method results in the most informative understanding of the environment with fine details.

How does LiDAR work?

The working methodology of LiDAR includes sending a pulse of light and waiting for the return. It measures the total time period i.e. how long it takes to return the pulse. This finally assists in figuring out the distance between objects.

LiDAR Sensor Representation for Autonomous Vehicle

Fig. 1. Working of LiDAR

Application Areas of LiDAR
The fusion of LiDAR point clouds and camera images is a popular example of Multi-Remote Sensing Image Registration (MRSIR). As of today, LiDAR is of various types and forms such as static and mobile LiDARs. According to the geographical use, LiDAR is of terrestrial, aerial, and marine kinds.
The application of LiDAR is very broad. It has uses in surveying, archaeology, geology, forestry, and other fields such as:

  • Autonomous driving: LIR is used to align sensor data to create a more accurate and complete representation of the environment.
  • Robotics: Align sensor data to create more accurate maps and enable more precise localization.
  • 3D mapping: Align data from multiple sensors to create detailed 3D models of the environment.
  • Augmented Reality (AR): Synchronizing virtual elements to correspond with the physical environment.

Utilization of LiDAR in Self-Driving Vehicles

3D Point Cloud and Calculation of Distance
In the realm of road safety, numerous automobile manufacturers are either using or exploring the installation of LiDAR technology in their vehicles.

LiDAR Technology in Self-Driving Vehicles

Fig. 1. LiDAR Technology in Self-Driving Vehicles [Source: https://velodynelidar.com/what-is-lidar/#:~:text=A%20typical%20lidar%20sensor%20emits,calculate%20the%20distance%20it%20traveled]

By iterating this process multiple times within seconds, a detailed, live 3D representation of the environment is generated, referred to as a point cloud.

Advantages of Mounting Lidar Above Autonomous Vehicles
Within an autonomous vehicle, the LiDAR sensor captures extensive data through rapid analysis of numerous laser pulses. This information, forming a ‘3D point cloud‘ from laser reflections, undergoes processing by an integrated computer to generate a dynamic three-dimensional representation of the surroundings. Training the onboard AI model with meticulously annotated point cloud datasets becomes pivotal to ensuring the precise creation of this 3D environment by LiDAR. The annotated data empowers autonomous vehicles to detect, identify, and categorize objects, enhancing their ability to accurately discern traffic lanes, road signs, and moving entities, and evaluate real-time traffic scenarios through image and video annotations.
Beyond research, active exploration delves into the use of LiDAR technology within autonomous vehicles. Automakers have begun integrating LiDAR into advanced driver assistance systems (ADAS), enabling a comprehensive grasp of dynamic traffic conditions. The journey toward autonomous driving safety relies on these systems, which swiftly make precise decisions through meticulous analysis of vast data points, ensuring security through rapid computations.

Cutting-edge approaches
However, there still are challenges in developing a fully automated vehicle with a guarantee of 100% accuracy in critical tasks such as object detection and navigation. To overcome this challenge, many researchers and automobile companies have been trying to improve this technology. The cutting-edge approaches include broadly categorized architecture of methodologies involving four distinct pipelines: information-based pipeline, feature-based pipeline, ego-motion-based pipeline, and deep learning-based pipeline. There has been more accuracy and improvement in the sector of deep learning-based pipelines. LiDAR technology not only enhances convenience but also plays a pivotal role in reducing severe collisions. The latest advancements in this domain include the innovation of LiDAR sensors and the shift from traditional mechanical methods to cutting-edge FMCW and flash technologies.

Patenting Trends for LiDAR Technology in Autonomous Vehicles

The field of autonomous vehicle technology has witnessed a notable rise in patent submissions, especially concerning sensor technology, mapping techniques, decision-making algorithms, and communication systems. Pioneering the advancements are entities such as Google, Tesla, and Uber, whereas longstanding automotive giants like Ford, General Motors, and BMW have also been actively filing patents. In the United States, a significant emphasis lies on artificial intelligence (AI) and augmented reality within the market, with car manufacturers and developers collaborating to introduce self-driving vehicles to the public. Autonomous cars are predicted to change the driving experience and introduce a whole new set of problems.
Despite Sartre’s initial patent submission in the autonomous vehicle domain, it was perceived primarily as a patent related to an AI system designed for highway navigation or restricted roadways. There was a scarcity of US patent filings for self-driving cars before 2006, largely influenced by a trend that emerged in the late 1990s and persists today: a limited number of patents granted by the US Patent Office.

Challenges in Patenting Technology for Autonomous Vehicles
The challenges in patenting technology for self-driving vehicles emerge when these vehicles are involved in incidents or insurance-related events. Owners typically confront three choices:

  1. Assuming liability for any harm or property damage caused by their vehicle.
  2. Taking steps toward legal recourse against the involved driver.
  3. Exploring compensation from their insurance company to address losses resulting from the other driver’s negligence.
    However, legislative uncertainty still clouds the landscape concerning autonomous vehicles and traffic incidents.

Analysis of Patent Applications filed under Lidar in Autonomous Vehicles
Over the past few years, there has been a rapid growth in filing Patent Applications regarding the use of LiDAR in Autonomous Vehicles. As of today, it is marked that there are ~81,697 patents recorded around the globe. It has been observed that Ford Global Tech LLC with ~3,426 patents is a dominant player in the market. Similarly, LG Electronics and Waymo LLC stand in second and third position in the chart.

Analysis of Patent Applications filed under Lidar in Autonomous Vehicles

[Source: https://www.lens.org/lens/search/patent/list?q=LiDAR%20%20%2B%20Autonomous%20vehicle]
The following visual representations show the charts representing Legal Status and Patent Documents Over Time.

Legal Status and Patent Documents Over Time.
Patent Documents Over Time

[Source: https://www.lens.org/lens/search/patent/list?q=LiDAR%20%20%2B%20Autonomous%20vehicle]

Through an examination of patent filings across different geographic regions, it is evident that the United States, constituting approximately 78% of the overall patents submitted, holds the foremost position in this chart.

patent filings across different geographic regions

[Source: https://www.lens.org/lens/search/patent/list?q=LiDAR%20%20%2B%20Autonomous%20vehicle]

Conclusion

In conclusion, LiDAR technology used in self-driving vehicles has a huge scope in improving road safety. With the cutting-edge FMCW and flash technologies, the application of LiDAR in autonomous vehicles shows great improvements in terms of accuracy and comfort providing features like object detection and incredible navigation. Automobile companies such as Tesla and Toyota have already practiced the technology in their vehicles and companies having such huge turnovers are seeking forward to utilize the full potential of the technology. Technology holds the future of global advancement in technology.

Categories
Computer Science

Unlocking Blockchain: Unveiling the Patent Landscape of Decentralized Innovation

Unlocking Blockchain: Unveiling the Patent Landscape of Decentralized Innovation

Introduction:

Blockchain is a revolutionary invention that is transforming businesses and changing how we think about value exchange in the ever-evolving digital ecosystem. With the ability to secure financial transactions and promote supply chain transparency, decentralized ledger technology has enormous promise. Come us on a voyage where we’ll delve in`to the significance, the implications for intellectual property, and developing trends of blockchain technology.

Decoding Core technology and Principles

Blockchain technology is an innovative approach to digital transaction management and recordkeeping. It is predicated on the idea of a distributed database kept up to date by a computer network, known as a decentralised ledger. This implies that the ledger is not under the control of a single, central authority, making it extremely safe and impenetrable.

At the foundation of a blockchain are units of data called Blocks. A record of all transactions and a special code known as a hash are included in every block. To link blocks together and guarantee that the ledger is unchangeable, utilise the hash, which is a cryptographic fingerprint of the block.

A mathematical function known as a hash function is used to construct Hashes. This function accepts a chunk of data as input and outputs a distinct value known as a hash. No matter how long the input data is, the hash is always the same length. Because of this feature, hashes are incredibly helpful for safeguarding blockchain ledgers.

By the way of example: Let’s imagine a business that tracks the delivery of its goods using blockchain technology. A new block is added to the blockchain whenever a product is sent. The block includes details on the package, including the tracking number, origin, and destination. The new block also contains the hash from the preceding block. As a result, a blockchain, or chain of blocks, is created. The blockchain cannot be tampered as the hashes are distinct and unforgeable. The hash of a block will no longer match the hash of the previous block if someone tries to alter the data in that block and the block will be refused as a result of alerting the network to the manipulation.
Blockchain is a sophisticated technology that has a wide range of possible uses. Though it’s still in the early stages of development, it might completely change how we interact with digital information.

The core principles are:

Decentralization: Blockchain works by utilizing a peer-to-peer network to do away with middlemen and create a trustless environment in which users authenticate and record transactions together.
Cryptography: Blockchain guarantees the security and integrity of data recorded on the distributed ledger by utilizing cutting-edge cryptographic algorithms. Cryptography protects transactions against unauthorized changes or tampering by ensuring their authenticity and immutability.
Smart Contracts: Smart contracts, sometimes referred to as self-executing contracts, automate and enforce pre-established rules inside the blockchain network. These self-activating contracts improve productivity across a range of applications, simplify procedures, and increase transparency.

Unveiling the Inner Workings of Blockchain

Unveiling the Inner Workings of Blockchain

Delving into the intricacies of blockchain technology necessitates a thorough understanding of its fundamental components:

Transaction Verification: The validation procedure is activated when a transaction is started, like sending bitcoin to another user. Network participants, or nodes, are involved in this process. Depending on the kind of blockchain (public or private), nodes can be either computers or people. These nodes carefully review the transaction to make sure it is legitimate and follows the rules of the blockchain.
Consensus Mechanisms: Consensus mechanisms are the cornerstone of blockchain operation. They are protocols created to promote agreement among all nodes in the network regarding the state of the blockchain at any given time. The proof-of-work (PoW) process is used in public blockchains like Bitcoin to reach this consensus. In order to be rewarded with Bitcoin and the ability to add a new block to the blockchain, miners compete to solve challenging mathematical riddles.
Immutable Integrity: The immutability of data on the blockchain ensures its permanence. A block’s contents are unchangeable once it is uploaded to the blockchain. Cryptographic hashing, a method that creates a distinct fingerprint for every block, protects this immutability. To change any of the data in a block, one would have to change the fingerprints of every block that came after it, which is not a computationally realistic process.

Advantages of Blockchain

  • The groundwork for cryptocurrencies, blockchain technology has proven to be a game-changer with uses that extend well beyond the financial sector. Its irrevocable and decentralised nature promises to change our interactions with digital assets and reshape industries, among many other benefits. The increased security of blockchain is one of its most enticing features. Blockchain disperses data over a network of linked computers, in contrast to conventional centralised systems, making it almost impervious to hackers and unauthorised changes. This strong security structure is especially helpful in protecting private data, such bank account details and health records.
  • Blockchain promotes traceability and transparency never seen before. Every transaction on the blockchain is documented in an unchangeable ledger that is available to all network users. Because of its transparency, a process can be followed and validated at every stage, which encourages responsibility and thwarts fraud. Decentralization structure of blockchain allows peer-to-peer transactions possible, which does away with the necessity for middlemen. It also lowers expenses, simplifies procedures, and gives people more authority over their assets and data.
  • The adaptability of blockchain goes beyond its technological capabilities. It encourages trust and cooperation amongst network users, which makes it possible for decentralized autonomous organizations (DAOs) to be established. These decentralized autonomous organizations (DAOs) function autonomously, relying on the agreement of its members to make decisions that are democratic and to create a feeling of shared ownership.


Navigating the Intellectual Property Landscape in the Blockchain Era

With the rapid development of blockchain technology, which has fundamentally altered how people see and use digital assets, a new era of innovation and transformation has begun. Equally rapidly advancing are the intellectual property (IP) concerns related to the development and application of this technology. This article examines the subtleties of managing the intellectual property (IP) environment in the blockchain age with an emphasis on significant trends, challenges, and opportunities.

Patent Trends in Blockchain Technology

Businesses are chasing patents on blockchain technology in an attempt to protect potentially revolutionary ideas. Blockchain technology has great promise for revolutionizing several industries, such as banking, healthcare, and supply chain management.


Decentralized Finance (DeFi)
The increasing interest in blockchain-based financial solutions is reflected in the remarkable growth of patent applications linked to decentralized finance (DeFi). DeFi protocols provide decentralized alternatives to centralized institutions with the goal of altering established financial systems. These developments include a wide range of DeFi topics, including as lending, borrowing, and trading protocols.

Interoperability
These days, innovations that improve blockchain interoperability are the main focus of patent applications. Interoperability is the capacity of many blockchain networks to easily exchange information and communicate with one another. This is necessary in order to facilitate cross-chain transactions and encourage widespread use of blockchain technology.

Blockchain Technology Patents: Crypto assets and Beyond

The graphs below show that for a number of years, there was an annual rise in the amount of patents filed for blockchain-related inventions, including crypto assets; however, activity has lately decreased due to various challenges in the field.

Patenting activity over the years

Patenting activity over the years (Source: insideglobaltech)


The main assignees of patent filings in the US and other nations in this field are shown in the charts below, respectively.

Major US Players in Blockchain patents

   Major US Players in Blockchain patents (Source: sagaciousresearch)

Top countries in blockchain patents in 2021

Top countries in blockchain patents in 2021 (Source: harrityllp)


Intellectual Property Challenges and Opportunities

While blockchain presents vast opportunities, navigating intellectual property challenges is crucial for sustainable innovation and growth. Key considerations include:


Open-Source Dynamics

A deliberate approach to intellectual property management is required because many blockchain initiatives are open source. When working in open-source settings, participants frequently share intellectual property rights, necessitating a delicate balance between invention protection and teamwork.

Patent Quality

To promote innovation and avoid overly broad claims, it is essential to ensure the quality of patents pertaining to blockchain technology. Patents that are too broad can stifle future innovation by limiting access to vital technology. The assessment of patent quality and its conformity to technological progress principles is largely dependent on the involvement of patent offices and industry specialists.


Current Trends and Future Trajectories

The versatility of blockchain technology is evident in its widespread adoption across various industries:


Supply Chain Management

Supply chain management is being revolutionized by blockchain technology, which improves transparency and traceability. Blockchain gives businesses the ability to follow the movement of commodities from point of origin to point of destination with an unprecedented level of precision and transparency by generating an unchangeable record of transactions. Improved traceability guarantees product legitimacy, keeps fake goods out of the market, and makes inventory management easier.

Healthcare

Blockchain is revolutionizing the healthcare sector by enhancing patient record accessibility, security, and data integrity. The tamper-proof and secure nature of blockchain guarantees the protection of sensitive patient data while facilitating easy access to vital medical information for authorized healthcare practitioners.

Integration with Emerging Technologies

Blockchain synergizes with other cutting-edge technologies to create innovative solutions that address a wide range of challenges.

Internet of Things (IoT)

IoT devices may share data with one other in a transparent and safe manner when blockchain and IoT are combined. In a variety of applications, including smart cities, industrial automation, and precision agriculture, this may help with real-time data processing, predictive maintenance, and automated decision-making.

Artificial Intelligence (AI)

Exploring how blockchain and AI interact might greatly improve data security and privacy. In addition to preserving the integrity and safety of sensitive data, blockchain’s decentralized and unchangeable structure may support AI’s data-driven insights by allowing AI models to function safely and independently.

Conclusion

The rapid advancement of blockchain technology necessitates careful consideration of the complexities of intellectual property (IP) management. Companies and people need to be proactive in navigating the distinct intellectual property (IP) landscape that surrounds blockchain breakthroughs in order to guarantee that their innovative concepts and works of art are suitably safeguarded. Through an awareness of the intricacies surrounding intellectual property in the context of blockchain technology, interested parties may make the most of this revolutionary tool, all the while protecting their proprietary knowledge and promoting a robust innovation community.