Central Point Of Failure Research Articles

Next-generation predictive maintenance: leveraging blockchain and dynamic deep learning in a domain-independent system.

The fourth industrial revolution, often referred to as Industry 4.0, has revolutionized the manufacturing sector by integrating emerging technologies such as artificial intelligence (AI), machine and deep learning, Industrial Internet of Things (IIoT), cloud computing, cyber physical systems (CPSs) and cognitive computing, throughout the production life cycle. Predictive maintenance (PdM) emerges as a critical component, utilizing data analytic to track machine health and proactively detect machinery failures. Deep learning (DL), is pivotal in this context, offering superior accuracy in prediction through neural networks' data processing capabilities. However, DL adoption in PdM faces challenges, including continuous model updates and domain dependence. Meanwhile, centralized DL models, prevalent in PdM, pose security risks such as central points of failure and unauthorized access. To address these issues, this study presents an innovative decentralized PdM system integrating DL, blockchain, and decentralized storage based on the InterPlanetary File System (IPFS) for accurately predicting Remaining Useful Lifetime (RUL). DL handles predictive tasks, while blockchain secures data orchestration. Decentralized storage safeguards model metadata and training data for dynamic models. The system features synchronized two DL pipelines for time series data, encompassing prediction and training mechanisms. The detailed material and methods of this research shed light on the system's development and validation processes. Rigorous validation confirms the system's accuracy, performance, and security through an experimental testbed. The results demonstrate the system's dynamic updating and domain independence. Prediction model surpass state-of-the-art models in terms of the root mean squared error (RMSE) score. Blockchain-based scalability performance was tested based on smart contract gas usage, and the analysis shows efficient performance across varying input and output data scales. A comprehensive CIA analysis highlights the system's robust security features, addressing confidentiality, integrity, and availability aspects. The proposed decentralized predictive maintenance (PdM) system, which incorporates deep learning (DL), blockchain technology, and decentralized storage, has the potential to improve predictive accuracy and overcome significant security and scalability obstacles. Consequently, this system holds promising implications for the advancement of predictive maintenance in the context of Industry 4.0.

Blockchain based Certificate Validation

Certificate management is a tedious task for any university or any other organization. These schemes impose problems in Public Key Infrastructure (PKI). Checking the validity and preserving the security of these documents is of utmost importance. In this work, we have devised a blockchain-based solution for preventing malfunctioning in certificate validation which is an important step for any university. Each certificate is uploaded in its hash format and is stored using blockchain. The hashes are stored in unique transactions in nodes, which are deployed on a private network. Using the SHA-256 hashing algorithm, the certificates are uploaded into the system and can be viewed by anyone with the right credentials. Due to the usage of blockchain technology, the certificates are stored in a decentralized manner, which ensures there is no central point of failure. Any changes in the uploaded document need to be validated by other nodes. This paper also improvises that when certificate uploading is required new nodes are added, instead of modifying the past blocks. This work provides a very user-friendly app where any user with the right credentials can upload documents. In this work, digitized documents are stored using Inter Planetary File System (IPFS) which is distributed method of storage. Our theoretical analysis proves that it is a user-friendly application with the security of blockchain technology in partnership with IPFS. Only the issuer can upload documents and others can only view them. Using our proposed solution, problem of malicious certificates can be tackled with E-certification. The proposed method solves all the issues of storing, validating, and sharing documents. Chaotic Map technique is used in hash generation which is quite simple to implement. The proposed approach Chaotic Key based Certificate validation (CK-Cert) provides a hassle-free solution for certificate managements since it better manages the block size as compared to previously proposed techniques (PBCert and CertChain) as discussed with the help of graphs.

Introduction to Cryptocurrency: An Overview

Cryptocurrency is one of the safest digital money. The currency has broader usage. Bitcoin and different sorts of tokens in addition to coins with all forms of cryptocurrency were utilized in India for a long term now. Cryptocurrency has no fund transfer limit, account of the people cannot be hacked and also there is no central point of failure. The transactions of these sites cannot be handled by a third party. Therefore this paper mainly focuses on secondary data to understand the concept, types, advantages, disadvantages, and legal status of cryptocurrency in India. The study found that cryptocurrency brought out an effective advancement to the sectors like e-business and e-payment. Nevertheless, the cryptocurrency had lack of trust yet. It is must to take adequate steps by the India Government to administer for making it safer, transparent and more trustworthy.

PETRI NETS MODELING FOR SDN TOPOLOGIES

The article examines some new algorithms and focuses mainly on suggesting new working topologies for software-defined controllers in order to ensure SDN security and to prevent the occurrence of a potential central point of failure (SPOF) by overcoming the centralization problem. This is a positive feature of the SDN structure, but could also be a threat, caused by the use of several controllers in different working topologies. This article focuses on exactly one of the suggested topologies, which features and models based on the Petri Nets system. The usual topology of a single controller is compared to verify the advantages and privileges of the proposed serial topology over the existing one. The paper tries to obtain a formula from the modeling of the serial topology and its advantages over the usual topology and that formula will be used to measure the level of security or the defense capacity of the network defined by the software against cyber attacks; in particular, denial of service attacks / distributed denial of service attacks / DDoS.

A Verified Session Protocol for Dynamic Service Chaining

Middleboxes are crucial for improving network security and performance, but only if the right traffic goes through the right middleboxes at the right time. Existing traffic-steering techniques rely on a central controller to install fine-grained forwarding rules in network elements—at the expense of a large number of rules, a central point of failure, challenges in ensuring all packets of a session traverse the same middleboxes, and difficulties with middleboxes that modify the “five tuple.” We argue that a session-level protocol is a fundamentally better approach to traffic steering, while naturally supporting host mobility and multihoming in an integrated fashion. In addition, a session-level protocol can enable new capabilities like dynamic service chaining, where the sequence of middleboxes can change during the life of a session, e.g., to remove a load-balancer that is no longer needed, replace a middlebox undergoing maintenance, or add a packet scrubber when traffic looks suspicious. Our Dysco protocol steers the packets of a TCP session through a service chain, and can dynamically reconfigure the chain for an ongoing session. Dysco requires no changes to end-host and middlebox applications, host TCP stacks, or IP routing. Dysco’s distributed reconfiguration protocol handles the removal of proxies that terminate TCP connections, middleboxes that change the size of a byte stream, and concurrent requests to reconfigure different parts of a chain. Through formal verification using Spin and experiments with our prototype, we show that Dysco is provably correct, highly scalable, and able to reconfigure service chains across a range of middleboxes.

Sink Location Protection Protocols Based on Packet Sending Rate Adjustment

Sink location protection is critical to the viability of sensor networks as the central point of failure. Most existing work related to sink location protection focuses on local traffic analysis attack. In this paper, we study the sink location protection problem under a more powerful type of attack, the global traffic analysis attack. In order to hide the sink location, a protocol based on packet sending rate adjustment (SRA) is proposed. By controlling the packet sending rate of each node according to the current number of source nodes, SRA conceals the real traffic volume generated by source nodes and hence disguises the location of the sink. For further reducing the communication cost, we propose a light weight SRA protocol (L-SRA), which protects the sink location while significantly decreasing the communication cost. Performance of both SRA and L-SRA has been validated by theoretical analysis and simulation results.

Running Jobs in the Vacuum

We present a model for the operation of computing nodes at a site using Virtual Machines (VMs), in which VMs are created and contextualized for experiments by the site itself. For the experiment, these VMs appear to be produced spontaneously "in the vacuum" rather having to ask the site to create each one. This model takes advantage of the existing pilot job frameworks adopted by many experiments. In the Vacuum model, the contextualization process starts a job agent within the VM and real jobs are fetched from the central task queue as normal. An implementation of the Vacuum scheme, Vac, is presented in which a VM factory runs on each physical worker node to create and contextualize its set of VMs. With this system, each node's VM factory can decide which experiments' VMs to run, based on site-wide target shares and on a peer-to-peer protocol in which the site's VM factories query each other to discover which VM types they are running. A property of this system is that there is no gate keeper service, head node, or batch system accepting and then directing jobs to particular worker nodes, avoiding several central points of failure. Finally, we describe tests of the Vac system using jobs from the central LHCb task queue, using the same contextualization procedure for VMs developed by LHCb for Clouds.

Virtual private social networks and a facebook implementation

The popularity of Social Networking Sites (SNS) is growing rapidly, with the largest sites serving hundreds of millions of users and their private information. The privacy settings of these SNSs do not allow the user to avoid sharing some information (e.g., name and profile picture) with all the other users. Also, no matter the privacy settings, this information is always shared with the SNS (that could sell this information or be hacked). To mitigate these threats, we recently introduced the concept of Virtual Private Social Networks (VPSNs). In this work we propose the first complete architecture and implementation of VPSNs for Facebook. In particular, we address an important problem left unexplored in our previous research—that is the automatic propagation of updated profiles to all the members of the same VPSN. Furthermore, we made an in-depth study on performance and implemented several optimization to reduce the impact of VPSN on user experience. The proposed solution is lightweight, completely distributed, does not depend on the collaboration from Facebook, does not have a central point of failure, it offers (with some limitations) the same functionality as Facebook, and apart from some simple settings, the solution is almost transparent to the user. Thorough experiments, with an extended set of parameters, we have confirmed the feasibility of the proposal and have shown a very limited time-overhead experienced by the user while browsing Facebook pages.

Robust implicit EDF

Advances in wireless technology have brought us closer to extensive deployment of distributed real-time embedded systems connected through a wireless channel. The medium-access control (MAC) layer protocol is critical in providing a real-time guarantee. We have devised a real-time wireless MAC protocol, robust implicit earliest deadline first, or RI-EDF. Packets are transmitted according to EDF scheduling rules, offering a protocol that implicitly avoids contention. In the event of a packet loss or a node failure, every node has the opportunity to recover the schedule based on a static recovery priority, offering a protocol that is robust with no central point of failure. We demonstrate in simulations that RI-EDF provides better goodput and lower packet loss than existing protocols like 802.11 PCF and EDCF. In our implementation and distributed control test-bed, we show that RI-EDF provides better throughput than the TinyOS MAC-layer protocol. Overall, RI-EDF provides predictable temporal behavior with minimal impact on node failures, packet losses, and noise in the channel.

Implementing aggregation and broadcast over Distributed Hash Tables

Peer-to-peer (P2P) networks represent an effective way to share information, since there are no central points of failure or bottleneck. However, the flip side to the distributive nature of P2P networks is that it is not trivial to aggregate and broadcast global information efficiently. We believe that this aggregation/broadcast functionality is a fundamental service that should be layered over existing Distributed Hash Tables (DHTs), and in this work, we design a novel algorithm for this purpose. Specifically, we build an aggregation/broadcast tree in a bottom-up fashion by mapping nodes to their parents in the tree with a parent function. The particular parent function family we propose allows the efficient construction of multiple interior-node-disjoint trees, thus preventing single points of failure in tree structures. In this way, we provide DHTs with an ability to collect and disseminate information efficiently on a global scale. Simulation results demonstrate that our algorithm is efficient and robust.