A NOVEL LINEAR DIOPHANTINE EQUATION-BAESD LOW DIAMETER STRUCTURED PEER-TO-PEER NETWORK

This research focuses on introducing a novel concept to design a scalable, hierarchical interest-based overlay Peer-to-Peer (P2P) system. We have used Linear Diophantine Equation (LDE) as the mathematical base to realize the architecture. Note that all existing structured approaches use Distributed Hash Tables (DHT) and Secure Hash Algorithm (SHA) to realize their architectures. Use of LDE in designing P2P architecture is a completely new idea; it does not exist in the literature to the best of our knowledge. We have shown how the proposed LDE-based architecture outperforms some of the most well established existing architecture. We have proposed multiple effective data query algorithms considering different circumstances, and their time complexities are bounded by (2+ r/2) only; r is the number of distinct resources. Our alternative lookup scheme needs only constant number of overlay hops and constant number of message exchanges that can outperform DHT-based P2P systems. Moreover, in our architecture, peers are able to possess multiple distinct resources. A convincing solution to handle the problem of churn has been offered. We have shown that our presented approach performs lookup queries efficiently and consistently even in presence of churn. In addition, we have shown that our design is resilient to fault tolerance in the event of peers crashing and leaving. Furthermore, we have proposed two algorithms to response to one of the principal requests of P2P applications’ users, which is to preserve the anonymity and security of the resource requester and the responder while providing the same light-weighted data lookup

HMS: A Hierarchical Mapping System for the Locator/ID Separation Network

The current Internet is facing serious scalability problems and the overloading of Internet Protocol (IP) addresses is regarded as an important reason. The Locator/ID Separation Protocol (LISP) is proposed as a network-based solution that separates IP addresses into Routing Locators (RLOCs) and Endpoint Identifiers (EIDs) to address the routing scalability problems. It is a critical challenge for LISP to design a scalable and efficient mapping system. In this paper, we propose a hierarchical mapping system (HMS). HMS consists of two levels with the bottom level maintaining the EID-to-RLOC mappings in an Autonomous System (AS) and the upper level storing the mappings between EID-prefixes and ASs in the global network. We adopt one-hop Distributed Hash Table (DHT) to organize EID-to-RLOC mappings in the bottom level and use a protocol like Border Gateway Protocol (BGP) to propagate EID-prefix-to-AS mappings in the upper level. HMS aggregates the prefixes in an AS and decreases the global mapping entries in the upper level. The evaluation results show that the number of mapping entries in HMS grows slower than the routing table size, which makes HMS scalable. In addition, the mobility in HMS does not cause mapping changes in the upper level. It makes HMS efficient in supporting host mobility. We estimate the map-requests sent to the mapping system, which show the load on HMS is small. Last, we compare HMS with LISP-TREE and LISP+ALT by quantitative analysis, in terms of resolution cost, and qualitative analysis. The results show that HMS has a good performance

Machine Learning and Data Mining Applications in Power Systems

This Special Issue was intended as a forum to advance research and apply machine-learning and data-mining methods to facilitate the development of modern electric power systems, grids and devices, and smart grids and protection devices, as well as to develop tools for more accurate and efficient power system analysis. Conventional signal processing is no longer adequate to extract all the relevant information from distorted signals through filtering, estimation, and detection to facilitate decision-making and control actions. Machine learning algorithms, optimization techniques and efficient numerical algorithms, distributed signal processing, machine learning, data-mining statistical signal detection, and estimation may help to solve contemporary challenges in modern power systems. The increased use of digital information and control technology can improve the grid’s reliability, security, and efficiency; the dynamic optimization of grid operations; demand response; the incorporation of demand-side resources and integration of energy-efficient resources; distribution automation; and the integration of smart appliances and consumer devices. Signal processing offers the tools needed to convert measurement data to information, and to transform information into actionable intelligence. This Special Issue includes fifteen articles, authored by international research teams from several countries

Review of name resolution and data routing for information centric networking

Information Centric Networking (ICN) a future Internet, presents a new paradigm by shifting the current network to the modern network protocols. Its goal, to improve the traditional network operations by enabling ICN packet routing and forwarding based on names.This shift will bring advantages, but at the same time, it is leading to a big challenge on routing approaches to implement ICN nodes. Routing approaches must use special techniques to publish messages to all the network nodes.Flooding approach is an easy and stateless, however, results in control overhead, depending on the network size.Moreover, designing, implementing, and evaluating routing approaches with higher capacity is really a key challenge in the overall ICN research area, because the state of ICN brings a significant cost; both in packet processing and router storage.Many approaches were proposed in the literatures over these years for the efficient control of forwarding on the network.This paper provides a classification and review of the routing mechanisms that are proposed on six ICN architectures.A summary in tabular form and a comparative study of these six architectures is also given in the paper as well as few open research challenges are highlighted

A Survey on Routing in Anonymous Communication Protocols

The Internet has undergone dramatic changes in the past 15 years, and now forms a global communication platform that billions of users rely on for their daily activities. While this transformation has brought tremendous benefits to society, it has also created new threats to online privacy, ranging from profiling of users for monetizing personal information to nearly omnipotent governmental surveillance. As a result, public interest in systems for anonymous communication has drastically increased. Several such systems have been proposed in the literature, each of which offers anonymity guarantees in different scenarios and under different assumptions, reflecting the plurality of approaches for how messages can be anonymously routed to their destination. Understanding this space of competing approaches with their different guarantees and assumptions is vital for users to understand the consequences of different design options. In this work, we survey previous research on designing, developing, and deploying systems for anonymous communication. To this end, we provide a taxonomy for clustering all prevalently considered approaches (including Mixnets, DC-nets, onion routing, and DHT-based protocols) with respect to their unique routing characteristics, deployability, and performance. This, in particular, encompasses the topological structure of the underlying network; the routing information that has to be made available to the initiator of the conversation; the underlying communication model; and performance-related indicators such as latency and communication layer. Our taxonomy and comparative assessment provide important insights about the differences between the existing classes of anonymous communication protocols, and it also helps to clarify the relationship between the routing characteristics of these protocols, and their performance and scalability

Intelligent query processing in P2P networks: semantic issues and routing algorithms

P2P networks have become a commonly used way of disseminating content on the Internet. In this context, constructing efficient and distributed P2P routing algorithms for complex environments that include a huge number of distributed nodes with different computing and network capabilities is a major challenge. In the last years, query routing algorithms have evolved by taking into account different features (provenance, nodes' history, topic similarity, etc.). Such features are usually stored in auxiliary data structures (tables, matrices, etc.), which provide an extra knowledge engineering layer on top of the network, resulting in an added semantic value for specifying algorithms for efficient query routing. This article examines the main existing algorithms for query routing in unstructured P2P networks in which semantic aspects play a major role. A general comparative analysis is included, associated with a taxonomy of P2P networks based on their degree of decentralization and the different approaches adopted to exploit the available semantic aspects.Fil: Nicolini, Ana Lucía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Lorenzetti, Carlos Martin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Maguitman, Ana Gabriela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; ArgentinaFil: Chesñevar, Carlos Iván. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentin