Implementation of a family of 2-3-4 trees in the hypercube

Computer Scienc

Optimising Structured P2P Networks for Complex Queries

With network enabled consumer devices becoming increasingly popular, the number of connected devices and available services is growing considerably - with the number of connected devices es- timated to surpass 15 billion devices by 2015. In this increasingly large and dynamic environment it is important that users have a comprehensive, yet efficient, mechanism to discover services. Many existing wide-area service discovery mechanisms are centralised and do not scale to large numbers of users. Additionally, centralised services suffer from issues such as a single point of failure, high maintenance costs, and difficulty of management. As such, this Thesis seeks a Peer to Peer (P2P) approach. Distributed Hash Tables (DHTs) are well known for their high scalability, financially low barrier of entry, and ability to self manage. They can be used to provide not just a platform on which peers can offer and consume services, but also as a means for users to discover such services. Traditionally DHTs provide a distributed key-value store, with no search functionality. In recent years many P2P systems have been proposed providing support for a sub-set of complex query types, such as keyword search, range queries, and semantic search. This Thesis presents a novel algorithm for performing any type of complex query, from keyword search, to complex regular expressions, to full-text search, over any structured P2P overlay. This is achieved by efficiently broadcasting the search query, allowing each peer to process the query locally, and then efficiently routing responses back to the originating peer. Through experimentation, this technique is shown to be successful when the network is stable, however performance degrades under high levels of network churn. To address the issue of network churn, this Thesis proposes a number of enhancements which can be made to existing P2P overlays in order to improve the performance of both the existing DHT and the proposed algorithm. Through two case studies these enhancements are shown to improve not only the performance of the proposed algorithm under churn, but also the performance of traditional lookup operations in these networks

Information sharing among ideal agents

Multi-agent systems operating in complex domains crucially require agents to interact with each other. An important result of this interaction is that some of the private knowledge of the agents is being shared in the group of agents. This thesis investigates the theme of knowledge sharing from a theoretical point of view by means of the formal tools provided by modal logic. More specifically this thesis addresses the following three points. First, the case of hypercube systems, a special class of interpreted systems as defined by Halpern and colleagues, is analysed in full detail. It is here proven that the logic S5WDn constitutes a sound and complete axiomatisation for hypercube systems. This logic, an extension of the modal system S5n commonly used to represent knowledge of a multi-agent system, regulates how knowledge is being shared among agents modelled by hypercube systems. The logic S5WDn is proven to be decidable. Hypercube systems are proven to be synchronous agents with perfect recall that communicate only by broadcasting, in separate work jointly with Ron van der Meyden not fully reported in this thesis. Second, it is argued that a full spectrum of degrees of knowledge sharing can be present in any multi-agent system, with no sharing and full sharing at the extremes. This theme is investigated axiomatically and a range of logics representing a particular class of knowledge sharing between two agents is presented. All the logics but two in this spectrum are proven complete by standard canonicity proofs. We conjecture that these two remaining logics are not canonical and it is an open problem whether or not they are complete. Third, following a influential position paper by Halpern and Moses, the idea of refining and checking of knowledge structures in multi-agent systems is investigated. It is shown that, Kripke models, the standard semantic tools for this analysis are not adequate and an alternative notion, Kripke trees, is put forward. An algorithm for refining and checking Kripke trees is presented and its major properties investigated. The algorithm succeeds in solving the famous muddy-children puzzle, in which agents communicate and reason about each other's knowledge. The thesis concludes by discussing the extent to which combining logics, a promising new area in pure logic, can provide a significant boost in research for epistemic and other theories for multi-agent systems

Data Fingerprinting -- Identifying Files and Tables with Hashing Schemes

Master's thesis in Computer scienceINTRODUCTION: Although hash functions are nothing new, these are not limited to cryptographic purposes. One important field is data fingerprinting. Here, the purpose is to generate a digest which serves as a fingerprint (or a license plate) that uniquely identifies a file. More recently, fuzzy fingerprinting schemes — which will scrap the avalanche effect in favour of detecting local changes — has hit the spotlight. The main purpose of this project is to find ways to classify text tables, and discover where potential changes or inconsitencies have happened. METHODS: Large parts of this report can be considered applied discrete mathematics — and finite fields and combinatorics have played an important part. Rabin’s fingerprinting scheme was tested extensively and compared against existing cryptographic algorithms, CRC and FNV. Moreover, a self-designed fuzzy hashing algorithm with the preliminary name No-Frills Hash has been created and tested against Nilsimsa and Spamsum. NFHash is based on Mersenne primes, and uses a sliding window to create a fuzzy hash. Futhermore, the usefullness of lookup tables (with partial seeds) were also explored. The fuzzy hashing algorithm has also been combined with a k-NN classifier to get an overview over it’s ability to classify files. In addition to NFHash, Bloom filters combined with Merkle Trees have been the most important part of this report. This combination will allow a user to see where a change was made, despite the fact that hash functions are one-way. Large parts of this project has dealt with the study of other open-source libraries and applications, such as Cassandra and SSDeep — as well as how bitcoins work. Optimizations have played a crucial role as well; different approaches to a problem might lead to the same solution, but resource consumption can be very different. RESULTS: The results have shown that the Merkle Tree-based approach can track changes to a table very quickly and efficiently, due to it being conservative when it comes to CPU resources. Moreover, the self-designed algorithm NFHash also does well in terms of file classification when it is coupled with a k-NN classifyer. CONCLUSION: Hash functions refers to a very diverse set of algorithms, and not just algorithms that serve a limited purpose. Fuzzy Fingerprinting Schemes can still be considered to be at their infant stage, but a lot has still happened the last ten years. This project has introduced two new ways to create and compare hashes that can be compared to similar, yet not necessarily identical files — or to detect if (and to what extent) a file was changed. Note that the algorithms presented here should be considered prototypes, and still might need some large scale testing to sort out potential flaw

Algorithms for Neural Prosthetic Applications

abstract: In the last 15 years, there has been a significant increase in the number of motor neural prostheses used for restoring limb function lost due to neurological disorders or accidents. The aim of this technology is to enable patients to control a motor prosthesis using their residual neural pathways (central or peripheral). Recent studies in non-human primates and humans have shown the possibility of controlling a prosthesis for accomplishing varied tasks such as self-feeding, typing, reaching, grasping, and performing fine dexterous movements. A neural decoding system comprises mainly of three components: (i) sensors to record neural signals, (ii) an algorithm to map neural recordings to upper limb kinematics and (iii) a prosthetic arm actuated by control signals generated by the algorithm. Machine learning algorithms that map input neural activity to the output kinematics (like finger trajectory) form the core of the neural decoding system. The choice of the algorithm is thus, mainly imposed by the neural signal of interest and the output parameter being decoded. The various parts of a neural decoding system are neural data, feature extraction, feature selection, and machine learning algorithm. There have been significant advances in the field of neural prosthetic applications. But there are challenges for translating a neural prosthesis from a laboratory setting to a clinical environment. To achieve a fully functional prosthetic device with maximum user compliance and acceptance, these factors need to be addressed and taken into consideration. Three challenges in developing robust neural decoding systems were addressed by exploring neural variability in the peripheral nervous system for dexterous finger movements, feature selection methods based on clinically relevant metrics and a novel method for decoding dexterous finger movements based on ensemble methods.Dissertation/ThesisDoctoral Dissertation Bioengineering 201

Learning of Generalized Manipulation Strategies in Service Robotics

This thesis makes a contribution to autonomous robotic manipulation. The core is a novel constraint-based representation of manipulation tasks suitable for flexible online motion planning. Interactive learning from natural human demonstrations is combined with parallelized optimization to enable efficient learning of complex manipulation tasks with limited training data. Prior planning results are encoded automatically into the model to reduce planning time and solve the correspondence problem

Structured P2P Technologies for Distributed Command and Control

The utility of Peer-to-Peer (P2P) systems extends far beyond traditional file sharing. This paper provides an overview of how P2P systems are capable of providing robust command and control for Distributed Multi-Agent Systems (DMASs). Specifically, this article presents the evolution of P2P architectures to date by discussing supporting technologies and applicability of each generation of P2P systems. It provides a detailed survey of fundamental design approaches found in modern large-scale P2P systems highlighting design considerations for building and deploying scalable P2P applications. The survey includes unstructured P2P systems, content retrieval systems, communications structured P2P systems, flat structured P2P systems and finally Hierarchical Peer-to-Peer (HP2P) overlays. It concludes with a presentation of design tradeoffs and opportunities for future research into P2P overlay systems

Enabling technologies for decentralized interpersonal communication

In the recent years the Internet users have witnessed the emergence of Peer-to-Peer (P2P) technologies and applications. One class of P2P applications is comprised of applications that are targeted for interpersonal communication. The communication applications that utilize P2P technologies are referred to as decentralized interpersonal communication applications. Such applications are decentralized in a sense that they do not require assistance from centralized servers for setting up multimedia sessions between users. The invention of Distributed Hash Table (DHT) algorithms has been an important, but not an inclusive enabler for decentralized interpersonal communication. Even though the DHTs provide a basic foundation for decentralization, there are still a number of challenges without viable technological solutions. The main contribution of this thesis is to propose technological solutions to a subset of the existing challenges. In addition, this thesis also presents the preliminary work for the technological solutions. There are two parts in the preliminary work. In the first part, a set of DHT algorithms are evaluated from the viewpoint of decentralized interpersonal communication, and the second part gives a coherent presentation of the challenges that a decentralized interpersonal communication application is going to encounter in mobile networks. The technological solution proposals contain two architectures and two algorithms. The first architecture enables an interconnection between a decentralized and a centralized communication network, and the second architecture enables the decentralization of a set of legacy applications. The first algorithm is a load balancing algorithm that enables good scalability, and the second algorithm is a search algorithm that enables arbitrary searches. The algorithms can be used, for example, in DHT-based networks. Even though this thesis has focused on the decentralized interpersonal communication, some of the proposed technological solutions also have general applicability outside the scope of decentralized interpersonal communication

Keyword-based search in peer-to-peer networks

Ph.DDOCTOR OF PHILOSOPH