Computational approach to solving problems of spatial processing of point sets on two-dimensional regular grids

The paper presents an approach to solving problems of spatial processing on sets of points on a plane. The presented method consists in plotting regions of an arbitrary geometric shape near given points of the set on a regular grid and determining the intersection points of the regions using spatial hash tables to improve the efficiency of operations. The proposed approach is implemented in the form of software for determining the spatial relationships between points as a sequence of operations with discretized sets and allows visualization of research results. Figs.: 2. Refs.: 13. Keywords: spatial processing task; point set; plane; regular grid; spatial hash table.

POET (v0.1): speedup of many-core parallel reactive transport simulations with fast DHT lookups

Coupled reactive transport simulations are extremely demanding in terms of required computational power, which hampers their application and leads to coarsened and oversimplified domains. The chemical sub-process represents the major bottleneck: its acceleration is an urgent challenge which gathers increasing interdisciplinary interest along with pressing requirements for subsurface utilization such as spent nuclear fuel storage, geothermal energy and CO2 storage. In this context we developed POET (POtsdam rEactive Transport), a research parallel reactive transport simulator integrating algorithmic improvements which decisively speed up coupled simulations. In particular, POET is designed with a master/worker architecture, which ensures computational efficiency in both multicore and cluster compute environments. POET does not rely on contiguous grid partitions for the parallelization of chemistry but forms work packages composed of grid cells distant from each other. Such scattering prevents particularly expensive geochemical simulations, usually concentrated in the vicinity of a reactive front, from generating load imbalance between the available CPUs (central processing units), as is often the case with classical partitions. Furthermore, POET leverages an original implementation of the distributed hash table (DHT) mechanism to cache the results of geochemical simulations for further reuse in subsequent time steps during the coupled simulation. The caching is hence particularly advantageous for initially chemically homogeneous simulations and for smooth reaction fronts. We tune the rounding employed in the DHT on a 2D benchmark to validate the caching approach, and we evaluate the performance gain of POET's master/worker architecture and the DHT speedup on a 3D benchmark comprising around 650 000 grid elements. The runtime for 200 coupling iterations, corresponding to 960 simulation days, reduced from about 24 h on 11 workers to 29 min on 719 workers. Activating the DHT reduces the runtime further to 2 h and 8 min respectively. Only with these kinds of reduced hardware requirements and computational costs is it possible to realistically perform the long-term complex reactive transport simulations, as well as perform the uncertainty analyses required by pressing societal challenges connected with subsurface utilization.

Generic Ownership Types for Java and the Collections Framework

<p>Generic programming has turned out very useful in the development of reusable software. With the Java programming language, genericity is not only meant for reusability, but also for type-safety. Java generics constrain a container object (e.g., list, hash table) to store objects of a pre-specified data type. Nevertheless, safe programming with aliasing (multiple pointers in a program may point to the same object) is still a concern in object-oriented programming language research. A pointing object can mutate the state of the aliased object, reflecting the changes to all of the other pointers (aka aliases) thus affecting their behaviour. As programs grow larger and more complex, such changes in behaviour can be undesirable and difficult to detect and reason about. With respect to container objects, the iterator pattern critically violates encapsulation, allowing aliases to the state (and thereof the components) of its container. Object ownership is one of the well-researched paradigms in the area of alias management. Ownership types support hierarchical object encapsulation rather than the traditional class-level encapsulation. This thesis introduces an extension of Java 6 with support for ownership types as supplementary generic types. That is, Java generics are extended with the ability of carrying ownership information. This extension provides generic ownership support for all of Java; that is, all major language features are addressed so that programs can safely manage and express their aliasing properties. The resulting language is expressive enough to support common programming idioms, with little programming and runtime overhead. We evaluated the programmability of the language by refactoring a major (the most essential) portion of the Java Collections Framework. We also evaluated the performance impact of our refactoring by conducting a small micro-benchmark study to measure the performance time overhead the refactored collections may impose.</p>

Generic Ownership Types for Java and the Collections Framework

<p>Generic programming has turned out very useful in the development of reusable software. With the Java programming language, genericity is not only meant for reusability, but also for type-safety. Java generics constrain a container object (e.g., list, hash table) to store objects of a pre-specified data type. Nevertheless, safe programming with aliasing (multiple pointers in a program may point to the same object) is still a concern in object-oriented programming language research. A pointing object can mutate the state of the aliased object, reflecting the changes to all of the other pointers (aka aliases) thus affecting their behaviour. As programs grow larger and more complex, such changes in behaviour can be undesirable and difficult to detect and reason about. With respect to container objects, the iterator pattern critically violates encapsulation, allowing aliases to the state (and thereof the components) of its container. Object ownership is one of the well-researched paradigms in the area of alias management. Ownership types support hierarchical object encapsulation rather than the traditional class-level encapsulation. This thesis introduces an extension of Java 6 with support for ownership types as supplementary generic types. That is, Java generics are extended with the ability of carrying ownership information. This extension provides generic ownership support for all of Java; that is, all major language features are addressed so that programs can safely manage and express their aliasing properties. The resulting language is expressive enough to support common programming idioms, with little programming and runtime overhead. We evaluated the programmability of the language by refactoring a major (the most essential) portion of the Java Collections Framework. We also evaluated the performance impact of our refactoring by conducting a small micro-benchmark study to measure the performance time overhead the refactored collections may impose.</p>

Inserção de Infraestrutura de Chave Pública no Projeto OpenDHT

As redes de sobreposição peer-to-peer (P2P) baseadas em Distributed Hash Table (DHT) tem ganhado atenção na literatura devido as suas características como alta disponibilidade, escalabilidade, entre outras. Uma implementação popularmente conhecida é o projeto OpenDHT, contudo, não é abordada a autenticidade dos nós, nem das mensagens. Dessa forma, ela é suscetível a diversos ataques, entre eles, ataque Sybil. O objetivo do trabalho é apresentar uma proposta para preencher essa lacuna através de uma Infraestrutura de Chave Pública (ICP). Os resultados obtidos através da ferramenta Scyther demonstram a segurança do protocolo de autenticação contra ataques bem conhecidos e os testes práticos demonstram êxito da implementação.

Massively Parallel Computation via Remote Memory Access

We introduce the Adaptive Massively Parallel Computation (AMPC) model, which is an extension of the Massively Parallel Computation (MPC) model. At a high level, the AMPC model strengthens the MPC model by storing all messages sent within a round in a distributed data store. In the following round, all machines are provided with random read access to the data store, subject to the same constraints on the total amount of communication as in the MPC model. Our model is inspired by the previous empirical studies of distributed graph algorithms [8, 30] using MapReduce and a distributed hash table service [17]. This extension allows us to give new graph algorithms with much lower round complexities compared to the best-known solutions in the MPC model. In particular, in the AMPC model we show how to solve maximal independent set in O (1) rounds and connectivity/minimum spanning tree in O (log log m / n n rounds both using O ( n δ ) space per machine for constant δ < 1. In the same memory regime for MPC, the best-known algorithms for these problems require poly log n rounds. Our results imply that the 2-C YCLE conjecture, which is widely believed to hold in the MPC model, does not hold in the AMPC model.

Distributed Address Table (DAT): A Decentralized Model for End-to-End Communication in IoT

To achieve a fully connected network in Internet of Things (IoT) there are number of challenges that have to be overcome. Among those, a big challenge is how to keep all of the devices accessible everywhere and every time. In the IoT network, the assumption is that each IoT device can be reached by any client at any given time. In practice, this is not always possible and without a proper mechanism the nodes behind a NAT are unable to communicate with each other directly, and their addresses have to be shared through a trusted third party. This challenge becomes harder by taking into consideration that most NAT traversal approaches have been developed prior to rising of the IoT, without taking into account the constrained nature of the participating devices and mostly depend on a centralized entity. In this paper we proposed the Distributed Address Table (DAT), a decentralized, secure and lightweight address distribution model that allows any two nodes to get the addresses of the other end without relying on a trusted third party. Structured Peer-to-Peer (P2P) overlay by utilizing Distributed Hash Table (DHT) technique is generated as its underlying communication scheme to ensure that all participating devices are accessible at any given time. This is achieved through simple, yet secure and efficient decentralized model. The DAT adopts the edge/fog computing paradigms to ensure a decentralized address distribution. The results showed that the proposed model is efficient. In addition, the security properties of the proposed model have been defined and proved.

MP-RW-LSH

Approximate Nearest Neighbor Search (ANNS) is a fundamental algorithmic problem, with numerous applications in many areas of computer science. Locality-Sensitive Hashing (LSH) is one of the most popular solution approaches for ANNS. A common shortcoming of many LSH schemes is that since they probe only a single bucket in a hash table, they need to use a large number of hash tables to achieve a high query accuracy. For ANNS- L 2 , a multi-probe scheme was proposed to overcome this drawback by strategically probing multiple buckets in a hash table. In this work, we propose MP-RW-LSH, the first and so far only multi-probe LSH solution to ANNS in L 1 distance, and show that it achieves a better tradeoff between scalability and query efficiency than all existing LSH-based solutions. We also explain why a state-of-the-art ANNS -L 1 solution called Cauchy projection LSH (CP-LSH) is fundamentally not suitable for multi-probe extension. Finally, as a use case, we construct, using MP-RW-LSH as the underlying "ANNS- L 1 engine", a new ANNS-E (E for edit distance) solution that beats the state of the art.

LaMRD: Location-Aware and Decentralized Multi-Layer Resource Discovery for IoT

The resources in the Internet of Things (IoT) network are distributed among different parts of the network. Considering huge number of IoT resources, the task of discovering them is challenging. While registering them in a centralized server such as a cloud data center is one possible solution, but due to billions of IoT resources and their limited computation power, the centralized approach leads to some efficiency and security issues. In this paper we proposed a location aware and decentralized multi layer model of resource discovery (LaMRD) in IoT. It allows a resource to be registered publicly or privately, and to be discovered in a decentralized scheme in the IoT network. LaMRD is based on structured peer-to-peer (p2p) scheme and follows the general system trend of fog computing. Our proposed model utilizes Distributed Hash Table (DHT) technology to create a p2p scheme of communication among fog nodes. The resources are registered in LaMRD based on their locations which results in a low added overhead in the registration and discovery processes. LaMRD generates a single overlay and it can be generated without specific organizing entity or location based devices. LaMRD guarantees some important security properties and it showed a lower latency comparing to the cloud based and decentralized resource discovery.