A Survey of Prediction and Classification Techniques in Multicore Processor Systems

In multicore processor systems, being able to accurately predict the future provides new optimization opportunities, which otherwise could not be exploited. For example, an oracle able to predict a certain application\u27s behavior running on a smart phone could direct the power manager to switch to appropriate dynamic voltage and frequency scaling modes that would guarantee minimum levels of desired performance while saving energy consumption and thereby prolonging battery life. Using predictions enables systems to become proactive rather than continue to operate in a reactive manner. This prediction-based proactive approach has become increasingly popular in the design and optimization of integrated circuits and of multicore processor systems. Prediction transforms from simple forecasting to sophisticated machine learning based prediction and classification that learns from existing data, employs data mining, and predicts future behavior. This can be exploited by novel optimization techniques that can span across all layers of the computing stack. In this survey paper, we present a discussion of the most popular techniques on prediction and classification in the general context of computing systems with emphasis on multicore processors. The paper is far from comprehensive, but, it will help the reader interested in employing prediction in optimization of multicore processor systems

Proactive Highly Ambulatory Sensor Routing (PHASeR) protocol for mobile wireless sensor networks

This paper presents a novel multihop routing protocol for mobile wireless sensor networks called PHASeR (Proactive Highly Ambulatory Sensor Routing). The proposed protocol uses a simple hop-count metric to enable the dynamic and robust routing of data towards the sink in mobile environments. It is motivated by the application of radiation mapping by unmanned vehicles, which requires the reliable and timely delivery of regular measurements to the sink. PHASeR maintains a gradient metric in mobile environments by using a global TDMA MAC layer. It also uses the technique of blind forwarding to pass messages through the network in a multipath manner. PHASeR is analysed mathematically based on packet delivery ratio, average packet delay, throughput and overhead. It is then simulated with varying mobility, scalability and traffic loads. The protocol gives good results over all measures, which suggests that it may also be suitable for a wider array of emerging applications

An Efficient Monte Carlo-based Probabilistic Time-Dependent Routing Calculation Targeting a Server-Side Car Navigation System

Incorporating speed probability distribution to the computation of the route planning in car navigation systems guarantees more accurate and precise responses. In this paper, we propose a novel approach for dynamically selecting the number of samples used for the Monte Carlo simulation to solve the Probabilistic Time-Dependent Routing (PTDR) problem, thus improving the computation efficiency. The proposed method is used to determine in a proactive manner the number of simulations to be done to extract the travel-time estimation for each specific request while respecting an error threshold as output quality level. The methodology requires a reduced effort on the application development side. We adopted an aspect-oriented programming language (LARA) together with a flexible dynamic autotuning library (mARGOt) respectively to instrument the code and to take tuning decisions on the number of samples improving the execution efficiency. Experimental results demonstrate that the proposed adaptive approach saves a large fraction of simulations (between 36% and 81%) with respect to a static approach while considering different traffic situations, paths and error requirements. Given the negligible runtime overhead of the proposed approach, it results in an execution-time speedup between 1.5x and 5.1x. This speedup is reflected at infrastructure-level in terms of a reduction of around 36% of the computing resources needed to support the whole navigation pipeline

Energy-aware Gossip Protocol for Wireless Sensor Networks

Dissertação de mestrado em Engenharia InformáticaIn Wireless Sensor Networks (WSNs), typically composed of nodes with resource constraints, leveraging efficient processes is crucial to enhance the network longevity and consequently the sustainability in ultra-dense and heterogeneous environments, such as smart cities. Epidemic algorithms are usually efficient in delivering packets to a sink or to all it’s peers but have poor energy efficiency due to the amount of packet redundancy. Directional algorithms, such as Minimum Cost Forward Algorithm (MCFA) or Directed Diffusion, yield high energy efficiency but fail to handle mobile environments, and have poor network coverage. This work proposes a new epidemic algorithm that uses the current energy state of the network to create a topology that is cyclically updated, fault tolerant, whilst being able to handle the challenges of a static or mobile heterogeneous network. Depending on the application, tuning in the protocol settings can be made to prioritise desired characteristics. The proposed protocol has a small computational footprint and the required memory is proportional not to the size of the network, but to the number of neighbours of a node, enabling high scalability. The proposed protocol was tested, using a ESP8266 as an energy model reference, in a simulated environment with ad-hoc wireless nodes. It was implemented at the application level with UDP sockets, and resulted in a highly energy efficient protocol, capable of leveraging extended network longevity with different static or mobile topologies, with results comparable to a static directional algorithm in delivery efficiency.Em Redes de Sensores sem Fios (RSF), tipicamente compostas por nós com recursos lim-itados, alavancar processos eficientes é crucial para aumentar o tempo de vida da rede e consequentemente a sustentabilidade em ambientes heterogéneos e ultra densos, como cidades inteligentes por exemplo. Algoritmos epidêmicos são geralmente eficientes em en-tregar pacotes para um sink ou para todos os nós da rede, no entanto têm baixa eficiência energética devido a alta taxa de duplicação de pacotes. Algoritmos direcionais, como o MCFA ou de Difusão Direta, rendem alta eficiência energética mas não conseguem lidar com ambientes móveis, e alcançam baixa cobertura da rede. Este trabalho propõe um novo protocolo epidêmico que faz uso do estado energético atual da rede para criar uma topologia que por sua vez atualizada ciclicamente, tolerante a falhas, ao mesmo tempo que é capaz de lidar com os desafios de uma rede heterogênea estática ou móvel. A depender da aplicação, ajustes podem ser feitos às configurações do protocolo para que o mesmo priorize determinadas características. O protocolo proposto tem um pequeno impacto computacional e a memória requerida é proporcional somente à quantidade de vizinhos do nó, não ao tamanho da rede inteira, permitindo assim alta escalabilidade. O algoritmo proposto foi testado fazendo uso do modelo energético de uma ESP8266, em um ambiente simulado com uma rede sem fios ad-hoc. Foi implementado à nível aplicacional com sockets UDP, e resultou em um protocol energeticamente eficiente, capaz de disponibilizar alta longevidade da rede mesmo com diferentes topologias estáticas ou móveis com resultados comparáveis à um protocolo direcional em termos de eficiência na entrega de pacotes