PRECISE DELTA EXTRACTION SCHEME FOR REPROGRAMMING OF WIRELESS SENSOR NODES

 In this paper, we present a precise delta extraction scheme and tool for use in wireless sensor network reprogramming processes. Our approach involves the use of a novel algorithm based on SET theory and the unique pattern of the Execution Link File (ELF) structure to extract delta from two distinct firmware (original and the modified). The delta consist of two set of unique values: one set clearly indicate the address of where the change has occurred and the second relays the change Data content. In addition, we developed a set of metrics that relays the degree of modification made with respect to the original file. The scheme capabilities, when compared with similar utilities referred in literature, shows an appreciable capacity to reduce energy consumption rate as well as effect a reduction in the amount of memory space used during reprogramming processes.  http://dx.doi.org/10.4314/njt.v35i1.2

Dioptase: a distributed data streaming middleware for the future web of things

International audienceThe Internet of Things (IoT) is a promising concept toward pervasive computing as it may radically change the way people interact with the physical world, by connecting sensors to the Internet and, at a higher level, to the Web, thereby enacting a Web of Things (WoT). One of the challenges raised by the WoT is the in-network continuous processing of data streams presented by Things, which must be investigated urgently because it affects the future data models of the IoT, and is critical regarding the scalability and the sustainability required by the IoT. This cross-cutting concern has been previously studied in the context of Wireless Sensor Networks (WSN) given the focus on the acquisition and in-network processing of sensed data. However, proposed solutions feature various proprietary and highly specialized technologies that are difficult to integrate and complex to use, which represents a hurdle to their wide deployment. At the other end of the spectrum, cloud-based solutions introduce a too high energy cost for the envisioned IoT scale, considering the energy cost of communication over computation. There is thus a need for a distributed middleware solution for data stream management that leverages existing WSN work, while integrating it with today's Web technologies in order to support the required flexibility and the interoperability of the IoT.Toward that goal, this paper introduces Dioptase, a lightweight Data Stream Management System for the WoT, which aims to integrate the Things and their streams into today's Web by presenting sensors and actuators as Web services. The middleware specifically provides a way to describe complex fully-distributed stream-based mashups and to deploy them dynamically, at any time, as task graphs, over available Things of the network, including resource-constrained ones

Roteamento Sensível ao Contexto em Redes de Sensores sem Fio: Uma Abordagem Baseada em Regras de Aplicação para o Protocolo RPL

A pesquisa na área de Redes de Sensores sem Fio (RSSF) tem contribuído de forma significativa para o desenvolvimento de aplicações de sensoriamento em larga escala. Em função de suas características e restrições (pouca capacidade de processamento, armazenamento e fonte de energia), diferentes protocolos de comunicação foram projetados para as RSSFs. Para atender a uma necessidade de padronização, o IETF (Internet Engineering Task Force) especificou um protocolo de roteamento denominado RPL (IPv6 Routing Protocol for Low-power and Lossy Networks), como protocolo padrão para redes RSSFs. Este protocolo possui uma grande quantidade de recursos e também fornece facilidades para incorporar métricas de natureza dinâmica.De forma a facilitar o acesso a uma variedade de informações requeridas pelo protocolo de roteamento adaptativo RPL para cálculo métricas e tomadas de decisão de encaminhamento, é proposto um gerenciador de contexto reconfigurável. Este gerenciador é responsável por coletar os dados contextuais das fontes de informação disponíveis, e atuar como uma camada de abstração, simplificando o uso dessas fontes e habilitando a experimentação e prototipagem de novas métricas de roteamento.Esta dissertação apresenta uma extensão ao protocolo de roteamento RPL. Esta extensão tem por objetivo prover mecanismos simples para que o protocolo RPL interaja com a aplicação, com a finalidade de otimização do roteamento. Tal interação é realizada através de regras de aplicação, permitindo ao RPL se adaptar em tempo de execução a mudanças no ambiente

Roteamento Sensível ao Contexto em Redes de Sensores sem Fio: Uma Abordagem Baseada em Regras de Aplicação para o Protocolo RPL

A pesquisa na área de Redes de Sensores sem Fio (RSSF) tem contribuído de forma significativa para o desenvolvimento de aplicações de sensoriamento em larga escala. Em função de suas características e restrições (pouca capacidade de processamento, armazenamento e fonte de energia), diferentes protocolos de comunicação foram projetados para as RSSFs. Para atender a uma necessidade de padronização, o IETF (Internet Engineering Task Force) especificou um protocolo de roteamento denominado RPL (IPv6 Routing Protocol for Low-power and Lossy Networks), como protocolo padrão para redes RSSFs. Este protocolo possui uma grande quantidade de recursos e também fornece facilidades para incorporar métricas de natureza dinâmica.De forma a facilitar o acesso a uma variedade de informações requeridas pelo protocolo de roteamento adaptativo RPL para cálculo métricas e tomadas de decisão de encaminhamento, é proposto um gerenciador de contexto reconfigurável. Este gerenciador é responsável por coletar os dados contextuais das fontes de informação disponíveis, e atuar como uma camada de abstração, simplificando o uso dessas fontes e habilitando a experimentação e prototipagem de novas métricas de roteamento.Esta dissertação apresenta uma extensão ao protocolo de roteamento RPL. Esta extensão tem por objetivo prover mecanismos simples para que o protocolo RPL interaja com a aplicação, com a finalidade de otimização do roteamento. Tal interação é realizada através de regras de aplicação, permitindo ao RPL se adaptar em tempo de execução a mudanças no ambiente

Generic Adaptation Support for Wireless Sensor Networks

Wireless Sensor Networks are used in various and expanding application scenarios and are also considered to be important elements of the Internet of Things. They monitor and deliver data, which is not only used for research but to an increasing degree also in business environments. With the increasing complexity of these scenarios and the increasing dependency on the availability of the sensor network data, the requirements to a Wireless Sensor Network increase at the same pace. Since Wireless Sensor Networks are typically implemented using resource-constrained platforms, sensor network algorithms are typically optimised for specific operating conditions such as static or mobile networks, high or low traffic etc. However, due to scenario complexity and dynamic real-world conditions a static configuration of a Wireless Sensor Network software cannot always meet the requirements. Moreover, these requirements of the sensor network's user can change over time, for example concerning accuracy. Therefore, the sensor network software has to adapt itself to cope with dynamic system conditions and user requirements. This thesis presents the TinyAdapt and TinySwitch frameworks to solve the aforementioned problems. TinyAdapt, our generic adaptation framework for Wireless Sensor Networks, allows for the autonomous adaptation of arbitrary sensor network algorithms based on explicit and intuitively defined user preferences and on automatically monitored network conditions. Due to a two-phase approach, run-time adaptation is executed completely and efficiently on standard sensor node hardware and does not need support from, e.g., the base station. The creation of adaptive applications is guided by a complete workflow, which is presented as well. When changing parameters of an algorithm is not enough to achieve the desired adaptation results, the algorithm has to be exchanged completely. However, several limitations of TinyOS and the sensor node hardware limit the use of simple code exchange by node reprogramming for efficient adaptation. TinySwitch, our generic switching framework, allows to switch between alternative algorithms that are already installed in parallel. TinySwitch analyses these algorithms, determines their dependencies and creates all code to enable one of the algorithms while isolating all others. Due to its minimal overhead, TinySwitch is perfectly suited for run-time adaptation in TinyAdapt