Modular Remote Reprogramming of Sensor Nodes

Wireless sensor networks are envisioned to be deployed in the absence of permanent network infrastructure and in environments with limited or no human accessibility. Hence, such deployments demand mechanisms to remotely (i.e., over the air) reconfigure and update the software on the nodes. In this paper we introduce DyTOS, a TinyOS based remote reprogramming approach that enables the dynamic exchange of software components and thus incrementally update the operating system and its applications. The core idea is to preserve the modularity of TinyOS, i.e., its componentisation, which is lost during the normal compilation process, and enable runtime composition of TinyOS components on the sensor node. The proposed solution integrates seamlessly into the system architecture of TinyOS: It does not require any changes to the programming model of TinyOS and all existing components can be reused transparently. Our evaluation shows that DyTOS incurs a low performance overhead while keeping a smaller – up to one third – memory footprint than other comparable solutions

Testbed architecture and framework for debugging wireless sensor networks

The Internet of Things has emerged as one of the key aspects for the future of the Wireless Sensor Networks and their impact on new applications in real environments. This concept poses new challenges in the implementation, testing and debugging of efficient, robust and reliable technologies under this paradigm, specially in a pre-deployment stage where HW-SW platform prototypes are to be optimized prior to their inclusion in actual deployments. In this work, the design and implementation of a complete testbed infrastructure as a support tool for improving the effectiveness and the applicability of sensor nodes to real systems is presented, focused on the modular architecture of the Cookie platform and aiming to help developers to integrate and improve the whole WSN operation to final real-world scenarios

Testbed infrastructure for debugging, analyzing and optimizing WSN nodes based on a modular HW-SW architecture

The Internet of Things has emerged as one of the key aspects to the future of the Wireless Sensor Networ ks and their impact in new applications in real environments. This concept poses new challenges in the implementation, testing and assessment of efficient, robust and reliable technologies and prototypes under this paradigm. In this way, the run-time remote interaction with the deployment of hundreds of in-f ield nodes in which developers have to be able to control and manage the wireless network anywhere at any time also implies new objectives to be achieved in order to adapt or even create new HW-SW platforms. In this work, the design and implementation of a complete testbed infrastructure as a support tool for improving the effectiveness and the applicability of sensor nodes to real applications is presented, focused on the m odular architecture of the Cookie hardware platform and aiming to help developers to integrate and optimize the whole WSN system to the final applications in the real world

On-the-fly dynamic reprogramming mechanism for increasing the energy efficiency and supporting multi-experimental capabilities in WSNs

Remote reprogramming capabilities are one of the major concerns in WSN platforms due to the limitations and constraints that low power wireless nodes poses, especially when energy efficiency during the reprogramming process is a critical factor for extending the battery life of the devices. Moreover, WSNs are based on low-rate protocols in which as greater the amount of data is sent, the more the possibility to lose packets during the transmitting process is. In order to overcome these limitations, in this work a novel on-the-fly reprogramming technique for modifying and updating the application running on the wireless sensor nodes is designed and implemented, based on a partial reprogramming mechanism that significantly reduces the size of the files to be downloaded to the nodes, therefore diminishing their power/time consumption. This powerful mechanism also addresses multi-experimental capabilities because it provides the possibility to download, manage, test and debug multiple applications into the wireless nodes, based on a memory map segmentation of the core. Being an on-the-fly reprogramming process, no additional resources to store and download the configuration file are needed

A network access control framework for 6LoWPAN networks

Low power over wireless personal area networks (LoWPAN), in particular wireless sensor networks, represent an emerging technology with high potential to be employed in critical situations like security surveillance, battlefields, smart-grids, and in e-health applications. The support of security services in LoWPAN is considered a challenge. First, this type of networks is usually deployed in unattended environments, making them vulnerable to security attacks. Second, the constraints inherent to LoWPAN, such as scarce resources and limited battery capacity, impose a careful planning on how and where the security services should be deployed. Besides protecting the network from some well-known threats, it is important that security mechanisms be able to withstand attacks that have not been identified before. One way of reaching this goal is to control, at the network access level, which nodes can be attached to the network and to enforce their security compliance. This paper presents a network access security framework that can be used to control the nodes that have access to the network, based on administrative approval, and to enforce security compliance to the authorized nodes

Wireless Sensor Networks Node with Remote HW/SW Reconfiguration Capabilities

The inclusion of reconfigurable HW in nodes for Wireless Sensor Networks (WSNs) is not a common issue in the framework of the design of state of the art HW platforms for WSNs, mainly due to its high power consumption. But, on the other hand, reconfigurable logic as FPGAs can contribute to improve the system performance by providing not only HW acceleration as it has already been demonstrated by several research groups, but also the possibility of node HW updates after WSN deployment. This paper presents an entire working flow to generate, remotely configure and reconfigure the HW and SW in a reconfigurable node platform for WSNs. The presented reconfiguration working flow targets the custom HW platform designed at CEI (Centro de Electronica Industrial), where the processing is carried out by both a microcontroller and a partially reconfigurable Xilinx FPGA. The presented reconfiguration process is based on the JTAG protocol and thus permits to port the system to new, less power consuming FPGAs that are appearing in the market to solve problems related to energy lifetim

A Low-Overhead Script Language for Tiny Networked Embedded Systems

With sensor networks starting to get mainstream acceptance, programmability is of increasing importance. Customers and field engineers will need to reprogram existing deployments and software developers will need to test and debug software in network testbeds. Script languages, which are a popular mechanism for reprogramming in general-purpose computing, have not been considered for wireless sensor networks because of the perceived overhead of interpreting a script language on tiny sensor nodes. In this paper we show that a structured script language is both feasible and efficient for programming tiny sensor nodes. We present a structured script language, SCript, and develop an interpreter for the language. To reduce program distribution energy the SCript interpreter stores a tokenized representation of the scripts which is distributed through the wireless network. The ROM and RAM footprint of the interpreter is similar to that of existing virtual machines for sensor networks. We show that the interpretation overhead of our language is on par with that of existing virtual machines. Thus script languages, previously considered as too expensive for tiny sensor nodes, are a viable alternative to virtual machines