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

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

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

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

Reprogramming embedded systems at run-time

The dynamic re-programming of embedded systems is a long-standing problem in the field. With the advent of wireless sensor networks and the 'Internet of Things' it has now become necessary to be able to reprogram at run-time due to the difficulty of gaining access to such systems once deployed. The issues of power consumption, flexibility, and operating system protections are examined for a range of approaches, and a critical comparison is given. A combination of approaches is recommended for the implementation of real-world systems and areas where further work is required are highlighted.Postprin

Optimizing Sensor Network Reprogramming via In-situ Reconfigurable Components

International audienceWireless reprogramming of sensor nodes is a critical requirement in long-lived Wireless Sensor Networks (WSNs) for several concerns, such as fixing bugs, upgrading the operating system and applications, and adapting applications behavior according to the physical environment. In such resource-poor platforms, the ability to efficiently delimit and reconfigure the necessary portion of sensor software--instead of updating the full binary image--is of vital importance. However, most of existing approaches in this field have not been widely adopted to date due to the extensive use of WSN resources or lack of generality. In this article, we therefore consider WSN programming models and run-time reconfiguration models as two interrelated factors and we present an integrated approach for addressing efficient reprogramming in WSNs. The middleware solution we propose, RemoWare, is characterized by mitigating the cost of post-deployment software updates on sensor nodes via the notion of in-situ reconfigurability and providing a component-based programming abstraction to facilitate the development of dynamic WSN applications. Our evaluation results show that RemoWare imposes a very low energy overhead in code distribution and component reconfiguration, and consumes approximately 6% of the total code memory on a TelosB sensor platform