Selective & Secured Code Distribution Approach for Multihop Wireless Sensor Networks

AbstractThis paper proposes an efficient code distribution approach for multihop wireless sensor networks in heterogeneous environment. Reprogramming a sensor network necessitate to fulfil the changing application requirements, bug fix as it is impractical to reach the node once deployed. We are presenting an efficient code distribution scheme to update the running code in sensors over the air with secure authentication & completion verification. The experimental results shows how proposed approach sdeluge is efficient in terms of significant reduction in average completion & dissemination time, advertisement rate, average energy consumption consequently improvement in lifetime of the network

A secure over-the-air programming scheme in wireless sensor networks

Over-The-Air dissemination of code updates in Wireless Sensor Networks (WSNs) have been researchers’ point of interest in past a few years and more importantly security challenges toward remote propagation of code update have taken the majority of efforts in this context. Many security models have been proposed to establish a balance between the energy consumption and security strengthen with having their concentration on constraint nature of WSN nodes. For authentication purposes most of them have used Merkle-Hash-Tree to avoid using multiple public cryptography operations. These models mostly have assumed an environment in which security has to be in a standard level and therefore they have not investigated the tree structure for mission-critical situations in which security has to be in maximum possible extent (e.g. military zones). Two major problems have been identified in Merkle Tree structure which is used in Seluge scheme, including: 1) an exponential growth in number of overhead packets when block size of hash algorithm used in design is increased. 2) Limitation of using hash algorithms with larger block size of 11 bytes when payload size is set to 72 bytes. Then several existing security models are investigated for possible vulnerabilities and a set of countermeasures correspondingly named Security Model Requirements (SMR) is provided. After concentrating on Seluge’s design, a new secure Over-The-Air Programming (OTAP) scheme named Seluge++ is proposed that complies with SMR and replaces the use of inefficient Merkle Tree with a novel method

GCP: Gossip-based Code Propagation for Large-scale Mobile Wireless Sensor Networks

Wireless sensor networks (WSN) have recently received an increasing interest. They are now expected to be deployed for long periods of time, thus requiring software updates. Updating the software code automatically on a huge number of sensors is a tremendous task, as ''by hand'' updates can obviously not be considered, especially when all participating sensors are embedded on mobile entities. In this paper, we investigate an approach to automatically update software in mobile sensor-based application when no localization mechanism is available. We leverage the peer-to-peer cooperation paradigm to achieve a good trade-off between reliability and scalability of code propagation. More specifically, we present the design and evaluation of GCP ({\emph Gossip-based Code Propagation}), a distributed software update algorithm for mobile wireless sensor networks. GCP relies on two different mechanisms (piggy-backing and forwarding control) to improve significantly the load balance without sacrificing on the propagation speed. We compare GCP against traditional dissemination approaches. Simulation results based on both synthetic and realistic workloads show that GCP achieves a good convergence speed while balancing the load evenly between sensors

Over-the-air software updates in the internet of things : an overview of key principles

Due to the fast pace at which IoT is evolving, there is an increasing need to support over-theair software updates for security updates, bug fixes, and software extensions. To this end, multiple over-the-air techniques have been proposed, each covering a specific aspect of the update process, such as (partial) code updates, data dissemination, and security. However, each technique introduces overhead, especially in terms of energy consumption, thereby impacting the operational lifetime of the battery constrained devices. Until now, a comprehensive overview describing the different update steps and quantifying the impact of each step is missing in the scientific literature, making it hard to assess the overall feasibility of an over-the-air update. To remedy this, our article analyzes which parts of an IoT operating system are most updated after device deployment, proposes a step-by-step approach to integrate software updates in IoT solutions, and quantifies the energy cost of each of the involved steps. The results show that besides the obvious dissemination cost, other phases such as security also introduce a significant overhead. For instance, a typical firmware update requires 135.026 mJ, of which the main portions are data dissemination (63.11 percent) and encryption (5.29 percent). However, when modular updates are used instead, the energy cost (e.g., for a MAC update) is reduced to 26.743 mJ (48.69 percent for data dissemination and 26.47 percent for encryption)

Doped Fountain Coding for Minimum Delay Data Collection in Circular Networks

This paper studies decentralized, Fountain and network-coding based strategies for facilitating data collection in circular wireless sensor networks, which rely on the stochastic diversity of data storage. The goal is to allow for a reduced delay collection by a data collector who accesses the network at a random position and random time. Data dissemination is performed by a set of relays which form a circular route to exchange source packets. The storage nodes within the transmission range of the route's relays linearly combine and store overheard relay transmissions using random decentralized strategies. An intelligent data collector first collects a minimum set of coded packets from a subset of storage nodes in its proximity, which might be sufficient for recovering the original packets and, by using a message-passing decoder, attempts recovering all original source packets from this set. Whenever the decoder stalls, the source packet which restarts decoding is polled/doped from its original source node. The random-walk-based analysis of the decoding/doping process furnishes the collection delay analysis with a prediction on the number of required doped packets. The number of doped packets can be surprisingly small when employed with an Ideal Soliton code degree distribution and, hence, the doping strategy may have the least collection delay when the density of source nodes is sufficiently large. Furthermore, we demonstrate that network coding makes dissemination more efficient at the expense of a larger collection delay. Not surprisingly, a circular network allows for a significantly more (analytically and otherwise) tractable strategies relative to a network whose model is a random geometric graph

Architectures for Wireless Sensor Networks

Various architectures have been developed for wireless sensor networks. Many of them leave to the programmer important concepts as the way in which the inter-task communication and dynamic reconfigurations are addressed. In this paper we describe the characteristics of a new architecture we proposed - the data-centric architecture. This architecture offers an easy way of structuring the applications designed for wireless sensor nodes that confers them superior performances

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