Sensor Operating System Research Articles

Securing Smart Cities using LSTM algorithm and lightweight containers against botnet attacks

Smart Cities contains millions of IoT sensors supporting critical applications such as Smart Transport, Buildings, Intelligent Vehicles, and Logistics. A central administrator appointed by the government manages and maintains the security of each node. Smart City relies upon millions of sensors that are heterogeneous and do not support standard security architecture. Different manufacturers have weak protection protocols for their products and do not update their firmware upon newly identified operating systems’ vulnerabilities. Adversaries using brute force methods exploit the lack of inbuilt security systems on IoT devices to grow their bot network. Smart cities require a standard framework combining soft computing and Deep Learning (DL) for device fleet management and complete control of sensor operating systems for absolute security. This paper presents a real-world application for IoT fleet management security using a lightweight container-based botnet detection (C-BotDet) framework. Using a three-phase approach, the framework using Artificial Intelligence detects compromised IoT devices sending malicious traffic on the network. Balena Cloud revokes API keys and prevents a compromised device from infecting other devices to form a more giant botnet. VPN (Virtual Private Network) prevents inter-device communication and routes all malicious traffic through an external server. The framework quickly updates the standard Linux-based operating system IoT device fleet without relying on different manufacturers to update their system security individually. The simulation and analysis of the C-BotDet framework are presented in a practical working environment to demonstrate its implementation feasibility.

Investigate Efficiency & Reliability of Various Reprogramming Architectures for Wireless Sensor Network: A Survey

This paper presents a survey on the current state-of-art in various Reprogramming Architectures for Wireless Sensor Network (WSN). Recent research in wireless sensor network has highlighted the importance of supporting the capability for remote reprogramming of sensor nodes via wireless network. Wireless sensor networks are expected to be deployed for long periods of time, and the nodes are likely to need software update during their lifetime, both for bug fixes and in order to support new requirements. Network reprogramming allows for over-the-air software updates in sensor networks. Dynamic reprogramming of sensor applications and sensor operating systems are emerging as a critical function required in wireless sensor networks. This ability to remotely patch or upgrade software in deployed sensor nodes via the wireless network is complicated by the increasing trend towards heterogeneity in WSN hardware platforms, sensor operating systems and role-based differentiation, e.g. between aggregators and leaf sensor nodes. Most of the current network reprogramming protocols focus on propagating the same code image to a network of homogeneous sensor nodes. Naive approaches to adapt such protocols for heterogeneity are largely inefficient. Ease of programming has long been recognized as a major hurdle to the adoption of WSN technology. In response to this need, several platform dependent programming solutions have been hitherto developed. A well-established characterization of the available approaches is, however, largely missing. As a result, researchers are unable to orient themselves in this diverse field, and developers struggle in identifying the solutions most appropriate to their application requirements. The purpose of this survey is to describe features of different reprogramming architectures in wireless sensor networks & highlight major concerns pertaining to investigation of efficiency and performance of these architectures for Wireless Sensor Network. The modern techniques in various reprogramming architectures for WSNs have been examined in terms of Reprogramming Architecture, Code dissemination/Code acquisition, Encoding /Decoding, Single-hop/Multihop reprogramming, MAC protocol, Hierarchy, Pipelining, Scope Selection Support and Idle listening to adaptive sleeping etc. These features are surveyed for various Code dissemination protocols both Entire Program Image based & Difference-based Methods for reprogramming WSN. Keywords: Dissemination protocols, network reprogramming, over the air programming (OAP), reprogramming architectures, wireless sensor network

Dynamic Memory Allocator for Sensor Operating System Design and Analysis

Dynamic memory allocation is an important mechanism used in operating systems. An efficient dynamic memory allocator can improve the performance of operating systems. In wireless sensor networks, sensor nodes have miniature computing device, small memory space and very limited battery power. Therefore, it is important that sensor operating systems operate efficiently in terms of energy consumption and resource management. And the role of dynamic memory allocator in sensor operating system is more important than one of general operating system. In this paper, we propose a new dynamic memory allocation scheme that resolves the existing problems in dynamic memory allocators. We implemented our scheme on Nano-Qplus which is a sensor operating system based on multi-threading. Our experimental results and static analysis result show our scheme performs efficiently in terms of the execution time and the memory space compared with existing memory allocation mechanisms.

A Real-Time-Enabled, Blackboard-Based, Publish/Subscribe Architecture for Wireless Sensor Nodes

Wireless sensor network nodes have only limited resources concerning memory and battery life-time. Mem- ory can be efficiently used by sharing data, and the life-time of a battery can be extended, when the node has long power saving sleep-phases. We propose a publish/subscribe architecture that achieves these two aims. The results of our work are of great interest for sensor application developers, giving them now the opportu- nity to use our architecture for sharing data among different applications on the node as well as the different layers of the operating system. We introduce a blackboard which is used for centrally storing published val- ues, like measured data from a monitored sensor. This makes it possible to share stored data without monitoring the sensors once again, which is advantageously concerning power consumption, memory space, and reaction time. Beside the proposed publish/subscribe method for sensor nodes with its notification possibili- ties, our architecture fulfills also real-time requirements. We show how the well-known sensor operating system MANTIS OS can be extended by a real-time enabled, blackboard-based publish/subscribe architect- ture. This architecture and first of all its implementation is of special interest for cross layer optimization of sensor applications. Cross-layer approaches benefit from our architecture because the available implementa- tion can be used as an efficient framework for central storing and managing of shared values.

A lightweight policy system for body sensor networks

Body sensor networks (BSNs) for healthcare have more stringent security and context adaptation requirements than required in large-scale sensor networks for environment monitoring. Policy-based management enables flexible adaptive behavior by supporting dynamic loading, enabling and disabling of policies without shutting down nodes. This overcomes many of the limitations of sensor operating systems, such as TinyOS, which do not support dynamic modification of code. Alternative schemes for adaptation, such as network programming, have a high communication cost and suffer from operational interruption. In addition, a policy-driven approach enables fine-grained access control through specifying authorization policies. This paper presents the design, implementation and evaluation of an efficient policy system called Finger which enables policy interpretation and enforcement on distributed sensors to support sensor level adaptation and fine-grained access control. It features support for dynamic management of policies, minimization of resources usage, high responsiveness and node autonomy. The policy system is integrated as a TinyOS component, exposing simple, well-defined interfaces which can easily be used by application developers. The system performance in terms of processing latency and resource usage is evaluated.

Molecule: An adaptive dynamic reconfiguration scheme for sensor operating systems

In wireless sensor networks, sensor nodes are located on remote-site and thus it is very difficult to re-gather them. To update or add a program at run-time of the sensor nodes, sensor operating system must support a dynamic reconfiguration. Many kinds of different mechanisms for reconfiguring sensor nodes have been developed ranging from full image replacement to virtual machines. In previous schemes, dynamic linker supports only indirect linking between modules, and the linking is performed on the sensor nodes. Those may increase overhead of the execution time and energy consumption. In this paper, we present an adaptive and dynamic reconfiguration scheme called Molecule for sensor nodes. In Molecule, applications, kernel features, and device drivers are managed as a form of module. By using the cost analysis of the expected execution time of each module, Molecule selects an appropriate method between direct and indirect linking to link modules. It also supports remote linker to exclude the linking overhead from the sensor nodes. Our experimental results show that Molecule performs efficiently in terms of the energy consumption and execution time compared with the existing dynamic reconfiguration schemes.