Operating System For Sensor Nodes Research Articles

Improving network formation in IEEE 802.15.4e DSME

Wireless Sensor and Actuator Networks are becoming attractive also for industrial applications, since recent standardization efforts have introduced significant improvement to reliability and deterministic communication delays. In this context, IEEE 802.15.4e is widely considered the major improvement, introducing many enhancements to the original IEEE 802.15.4 standard aimed at supporting critical applications. Among the new defined MAC protocols, Deterministic and Synchronous Multi-channel Extension (DSME) represents the most suitable option for applications with time-varying requirements. In this paper, an analysis of the IEEE 802.15.4 DSME MAC protocol during network formation is presented. The goal is to study the protocol performance and propose solutions to reduce the network formation time, improving energy and resource efficiency. To carry out the performance evaluation, DSME has been fully implemented in Contiki OS, an actual operating system for sensor nodes. The study has highlighted issues and inefficiencies in the network formation process, allowing to consequently propose effective solutions. In particular, it is proposed a set of guidelines for DSME configuration to the original MAC protocol that are proved to increase significantly the network formation efficiency.

Design, Implementation and Testing of a Cost Function Based Scheduling Mechanism for a Water Management System

The IEEE 802.15.4 standard for low data rate and low power devices is currently in use by many Internet of Things (IoT) networks and control networks based on wireless sensor networks. One such application area is the water management systems for water supply and usage control. With the implementation of this standard in Contiki, no mechanism is present for control messages when other packets are being transmitted as well in the network. The gateway devices in these networks are usually exposed to more load in the network. During periods of high demand, packet dropping can occur at these nodes as well as other intermediate nodes that forward data. To address the high packet loss and congestion that takes place when the load level is high in a water telemetry management network, we propose a novel scheduling mechanism. This scheduling mechanism was implemented in the COOJA simulator using the Contiki operating system for wireless sensor nodes as an enhancement to carrier sense multiple access with collision avoidance (CSMA/CA). The results show that with the application of the proposed cost function (CF) scheduling strategy, packet loss is reduced and throughput is improved in multi-hop networks over the default scheduling mechanism. This mechanism can also be implemented in other rapid growing Internet of Things (IoT) networks and can improve performance when carrying high loads.

An SDN-Assisted Framework for Optimal Deployment of MapReduce Functions in WSNs

In this paper, we propose a solution to support big data processing with MapReduce inside a wireless sensor network (WSN). The proposed framework provides a simple MapReduce interface, whose implementation can be dynamically loaded into the appropriate nodes. The execution of map and reduce functions inside the network is achieved by leveraging software defined networking principles and in particular by enhancing the SDN-WISE protocol on both the Controller and the sensor node sides. On the Controller side, the proposed framework introduces a functionality, which evaluates the optimal deployment of the processing functions in the network taking the typical WSN requirements into account and enforces it by instructing the flow tables to forward traffic from the mappers to the appropriate reducers. Then, on the node side, SDN-WISE is integrated with Contiki, a widely popular operating system for sensor nodes, which has the capability to load and execute new functions without service disruption, i.e., on the fly. The proposed framework is evaluated considering different network topologies and approaches about the data processing location.

Design and Implementation of a State-Driven Operating System for Highly Reconfigurable Sensor Networks

Due to the low-cost and low-power requirement in an individual sensor node, the available computing resources turn out to be very limited like small memory footprint and irreplaceable battery power. Sensed data fusion might be needed before being transmitted as a tradeoff between procession and transmission in consideration of saving power consumption. Even worse, the application program needs to be complicated enough to be self-organizing and dynamically reconfigurable because changes in an operating environment continue even after deployment. State-driven operating system platform offers numerous benefits in this challenging situation. It provides a powerful way to accommodate complex reactive systems like diverse wireless sensor network applications. The memory usage can be bounded within a state transition table. The complicated issues like concurrency control and asynchronous event handling capabilities can be easily achieved in a well-defined behavior of state transition diagram. In this paper, we present an efficient and effective design of the state-driven operating system for wireless sensor nodes. We describe that the new platform can operate in an extremely resource constrained situation while providing the desired concurrency, reactivity, and reconfigurability. We also compare the executing results after comparing some benchmark test results with those on TinyOS.

Modeling and Analysis of TinyOS Sensor Node Firmware

Wireless sensor networks are an increasingly popular application area for embedded systems. Individual sensor nodes within a network are typically resource-constrained, event-driven, and require a high degree of concurrency. This combination of requirements motivated the development of the widely used TinyOS sensor node operating system. The TinyOS concurrency model is a lightweight nonpreemptive system designed to suit the needs of typical sensor network applications. Although the TinyOS concurrency model is easier to reason about than preemptive threads, it can still give rise to undesirable behavior due to unexpected interleavings of related tasks, or unanticipated preemption by interrupt handlers. To aid TinyOS developers in understanding the behavior of their programs we have developed a technique for using the process algebra Communicating Sequential Processes (CSP) to model the interactions between TinyOS components, and between an application and the TinyOS scheduling and preemption mechanisms. Analysis of the resulting models can help TinyOS developers to discover and diagnose concurrency-related errors in their designs that might otherwise go undetected until after the application has been widely deployed. Such analysis is particularly valuable for the TinyOS components that are used as building blocks for a large number of other applications, since a subtle or sporadic error in a widely deployed building block component could be extremely costly to repair.

A Reusable Device Driver Framework for the Sensor Nodes in Internet of Things

Due to the rapid development of Internet of Things (IoT), kinds of sensor nodes have been introduced to the different applications. Because of the variety of MCUs, sensors and radio modules, it’s challenging to reuse the device drivers between different sensor node platforms. To address this issue, a reusable device driver framework is proposed in this paper. Comparing with existed work, our framework is flexible, efficient, and easy to learn. The flexibility is achieved by layered encapsulation, which decouples the device driver with the sensor node operating system kernel. Our framework gives the reusability at the source code level, so it’s efficient. At the end, our framework is implemented in C programming language, which is the most common tool adopted by embedded system developing. This framework has applied to SenSpire OS, a micro-kernel real-time operating system for IoT sensor nodes.

PAVENET OS: A Compact Hard Real-Time Operating System for Precise Sampling in Wireless Sensor Networks

The paper shows a compact hard real-time operating system for wireless sensor nodes called PAVENET OS. PAVENET OS provides hybrid multithreading: preemptive multithreading and cooperative multithreading. Both of the multithreading are optimized for two kinds of tasks on wireless sensor networks, and those are real-time tasks and best-effort ones. PAVENET OS can efficiently perform hard real-time tasks that cannot be performed by TinyOS. The paper demonstrates the hybrid multithreading realizes compactness and low overheads, which are comparable to those of TinyOS, through quantitative evaluation. The evaluation results show PAVENET OS performs 100 Hz sensor sampling with 0.01% jitter while performing wireless communication tasks, whereas optimized TinyOS has 0.62% jitter. In addition, PAVENET OS has a small footprint and low overheads (minimum RAM size: 29 bytes, minimum ROM size: 490 bytes, minimum task switch time: 23 cycles).

TinyOS에서의 선점적 EDF 스케줄링 알고리즘 설계 및 구현

A sensor network is a special network that makes physical data sensed by sensor nodes and manages the data. The sensor network is a technology that can apply to many parts of field. It is very important to transmit the data to a user at real-time. The core of the sensor network is a sensor node and small operating system that works in the node. TinyOS developed by UC Berkeley is a sensor network operating system that used many parts of field. It is event-driven and component-based operating system. Basically, it uses non-preemptive scheduler. If an urgent task needs to be executed right away while another task is running, the urgent one must wait until another one is finished. Because of that property, it is hard to guarantee real-time requirement in TinyOS. According to recent study, Priority Level Scheduler, which can let one task preempt another task, was proposed in order to have fast response in TinyOS. It has restrictively 5 priorities, so a higher priority task can preempt a lower priority task. Therefore, this paper suggests Preemptive EDF(Earliest Deadline First) Scheduler that guarantees a real-time requirement and reduces average respond time of user tasks in TinyOS.

무선 센서 노드를 위한 FSM 기반 운영체제의 구현

무선 센서 네트워크는 단거리 무선 통신으로 연결된 지능 센서가 사람과 실세계 객체간의 효과적인 매개자 역할을 하므로 최근 유비쿼터스 컴퓨팅 환경을 가능하게 할 수 있는 핵심적인 기술 중 하나로 각광을 받고 있다. 무선 센서 네트워크는 대량으로 분산된 극도의 내장형 시스템으로 볼 수 있다. 이 시스템은 분산 시스템으로서 병행성과 비동기적 이벤트 처리 능력에 대한 요구사항과 함께 내장형 시스템으로서 자원제한성에 따른 심각한 요구사항을 갖고 있다. 이러한 일견 상충하는 두 가지 요구사항을 갖는 무선 센서 네트워크의 운영 환경과 구조는 시스템 개발자에게 매우 독특한 어려움을 제기하고 있으므로 우리는 유한상태기계에 기반을 둔, 매우 새로운 형태의 센서 네트워크용 운영체제를 제안한다. 본 논문에서는 센서 네트워크의 특성을 감안한 설계 목표를 명시하고, 간결하고 효율적인 상태기반 운영체제인 SenOS 설계와 구현의 핵심 사항을 제시한다. 또한 이러한 SenOS가 심각한 자원제한성을 갖는 센서 노드 상에서 원하는 반응성을 갖으면서도 적은 비용으로 동적 재구성이 가능하다는 것을 설명한다. 이러한 성능은 대표적인 센서 노드용 운영체제인 TinyOS의 성능평가에 사용된 벤치마크 프로그램을 수행하고 그 결과를 TinyOS의 경우와 비교한다. Wireless sensor networks have emerged as one of the key enabling technologies for ubiquitous computing since wireless intelligent sensor nodes connected by short range communication media serve as a smart intermediary between physical objects and people in ubiquitous computing environment. We recognize the wireless sensor network as a massively distributed and deeply embedded system. Such systems require concurrent and asynchronous event handling as a distributed system and resource-consciousness as an embedded system. Since the operating environment and architecture of wireless sensor networks, with the seemingly conflicting requirements, poses unique design challenges and constraints to developers, we propose a very new operating system for sensor nodes based on finite state machine. In this paper, we clarify the design goals reflected from the characteristics of sensor networks, and then present the heart of the design and implementation of a compact and efficient state-driven operating system, SenOS. We describe how SenOS can operate in an extremely resource constrained sensor node while providing the required reactivity and dynamic reconfigurability with low update cost. We also compare our experimental results after executing some benchmark programs on SenOS with those on TinyOS.

Wireless Sensor Networks for Indoor Environment Monitoring Using LabVIEW

Wireless sensor networks (WSNs) have gained worldwide attention in recent years, particularly with the rapid progress in Micro-Electro-Mechanical Systems (MEMS) technology which has facilitated the development of smart sensors. These sensors are small, with limited processing and computing resources, and they are inexpensive compared to traditional sensors. These sensor nodes can sense, measure, and gather information from the environment and, based on some local decision process, they can transmit the sensed data to the user. WSNs are large networks made of a numerous number of sensor nodes with sensing, computation, and wireless communication capabilities. In present work we provide a brief summary of the state-ofthe- art in wireless sensor networks, investigate the feasibility of indoor environment monitoring using crossbow wireless sensor nodes. Here we used nesC programming language and TinyOS operating system for programming Crossbow sensor nodes and LabVIEW GUI is used for displaying different indoor environmental parameters such as temperature, humidity and light acquired from different Wireless sensor nodes. These sensor readings can help building administrators to monitor the physical conditions of the environment in a building for creating optimized energy usage.

원격 코드 업데이트가 가능한 무선 센서 노드용 운영체제

센서 네트워크 기술은 이러한 센서 노드를 특정한 지역에 대량으로 배치하여 네트워크를 구성한 후 센서 노드를 정보 제공의 매체로 활용하는 기술이다. 센서 노드는 매우 제한적인 하드웨어 자원을 가지고 있기 때문에 효율적인 자원 관리와 센서 네트워크상에서의 다양한 응용 환경을 제공하는 운영체제가 필요하다. 또한 원격 코드 업데이트는 이미 배포된 네트워크에서 응용 프로그램의 오류가 발생하여 이를 수정하거나 성능 개선을 위해 꼭 필요한 기술이다. 본 논문에서는 원격 코드 업데이트가 용이한 새로운 센서 노드용 운영체제, EPRCU(Easy to Perform Remote Code Update)를 제안한다. EPRCU는 이벤트 드리븐 방식의 실행 모델에서 에이징(Aging) 기법을 적용한 우선순위 기반의 프로세스 스케줄링 방식을 사용한다. 작업의 기본 단위인 프로세스는 로더에 의한 동적 메모리 할당 및 프로그램 메모리 관리 기능을 제공함으로써 무선 통신을 이용한 코드 업데이트 수행이 용이할 뿐만 아니라 다양한 센서 네트워크 응용에도 적합하다. Sensor networks monitor the environment, collect sensed data, and relay the data back to a collection point. Although sensor nodes have very limited hardware resources, they require an operating system that can provide efficient resource management and various application environments. In addition, the wireless sensor networks require the code update previously deployed to patch bugs in program and to improve performance of kernel service routines and application programs. This paper presents EPRCU (Easy to Perform Remote Code Update), a new operating system for wireless sensor nodes, which has enhanced functionalities to perform remote code update. To achieve an efficient code update, the EPRCU provides dynamic memory allocation and program memory management. It supports the event-driven kernel, which uses priority-based scheduling with the application of aging techniques. Therefore, the proposed operating system is not only easy to perform wireless communication with the remote code update but also suitable for various sensor network applications.

센서노드의 센서 투명성을 지원하는 TinyOS의 확장

본 논문에서는 범용 운영체제에서 제공하는 디바이스 투명성을 센서노드 운영체제에 적용한 센서 투명성 아키텍처를 제안하였다. 센서 투명성을 지원하기 위한 표준 API와 센서 디바이스 추상화를 설계하고 TinyOS 운영체제에서 구현하였다. 본 논문에서 제안한 센서 투명성 지원 센서노드 운영체제를 사용하면 응용 개발자는 운영체제에서 제공되는 표준 API를 통해 센서 디바이스에 독립적으로 응용 프로그램을 개발할 수 있고, 센서 디바이스 공급자 또한 표준화된 하드웨어 인터페이스와 HAL 인터페이스를 통해 센서노드 하드웨어 플랫폼에 독립적으로 센서 디바이스 드라이버를 개발하고 공급할 수 있다. In this paper, we proposed an architecture for supporting sensor transparency in sensor node operating systems, design the standard APIs (Application Programming Interfaces) and sensor device abstraction to provide the sensor transparency and implemented the sensor transparency in the TinyOS, the most well known sensor node operating system. With the proposed sensor node operating system which can support the sensor transparency, application developers can develop the target applications independent to each sensor device by using the standard APIs provided by the sensor node operating system and the sensor device manufacturers also can develop sensor device drivers by using the standard hardware interfaces and HAL (Hardware Adaptation Layer) interfaces independent to the specific hardware platform of sensor nodes.

A Comprehensive Experimental Comparison of Event Driven and Multi-Threaded Sensor Node Operating Systems

The capabilities of a sensor network are strongly influenced by the operating system used on the sensor nodes. In general, two different sensor network operating system types are currently considered: event driven and multi-threaded. It is commonly assumed that event driven operating systems are more suited to sensor networks as they use less memory and processing resources. However, if factors other than resource usage are considered important, a multi-threaded system might be preferred. This paper compares the resource needs of multi-threaded and event driven sensor network operating systems. The resources considered are memory usage and power consumption. Additionally, the event handling capabilities of event driven and multi-threaded operating systems are analyzed and compared. The results presented in this paper show that for a number of application areas a thread-based sensor network operating system is feasible and preferable.