On software verification for sensor nodes

Techniques and tools for verification of multi-threaded programs must cope with the huge number of possible thread interleavings. Tools based on systematic exploration of a program state space employ partial order reduction to avoid redundant thread interleavings. The key idea is to make non-deterministic thread scheduling choices only at statements that read or modify the global state shared by multiple threads. We focus on the approach to partial order reduction used in tools such as Java Pathfinder (JPF), which construct the program state space on-the-fly, and therefore can use only information available in the current program state and execution history to identify statements that may be globally-relevant. In our previous work, we developed a field access analysis that provides information about fields that may be accessed during program execution, and used it in JPF for more precise identification of globally-relevant statements. We build upon that and propose a may-happen-before analysis that computes a sound approximation of the happens-before ordering. Partial order reduction techniques can use the happens-before ordering to detect pairs of globally-relevant field access statements that cannot be interleaved arbitrarily (due to thread synchronization), and based on that avoid making unnecessary thread scheduling choices. The may-happen-before analysis combines static analysis with knowledge of information available from the dynamic program state. Results of experiments with several Java programs show that usage of the may-happen-before analysis further improves the performance of JPF.

In software security testing, fuzz testing and symbolic execution are two main testing techniques. Fuzz testing finds program bugs by executing the target program with random inputs it generates while monitoring the execution for abnormal behaviors. Though fuzz testing is able to explore deep into a program's state space efficiently, it usually cannot guarantee the code coverage ratio in many situations. Symbolic execution treats a program's input as symbols and executes the program with such symbolic input. Symbolic execution tries to explore the whole state space of a program by analyzing all of the program's paths. Symbolic execution always guarantees the code coverage ratio in theory, but for real programs it has many problems such as path explosion. Our new method, hybrid fuzz testing, combines the benefits of fuzz testing and symbolic execution. Symbolic execution will start to work and to generate new program input when fuzz testing cannot increase the code coverage ratio. The experiment result implies that our hybrid fuzz testing method can obviously increase the code coverage ratio efficiently in reasonable resources using.

An effective way to maximize code coverage in software tests is through dynamic symbolic execution$-$a technique that uses constraint solving to systematically explore a program's state space. We introduce an open-source dynamic symbolic execution framework called Manticore for analyzing binaries and Ethereum smart contracts. Manticore's flexible architecture allows it to support both traditional and exotic execution environments, and its API allows users to customize their analysis. Here, we discuss Manticore's architecture and demonstrate the capabilities we have used to find bugs and verify the correctness of code for our commercial clients.

A wireless pressure sensor node design method and realization is put forward aiming at problems of dynamic pressure test in the hermetic cavity or cabin, such as high wiring difficulty and influence on air flow field. Dynamic gauge pressure signal is transmitted by a wireless sensor node in consideration of temperature affection factors. The sensor node is mainly composed of gauge and atmospheric pressure, temperature sensor, signal acquisition and modulation module, wireless RF module, data memory, lithium battery. On the basis of the above, the prototype is developed. The effectiveness and reliability of the wireless pressure sensor node are verified in means of sea trial test.

Many sensor nodes contain resource constrained microcontrollers where user level applications, operating system components, and device drivers share a single address space with no form of hardware memory protection. Programming errors in one application can easily corrupt the state of the operating system or other applications. In this paper, we propose Harbor, a memory protection system that prevents many forms of memory corruption. We use software based fault isolation ("sandboxing") to restrict application memory accesses and control flow to protection domains within the address space. A flexible and efficient memory map data structure records ownership and layout information for memory regions; writes are validated using the memory map. Control flow integrity is preserved by maintaining a safe stack that stores return addresses in a protected memory region. Run-time checks validate computed control flow instructions. Cross domain calls perform low-overhead control transfers between domains. Checks are introduced by rewriting an application's compiled binary. The sand-boxed result is verified on the sensor node before it is admitted for execution. Harbor's fault isolation properties depend only on the correctness of this verifier and the Harbor runtime. We have implemented and tested Harbor on the SOS operating system. Harbor detected and prevented memory corruption caused by programming errors in application modules that had been in use for several months. Harbor's overhead, though high, is less than that of application-specific virtual machines, and reasonable for typical sensor workloads.

Sensors have a strong connection to the real world, which sets them apart from conventional networks in a major way. Through the use of a variety of sensing devices as well as the processing of raw data, sensor networks may detect & monitor physical phenomena occurring in the locations/regions where even the sensors are located or deployed. Physical phenomena linked with geographic locations/regions are much more important to users of wireless sensor networks over raw data from individual sensor nodes. Geospatial information is becoming more important in sensor networks and applications, and sensor nodes having GPS signal receivers become more widely available. Sensor nodes may also be located without GPS using a variety of localization methods. A location-aware sensor network is now possible thanks to these recent technological advancements. To address the issue of estimating the location and position among wireless sensor nodes, new approaches, techniques, and algorithms must be created. In order to achieve this goal, In this Paper, we are proposing a Distance Vector Hop (DV-Hop) algorithm that Significantly decreases the average of localization error of sensor nodes and which is a solution for localizing nodes having few adjacent anchors. simulation results prove that the proposed algorithm substantially reduces the average of localization error of sensor nodes

A large number of potential applications for Wireless Sensor and Actuator Networks (WSAN) have yet to be embraced by industry despite high interest amongst academic researchers. This is due to various factors such as unpredictable costs related to development, deployment and maintenance of WSAN, especially when integration with existing IT infrastructure and legacy systems is needed. Service-Oriented Architecture (SOA) is seen as a promising technique to bridge the gap between sensor nodes and enterprise applications such as factory monitoring, control, and tracking systems where sensor data is used. To date, research efforts have focused on middleware software systems located in gateway devices that implement standard service technology, such as Devices Profile for Web Services (DPWS), for interacting with the sensor network. This paper takes a different approach-deploying interoperable Simple Object Access Protocol (SOAP)-based web services directly on the nodes and not using gateways. This strategy provides for easy integration with legacy IT systems and supports heterogeneity at the lowest level. Twofold analysis of the related overhead, which is the main challenge of this solution, is performed; Quantification of resource consumption as well as techniques to mitigate it are presented, along with latency measurements showing the impact of different parts of the system on system performance. A proof-of-concept application using Mulle-a resource-constrained sensor platform-is also presented.

Proposed wireless sensor node is a highly flexible and programmable system on chip (PSoC) architecture along with integrated RF radio chip, which can be adapted to any IEEE 802.15.4 standard based protocol, working at the band of 2.4GHz.This can be accompanied by the RF antenna matched with the interface circuit for various kinds of sensors and peripherals to form a wireless sensor node.This can be very well used to form a wireless sensor network in different domains.This proposed methodology can be used for specific application for improving the WSN stability and performance.This article will mainly present the design of wireless sensor nodes based on PSoC and CyFi radio chip, including the application specific antenna and hardware design for the system on chip for the sensor node and the simple introduction of the application domain.The proposed nodes are used with a special antenna and application based protocol for communication.This design has a better power handling and performing capacity.Further, we have implemented this for the wireless sensor node as well.

In recent work we have introduced performance evaluation programming - a programming paradigm supporting performance analysis and formal verification of concurrent programs. For software verification the ranges of variables must be bounded, and programs are translated into finite-state continuous-time Markov chains verified formally by using probabilistic model checking techniques. Our present aim is to increase the size of the state space of programs that can be verified formally. The solution investigated in this paper is inspired by equivalence partitioning - a well-known software testing technique. We provide experimental results showing that, by partitioning the state space of concurrent programs into behavioral equivalence classes, the performance evaluation programming paradigm can be used to design and verify formally concurrent programs with large state spaces.

The efficiency of transportation system depends on many factors, such as traffic congestion, vehicle accidents and road conditions. To improve the reliability, productivity and safety of the system, many researchers propose to use a wireless sensor network (WSN) as a solution. A WSN usually consists of many tiny sensor nodes for sensing, data processing and communication. In this study, we present the development of a small-sized, low-power and lightweight wireless sensor node. It is equipped with a 3-axes accelerometer, an altimeter sensor, humidity sensor, temperature sensor, 315 MHz RF transceiver module and a typical coin-sized lithium battery (3.0 V, 220 mAh). The entire sensor node fits within a 28 × 20 × 8 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> volume and is only 7 grams (not including the antenna). An 8-bit MCU is included in the RF transceiver module to control sensor node operation. It collects and transmits sensors data in real time to the RF repeater with bit rate 24 kbps. During continuous operation, the sensor node consumes less than 3 mA current. Thus for a 220 mAh battery, the wireless sensor node can continue operating for more than 75 hours.

Over the last few years, IoT devices have multiplied their number and functionality. These devices are located all over the world and batteries are their main source of energy. In this paper the usage of wireless LoRaWAN sensor node in smart Internet of Things applications was analyzed. The study focuses on the reduction of power consumption from wireless LoRaWAN sensor nodes. An analysis of the energy consumption of the various components of the architecture of the wireless sensor nodes is performed. An energy model of the energy consumed by the sensor nodes is presented and analyzed. The result of the analysis provides an accurate identification of the main energy consumers, the magnitude of their consumption and an in-depth understanding of the key mechanisms that need to be applied to improve energy efficiency in wireless sensor nodes. The emphasis is on the presented energy efficient protocol. Three action scenarios from the sensor nodes are presented, outlining the main guidelines and strategies for improving the efficiency of the wireless nodes. In addition, the research results reveal the magnitude of energy savings that can be achieved by implementing the improved duty cycle mechanisms in wireless sensor nodes.

A multi-Mobile Agent and optimal itinerary planning-based data aggregation in Wireless Sensor Networks

Wireless sensor node is an autonomous and compact device that has capability to monitor a variety of real-world phenomena. It is designed composed of sensing device, embedded processor, communication module, and power equipment. Wireless sensor node is part of wireless sensor network where hundred or thousand sensor node can be deployed. Over the past decade Wireless Sensor Networks (WSNs) have emerged as one of the computing platforms of note within the electronics community. In prediction, there will be more than 127 million wireless sensor nodes deployed worldwide by 2014. We have surveyed 100 currently available wireless sensor network node platforms have been developed and produced not only by the research institutions, the universities but also some companies in last ten years. In this paper, we present a review of 27 different wireless sensor node platforms. We review these devices under a number of different parameters, and we highlight the key advantages of each node platform according to dimension and power consumption. We also discuss the characteristics and trend of development and deployment a wireless sensor node technology.

In order to solve the problems that ever wireless sensor nodes' energy consumption is high and solar-powered wireless nodes are greatly influenced by the weather and the system is not stable, comprehensive utilization of solar energy power supply technology, sensor technology and wireless communication technology, this paper designs a new type of wireless sensor nodes, which is powered by solar energy. The wireless sensor nodes which is supplied by solar energy, solving the problem of the energy consumption of sensor nodes effectively. After tested, it has simple operation, high reliability and it can satisfy the requirement of environmental parameter acquisition and monitoring work.

Pervasive computing is an environment consisting set of sensor nodes with the characteristics of perception, computation and communication capabilities. Wireless sensor nodes are deployed in various pervasive computing applications to observe the happenings in the surroundings. Data gathered from such wireless sensor nodes are utilized for critical decision making in context-aware environment. The Frequent incorrect data sampling, missing values, untrustworthy data, misbehavior and selfishness of nodes are common in pervasive applications since they are deployed in unfriendly and harsh environment. Moreover, the increasing number of sensor node fabricator leads to interoperability problems in context aware pervasive applications because they are represented in different formats and processed using different techniques. In this paper, we propose an ontology based trust framework for sensor driven pervasive environment for evaluating node and data trustworthiness which suffers from heterogeneity and interoperability problems. The proposed approach is capable of handling all types of nodes in pervasive environment and heterogeneous data generated from harsh and unfriendly environments of context aware pervasive applications. The proposed method comprises of semantic sensor data model and an ontology which is written in OWL language and implemented in protege. The proposed ontology is validated against use case and used for finding the trustworthiness of different sensor nodes and its data using a generic TRUST ontology.