TinyOS-New Trends, Comparative Views, and Supported Sensing Applications: A Review

This paper presents a survey on the current state-of-the-art in Wireless Sensor Network (WSN) Operating Systems (OSs). In recent years, WSNs have received tremendous attention in the research community, with applications in battlefields, industrial process monitoring, home automation, and environmental monitoring, to name but a few. A WSN is a highly dynamic network because nodes die due to severe environmental conditions and battery power depletion. Furthermore, a WSN is composed of miniaturized motes equipped with scarce resources e.g., limited memory and computational abilities. WSNs invariably operate in an unattended mode and in many scenarios it is impossible to replace sensor motes after deployment, therefore a fundamental objective is to optimize the sensor motes’ life time. These characteristics of WSNs impose additional challenges on OS design for WSN, and consequently, OS design for WSN deviates from traditional OS design. The purpose of this survey is to highlight major concerns pertaining to OS design in WSNs and to point out strengths and weaknesses of contemporary OSs for WSNs, keeping in mind the requirements of emerging WSN applications. The state-of-the-art in operating systems for WSNs has been examined in terms of the OS Architecture, Programming Model, Scheduling, Memory Management and Protection, Communication Protocols, Resource Sharing, Support for Real-Time Applications, and additional features. These features are surveyed for both real-time and non-real-time WSN operating systems.

The design of operating system for Wireless Sensor Network (WSN) deviates from the traditional operating system design due to their specific characteristics like constrained resources, high dynamics and inaccessible deployment environments. We provide a classification framework that surveys the state of the art in WSN Operating Systems (OS). The purpose of this survey is two-fold, one is to classify the existing operating systems according to important OS features, and the other is to suggest appropriate OSs for different categories of WSN applications, mapping the application requirements and OS features. This classification helps in understanding the contrasting differences among existing operating systems, and lays a foundation to design an ideal WSN OS. We also classified existing WSN applications, to help the application developer in choosing the appropriate OS, based on the application requirements. Summary and analysis, and discussion of future research directions in this area have been presented.

Nowadays, the efficiency of multiagent systems in wireless sensor networks prompts the researchers to use these emerging mobile software packets in different simulated approaches or real-world applications. Heterogeneous and distributed wireless sensor networks could be integrated with the multiagent systems to map the real-world challenges into the artificial intelligence world. The multiagent systems have been applied from simulated approaches like object detection/tracking, healthcare, control/assistant, and security systems to real-world applications, including medical/human-care systems and unmanned aerial vehicles. Furthermore, the integration of wireless sensor networks with multiagent systems have emerged novel application, which is known as mobile robots. However, the extensive use of mobile agents in wireless sensor networks has posed different challenges for researchers, including security, resource, and timing limitation. In this work, we review recent simulated approaches and real-world applications of multiagent systems in wireless sensor networks, in which a set of common factors about the things that have been studied are extracted and compared to analyze the performance of mobile agent–based systems in the wireless sensor networks, as well. This analysis provides new research directions about multiagent systems in wireless sensor networks for interested researchers. Finally, a novel framework for dealing with the challenges of multiagent-based applications in the wireless sensor networks which have been mentioned is suggested.

Disseminating sensory information from sensor nodes to the gateway node towards Data Center Server has to be guaranteed its fruitfulness. However, these important information commonly are transmitted over wireless connections whereas everyone including adversaries may join freely in the network. Hence, the correctness of received information should be emphasized. To do so, such information should be ascertained from the authenticated sensor nodes, kept its secrecy, prevented from the alteration, and guaranteed its integrity, respectively without revealing sensor nodes' identity. On the other hand, data sensors in the Data Center Server also should be kept secret and only be accessed by authenticated users over common public connection such as Internet without exposing the users' privacy. Therefore, an anonymous authentication system in collecting data sensors from sensor nodes to the Data Center Server and accessing them by everyone would be strongly desirable. In this paper, we propose an implementation of anonymous authentication system in the wireless sensor network using VLR group signature.

A scheme for WSNs (wireless sensor networks) security is given by dividing sensing tetrahedron into clusters and using the symmetric polynomials in this paper.The sensing tetrahedron is divided into a number of small grids.All those sensor nodes, both ordinary sensor nodes and heterogeneous sensor nodes are distributed in the sensing tetrahedron.In a grid, all ordinary sensor nodes and heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.All the heterogeneous sensor nodes establish their shared keys through using the symmetric polynomials.At last, all sensor nodes establish their keys directly or indirectly in the whole sensing tetrahedron.Analysis and comparison demonstrate this scheme enhances the WSN security, has good network connectivity, saves node storage, reduces network computing load, and extends the network lifetime.

Background and Objectives: In this work, we explore the implementation of the binary consensus algorithm in wireless sensor networks. Binary consensus is used to allow a collection of distributed entities to reach consensus regarding the answer to a binary question. Existing work on the algorithm focuses on simulation of the algorithm under the assumption of a fully connected network topology and unlimited messaging capabilities. In this new work, we adapt the algorithm to function in wireless sensor networks where the topology might not be fully connected and the number of messages sent should be minimized in order to save power. Methods: We are deploying and testing our implementation in a hardware embedded systems, mainly IRIS Motes. Our implementation of the binary consensus algorithm is written in NesC and runs on the Tiny Operating System (TinyOS). The implementation was tested on 11 sensor nodes, with current plans to test it on far more. Results: To support our hardware implementation results, a simulation using the Tiny Operating System SIMulator (TOSSIM) was done. Our results in hardware implementation and simulation are consistent with the original binary consensus algorithm. Conclusion: In this work, we adapted the binary consensus algorithm for use in wireless sensor networks. Our implementation for a small number of IRIS motes shows correct results consistent with those of simulation. In future work we will evaluate the effectiveness of the algorithm when scaled to hundreds of sensor motes.

One important issue in wireless sensor networks is how to gather sensed information in an energy efficient way since the energy is a scarce resource in a sensor node. Many protocols have been proposed for data-gathering between wireless sensor nodes. However, most of these protocols work on static wireless sensor networks. In this paper, we provide clustering-based and time-driven protocols which minimize energy dissipation for data-gathering in wireless mobile sensor networks where the sensor nodes are capable of mobility. We first consider the node mobility when organizing clusters. Our protocols will have a sensor node select a proper cluster-head to join in order to save energy. We then consider how to elect the cluster-heads and provide two algorithms for cluster-head election. Last, we implement all the protocols and perform the experiments for evaluating the protocols.

Underground coal mines are susceptible to many kinds of hazards. Mine fire is one of the most vulnerable threats that leads to loss of human lives and other resources inside the mines. Hence, continuous monitoring of underground coal mines is very important for early detection of mine fire. Nowadays, wireless sensor networks are being widely used for monitoring underground coal mines. However, the collected data from sensor nodes are inaccurate in nature, and there is a need for analyzing such data for taking preventive measure. In this article, we propose an optimized fuzzy logic-based fire monitoring system for wireless underground sensor network, which strengthens reliability of making decision in preventing mine fire. However, storing of large fuzzy rule set in the memory constraint sensor nodes and their traversal for every sensor reading are very challenging. Therefore, we use the binary particle swarm optimization (BPSO) algorithm to optimize the proposed fuzzy system that eliminates redundant rules but preserves event detection accuracy of the monitoring system. The proposed system is simulated using BPSO algorithm and Fuzzy Logic Toolbox inbuilt in the MATLAB. The simulation results demonstrate that the proposed system outperforms the existing monitoring systems for underground coal mines.

Node placement for connected target coverage in wireless sensor networks with dynamic sinks

The outdoor ambient temperature variations impact the performance of devices in wireless sensor network (WSN) systems. This paper presents a WSN system for researching the impact of temperature changing on the signal intensity of the WSN system. The system consists of a PC, a getaway and a sensor node. A transmission power self-adjusting algorithm is proposed. The influence of temperature on the WSN system and the function of the transmission power self-adjusting algorithm are tested respectively. The experimental results show that the signal intensity of the WSN system decreases 3.5 dBm while ambient temperature increases from 20 °C to 50 °C. The results verify that the transmission power self-adjusting algorithm is effective for stable communication and energy saving.

Virtualization has become a core technique to support a data center, which usually consists of hardware, virtual machine(VM), and operating system(OS) etc. With virtualization, users can make good use of resources provided in a data center with resource protection and efficient hardware utilization. However, as data amount has increased very rapidly, many issues such as low power and resource sharing have become very critical. To resolved these issues, this paper presents a novel simulation environment based on a tiny OS, Hard Disk Drive (HDD), and Solid State Drive(SSD) to help users and designers understand a data center via simulation and analysis. Compared with the previous work, our tool can simulate and analyze homogeneous and heterogeneous systems with a multi-layer approach. Although each part of a data center has been studied by researchers, the analysis for data centers with multiple layers or heterogeneous devices is still an important issue. If programmers cannot analyze a data center, they are not easy to handle resources efficiently or understand cross-layer influence. They may encounter unpredictable challenges arising from the integration of various components. To address these challenges, programmer and system designer will be need thorough understanding of multi-layer heterogenous system. We propose a new simulation tool called Data Center Simulator(DCSim). We have used small-scale os and storage simulation to achieve multi-layer system simulation to help us to understand multi-layer heterogenous system. Therefore, programmer can simulate and analysis the system that we will analysis the parallel program and different storage deices on DCSim.

In a ZigBee network, low-cost, low-power sensor nodes are deployed to carry out specific tasks like environment sensing, home automation, human and animal condition monitoring, and robot navigation monitoring etc. Normally the network comprises of numerous sensor nodes deployed in different locations and a coordinator node where the sensor nodes report back the sensed data for possible analysis and further action. For certain applications it is desirable to be able to locate the sensor node within the network. Currently localisation can be achieved using time dependent methods (TOA and TDOA) or received signal strength (RSS). Time dependent approaches require time synchronisation at all times which can be difficult to achieve. RSS based method is simple and cost effective but require at least three anchor nodes for a nodes location to be calculated via triangulation. Such a method can increase the complexity and cost of a network deployment. This paper presents a single anchor based location system which utilizes a differential two-element antenna array to perform node localization. An experimental system is introduced and results demonstrate the effectiveness of the proposed system. The anchor node, which can also be the network gateway, is connected to two dipole antennas separated by ⋋/2. The relative phase of each antenna can be varied using a phase shifter. The combined output of the two antennas can be used to create sum and difference radiation patterns, and to steer the antenna radiation pattern. Experimental validation was performed using seven XBee sensor nodes. Accurate azimuthal localization (relative to the anchor node) can be achieved and range estimation can be made with minimal errors. Adaptive path-loss model estimation can further improve range estimation. Overall, this cost effective localisation system performs well for ZigBee based wireless sensor networks.

We leverage the frontiers of the Internet of Things technology in a recently developed end-to-end wireless sensor network (WSN) system that samples, collects, stores, and displays mountain hydrology measurements in near real-time. At the core of the system lies an ultra-low power, radio channel-hoping, and self-organizing mesh that allows for remote autonomous sampling of snow. Such properties, combined with a rugged weather-sealed design of the devices and multi-level data replication, provides reliable real-time data at spatial and temporal scales previously impractical to achieve in mountain environments. The system was deployed at three 1 km 2 sites across the North Fork of the Feather River basin with a cluster of 12 sensor nodes for each location. Measurements show that existing operational autonomous systems are non-representative spatially, with biases that can reach up to 50%. A comparison between a wet and dry year showed that snow depths exhibit strong multi-scale inter-year spatial stationarity with major rank conservation. Temporally dense analysis using elastic net regression shows that dominant features at the sub-km 2 scale are site-dependent and differ from the watershed scale. Newly introduced explanatory variables, based on the nearest neighbor with a Landsat assimilated historical product, consistently explained up to 90% of the variance in the watershed-scale SWE for both years. At two WSN sites, lagged cross-correlation of snowmelt with stream flow measurements showed a significant improvement of up to 100% compared with existing systems, suggesting that WSNs can be instrumental in improving runoff forecasting and water management.

Conventional wireless sensor networks rely mostly on simple scalar data (such as temperature or humidity) and specialize in single-purpose applications. Taking a fundamental departure, in this article we motivate information-rich wireless video sensor networks that emulate the compound eyes found in certain arthropods. Although constrained by scarce resources, sensor nodes can only serve extremely low-resolution video streams; the availability of vast amount of such streams due to deployment redundance can suffice for the need of information hungry applications. Unfortunately, the unique characteristics of wireless video sensor networks will introduce novel uncertainty-driven challenges in the information-intensive and yet resource-constrained environment. Correspondingly, we describe key research problems in the areas of networking, security, sensor design, and video-data analysis

Pattern transformation-invariant schemes for wireless sensor networks based on an edge detection gradient-based mechanism