Quality-aware data abstraction layer for collaborative 2-tier sensor network applications

In sensor network applications, data gathering mechanisms, which are based on multi-hop forwarding can be expensive in terms of energy. This limitation reduces the lifetime of the network and challenges the use of sensor networks for applications that demand a predefined operational lifetime. To avoid this problem, the benefits of using mobile gateway to prolong sensor life-time have been explored in the literature. However, practical considerations such as the gateway speed and route planning, sensor buffer size and data frequency generation constraints impose limits on the mobile elements. In this work, we consider the natural hybrid solution that combines the two approaches of mobile gateways and multi-hop forwarding to address more constraints for sensor applications. We provide algorithmic solutions that attempt to balance the benefits of both approaches. Based on a given predetermined time deadline, a gateway tour will be established to involve a subset of the sensors. These selected sensors will work as gathering points and will aggregate the other sensors' data. The gathering points/nodes are selected with the aim of reducing the energy expenditures due to multi-hop forwarding. Using approximation-preserving reductions, we discuss the hardness of this problem. We also present a heuristic-based solution and validate its performance through an extensive set of experiments.

The Wireless sensor network has a great applied prospect, so the military, academia and industry pay more and more extensive attention. The first, this article introduces the concept of sensor networks and development background; the second, compared with traditional networks, it summarizes the characteristics of sensor networks. In this basis, the application of the sensor network and the direction of the current study are a given brief introduction and a further discussion.

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.

Wireless sensor networks are self-organizing systems with resource-constraints that are often deployed in inhospitable and inaccessible environments in order to gather data about some phenomenon in the outside world. For most sensor network applications, point-to-point reliability is not the main objective (Paradis & Qi, 2007); Instead, reliable delivery of the interesting event to the server has to be guaranteed (may be with a certain probability). The communication in such networks is unpredictable and failure-prone, even more so than in regular wireless ad hoc networks. Hence, it is vital to provide fault tolerant techniques for distributed applications in sensor network. Several approaches have been proposed in many recent studies to address the fault tolerance issue in application, transport and/or routing layers. In this paper, we propose a slight modification of the conventional routing (destination, next hop) by introducing the second hop information in the route construction phase in order to use it in case of node/link failure (skip only the failed link). Furthermore, the implementation of this proposed routing technique stabilizes the throughput, reduces the average jitter, provides low control overhead and decreases the energy consumption of the network. As a result, the reliability, availability, energy-efficiency and maintainability of the network are achieved.

The energy problem is one of the most important challenges in the application of sensor networks. With the development of wireless charging technology and intelligent mobile charger (MC), the energy problem can be solved by the wireless charging strategy. In the practical application of wireless rechargeable sensor networks (WRSNs), the energy consumption rate of nodes is dynamically changed due to many uncertainties, such as the death and different transmission tasks of sensor nodes. However, existing works focus on on-demand schemes, which not fully consider real-time global charging scheduling. In this article, a novel dynamic charging scheme (DCS) in WRSN based on the actor-critic reinforcement learning (ACRL) algorithm is proposed. In the ACRL, we introduce gated recurrent units (GRUs) to capture the relationships of charging actions in time sequence. Using the actor network with one GRU layer, we can pick up an optimal or near-optimal sensor node from candidates as the next charging target more quickly and speed up the training of the model. Meanwhile, we take the tour length and the number of dead nodes as the reward signal. Actor and critic networks are updated by the error criterion function of R and V. Compared with current on-demand charging scheduling algorithms, extensive simulations show that the proposed ACRL algorithm surpasses heuristic algorithms, such as the Greedy, DP, nearest job next with preemption, and TSCA in the average lifetime and tour length, especially against the size and complexity increasing of WRSNs.

A wireless sensor network consists of many sensors that collect and transmit physical or environmental conditions at different locations to a server continuously. Many researches mainly focus on processing continuous queries on real-time data stream. However, they do not concern the problem of storing the historical data, which is mandatory to the historical queries. In this paper, we propose a system architecture for handling and storing sensor data stream in real-time to support the spatial and/or temporal queries besides continuous queries. We exploit a segment-based method to store the sensor data stream and reduce the managed tuples without any loss of information, which lead to the improvement of the accuracy of query results. In addition, we offer a method to reduce the cost of join operations in processing spatiotemporal queries by filtering out the list of irrelevant sensors from the query range before making the join operation. We then present a design of the system architecture for processing spatial and/or temporal queries. Finally, we implement a climate monitoring application system based on our proposed system architecture.

In this paper, we propose a system architecture for handling and storing sensor data stream in real-time to support the spatial and/or temporal queries besides continuous queries. We exploit a segment-based method to store the sensor data stream and reduce the managed tuples without any loss of information, which lead to the improvement of the accuracy of query results. In addition, we offer a method to reduce the cost of join operations in processing spatiotemporal queries by filtering out the list of irrelevant sensors from the query range before making the join operation. We then present a design of the system architecture for processing spatial and/or temporal queries. Finally, we implement a climate monitoring application system.KeywordsWireless Sensor NetworkSensor Data StreamSpatiotemporal Data StreamContinuous QueryHistorical Query

Many sensor network applications, such as object tracking and disaster monitoring, require effective techniques for event detection. In this paper, we propose a novel event detection mechanism based on matching the contour maps of in-network sensory data distribution. Our key observation is that events in sensor networks can be abstracted into spatio-temporal patterns of sensory data and that pattern matching can be done efficiently through contour map matching. Therefore, we propose simple SQL extensions to allow users to specify common types of events as patterns in contour maps and study energy-efficient techniques of contour map construction and maintenance for our pattern-based event detection. Our experiments with synthetic workloads derived from a real-world coal mine surveillance application validate the effectiveness and efficiency of our approach.

Wireless sensor networking is a rapidly merging research area. There are many areas where Wireless Sensor Network (WSN) applications are very important such as military, healthcare, agricultural and transportation. In WSN applications, power consumption is foremost crucial. Therefore reducing power consumption is a focal concern when developing WSN applications. Majority of power in WSN environment is used for communication purpose. As such the facility to acquire data based on location only from sensor node at required location would save power consumption. However this type of data acquisition has not been possible due to the unavailability of spatial queries. The acquisitional queries should be enhanced with the location aspect and moreover each sensor node should also be made aware of its location. This will enable user to specify queries based on the location and only the corresponding nodes respond by acquiring data. Thus main objective of this research is to come up with this enhancement. We have purposed spatial query syntaxes which have similar features as in Relational database spatial queries and main target of that approach is to increase the user friendliness. Other than that sensor nodes in the sensor network are capable to identify its location based on the GPS value. We evaluate these issues in the context of TikiriDB, a distributed, shared WSN, query processor for smart sensor devices, and show how acquisitional data based on location can provide significant reductions in power consumption on our sensor devices.

Many investigations of scientific collaboration are based on statistical analyses of large networks constructed from bibliographic repositories. These investigations often rely on a wealth of bibliographic data, but very little or no other information about the individuals in the network, and thus, fail to illustrate the broader social and academic landscape in which collaboration takes place. In this article, we perform an in-depth longitudinal analysis of a relatively small network of scientific collaboration (N = 291) constructed from the bibliographic record of a research centerin the development and application of wireless and sensor network technologies. We perform a preliminary analysis of selected structural properties of the network, computing its range, configuration and topology. We then support our preliminary statistical analysis with an in-depth temporal investigation of the assortative mixing of selected node characteristics, unveiling the researchers’ propensity to collaborate preferentially with others with a similar academic profile. Our qualitative analysis of mixing patterns offers clues as to the nature of the scientific community being modeled in relation to its organizational, disciplinary, institutional, and international arrangements of collaboration.

Many applications of wireless sensor networks, such as object tracking and disaster monitoring, require effective and efficient techniques to detect events of interest in the physical world. Despite the simplicity in implementation, the existing threshold-based approach to event detection suffers from a limited expressive power and a poor tolerance to missing values and errors in sensor data. In this thesis, we present three novel database approaches to event detection for sensor networks: (i) a pattern-based approach that abstracts events as temporal patterns on individual sensor nodes, (ii) a contour map-based approach that represent events as spatial shapes in the sensor value distribution across nodes, and (iii) a model-based approach that specifies events as regression models over spatial regions in the sensor network. The key observation of all three approaches is that, because an event generates a particular kind of sensor data distribution, the problem of event detection can be converted into that of matching this distribution. In each of the three proposed approaches, we formalize the event specification and develop efficient matching algorithms. The experimental results on both real-world and synthetic data sets demonstrate the effectiveness and efficiency of our proposed approaches.

Recent work has shown an increased use in the application of mobile unmanned aerospace sensor networks for complex sensing applications. Future UAS sensor networks will employ complex and dynamic network topologies and the use of heterogeneous platforms with sensors of different configurations and capabilities. Onboard or “in-situ” assessment of payload sensor data at the vehicle level will likely be critical in many future applications. We review some current and recent uses of UAS sensor networks in various application domains, and examine the potential for improved performance with some simple sensor data assessment models. We describe a simple wide-area survey problem as a paradigm for many future heterogeneous sensor network missions; this problem is similar to several currently being investigated for different sensing applications. We describe a simple modeling tool that can be used to simulate the effects of vehicle behavior on mission performance, and present results from a simple example which explores the effects of data assessment. We discuss applications to future UAS networks and extensions to additional real-world effects.

Recent advances in low-power sensing devices coupled with the widespread availability of wireless ad-hoc networks have fueled the development of sensor networks. These are typically deployed over wide areas to gather data in the environment and monitor events of interest. The ability to run spatial queries is extremely useful for sensor networks. Spatial query execution has been extensively studied in the context of centralized spatial databases; however because of the energy and bandwidth limitation of sensor nodes these solutions are not directly applicable to the sensor network. In this paper we propose a scalable and distributed way of spatial query execution in sensor networks. We develop a distributed spatial index over the sensor nodes that is used in processing spatial queries in a distributed fashion. We evaluate the behavior of our approach and show that our mechanism provides an efficient and scalable way to run spatial queries over sparse and dense sensor networks.

The Steiner tree problem asks for a minimum cost tree spanning a given set of terminals S⊂eqV in a weighted graph G = (V,E,c), c:E→ R+. In this paper we consider a generalization of the Steiner tree problem, so called Polymatroid Steiner Problem, in which a polymatroid P = P(V) is defined on V and the Steiner tree is required to span at least one base of P (in particular, there may be a single base S⊂eqV). This formulation is motivated by the following application in sensor networks – given a set of sensors S = {s1,…,s k }, each sensor s i can choose to monitor only a single target from a subset of targets X i , find minimum cost tree spanning a set of sensors capable of monitoring the set of all targets X = X1 ∪ … ∪ X k . The Polymatroid Steiner Problem generalizes many known Steiner tree problem formulations including the group and covering Steiner tree problems. We show that this problem can be solved with the polylogarithmic approximation ratio by a generalization of the combinatorial algorithm of Chekuri et al. (2002). We also define the Polymatroid directed Steiner problem which asks for a minimum cost arborescence connecting a given root to a base of a polymatroid P defined on the terminal set S. We show that this problem can be approximately solved by algorithms generalizing methods of Chekuri et al. (2002).

In-network aggregation is a useful technique to mitigate the limited power problem in sensor networks. In order to further reduce power usage, many efforts have focused on the application layer. In contrast, our work integrates the application and network layers with a focus on the generation of a routing topology for sensor networks. We present a grouping technique to construct a routing tree topology based on information contained within specific queries. This "query informed" method enables the query process to be efficient in terms of energy consumption. The technique is aimed at applications that require long-duration queries, and is described in terms of algorithmic behavior, simulation experiments, and comparative analysis to conventional techniques