Sensor positioning is a crucial part of many location-dependent applications that utilize wireless sensor networks (WSNs). Current localization approaches can be divided into two groups: range-based and range-free. Due to the high costs and critical assumptions, the range-based schemes are often impractical for WSNs. The existing range-free schemes, on the other hand, suffer from poor accuracy and low scalability. Without the help of a large number of uniformly deployed seed nodes, those schemes fail in anisotropic WSNs with possible holes. To address this issue, we propose the Rendered Path (REP) protocol. To the best of our knowledge, REP is the only range-free protocol for locating sensors with constant number of seeds in anisotropic sensor networks.

Contour mapping is a crucial part of many wireless sensor network applications. Many efforts have been made to avoid collecting data from all the sensors in the network and producing maps at the sink, which is proven to be inefficient. The existing approaches (often aggregation based), however, suffer from heavy transmission traffic and incur large computational overheads on each sensor node. We propose Iso-Map, an energy-efficient protocol for contour mapping, which builds contour maps based solely on the reports collected from intelligently selected “isoline nodes” in wireless sensor networks. Iso-Map achieves high-quality contour mapping while significantly reducing the generated traffic from O(n) to O ( n), where n is the total number of sensor nodes in the field. The per-node computation overhead is also restrained as a constant. We conduct comprehensive trace-driven simulations to verify this protocol, and demonstrate that Iso-Map outperforms the previous approaches in the sense that it produces contour maps of high fidelity with significantly reduced energy cost. 1.

Abstract—The proliferation of wireless and mobile devices has fostered the demand for context-aware applications, in which location is one of the most significant contexts. Multilateration, as a basic building block of localization, however, has not yet overcome the challenges of 1) poor ranging measurements; 2) dynamic and noisy environments; and 3) fluctuations in wireless communications. Hence, multilateration-based approaches often suffer from poor accuracy and can hardly be employed in practical applications. In this study, we propose Quality of Trilateration (QoT) that quantifies the geometric relationship of objects and ranging noises. Based on QoT, we design a confidence-based iterative localization scheme, in which nodes dynamically select trilaterations with the highest quality for location computation. To validate this design, a prototype network based on wireless sensor motes is deployed and the results show that QoT well represents trilateration accuracy, and the proposed scheme significantly improves localization accuracy. Index Terms—Localization, noisy range measurements, trilateration, wireless ad-hoc and sensor networks. Ç 1

Abstract. We propose FIT, a flexible, light-weight and real-time scheduling system for wireless sensor platforms. There are three salient features of FIT. First, its two-tier hierarchical framework supports customizable application-specific scheduling policies, hence FIT is very flexible. Second, FIT is light-weight in terms of minimizing thread number to reduce preemptions and memory consumption while at the same time ensuring system schedulability. We propose a novel Minimum Thread Scheduling Policy (MTSP) exploration algorithm within FIT to achieve this goal. Finally, FIT provides a detailed real-time schedulability analysis method to help check if application’s temporal requirements can be met. We implemented FIT on MICAz motes, and carried out extensive evaluations. Results demonstrate that FIT is indeed flexible and light-weight for implementing real-time applications, at the same time, the schedulability analysis provided can predict the real-time behavior. FIT is a promising scheduling system for implementing complex real-time applications in sensor networks. 1

Existing deployments of wireless sensor networks (WSNs) are often conceived as stand-alone monitoring tools. In this paper, we report instead on a deployment where the WSN is a key component of a closed-loop control system for adaptive lighting in operational road tunnels. WSN nodes along the tunnel walls report light readings to a control station, which closes the loop by setting the intensity of lamps to match a legislated curve. The ability to match dynamically the lighting levels to the actual environmental conditions improves the tunnel safety and reduces its power consumption. The use of WSNs in a closed-loop system, combined with the real-world, harsh setting of operational road tunnels, induces tighter requirements on the quality and timeliness of sensed data, as well as on the reliability and lifetime of the network. In this work, we test to what extent mainstream WSN technology meets these challenges, using a dedicated design that however relies on wellestablished techniques. The paper describes the hw/sw architecture we devised by focusing on the WSN component, and analyzes its performance through experiments in a real, operational tunnel.

Abstract—Knowing accurate positions of nodes in wireless ad-hoc and sensor networks is essential for a wide range of pervasive and mobile applications. However, errors are inevitable in distance measurements and we observe that a small number of outliers can degrade localization accuracy drastically. To deal with noisy and outlier ranging results, triangle inequality is often employed in existing approaches. Our study shows that triangle inequality has a lot of limitations which make it far from accurate and reliable. In this study, we formally define the outlier detection problem for network localization and build a theoretical foundation to identify outliers based on graph embeddability and rigidity theory. Our analysis shows that the redundancy of distance measurements plays an important role. We then design a bilateration generic cycles based outlier detection algorithm, and examine its effectiveness and efficiency through a network prototype implementation of MicaZ motes as well as extensive simulations. The results shows that our design significantly improves the localization accuracy by wisely rejecting outliers. 1.

Abstract — Location awareness is highly critical for wireless ad-hoc and sensor networks. Many efforts have been made to solve the problem of whether or not a network can be localized. Nevertheless, based on the data collected from a working sensor network, it is observed that the network is NOT always entirely localizable. Theoretical analyses also suggest that, in most cases, it is unlikely that all nodes in a network are localizable, although a (large) portion of the nodes can be uniquely located. Existing studies merely examine whether or not a network is localizable as a whole; yet two fundamental questions remain unaddressed: First, given a network configuration, whether or not a specific node is localizable? Second, how many nodes in a network can be located and which are them? In this study, we analyze the limitation of previous works and propose a novel concept of node localizability. By deriving the necessary and sufficient conditions for node localizability, for the first time, it is possible to analyze how many nodes one can expect to locate in sparsely or moderately connected networks. To validate this design, we implement our solution on a real-world system and the experimental results show that node localizability provides useful guidelines for network deployment and other location-based services. I.

In this paper, we study the co-scheduling problem of periodic application transactions and update transactions in real-time database systems for surveillance of critical events. To perform the surveillance functions effectively, it is important to meet the deadlines of the application transactions while maintaining the quality of the real-time data objects accessed by them. Unfortunately, these two goals are conflicting and difficult to be achieved at the same time. To address the co-scheduling problem, we propose a real-time coscheduling algorithm, called Adaptive Earliest Deadline First Co-Scheduling (AEDF-Co) in which we adopt a dynamic scheduling approach to adaptively schedule the update and application jobs based on their deadlines. The performance goal of AEDF-Co is that for given sets of periodic application and update transactions, it determines a schedule such that the deadline constraints of all the application transactions are satisfied and at the same time the quality of data (QoD) of the real-time data objects are maximized. Extensive simulation experiments are performed to evaluate the performance of AEDF-Co. The results show that by adaptively adjusting the release times of update jobs and scheduling the update and application jobs dynamically based on their urgencies, AEDF-Co is effective in achieving the performance goals and maximizing the overall system performance. Keywords: Real-time database systems; Data freshness; Real-time co-scheduling; Update generation and processing; 1.

Abstract—In spite of the remarkable efforts the community put to build the sensor systems, an essential question still remains unclear at the system level, motivating us to explore the answer from a point of real-world deployment view. Does the wireless sensor network really scale? We present findings from a large scale operating sensor network system, GreenOrbs, with up to 330 nodes deployed in the forest. We instrument such an operating network throughout the protocol stack and present observations across layers in the network. Based on our findings from the system measurement, we propose and make initial efforts to validate three conjectures that give potential guidelines for future designs of large scale sensor networks. (1) A small portion of nodes bottlenecks the entire network, and most of the existing network indicators may not accurately capture them. (2) The network dynamics mainly come from the inherent concurrency of network operations instead of environment changes. (3) The environment, although the dynamics are not as significant as we assumed, has an unpredictable impact on the sensor network. We suggest that an event-based routing structure can be trained optimal and thus better adapt to the wild environment when building a large scale sensor network. I.

Energy-efficient transmission and bit allocation