Abstract—In this paper, we investigate the theoretical aspects of the nonuniform node distribution strategy used to mitigate the energy hole problem in wireless sensor networks (WSNs). We conclude that in a circular multihop sensor network (modeled as concentric coronas) with nonuniform node distribution and constant data reporting, the unbalanced energy depletion among all the nodes in the network is unavoidable. Even if the nodes in the inner coronas of the network have used up their energy simultaneously, the ones in the outermost corona may still have unused energy. This is due to the intrinsic many-to-one traffic pattern of WSNs. Nevertheless, nearly balanced energy depletion in the network is possible if the number of nodes increases in geometric progression from the outer coronas to the inner ones except the outermost one. Based on the analysis, we propose a novel nonuniform node distribution strategy to achieve nearly balanced energy depletion in the network. We regulate the number of nodes in each corona and derive the ratio between the node densities in the adjacent ði þ 1Þth and ith coronas by the strategy. Finally, we propose q-Switch Routing, a distributed shortest path routing algorithm tailored for the proposed nonuniform node distribution strategy. Extensive simulations have been performed to validate the analysis. Index Terms—Wireless sensor networks, nonuniform node distribution, energy hole problem, energy-efficient routing. 1

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.

Sensor network application experts such as biologists, geologists, and environmental engineers generally have little experience with, and little patience for, general-purpose and often low-level sensor network programming languages. We believe sensor network languages should be designed for application experts, who may not be expert programmers. To further that goal, we propose the concepts of sensor network application archetypes, archetype-specific languages, and archetype templates. Our work makes the following contributions. (1) We have examined a wide range of wireless sensor networks to develop a taxonomy of seven archetypes. This taxonomy permits the design of compact languages that are appropriate for novice programmers. (2) We developed a language (named WASP) and its associated compiler for a commonly encountered archetype. (3) We conducted user studies to evaluate the suitability of WASP and several alternatives for novice programmers. To the best of our knowledge, this 56-hour 28-user study is the first to evaluate a broad range of sensor network languages (TinyScript, Tiny-SQL, SwissQM, and TinyTemplate). On average, users of other languages successfully implemented their assigned applications 30.6 % of the time. Among the successful completions, the average development time was 21.7 minutes. Users of WASP had an average success rate of 80.6%, and an average development time of 12.1 minutes (an improvement of 44.4%).

Recently, wireless sensor networks (WSNs) attract a great deal of research attention, and are envisioned to support a variety of applications, including military surveillance, habitat monitoring, and infrastructure protection, etc. Operating system (OS) support for WSNs plays a central role in building scalable distributed applications that are efficient and reliable. Over the years, we have seen a variety of OSes emerging in the sensornet community to facilitate developing WSN applications. Aside from the basic system implementations, there is also a large body of work devoted to improving OS capabilities in different dimensions. In this paper, we provide a comprehensive review of existing work in sensornet OS design. We first examine the challenges in the OS design space. We then introduce the major components of a sensornet OS. Next, we provide an overview of existing work, present a taxonomy of state-of-the-art OSes, and discuss various approaches to address the design challenges. Finally we discuss evaluations of a sensornet OS and present some recommendations in the perspectives of OS developers and OS users. We have also identified several open problems that need further investigation to make the OS provide stronger support for WSNs.

Abstract—Existing approaches to diagnosing sensor networks are generally sink-based, which rely on actively pulling state information from all sensor nodes so as to conduct centralized analysis. However, the sink-based diagnosis tools incur huge communication overhead to the traffic sensitive sensor networks. Also, due to the unreliable wireless communications, sink often obtains incomplete and sometimes suspicious information, leading to highly inaccurate judgments. Even worse, we observe that it is always more difficult to obtain state information from the problematic or critical regions. To address the above issues, we present the concept of self-diagnosis, which encourages each single sensor to join the fault decision process. We design a series of novel fault detectors through which multiple nodes can cooperate with each other in a diagnosis task. The fault detectors encode the diagnosis process to state transitions. Each sensor can participate in the fault diagnosis by transiting the detector’s current state to a new one based on local evidences and then pass the fault detector to other nodes. Having sufficient evidences, the fault detector achieves the Accept state and outputs the final diagnosis report. We examine the performance of our self-diagnosis tool called TinyD2 on a 100 nodes testbed. I.

Abstract — Data aggregation is an efficient mechanism widely used in wireless sensor networks (WSN) to collect statistics about data of interests. However, the shared-medium nature of communication makes the WSNs are vulnerable to eavesdropping and packet tampering/injection by adversaries. Hence, how to protect data privacy and data integrity are two major challenges for data aggregation in wireless sensor networks. In this paper, we present iPDA — an integrity-protecting private data aggregation scheme. In iPDA, data privacy is achieved through data slicing and assembling technique; and data integrity is achieved through redundancy by constructing disjoint aggregation paths/trees to collect data of interests. In iPDA, the data integrity-protection and data privacy-preservation mechanisms work synergistically. We evaluate the performance of iPDA scheme in terms of communication overhead and data aggregation accuracy, comparing with a typical data aggregation scheme – TAG, where no integrity protection and privacy preservation is provided. Simulation results show that iPDA achieves the design goals while still maintains the efficiency of data aggregation. 1 I.

This work proposes to utilize the wireless sensor network as an infrastructure system for navigating internal users under emergencies. The users are equipped with communicating devices like 802.15.4 compatible PDAs that talk with

Abstract—We propose a measure to characterize the energy efficiency of algorithms for localization in wireless networks. The measure presented differs from previous approaches in that it is bounded and supports objective comparison. Furthermore, it corresponds to the general understanding that a high value should indicate high efficiency. Simulation results for localization using Maximum Likelihood Estimation (MLE), for Least Squares Estimation (LS) and for Multidimensional Scaling (MDS) are briefly discussed. I.

Abstract—Event detection is a crucial task for wireless sensor network applications, especially environment monitoring. Existing approaches for event detection are mainly based on some predefined threshold values and, thus, are often inaccurate and incapable of capturing complex events. For example, in coal mine monitoring scenarios, gas leakage or water osmosis can hardly be described by the overrun of specified attribute thresholds but some complex pattern in the full-scale view of the environmental data. To address this issue, we propose a nonthreshold-based approach for the real 3D sensor monitoring environment. We employ energy-efficient methods to collect a time series of data maps from the sensor network and detect complex events through matching the gathered data to spatiotemporal data patterns. Finally, we conduct trace-driven simulations to prove the efficacy and efficiency of this approach on detecting events of complex phenomena from real-life records. Index Terms—Distributed applications, data compaction and compression, query processing, wireless sensor networks. Ç 1

any additional equipment like GPS. SaSa supports safety evaluation through the analysis of the global topology information. In addition, it can notify the others for help when a team member falls in danger.