Octav Chipara

Real-time Power-Aware Routing in Sensor Networks

Many wireless sensor network applications must resolve the inherent conflict between energy efficient communication and the need to achieve desired quality of service such as end-to-end communication delay. To address this challenge, we propose the real-time power-aware routing (RPAR) protocol, which achieves application-specified communication delays at low energy cost by dynamically adapting transmission power and routing decisions. RPAR features a power-aware forwarding policy and an efficient neighborhood manager that are optimized for resource-constrained wireless sensors. Moreover, RPAR addresses important practical issues in wireless sensor networks, including lossy links, scalability, and severe memory and bandwidth constraints. Simulations based on a realistic radio model of MICA2 motes show that RPAR significantly reduces the number of deadlines missed and energy consumption compared to existing real-time and energy-efficient routing protocols

Reliable clinical monitoring using wireless sensor networks: experiences in a step-down hospital unit

This paper presents the design, deployment, and empirical study of a wireless clinical monitoring system that collects pulse and oxygen saturation readings from patients. The primary contribution of this paper is an in-depth clinical trial that assesses the feasibility of wireless sensor networks for patient monitoring in general hospital units. We present a detailed analysis of the system reliability from a long term hospital deployment over seven months involving 41 patients in a step-down cardiology unit. The network achieved high reliability (median 99.68%, range 95.21% -- 100%). The overall reliability of the system was dominated by sensing reliability of the pulse oximeters (median 80.85%, range 0.46% -- 97.69%). Sensing failures usually occurred in short bursts, although longer periods were also present due to sensor disconnections. We show that the sensing reliability could be significantly improved through oversampling and by implementing a disconnection alarm system that incurs minimal intervention cost. A retrospective data analysis indicated that the system provided sufficient temporal resolution to support the detection of clinical deterioration in three patients who suffered from significant clinical events including transfer to Intensive Care Units. These results indicate the feasibility and promise of using wireless sensor networks for continuous patient monitoring and clinical deterioration detection in general hospital units.

A component-based architecture for power-efficient media access control in wireless sensor networks

The diverse requirements of wireless sensor network applications necessitate the development of multiple media access control (MAC) protocols to meet their varying throughput, latency, and network lifetime needs. Building new MAC protocols has proven to be extremely difficult, however, given the monolithic nature of existing protocol implementations as well as their dependence on a particular radio or processor platform. To address these issues, we propose the MAC Layer Architecture (MLA), a component-based architecture for power-efficient MAC protocol development in wireless sensor networks. MLA consists of optimized, reusable components that implement a common set of features shared by existing MAC protocols, as well as abstractions that encapsulate the intricacies of the hardware platforms they run on. Through an instantiation of MLA in TinyOS 2.0.1, we have implemented five representative MAC protocols. Empirical results show that MLA results in significant code reuse among different protocols, while achieving comparative performance and memory footprints to monolithic implementations of the same protocols.

Robust topology control for indoor wireless sensor networks

Topology control can reduce power consumption and channel contention in wireless sensor networks by adjusting the transmission power. However, topology control for wireless sensor networks faces significant challenges, especially in indoor environments where wireless characteristics are extremely complex and dynamic. We first provide insights on the design of robust topology control schemes based on an empirical study in an office building. For example, our analysis shows that Received Signal Strength Indicator and Link Quality Indicator are not always robust indicators of Packet Reception Rate in indoor environments due to significant multi-path effects. We then present Adaptive and Robust Topology control (ART), a novel and practical topology control algorithm with several salient features: (1) ART is robust in indoor environments as it does not rely on simplifying assumptions about the wireless properties; (2) ART can adapt to variations in both link quality and contention; (3) ART introduces zero communication overhead for applications which already use acknowledgements. We have implemented ART as a topology layer in TinyOS 2.x. Our topology layer only adds 12 bytes of RAM per neighbor and 1.5 kilobytes of ROM, and requires minimal changes to upper-layer routing protocols. The advantages of ART have been demonstrated through empirical results on a 28-node indoor testbed.

A Spatiotemporal Query Service for Mobile Users in Sensor Networks

This paper presents MobiQuery, a spatiotemporal query service that allows mobile users to periodically gather information from their surrounding areas through a wireless sensor network. A key advantage of MobiQuery lies in its capability to meet stringent spatiotemporal performance constraints crucial to many applications. These constraints include query latency, data freshness and fidelity, and changing query areas due to user mobility. A novel just-in-time prefetching algorithm enables MobiQuery to maintain robust spatiotemporal guarantees even when nodes operate under extremely low duty cycles. Furthermore, it significantly reduces the storage cost and network contention caused by continuous queries from mobile users. We validate our approach through both theoretical analysis and simulation results under a range of realistic settings

Building Grid Portal Applications From a Web Service Component Architecture

This work describes an approach to building Grid applications based on the premise that users who wish to access and run these applications prefer to do so without becoming experts on Grid technology. We describe an application architecture based on wrapping user applications and application workflows as Web services and Web service resources. These services are visible to the users and to resource providers through a family of Grid portal components that can be used to configure, launch, and monitor complex applications in the scientific language of the end user. The applications in this model are instantiated by an application factory service. The layered design of the architecture makes it possible for an expert to configure an application factory service with a custom user interface client that may be dynamically loaded into the portal.

Dynamic Conflict-free Query Scheduling for Wireless Sensor Networks

With the emergence of high data rate sensor network applications, there is an increasing demand for high- performance query services in such networks. To meet this challenge, we propose Dynamic Conflict-free Query Scheduling (DCQS), a novel scheduling technique for queries in wireless sensor networks. In contrast to earlier TDMA protocols designed for general-purpose networks and workloads, DCQS is specifically designed for query services supporting in-network data aggregation. DCQS has several important features. First, it optimizes the query performance and energy efficiency by exploiting the temporal properties and precedence constraints introduced by data aggregation. Second, it can efficiently adapt to dynamic workloads and rate changes without explicitly reconstructing the transmission schedule. In addition, we provide an analytical capacity bound for DCQS in terms of query completion rate. This bound enables DCQS to handle overload through rate control. NS2 simulation results demonstrate that DCQS significantly outperforms a representative TDMA protocol (DRAND) and the 802.11 protocol in terms of query latency, throughput, and energy efficiency.

Real-time Power Aware Routing in Wireless Sensor Networks

Many mission-critical wireless sensor network applications must resolve the inherent conflict between the tight resource constraints on each sensor node, particularly in terms of energy, with the need to achieve desired quality of service such as end-to-end real-time performance. To address this challenge we propose the Real-time Power-Aware Routing (RPAR) protocol. RPAR achieves required communication delays at minimum energy cost by dynamically adapting the transmission power and routing decisions based on packet deadlines. RPAR integrates a geographic forwarding policy cognizant of deadlines, power, and link quality with new algorithms for on-demand power adaptation and efficient neighborhood discovery. Simulations based on a realistic radio model of MICA2 motes show that RPAR significantly reduces the number of deadline misses and energy consumption when compared to existing real-time and energyefficient routing protocols and beacon based neighborhood management schemes.

Dynamic wake-up and topology maintenance protocols with spatiotemporal guarantees

Many mission-critical applications require spatiotemporal data services for mobile users or objects. Examples include distributed object tracking and fire monitoring by firefighters. To support such applications, wireless sensor networks must satisfy a set of stringent spatiotemporal constraints despite having low network duty cycles and scarce resources. We have developed two new wake-up and topology maintenance protocols, directional tree maintenance (DTM) and omnidirectional tree creation (OTC), to support spatiotemporal services in mobile environments. A key feature of our protocols is that they provide robust spatiotemporal performance while maintaining low overhead and energy consumption. Our simulations showed that both DTM and OTC can successfully deliver over 85% of query results to a mobile user within desired spatiotemporal constraints, even when the sleep schedule is as long as 15 s, the user changes direction every minute, and the location error is as high as 10 m. The benefits of our protocols have been validated through theoretical analysis and empirical results on a testbed of Mica2 motes.

Practical modeling and prediction of radio coverage of indoor sensor networks

The robust operation of many sensor network applications depends on deploying relays to ensure wireless coverage. Radio mapping aims to predict network coverage based on a small number of link measurements. This problem is particularly challenging in complex indoor environments where walls significantly affect radio signal propagation. Nevertheless, we show that it is feasible to accurately predict coverage through a two-step process: a propagation model is used to predict signal strength at a recipient node, which is then mapped to a coverage prediction. Through an in-depth empirical study, we show that complex models do not necessarily produce accurate estimates of signal strength: there is an important tradeoff between model accuracy and the number of parameters that must be estimated from limited training data. We find that the best performance is achieved by a family of models which classify walls based on their attenuation into a small number of classes and develop an algorithm to perform this classification automatically. Based on these insights, we build a novel Radio Mapping Tool (RMT) for predicting radio converge in indoor environments. Experimental results demonstrate RMTs effectiveness in two buildings: RMT reduces the number of locations where coverage is erroneously predicted to exist by as much as 39% and 54% compared to the classic log-normal radio propagation model.