Pei Zhang

Hardware design experiences in ZebraNet

The enormous potential for wireless sensor networks to make a positive impact on our society has spawned a great deal of research on the topic, and this research is now producing environment-ready systems. Current technology limits coupled with widely-varying application requirements lead to a diversity of hardware platforms for different portions of the design space. In addition, the unique energy and reliability constraints of a system that must function for months at a time without human intervention mean that demands on sensor network hardware are different from the demands on standard integrated circuits. This paper describes our experiences designing sensor nodes and low level software to control them.n In the ZebraNet system we use GPS technology to record fine-grained position data in order to track long term animal migrations [14]. The ZebraNet hardware is composed of a 16-bit TI microcontroller, 4 Mbits of off-chip flash memory, a 900 MHz radio, and a low-power GPS chip. In this paper, we discuss our techniques for devising efficient power supplies for sensor networks, methods of managing the energy consumption of the nodes, and methods of managing the peripheral devices including the radio, flash, and sensors. We conclude by evaluating the design of the ZebraNet nodes and discussing how it can be improved. Our lessons learned in developing this hardware can be useful both in designing future sensor nodes and in using them in real systems.

Implementing software on resource-constrained mobile sensors: experiences with Impala and ZebraNet

ZebraNet is a mobile, wireless sensor network in which nodes move throughout an environment working to gather and process information about their surroundings[10]. As in many sensor or wireless systems, nodes have critical resource constraints such as processing speed, memory size, and energy supply; they also face special hardware issues such as sensing device sample time, data storage/access restrictions, and wireless transceiver capabilities. This paper discusses and evaluates ZebraNets system design decisions in the face of a range of real-world constraints.Impala---ZebraNets middleware layer---serves as a light-weight operating system, but also has been designed to encourage application modularity, simplicity, adaptivity, and repairability. Impala is now implemented on ZebraNet hardware nodes, which include a 16-bit microcontroller, a low-power GPS unit, a 900MHz radio, and 4Mbits of non-volatile FLASH memory. This paper discusses Impalas operation scheduling and event handling model, and explains how system constraints and goals led to the interface designs we chose between the application, middleware, and firmware layers. We also describe Impalas network interface which unifies media access control and transport control into an efficient network protocol. With the minimum overhead in communication, buffering, and processing, it supports a range of message models, all inspired by and tailored to ZebraNets application needs. By discussing design tradeoffs in the context of a real hardware system and a real sensor network application, this papers design choices and performance measurements offer some concrete experiences with software systems issues for the mobile sensor design space. More generally, we feel that these experiences can guide design choices in a range of related systems.

Location-based trust for mobile user-generated content: applications, challenges and implementations

The recent explosion in shared media content and sensed data produced by mobile end-users is challenging well-established principles and assumptions in data trust models. A fundamental issue we address in this paper is how to establish some trust level in the authenticity of content created by untrusted mobile users. We advocate a secure localization and certification service that allows content producers to tag their content with with a spatial times-tamp indicating its physical location. At the same time, however, our approach preserves the privacy of producers by not exposing their identity to the potential content consumers. We provide a list of existing and possible applications that would profit from such a secure localization service and sketch possible implementations of the service, highlighting advantages and drawbacks.

LOCALE: Collaborative Localization Estimation for Sparse Mobile Sensor Networks

As the field of sensor networks matures, research in this area is focusing not only on fixed networks, but also on mobile sensor networks. For many reasons, both technical and logistical, such networks will often be very sparse for all or part of their operation, sometimes functioning more as disruption-tolerant networks (DTNs). While much work has been done on localization methods for densely populated fixed networks, most of these methods are inefficient or ineffective for sparse mobile networks, where connections can be infrequent. While some mobile networks rely on fixed location beacons or per-node, onboard GPS, these methods are not always possible due to cost, power and other constraints. In this paper we present the Low-density Collaborative Ad-Hoc Localization Estimation (LOCALE) system for sparse sensor networks. In LOCALE, each node estimates its own position, and collaboratively refines that location estimate by updating its prediction based on neighbors it encounters. Nodes also estimate (as a probability density function) the likelihood their prediction is accurate. We evaluate LOCALES collaborative localization both through real implementations running on sensor nodes, as well as through simulations of larger systems. We consider scenarios of varying density (down to 0.02 neighbors per communication attempt), as well as scenarios that demonstrate LOCALES resilience in the face of extremely-inaccurate individual nodes. Overall, our algorithms yield up to a median of 21X better accuracy for location estimation compared to existing approaches. In addition, by allowing nodes to refine location estimates collaboratively, LOCALE also reduces the need for fixed location beacons (i.e. GPS- enabled beacon towers) by as much as 64X.

CA-TSL: Energy Adaptation for Targeted System Lifetime in Sparse Mobile Ad Hoc Networks

With the proliferation of mobile devices, an increasing number of sensing applications are using mobile sensor networks. These mobile networks are severely energy-constrained, and energy usage is one of the most common causes of failure in their deployments. In these networks, nodes that exhaust their energy before the targeted system lifetime degrade system performance; nodes that run past the system lifetime cannot fully utilize their stored energy. Although much work has focused on policies to reduce and regulate energy usage in fixed and dense networks, intermittently connected networks have been largely overlooked. Due to variations in hardware, software, node mobility, and environment, it is especially difficult for intermittently connected mobile networks to improve operations collectively in a dynamic environment. Here, we present and evaluate Collaborative Adaptive Targeted System Lifetime (CA-TSL), an adaptive policy that enforces a system-wide targeted lifetime in an intermittently connected system by adapting node energy usage to an estimated desired energy profile. For evaluation, we present both real-system and large-scale simulated results. Our approach improves sink data reception by an average of 50 percent, and an additional 30 percent when a density estimation technique is also employed. In addition, it reduces system lifetime variations by up to 5.5 ×.

SARANA: language, compiler and run-time system support for spatially aware and resource-aware mobile computing

Increasingly, spatial awareness plays a central role in many distributed and mobile computing applications. Spatially aware applications rely on information about the geographical position of compute devices and their supported services in order to support novel functionality. While many spatial application drivers already exist in mobile and distributed computing, very little systems research has explored how best to program these applications, to express their spatial and temporal constraints, and to allow efficient implementations on highly dynamic real-world platforms. This paper proposes the SARANA system architecture, which includes language and run-time system support for spatially aware and resource-aware applications. SARANA allows users to express spatial regions of interest, as well as trade-offs between quality of result (QoR), latency and cost. The goal is to produce applications that use resources efficiently and that can be run on diverse resource-constrained platforms ranging from laptops to personal digital assistants and to smart phones. SARANAs run-time system manages QoR and cost trade-offs dynamically by tracking resource availability and locations, brokering usage/pricing agreements and migrating programs to nodes accordingly. A resource cost model permeates the SARANA system layers, permitting users to express their resource needs and QoR expectations in units that make sense to them. Although we are still early in the system development, initial versions have been demonstrated on a nine-node system prototype.

Energy adaptation techniques to optimize data delivery in store-and-forward sensor networks

Wireless sensor networks are severely-energy constrained devices. Energy-related issues are one of the common failure modes in sensor deployments. One challenge in systemwide energy management is that individual nodes in a sensor network often have widely varying energy profiles due to the amount of data transmitted, hardware construction, and other environmental effects. These differences result in unpredictable node and system lifetimes. As a result, sensor network bit-rate and reliability may degrade prematurely. Our research explores and evaluates an easily implemented dynamic scheduling policy supported by a battery gauge aimed to solve this problem.The dynamic scheduling policy presented here operates in a slotted manner. The decision for each node to communicate is based on the available energy of that node. Our policy guarantees a minimum communication bandwidth, while allowing nodes with more energy to increase their available bandwidth by a factor related to the amount of extra energy they have. We present real-system results measured on test nodes in several different network scenarios. The results show our scheduling, when compared to a fixed schedule, guarantees a longer usable system lifetime by preventing premature degradation of connections. In addition to improving connectivity, it reduces data delay by as much as 50% for intermittently connected nodes, with no added communication overhead.