OceanStore is a utility infrastructure designed to span the globe and provide continuous access to persistent information. Since this infrastructure is comprised of untrusted servers, data is protected through redundancy and cryptographic techniques. To improve performance, data is allowed to be cached anywhere, anytime. Additionally, monitoring of usage patterns allows adaptation to regional outages and denial of service attacks; monitoring also enhances performance through pro-active movement of data. A prototype implementation is currently under development. 1

We provide an in-depth study of applying wireless sensor networks (WSNs) to real-world habitat monitoring. A set of system design requirements were developed that cover the hardware design of the nodes, the sensor network software, protective enclosures, and system architecture to meet the requirements of biologists. In the summer of 2002, 43 nodes were deployed on a small island off the coast of Maine streaming useful live data onto the web. Although researchers anticipate some challenges arising in real-world deployments of WSNs, many problems can only be discovered through experience. We present a set of experiences from a four month long deployment on a remote island. We analyze the environmental and node health data to evaluate system performance. The close integration of WSNs with their environment provides environmental data at densities previously impossible. We show that the sensor data is also useful for predicting system operation and network failures. Based on over one million 2 Polastre et. al. data readings, we analyze the node and network design and develop network reliability profiles and failure models.

This paper proposes S-MAC, a medium-access control (MAC) protocol designed for wireless sensor networks. Wireless sensor networks use battery-operated computing and sensing devices. A network of these devices will collaborate for a common application such as environmental monitoring. We expect sensor networks to be deployed in an ad hoc fashion, with individual nodes remaining largely inactive for long periods of time, but then becoming suddenly active when something is detected. These characteristics of sensor networks and applications motivate a MAC that is different from traditional wireless MACs such as IEEE 802.11 in almost every way: energy conservation and self-configuration are primary goals, while per-node fairness and latency are less important. S-MAC uses three novel techniques to reduce energy consumption and support self-configuration. To reduce energy consumption in listening to an idle channel, nodes periodically sleep. Neighboring nodes form virtual clusters to auto-synchronize on sleep schedules. Inspired by PAMAS, S-MAC also sets the radio to sleep during transmissions of other nodes. Unlike PAMAS, it only uses in-channel signaling. Finally, S-MAC applies message passing to reduce contention latency for sensor-network applications that require store-andforward processing as data move through the network. We evaluate our implementation of S-MAC over a sample sensor node, the Mote, developed at University of California, Berkeley. The experiment results show that, on a source node, an 802.11-like MAC consumes 2--6 times more energy than S-MAC for traffic load with messages sent every 1-10s.

As sensor networks edge closer towards wide-spread deployment, security issues become a central concern. So far, the main research focus has been on making sensor networks feasible and useful, and less emphasis was placed on security. We design a suite of security...

The dynamic and lossy nature of wireless communication poses major challenges to reliable, self-organizing multihop networks. These non-ideal characteristics are more problematic with the primitive, low-power radio transceivers found in sensor networks, and raise new issues that routing protocols must address. Link connectivity statistics should be captured dynamically through an efficient yet adaptive link estimator and routing decisions should exploit such connectivity statistics to achieve reliability. Link status and routing information must be maintained in a neighborhood table with constant space regardless of cell density. We study and evaluate link estimator, neighborhood table management, and reliable routing protocol techniques. We focus on a many-to-one, periodic data collection workload. We narrow the design space through evaluations on large-scale, high-level simulations to 50-node, in-depth empirical experiments. The most effective solution uses a simple time averaged EWMA estimator, frequency based table management, and cost-based routing.

Distributed Sensor Networks (DSNs) are ad-hoc mobile networks that include sensor nodes with limited computation and communication capabilities. DSNs are dynamic in the sense that they allow addition and deletion of sensor nodes after deployment to grow the network or replace failing and unreliable nodes. DSNs may be deployed in hostile areas where communication is monitored and nodes are subject to capture and surreptitious use by an adversary. Hence DSNs require cryptographic protection of communications, sensorcapture detection, key revocation and sensor disabling. In this paper, we present a key-management scheme designed to satisfy both operational and security requirements of DSNs.

Accurate and scalable simulation has historically been a key enabling factor for systems research. We present TOSSIM, a simulator for TinyOS wireless sensor networks. By exploiting the sensor network domain and TinyOS’s design, TOSSIM can capture network behavior at a high fidelity while scaling to thousands of nodes. By using a probabilistic bit error model for the network, TOSSIM remains simple and efficient, but expressive enough to capture a wide range of network interactions. Using TOSSIM, we have discovered several bugs in TinyOS, ranging from network bitlevel MAC interactions to queue overflows in an ad-hoc routing protocol. Through these and other evaluations, we show that detailed, scalable sensor network simulation is possible.

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Over the past decade, mobile computing and wireless communication have become increasingly important drivers of many new computing applications. The eld of wireless sensor networks particularly focuses on applications involving autonomous use of compute, sensing, and wireless communication devices for both scienti c and commercial purposes. This paper examines the research decisions and design tradeos that arise when applying wireless peer-to-peer networking techniques in a mobile sensor network designed to support wildlife tracking for biology research.

Wireless sensor networks promise fine-grain monitoring in a wide variety of environments. Many of these environments (e.g., indoor environments or habitats) can be harsh for wireless communication. From a networking perspective, the most basic aspect of wireless communication is the packet delivery performance:the spatio-temporal characteristics of packet loss, and its environmental dependence. These factors will deeply impact the performance of data acquisition from these networks. In this paper, we report on a systematic medium-scale (up to sixty nodes) measurement of packet delivery in three different environments:an indoor office building, a habitat with moderate foliage, and an open parking lot. Our findings have interesting implications for the design and evaluation of routing and medium-access protocols for sensor networks. Categories and Subject Descriptors C.2.1 [Network Architecture and Design]:Wireless communication; C.4 [Performance of Systems]:Performance