Permission is granted for noncommercial reproduction of the work for educational or research purposes.

Advances in processor, memory and radio technology will enable small and cheap nodes capable of sensing, communication and computation. Networks of such nodes can coordinate to perform distributed sensing of environmental phenomena. In this paper, we explore the directed diffusion paradigm for such coordination. Directed diffusion is datacentric in that all communication is for named data. All nodes in a directed diffusion-based network are application-aware. This enables diffusion to achieve energy savings by selecting empirically good paths and by caching and processing data in-network (e.g., data aggregation). We explore and evaluate the use of directed diffusion for a simple remote-surveillance sensor network analytically and experimentally. Our evaluation indicates that directed diffusion can achieve significant energy savings and can outperform idealized traditional schemes (e.g., omniscient multicast) under the investigated scenarios.

Abstract- Wireless sensor network applications, similarly to other distributed systems, often require a scalable time synchronization service enabling data consistency and coordination. This paper introduces the robust Flooding Time Synchronization Protocol (FTSP), especially tailored for applications requiring stringent precision on resource limited wireless platforms. The proposed time synchronization protocol utilizes low communication bandwidth, scales well for medium sized multi-hop networks, and is robust against topology changes and node failures. The FTSP achieves its robustness by utilizing periodic radio broadcast of synchronization messages, and implicit dynamic topology update. The unique high precision performance is reached by utilizing MAC-layer time-stamping, comprehensive error compensation, including linear regression, which reduces time skew and keeps network traffic overhead low. The performance of the FTSP, implemented on Berkeley MICA2 platform, was evaluated in a multi-hop experiment. The average network-wide synchronization error was in the microsecond range, which is approximately a magnitude lower than that of the existing RBS and TPSN algorithms. The protocol was further validated as part of our counter-sniper system that was field tested in a US military facility. 1.

Structural monitoring---the collection and analysis of structural response to ambient or forced excitation--is an important application of networked embedded sensing with significant commercial potential. The first generation of sensor networks for structural monitoring are likely to be data acquisition systems that collect data at a single node for centralized processing. In this paper, we discuss the design and evaluation of a wireless sensor network system (called Wisden) for structural data acquisition. Wisden incorporates two novel mechanisms, reliable data transport using a hybrid of end-to-end and hop-by-hop recovery, and low-overhead data time-stamping that does not require global clock synchronization. We also study the applicability of wavelet-based compression techniques to overcome the bandwidth limitations imposed by lowpower wireless radios. We describe our implementation of these mechanisms on the Mica-2 motes and evaluate the performance of our implementation. We also report experiences from deploying Wisden on a large structure.

OF THE DISSERTATION University of California, Los Angeles, 2003 Professor Deborah L. Estrin, Chair active research in large-scale networks of small, wireless, low-power sensors and actuators. Time synchronization is a critical piece of infrastructure in any dis- tributed system, but wireless sensor networks make particularly extensive use physical world. However, while the clock accuracy and precision requirements are often stricter in sensor networks than in traditional distributed systems, energy and channel constraints limit the resources available to meet these goals.

We consider an environment where distributed data sources continuously stream updates to a centralized processor that monitors continuous queries over the distributed data. Significant communication overhead is incurred in the presence of rapid update streams, and we propose a new technique for reducing the overhead. Users register continuous queries with precision requirements at the central stream processor, which installs filters at remote data sources. The filters adapt to changing conditions to minimize stream rates while guaranteeing that all continuous queries still receive the updates necessary to provide answers of adequate precision at all times. Our approach enables applications to trade precision for communication overhead at a fine granularity by individually adjusting the precision constraints of continuous queries over streams in a multi-query workload.

We propose a formal definition for the timed asynchronous distributed system model. We present extensive measurements of actual message and process scheduling delays and hardware clock drifts. These measurements confirm that this model adequately describes current distributed systems such as a network of workstations. We also give an explanation of why practically needed services, such as consensus or leader election, which are not implementable in the time-free model, are implementable in the timed asynchronous system model.

The Network Time Protocol (NTP) is widely deployed in the Internet to synchronize computer clocks to each other and to international standards via telephone modem, radio and satellite. The protocols and algorithms have evolved over more than a decade to produce the present NTP Version 3 specification and implementations. Most of the estimated deployment of 100,000 NTP servers and clients enjoy synchronization to within a few tens of milliseconds in the Internet of today. This paper describes specific improvements developed for NTP Version 3 which have resulted in increased accuracy, stability and reliability in both local-area and wide-area networks. These include engineered refinements of several algorithms used to measure time differences between a local clock and a number of peer clocks in the network, as well as to select the best ensemble from among a set of peer clocks and combine their differences to produce a clock accuracy better than any in the ensemble. This paper also describes engineered refinements of the algorithms used to adjust the time and frequency of the local clock, which functions as a disciplined oscillator. The refinements provide automatic adjustment of message-exchange intervals in order to minimize network traffic between clients and busy servers while maintaining the best accuracy. Finally, this paper describes certain enhancements to the Unix operating system software in order to realize submillisecond accuracies with fast workstations and networks.

Launching a denial of service (DoS) attack is trivial, but detection and response is a painfully slow and often a manual process. Automatic classification of attacks as single- or multi-source can help focus a response, but current packet-header-based approaches are susceptible to spoofing. This paper introduces a framework for classifying DoS attacks based on header content, transient ramp-up behavior and novel techniques such as spectral analysis. Although headers are easily forged, we show that characteristics of attack ramp-up and attack spectrum are more difficult to spoof. To evaluate our framework we monitored access links of a regional ISP detecting 80 live attacks. Header analysis identified the number of attackers in 67 attacks, while the remaining 13 attacks were classified based on ramp-up and spectral analysis. We validate our results through monitoring at a second site, controlled experiments, and simulation. We use experiments and simulation to understand the underlying reasons for the characteristics observed. In addition to helping understand attack dynamics, classification mechanisms such as ours are important for the development of realistic models of DoS traffic, can be packaged as an automated tool to aid in rapid response to attacks, and can also be used to estimate the level of DoS activity on the Internet.

Wireless sensor networks (WSNs) consist of large populations of wirelessly connected nodes, capable of computation, communication, and sensing. Sensor nodes cooperate in order to merge individual sensor readings into a high-level sensing result, such as integrating a time series of position measurements into a velocity estimate. The physical time of sensor readings is a key element in this process called data fusion. Hence, time synchronization is a crucial component of WSNs. We argue that time synchronization schemes developed for traditional networks such as NTP [21] are ill-suited for WSNs and suggest more appropriate approaches.