Ted Herman

ExScal: elements of an extreme scale wireless sensor network

Project ExScal (for extreme scale) fielded a 1000+ node wireless sensor network and a 200+ node peer-to-peer ad hoc network of 802.11 devices in a 13km by 300m remote area in Florida, USA during December 2004. In comparison with previous deployments, the ExScal application is relatively complex and its networks are the largest ones of either type fielded to date. In this paper, we overview the key requirements of ExScal, the corresponding design of the hardware/software platform and application, and some results of our experiments.

Probabilistic self-stabilization

Abstract A probabilistic self-stabilizing algorithm for a ring of identical processes is presented; the number of processes in the ring is odd, the processes operate synchronously, and communication is unidirectional in the ring. The normal function of the algorithm is to circulate a single token in the ring. If the initial state of the ring is abnormal, i.e. the number of tokens differs from one, then execution of the algorithm results probabilistically in convergence to a normal state with one token.

A Distributed TDMA Slot Assignment Algorithm for Wireless Sensor Networks

Wireless sensor networks benefit from communication protocols that reduce power requirements by avoiding frame collision. Time Division Media Access methods schedule transmission in slots to avoid collision, however these methods often lack scalability when implemented in ad hoc networks subject to node failures and dynamic topology. This paper reports a distributed algorithm for TDMA slot assignment that is self-stabilizing to transient faults and dynamic topology change. The expected local convergence time is O(1) for any size network satisfying a constant bound on the size of a node neighborhood.

Shared-memory mutual exclusion: major research trends since 1986

Abstract.In 1986, Michel Raynal published a comprehensive survey of algorithms for mutual exclusion [72]. In this paper, we survey major research trends since 1986 in work on shared-memory mutual exclusion.

Fault-containing self-stabilizing algorithms

Self-stabilization provides a non-masking approach to fault tolerance. Given this fact, one would hope that in a self-stabilizing system, the amount of disruption caused by a fault is proportional to the severity of the fault. However, this is not true for many self-stabilizing systems. Our paper addresses this weakness of distributed self-stabilizing systems by introducing the notion of fault containment. Informally, a fault-containing self-stabilizing algorithm is one that contains the effects of limited transient faults while retaining the property of self-st abilization. The paper begins with a formal framework for specifying and evaluating fault-containing self-stabilizing protocols. Then, it is shown that self-stabilization and fault containment are goals that can conflict. For example, it is shown that imposing a O(1) bound on the worst case recovery time from a l-faulty state necessitates added overhead for stabilization: for some tasks, the O(1) recovery time implies sfiabilization time cannot be within O(1) rounds from the optimum value. The paper then presents a transformer T that maps any non-reactive self-stabilizing algorithm P into an equivalent fault-containing self-stabilizing algorithm Pf that can repair any l-faulty state in O(1) time with O(1) space overhead. This transformation is baaed on a novel stabilizing timer paradigm that significantly simplifies the ti=k of fault containment. The paper concludes by generalizing the transformer ‘T into a parameterized transformer 7(k) such that for varying k we obtain varying performance measures for Pf.

Self-Stabilizing Systems

This book constitutes the refereed proceedings of the 7th International Symposium on Self-Stabilizing Systems, SSS 2005, held in Barcelona, Spain, in October 2005. The 15 revised full papers presented were carefully reviewed and selected from 33 submissions. The papers address classical topics of self-stabilization, prevailing extensions to the field, such as snap-stabilization, code stabilization, self-stabilization with either dynamic, faulty or Byzantine components, or deal with applications of self-stabilization, either related to operating systems, security, or mobile and ad hoc networks.

Adaptive programming

An adaptive program is one that changes its behavior base on the current state of its environment. This notion of adaptivity is formalized, and a logic for reasoning about adaptive programs is presented. The logic includes several composition operators that can be used to define an adaptive program in terms of given constituent programs; programs resulting from these compositions retain the adaptive properties of their constituent programs. The authors begin by discussing adaptive sequential programs, then extend the discussion to adaptive distributed programs. The relationship between adaptivity and self-stabilization is discussed. A case study for constructing an adaptive distributed program where a token is circulated in a ring of processes is presented. >

Using Sensor Networks to Study the Effect of Peripatetic Healthcare Workers on the Spread of Hospital-Associated Infections

BACKGROUND Super-spreading events, in which an individual with measurably high connectivity is responsible for infecting a large number of people, have been observed. Our goal is to determine the impact of hand hygiene noncompliance among peripatetic (eg, highly mobile or highly connected) healthcare workers compared with less-connected workers. METHODS We used a mote-based sensor network to record contacts among healthcare workers and patients in a 20-bed intensive care unit. The data collected from this network form the basis for an agent-based simulation to model the spread of nosocomial pathogens with various transmission probabilities. We identified the most- and least-connected healthcare workers. We then compared the effects of hand hygiene noncompliance as a function of connectedness. RESULTS The data confirm the presence of peripatetic healthcare workers. Also, agent-based simulations using our real contact network data confirm that the average number of infected patients was significantly higher when the most connected healthcare worker did not practice hand hygiene and significantly lower when the least connected healthcare workers were noncompliant. CONCLUSIONS Heterogeneity in healthcare worker contact patterns dramatically affects disease diffusion. Our findings should inform future infection control interventions and encourage the application of social network analysis to study disease transmission in healthcare settings.

SuperStabilizing protocols for dynamic distributed systems

Two aspects of distributed-protocol reliability are the ability to recover from transient faults and the ability to function in a dynamic environment. Approaches for both of these aspects have been separately developed, but have revealed drawbacks when applied to environments with both transient faults and dynamic changes. This paper introduces definitions and methods for addressing both concerns in system design. A protocol is superstabilizing if it is (1) self-stabilizing, meaning that it is guaranteed to respond to an arbitrary transient fault by eventually satisfying and maintaining a legitimacy predicate, and it is (2) guaranteed to satisfy a passage predicate at all times when the system undergoes topology changes starting from a legitimate state. The passage predicate is typically a safety property that should hold while the protocol makes progress toward reestablishing legitimacy following a topology change. Specific contributions of the paper include: the definition of the class of superstabilizing protocols; metrics for evaluating superstabilizing protocols; superstabilizing protocols for coloring and spanning tree construction; a general method for converting self-stabilizing protocols into superstabilizing ones; and a generalized form of a self-stabilizing topology update protocol which may have useful applications for other research.

Models of Self-Stabilization and Sensor Networks

The advent of large-scale sensor networks highlights problems of fault tolerance and scale in distributed system, motivating designs that autonomously recover from transient faults and spontaneous reconfiguration. Self-stabilization is an attractive approach for such problems, however the standard model of research for self-stabilizing algorithms does not suit ad hoc networks of wirelessly communicating sensor nodes. The paper surveys some standard models of self-stabilization and relates these models to a sensor network. Challenges and opportunities are for integrating self-stabilization with sensor networks are illustrated with examples.