Amy L. Murphy

Bio: Amy L. Murphy is an academic researcher from Kessler Foundation. The author has contributed to research in topics: Wireless sensor network & Mobile computing. The author has an hindex of 35, co-authored 121 publications receiving 5394 citations. Previous affiliations of Amy L. Murphy include Center for Information Technology & Washington University in St. Louis.

Middleware to support sensor network applications

Abstract: Current trends in computing include increases in both distribution and wireless connectivity, leading to highly dynamic, complex environments on top of which applications must be built. The task of designing and ensuring the correctness of applications in these environments is similarly becoming more complex. The unified goal of much of the research in distributed wireless systems is to provide higher-level abstractions of complex low-level concepts to application programmers, easing the design and implementation of applications. A new and growing class of applications for wireless sensor networks require similar complexity encapsulation. However, sensor networks have some unique characteristics, including dynamic availability of data sources and application quality of service requirements, that are not common to other types of applications. These unique features, combined with the inherent distribution of sensors, and limited energy and bandwidth resources, dictate the need for network functionality and the individual sensors to be controlled to best serve the application requirements. In this article, we describe different types of sensor network applications and discuss existing techniques for managing these types of networks. We also overview a variety of related middleware and argue that no existing approach provides all the management tools required by sensor network applications. To meet this need, we have developed a new middleware called MiLAN. MiLAN allows applications to specify a policy for managing the network and sensors, but the actual implementation of this policy is effected within MiLAN. We describe MiLAN and show its effectiveness through the design of a sensor-based personal health monitor.

LIME: a middleware for physical and logical mobility

Abstract: LIME is a middleware supporting the development of applications that exhibit physical mobility of hosts, logical mobility of agents, or both. LIME adapts a coordination perspective inspired by work on the Linda model. The context for computation, represented in Linda by a globally accessible, persistent tuple space, is represented in LIME by transient sharing of the tuple spaces carried by each individual mobile unit. Linda tuple spaces are also extended with a notion of location and with the ability to react to a given state. The hypothesis underlying our work is that the resulting model provides a minimalist set of abstractions that enable rapid and dependable development of mobile applications. In this paper, we illustrate the model underlying LIME, present its current design and implementation, and discuss initial lessons learned in developing applications that involve physical mobility.

LIME: Linda meets mobility

Abstract: LIME is a system designed to assist in the rapid development of dependable mobile applications over both wired and ad hoc networks. Mobile agents reside on mobile hosts and all communication takes place via transiently shared tuple spaces distributed across the mobile hosts. The decoupled style of computing characterizing the Linda model is extended to the mobile environment. At the application level, both agents and hosts perceive movement as a sudden change of context. The set of tuples accessible by a particular agent residing on a given host is altered transparently in response to changes in the connectivity pattern among the mobile hosts. In this paper we present the key design concepts behind the LIME system.

Monitoring heritage buildings with wireless sensor networks: The Torre Aquila deployment

Abstract: Wireless sensor networks are untethered infrastructures that are easy to deploy and have limited visual impact—a key asset in monitoring heritage buildings of artistic interest. This paper describes one such system deployed in Torre Aquila, a medieval tower in Trento (Italy). Our contributions range from the hardware to the graphical front-end. Customized hardware deals efficiently with high-volume vibration data, and specially-designed sensors acquire the building's deformation. Dedicated software services provide: i) data collection, to efficiently reconcile the diverse data rates and reliability needs of heterogeneous sensors; ii) data dissemination, to spread configuration changes and enable remote tasking; iii) time synchronization, with low memory demands. Unlike most deployments, built directly on the operating system, our entire software layer sits atop our TeenyLIME middleware. Based on 4 months of operation, we show that our system is an effective tool for assessing the tower's stability, as it delivers data reliably (with loss ratios ≪0.01%) and has an estimated lifetime beyond one year.

LIME: A coordination model and middleware supporting mobility of hosts and agents

Abstract: LIME (Linda in a mobile environment) is a model and middleware supporting the development of applications that exhibit the physical mobility of hosts, logical mobility of agents, or both. LIME adopts a coordination perspective inspired by work on the Linda model. The context for computation, represented in Linda by a globally accessible persistent tuple space, is refined in LIME to transient sharing of the identically named tuple spaces carried by individual mobile units. Tuple spaces are also extended with a notion of location and programs are given the ability to react to specified states. The resulting model provides a minimalist set of abstractions that facilitates the rapid and dependable development of mobile applications. In this article we illustrate the model underlying LIME, provide a formal semantic characterization for the operations it makes available to the application developer, present its current design and implementation, and discuss lessons learned in developing applications that involve physical mobility.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

The vision of autonomic computing

Abstract: A 2001 IBM manifesto observed that a looming software complexity crisis -caused by applications and environments that number into the tens of millions of lines of code - threatened to halt progress in computing. The manifesto noted the almost impossible difficulty of managing current and planned computing systems, which require integrating several heterogeneous environments into corporate-wide computing systems that extend into the Internet. Autonomic computing, perhaps the most attractive approach to solving this problem, creates systems that can manage themselves when given high-level objectives from administrators. Systems manage themselves according to an administrator's goals. New components integrate as effortlessly as a new cell establishes itself in the human body. These ideas are not science fiction, but elements of the grand challenge to create self-managing computing systems.

Spray and wait: an efficient routing scheme for intermittently connected mobile networks

Abstract: Intermittently connected mobile networks are sparse wireless networks where most of the time there does not exist a complete path from the source to the destination. These networks fall into the general category of Delay Tolerant Networks. There are many real networks that follow this paradigm, for example, wildlife tracking sensor networks, military networks, inter-planetary networks, etc. In this context, conventional routing schemes would fail.To deal with such networks researchers have suggested to use flooding-based routing schemes. While flooding-based schemes have a high probability of delivery, they waste a lot of energy and suffer from severe contention, which can significantly degrade their performance. Furthermore, proposed efforts to significantly reduce the overhead of flooding-based schemes have often be plagued by large delays. With this in mind, we introduce a new routing scheme, called Spray and Wait, that "sprays" a number of copies into the network, and then "waits" till one of these nodes meets the destination.Using theory and simulations we show that Spray and Wait outperforms all existing schemes with respect to both average message delivery delay and number of transmissions per message delivered; its overall performance is close to the optimal scheme. Furthermore, it is highly scalable retaining good performance under a large range of scenarios, unlike other schemes. Finally, it is simple to implement and to optimize in order to achieve given performance goals in practice.

Probabilistic routing in intermittently connected networks

Abstract: We consider the problem of routing in intermittently connected networks. In such networks there is no guarantee that a fully connected path between source and destination exist at any time, rendering traditional routing protocols unable to deliver messages between hosts. We propose a probabilistic routing protocol for such networks.

Big Data: A Survey

Abstract: In this paper, we review the background and state-of-the-art of big data. We first introduce the general background of big data and review related technologies, such as could computing, Internet of Things, data centers, and Hadoop. We then focus on the four phases of the value chain of big data, i.e., data generation, data acquisition, data storage, and data analysis. For each phase, we introduce the general background, discuss the technical challenges, and review the latest advances. We finally examine the several representative applications of big data, including enterprise management, Internet of Things, online social networks, medial applications, collective intelligence, and smart grid. These discussions aim to provide a comprehensive overview and big-picture to readers of this exciting area. This survey is concluded with a discussion of open problems and future directions.