Amy L. Murphy

Middleware to support sensor network applications

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

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

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.

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

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.

Software engineering for mobility: a roadmap

The term distributed computing conjures the image of a fixed network structure whose nodes support the execution of processes that communicate with each other via messages traveling along links. Peer-to-peer communication is feasible but client-server relationships dominate. More recently, servers have been augmented with brokerage capabilities to facilitate discovery of available services. Stability is the ideal mode of operation; changes are relatively slow; even in the case of failure, nodes and links are expected eventually to come back up. By contrast, mobility represents a total meltdown of all the stability assumptions (explicit or implicit) associated with distributed computing. The network structure is no longer fixed, nodes may come and go, processes may move among nodes, and even programs (the code executed by processes) may evolve and change structure. The challenges and opportunities associated with this computational melee form the main subject of this paper. We seek to sort out this chaotic form of computing by focusing our attention on the formulation of a simple framework for viewing mobility, on precise definition of terms, and on research issues mobility poses for the software engineering community.

Reliable communication for highly mobile agents

The provision of a reliable communication infrastructure for mobile agents is still an open research issue. The challenge to reliability we address in this work does not come from the possibility of faults, but rather from the mere presence of mobility, which complicates the problem of ensuring the delivery of information even in a fault-free network. For instance, the asynchronous nature of message passing and agent migration may cause situations where messages forever chase a mobile agent that moves frequently from one host to another. Current solutions rely on conventional technologies that either do not provide a solution for the aforementioned problem, because they were not designed with mobility in mind, or enforce continuous connectivity with the message source, which in many cases defeats the very purpose of using mobile agents.In this paper, we propose an algorithm that guarantees delivery to highly mobile agents using a technique similar to a distributed snapshot. A number of enhancements to this basic idea are discussed, which limit the scope of message delivery by allowing dynamic creation of the connectivity graph. Notably, the very structure of our algorithm makes it amenable not only to guarantee message delivery to a specific mobile agent, but also to provide multicast communication to a group of agents, which constitutes another open problem in research on mobile agents. After presenting our algorithm and its properties, we discuss its implementability by analyzing the requirements on the underlying mobile agent platform, and argue about its applicability.

TinyLIME: bridging mobile and sensor networks through middleware

In the rapidly developing field of sensor networks, bridging the gap between the applications and the hardware presents a major challenge. Although middleware is one solution, it must be specialized to the qualities of sensor networks, especially energy consumption. The work presented here provides two contributions: a new operational setting for sensor networks and a middleware for easing software development in this setting. The operational setting we target removes the usual assumption of a central collection point for sensor data. Instead the sensors are sparsely distributed in an environment, not necessarily able to communicate among themselves, and a set of clients move through space accessing the data of sensors nearby, yielding a system which naturally provides context relevant information to client applications. We further assume the clients are wirelessly networked and share locally accessed data. This scenario is relevant, for example, when relief workers access the information in their zone and share this information with other workers. Our second contribution, the middleware itself is an extension of LlME, our earlier work on middleware for mobile ad hoc networks. The model makes sensor data available through a tuple space interface, providing the illusion of shared memory between applications and sensors. This paper presents both the model and the implementation of our middleware incorporated with the Crossbow Mote sensor platform.

Efficient content-based event dispatching in the presence of topological reconfiguration

Distributed content-based publish-subscribe middleware provides the decoupling, flexibility, expressiveness, and scalability required by highly dynamic distributed applications, e.g., mobile ones. Nevertheless, the available systems exploiting a distributed event dispatcher are unable to rearrange dynamically their behavior to adapt to changes in the topology of the dispatching infrastructure. In this work, we first define a strawman solution based on ideas proposed (but never precisely characterized) in existing work. We then analyze this solution and achieve a deeper understanding of how the event dispatching information is reconfigured. Based on this analysis, we modify the strawman approach to reduce its overhead. Simulations show that the reduction is significant (up to 50%), and yet the algorithm is resilient to concurrent reconfigurations.

Not all wireless sensor networks are created equal: A comparative study on tunnels

Wireless sensor networks (WSNs) are envisioned for a number of application scenarios. Nevertheless, the few in-the-field experiences typically focus on the features of a specific system, and rarely report about the characteristics of the target environment, especially with respect to the behavior and performance of low-power wireless communication. The TRITon project, funded by our local administration, aims to improve safety and reduce maintenance costs of road tunnels, using a WSN-based control infrastructure. The access to real tunnels within TRITon gives us the opportunity to experimentally assess the peculiarities of this environment, hitherto not investigated in the WSN field. We report about three deployments: (i) an operational road tunnel, enabling us to assess the impact of vehicular traffic; (ii) a nonoperational tunnel, providing insights into analogous scenarios (e.g., underground mines) without vehicles; (iii) a vineyard, serving as a baseline representative of the existing literature. Our setup, replicated in each deployment, uses mainstream WSN hardware, and popular MAC and routing protocols. We analyze and compare the deployments with respect to reliability, stability, and asymmetry of links, the accuracy of link quality estimators, and the impact of these aspects on MAC and routing layers. Our analysis shows that a number of criteria commonly used in the design of WSN protocols do not hold in tunnels. Therefore, our results are useful for designing networking solutions operating efficiently in similar environments.

TeenyLIME: transiently shared tuple space middleware for wireless sensor networks

Recent developments in wireless sensor networks (WSNs) are pushing scenarios where application intelligence is no longer relegated to the fringes of the system (i.e., on a data sink running on a powerful node) rather it is distributed within the WSN itself.To support this scenario, we propose TeenyLIME, a tuple space model and middleware supporting applications where sensing and acting devices themselves drive the network behavior. In other words, the application core is not confined to the powerful sinks, rather it is deployed on the devices embedded within the physical world. Tuple space operations are used both for data collection as well as to effect coordination among sensing and acting devices. This paper describes the TeenyLIME model and corresponding middleware implementation.