Adaptive Middleware for Resource-Constrained Mobile Ad Hoc and Wireless Sensor Networks

Mobile ad hoc networks: MANETs) and wireless sensor networks: WSNs) are two recently-developed technologies that uniquely function without fixed infrastructure support, and sense at scales, resolutions, and durations previously not possible. While both offer great potential in many applications, developing software for these types of networks is extremely difficult, preventing their wide-spread use. Three primary challenges are: 1) the high level of dynamics within the network in terms of changing wireless links and node hardware configurations,: 2) the wide variety of hardware present in these networks, and: 3) the extremely limited computational and energy resources available. Until now, the burden of handling these issues was put on the software application developer. This dissertation presents three novel programming models and middleware systems that address these challenges: Limone, Agilla, and Servilla. Limone reliably handles high levels of dynamics within MANETs. It does this through lightweight coordination primitives that make minimal assumptions about network connectivity. Agilla enables self-adaptive WSN applications via the integration of mobile agent and tuple space programming models, which is critical given the continuously changing network. It is the first system to successfully demonstrate the feasibility of using mobile agents and tuple spaces within WSNs. Servilla addresses the challenges that arise from WSN hardware heterogeneity using principles of Service-Oriented Computing: SOC). It is the first system to successfully implement the entire SOC model within WSNs and uniquely tailors it to the WSN domain by making it energy-aware and adaptive. The efficacies of the above three systems are demonstrated through implementation, micro-benchmarks, and the evaluation of several real-world applications including Universal Remote, Fire Detection and Tracking, Structural Health Monitoring, and Medical Patient Monitoring

A Unified Specification Framework for Spatiotemporal Communication

Traditionally, network communication entailed the delivery of messages to specific network addresses. As computers acquired multimedia capabilities, new applications such as video broadcasting dictated the need for real-time quality of service guarantees and delivery to multiple recipients. In light of this, a subtle transition took place as a subset of IP addresses evolved into a group-naming scheme and best-effort delivery became subjugated to temporal constraints. With recent developments in mobile and sensor networks new applications are being considered in which physical locations and even temporal coordinates play a role in identifying the set of desired recipients. Other applications involved in the delivery of spatiotemporal services are pointing to increasingly sophisticated ways in which the name, time, and space dimensions can be engaged in specifying the recipients of a given message. In this paper we explore the extent to which these and other techniques for implicit and explicit specification of the recipient list can be brought under a single unified frame-work. The proposed framework is shown to be expressive enough so as to offer precise specifications for ex-isting communication mechanisms. More importantly, its analysis suggests novel forms of communication relevant to the emerging areas of spatiotemporal service provision in sensor and mobile networks

A Lightweight Coordination Model and Middleware for Mobile Computing **Please see WUCSE-03-12**

LimeLite is a new coordination model and middleware designed to support rapid development of applications entailing logical mobility of agents and physical mobility of hosts. Designed to function in open environments, LimeLite performs automatic agent discovery but filters the results to define for each agent an individualized acquaintance list in accordance with run-time policies specified at the application level. This asymmetry among participants in the coordination process is dictated by the need to accommodate settings involving large numbers of agents and hosts that come and go freely. It represents an important departure from coordination research in general. The coordination context is limited to the specific needs of the individual agent and its coordination activities are restricted to tuple spaces owned by peers present in the acquaintance list. Linda-like primitives typically used in coordination middleware are tailored in LimeLite to address the challenges of mobile environments. Among other things, this entails the elimination of remote blocking and data pushing operations since the affected agents may no longer be within communication range. It also entails the addition of reactions that are triggered by the presence of information of interest on agents listed in the acquaintance list and not by events that could have occurred prior to discovery. Finally, to ensure both performance and ease of deployment on small devices the granularity of atomic operations and the reliance on transport layer guarantees have been minimized. This paper introduces LimeLite, explains its key features, illustrates its usage in application development, and explores its effectiveness as a software engineering tool

A Lightweight Coordination Model and Middleware for Mobile Computing

Limone is a new coordination model and middleware that enables rapid application development for wireless ad hoc networks entailing logical mobility of agents and physical mobility of hosts. Designed to function in open environments, Limone performs automatic agent discovery but filters the results to define for each agent an individualized acquaintance list in accordance with run-time policies that are customizable by the application. This asymmetry among participants represents a new direction in coordination research and is dictated by the need to accommodate settings involving large numbers of agents and hosts that come and go freely. The coordination context is limited to the specific needs of the individual agent and its coordination activities are restricted to tuple spaces owned by peers present in the acquaintance list. Designed for wireless ad hoc networks, Limone tailors Linda-like primitives to address the challenges of mobile environments. This entails the elimination of remote blocking operations and the addition of timeouts to all distributed operations since disconnection with the affected agents may occur at any time. It also entails the addition of reactions that are triggered by the presence of information of interest on agents listed in the acquaintance list. Finally, to ensure performance and ease of deployment on small devices the granularity of atomic operations and the assumptions about the environment have been minimized. This paper introduces Limone, explains its key features, illustrates its usage, and explores its effectiveness as a software engineering tool

Mobile Agent Middleware for Sensor Networks: An Application Case Study

Agilla is a mobile agent middleware that facilitates the rapid deployment of adaptive applications in wireless sensor networks (WSNs). Agilla allows users to create and inject special programs called mobile agents that coordinate through local tuple spaces, and migrate across the WSN performing application-specific tasks. This fluidity of code and state has the potential to transform a WSN into a shared, general-purpose computing platform capable of running several autonomous applications at a time, allowing us to harness its full potential. We have implemented and evaluated a fire tracking application to determine how well Agilla achieves its goals. Fire is modeled by agents that gradually spread throughout the network, engulfing nodes by inserting fire tuples into their local tuple spaces. Fire tracker agents are then used to form a perimeter around the fire. Using Agilla, we were able to rapidly create and deploy 47 byte fire agents, and 100 byte tracker agents on a WSN consisting of 26 MICA2 motes. Our experiments show that the tracker agents can form an 8-node perimeter around a burning node within 6.5 seconds and that it can adapt to a fire spreading at a rate of 7 seconds per hop. We also present the lessons learned about the adequacy of Agilla’s primitives, and regarding the efficiency, reliability, and adaptivity of mobile agents in a WSN

Agilla: A Mobile Agent Middleware for Sensor Networks

Agilla is a mobile agent middleware for sensor networks. Mobile agents are special processes that can migrate across sensors. They increase network flexibility by enabling active in-network reprogramming. Neighbor lists and tuple spaces are used for agent coordination. Agilla was originally implemented on Mica2 motes, but has been ported to other platforms. Its Mica2 implementation consumes 41.6KB of code and 3.59KB of data memory. Agents can move five hops in less than 1.1s with over 92% success. Agilla was used to develop multiple applications related to fire detection and tracking, cargo container monitoring, and robot navigation

Adaptive Service Provisioning for Wireless Sensor Networks

Service provisioning has gained significant attention as a promising programming model for heterogeneous wireless sensor networks. Its key idea is to exploit the decoupling of service providers and consumers to enable platform-independent applications that are dynamically bound to platform-specific services. We explore novel adaptive service binding strategies that are able to cope with network dynamics and to promote energy conservation. To achieve this goal, we developed policies and algorithms that automatically switch providers in response to network topology changes and adapt application behavior when opportunities for energy savings surface. The latter is accomplished by providing limited information about the energy consumption associated with using various services, by systematically exploiting opportunities for sharing service invocations, and by exploiting the broadcast nature of wireless communication in WSNs. The policies and algorithms have been implemented and evaluated on two disparate WSN platforms, the TelosB and Imote2. Empirical results show that adaptive service provisioning can significantly increase service availability and enable energy-aware service binding decisions that result in increased energy efficiency, while imposing minimal additional burden on the application, service, and device developers. Applications involving medical patient monitoring and structural health monitoring are used in the evaluation process

Rapid Development and Flexible Deployment of Adaptive Wireless Sensor Network Applications

Wireless sensor networks (WSNs) are difficult to pro-gram and usually run statically-installed software limiting its flexibility. To address this, we developed Agilla, a new middleware that increases network flexibility while simplifying application development. An Agilla network is deployed with no pre-installed application. Instead, users inject mobile agents that spread across nodes performing application-specific tasks. Each agent is autonomous, allowing multiple applications to share a network. Programming is simplified by allowing programmers to create agents using a high-level language. Linda-like tuple spaces are used for inter-agent communication and context discovery. This preserves each agent’s autonomy while providing a rich infrastructure for building complex applications, and marks the first time mobile agents and tuple spaces are used in a unified framework for WSNs. Our efforts resulted in an implementation for MICA2 motes and the development of several applications. The implementation consumes a mere 41.6KB of code and 3.59KB of data memory. An agent can migrate 5 hops in less than 1.1 seconds with 92% reliability. In this paper, we present Agilla and provide a detailed evaluation of its implementation, an empirical study of its overhead, and a case study demonstrating its use

Flexible Service Provisioning for Heterogeneous Sensor Networks

This paper presents Servilla, a highly flexible service provisioning framework for heterogeneous wireless sensor networks. Its service-oriented programming model and middleware enable developers to construct platform-independent applications over a dynamic set of devices with diverse computational resources and sensors. A salient feature of Servilla is its support for dynamic discovery and binding to local and remote services, which enables flexible and energy-efficient in-network collaboration among heterogeneous devices. Furthermore, Servilla provides a modular middleware architecture that can be easily tailored for devices with a wide range of resources, allowing even resource-limited devices to provide services and leverage resource-rich devices for in-network processing. Microbenchmarks demonstrate the efficiency of Servilla\u27s middleware, and an application case study for structural health monitoring on a heterogeneous testbed consisting of TelosB and Imote2 nodes demonstrates the efficacy of its programming model.This paper is replaced by tech report WUCSE-2009-2

MLDS: A Flexible Location Directory Service for Tiered Sensor Networks

Many emergent distributed sensing applications need to keep track of mobile entities across multiple sensor networks connected via an IP network. To simplify the realization of such applications, we present MLDS, a Multi-resolution Location Directory Service for tiered sensor networks. MLDS provides a rich set of spatial query services ranging from simple queries about entity location, to complex nearest neighbor queries. Furthermore, MLDS supports multiple query granularities which allow an application to achieve the desired tradeoff between query accuracy and communication cost. We implemented MLDS on Agimone, a unified middleware for sensor and IP networks. We then deployed and evaluated the service on a tiered testbed consisting of tmote nodes and base stations. Our experimental results show that, when compared to a centralized approach, MLDS achieves significant savings in communication cost while still providing a high degree of accuracy, both within a single sensor network and across multiple sensor networks