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 approach to the development and usage of mobile agents

Mobile agents are an interesting approach to the development of distributed systems. By moving freely accross the network, they allow for the distribution of computation as well as gathering and filtering of information in an autonomous way. Over the last decade, the agent research community has decidedly achieved tremendous results. However, the community was not able to provide easy to use toolkits to make this paradigm available to a broader audience. By embracing simplicity during the creation of a formal model and a reference implementation to create and execute instances of that model, our aim is to enable a wide audience – even non-experts – to create, adapt and use mobile agents. The proposed model allows for the creation of agents by combining atomic, self-contained building blocks and we provide an approachable, easy to use graphical editor for the creation of model instances. In two evaluations, we could reinforce our believes that, with the achieved results, we could reach our aims

Exploring sensor networks using mobile agents

Wireless sensor networks are often difficult to program and unable to adapt to a changing environment. Mobile agent middleware promises to address both concerns by providing higher-level programming abstractions and the ability to inject new agents into a preexisting network. The unique characteristics of wireless sensor networks like resource scarcity and emphasis on spatial locality require new algorithms for controlling agent behavior. This paper presents a procedure for one specific behavior: network exploration. Network exploration is needed by many tasks ranging from simple data collection to network health monitoring. Our proposed procedure uses a genetic algorithm to determine the number of agents and their itineraries, followed by techniques for in-network adaptation to unpredictable situations like node failure. This paper presents a genetic algorithm and its adaptation strategies. The procedure is evaluated using a wireless sensor network consisting of 25 Mica2 motes running Agilla, a mobile agent middleware for wireless sensor networks