Methodologies and Practical Tools for Realistic Large Scale Simulations of Wireless Sensor Networks

Abstract: Wireless Sensor Networks (WSNs) have evolved into large and complex systems and are now one of the major technologies used in Cyber-Physical Systems (CPS) and the Internet of Things (IoT). Extensive research on WSNs has led to the development of diverse solutions for all layers of software architecture, including protocol stacks for communications. For example, more than one hundred distinct medium access control protocols and fifty routing and transport-level solutions have been proposed. This multitude of solutions is due to the limited computational power and restrictions on energy consumption that must be accounted for when designing typical WSN systems. The performance of a given high-level application task may depend strongly on the specific composition of the system's protocol stack, the run-time specifics of the underlying operating system, and the potential non-deterministic behavior of the devices used in the network. This makes it very difficult to identify the optimal software architecture forany particular situation. In many cases, software components must be developed specifically for each combination of task, environment and hardware. It is therefore challenging to develop, test, and validate even small WSN applications and this process can easily consume significant resources. This dissertation investigates various approaches for making the testing and validation of large scale WSN systems more efficient. The theoretical contribution presented is a method that enables the accurate reproduction of phenomena occurring inside real sensor node hardware and software at all layers of abstraction. This will expedite the design, development, and testing of WSN functionality. The main technical contribution is a prototype of a simulation framework named Symphony, which implements the proposed method. The framework's key feature is its ability to perform ultra-large scale holistic experiments on WSN functionality with millions of nodes using configurable levels of abstraction. The behavior observable using Symphony is very similar to the run-time behavior that developers would observe in reality. This is achieved via the virtualization of real-world operating systems and by using measurement-based hardware emulation and software component models. The impact of this dissertation is twofold. First, the proposed methodology and associated development framework will facilitate the education and training of specialists in the future IoT. Second, from a more long-term perspective, the thesis paves the way to solutions for several critical problems that have been highlighted in many strategic research agendas concerning the development of future industrial systems, including the streamlined validation of equipment and service interoperability across different vendors and application domains, and the rapid integrated design of future large scale CPS.