Dynamic Wireless Sensor Networks

The last decade witnessed a growing body of knowledge on the design and operation of Wireless Sensor Networks (WSNs) in a broad spectrum of applications. The premise of advancements in hardware design (MEMS, transceivers, sensors, etc.) potentiated a cost-effective base for many sensing domains. The protocols and paradigms devised for WSNs grew, both in scope and depth, to span many scenarios, advancing on energy efficiency and resilience as two main cores. However, recent attempts to scale WSN deployments to larger regions, and augment their functionality after deployment, elicited significant voids. We are faced with a technology that is advancing towards saturation in delta-improvements, many caps on performance, and a demand that is increasingly underachieved. In a technology where case-specific approaches have always been employed, much rigidity and stalled designs dominate the current state of the art. In this title, we leap into a novel paradigm of scalability and cost-effectiveness, on the basis of resource reuse. In a world with much abundance of wirelessly accessible devices, WSN deployments should capitalize on the resources already available in the region of deployment, and only augment it with the components required to meet new application requirements. However, if the required resources already exist in that region, WSN deployment converges to an assignment and scheduling scheme to accommodate for the new application given the existing resources. Such resources are polled from many fields, including multiple WSNs already in the field, static networks (WiFi, WiMAX, cellular, etc) in addition to municipal, industrial and mobile resources. The architecture, framework and pricing policy, as well as approaches for backward compatibility with existing deployments, are presented in this book. We elaborate on the formalization of the problem, and contrast with existing work on coverage. This paradigm adopts optimal assignments in WSNs and exploits dynamic re-programming for boosting post-deployment and backward compatible protocols.