Opportunistic Communication in Extreme Wireless Sensor Networks: A step back towards the smart dust dream

Sensor networks can nowadays deliver 99.9% of their data with duty cycles below 1%. This remarkable performance is, however, dependent on some important underlying assumptions: low traffic rates, medium size densities and static nodes. In this thesis, we investigate the performance of these same resource-constrained devices, but under scenarios that present extreme conditions: high traffic rates, high densities and mobility: the so-called ExtremeWireless Sensor Networks (EWSNs). From a networking perspective, communicating in these extreme scenarios is very challenging. The combined effect of high network densities and dynamics makes the network’s characteristics fluctuate drastically both in space and time. Traditional mechanisms struggle to cope with these sudden changes, resulting in a continuous exchange of information that saturates the bandwidth and increases the energy consumption. Once this saturation threshold is reached, mechanisms take decisions based on wrong, outdated information and soon stop working. Even flexible mechanisms have difficulties adapting their settings to the fickly conditions of EWSNs and result in poor performance.
To efficiently communicate in EWSNs, mechanisms must therefore comply to a set of requirements i. e., design principles, which are explained next. First, they need to be resilient to local and remote failures and operate as independent as possible from the status of other nodes (state-less principle). Second, because in EWSNs bandwidth is a scarce resource, it should be mainly used for the transmission of the actual data. Mechanisms should not be artificially orchestrated and should exploit each other in a cross-layer fashion to reduce as much as possible their communication overhead (opportunistic principle). Third, mechanisms should support extreme network conditions from their inception. Adapting traditional mechanisms, which are designed for milder conditions, would otherwise result in complex and fragile mechanisms (anti-fragile principle). Fourth, in the case the resources saturate, mechanisms should operate in a conservative fashion, so that performance degrades gracefully without drastic disruptions (robustness principle).
Inspired by these four principles, this thesis detaches from traditional communication primitives – which are deterministic and based on rigid structures – and proposes a novel communication stack based on opportunistic anycast. According to this primitive, nodes communicate with the first available neighbor, independently of its location and identity. The more neighbors, themore efficient the communication.
At the foundation of this communication stack lays SOFA, a medium access control (MAC) protocol that exploits opportunistic anycast to handle extreme densities in an efficient manner. Its implementation details are presented in Chapter 2. On top of the SOFA layer, this thesis builds two essential network services: neighborhood cardinality (density) estimation and data collection. The former service is provided by Estreme, a mechanism presented in Chapter 3, which exploits the rendezvous time of SOFA to estimate the number of neighbors with almost zero overhead. The latter service is provided by Staffetta in Chapter 4, a mechanism that adapts the wake-up frequency of nodes to bias the opportunistic neighbor-selection of SOFA towards the desired direction e. g., towards the sink node collecting all data.
Finally, this thesis presents an extensive evaluation of a complete opportunistic stack on simulations, testbeds and a challenging real-world deployment in the formof the NEMO science museumin Amsterdam. Results showthat opportunistic behavior can lead to mechanisms that are both lightweight and robust and, thus, are able to scale to EWSNs.