Self-organizing virtual macro sensors

Abstract

The future large-scale deployment of pervasive sensor network infrastructures calls for mechanisms enabling the extraction of general-purpose data at limited energy costs. The approach presented in this article relies on a simple algorithm to let a sensor network self-organize a virtual partitioning in correspondence to spatial regions characterized by similar sensing patterns, and to let distributed aggregation of sensorial data take place on a per-region basis. The result of this process is that a sensor network can be modeled as a collection of virtual macro sensors, each associated to a well-characterized region of the physical environment. Within each region, each physical sensor has the local availability of aggregated data about its region and is able to act as an access point to such data. This feature promises to be very suitable for a number of emerging usage scenarios. Our approach is described and evaluated in both a simulation environment and a real test bed, and quantitatively compared with related works in the area. Current limitations and areas of future development are also discussed.

Spatial awareness in pervasive ecosystems

“…However, the definition of the regions in which to produce aggregated data is mostly network driven, and does not take into account specific characteristics of the environment being monitored or of the phenomena being sensed. To overcome this limitation, Bicocchi et al [2012b] propose the Virtual Macro Sensors approach to make a sensor network self-organise into regions characterised by similar sensing patterns, which helps to promote aggregation of data on a per-region basis, as if each region were monitored by a single macro sensor. Such an approach can be very e↵ective in facilitating data collection in dense large-scale sensor networks, and as well as in identifying the regions in which specific situations take place.…”

Engineering Pervasive Service Ecosystems

“…Gossip-based/epidemic protocols are inspired by the form of gossip seen in social networks, and by the way a virus spreads in a biological community [Jelasity et al 2005;Bicocchi et al 2012]. These approaches well address the requirement of contextawareness, and particularly situation-awareness, in that they allow one to flexibly combine and aggregate contextual information from multiple sources in a decentralized and robust way.…”

Behavior Predictability Despite Non-Determinism in the SAPERE Ecosystem

“…Another similar example is represented by gossip-based aggregation in sensor network [3]. In this kind of systems global aggregated values are computed in a decentralized way via the local exchange of messages among distributed nodes.…”

“…3) Each node updates its estimate as the average of its current estimate and the neighbor's one. 4) Nodes cyclically repeat step 2 and 3 It is rather easy to show that this algorithm allows each estimate to rapidly converge to the actual average value [3].…”

“…These eco-laws basically implement order and duplicate insensitive aggregation functions such as (min, max, average, etc.) [3]. These eco-laws can be used to properly propagate and maintain a gradient LSA so that is is properly spread across the network [16].…”