Self-Stabilising Target Counting in Wireless Sensor Networks Using Euler Integration

Pianini, Danilo; Dobson, Simon; Viroli, Mirko

doi:10.1109/saso.2017.10

Cited by 10 publications

(14 citation statements)

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“…That is, we take the sensors to be arranged in two rows of three sensors each, and each sensor is overlapping with its neighbours, and no other sensor. This type of topology is similar to some examples analysed by Pianini et al [5].…”

Section: (C) Random and Grid Topologiessupporting

confidence: 89%

“…By applying the algorithm of Baryshnikov and Ghrist [4] to the same topology, the estimated target count is zero, which does not correspond to any feasible distribution. Experimental results in a study by Pianini et al [5] have also confirmed the difficulty in obtaining reliable results with this algorithm.…”

Section: Introductionmentioning

confidence: 74%

“…For example, if we place a target in zone {a, b, c}, we can only place a target in zone {c} afterwards. 5 On the other hand, if we initially choose {a, c}, then the next target can be placed in zones {b}, {c} or {b, c}. Hence, different choices of placement of a target, thus different probabilities, are possible at each step.…”

Section: Definition 31 (Weighted Topology Model)mentioning

confidence: 99%

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Target counting with Presburger constraints and its application in sensor networks

Linker

Sevegnani

2019

Proc. R. Soc. A.

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One of the applications popularized by the emergence of wireless sensor networks is target counting: the computational task of determining the total number of targets located in an area by aggregating the individual counts of each sensor. The complexity of this task lies in the fact that sensing ranges may overlap, and therefore, targets may be overcounted as, in this setting, they are assumed to be indistinguishable from each other. In the literature, this problem has been proven to be unsolvable, hence the existence of several estimation algorithms. However, the main limitation currently affecting these algorithms is that no assurance regarding the precision of a solution can be given. We present a novel algorithm for target counting based on exhaustive enumeration of target distributions using linear Presburger constraints. We improve on current approaches since the estimated counts obtained by our algorithm are by construction guaranteed to be consistent with the counts of each sensor. We further extend our algorithm to allow for weighted topologies and sensing errors for applicability in real-world deployments. We evaluate our approach through an extensive collection of synthetic and real-life configurations.

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Section: (C) Random and Grid Topologiessupporting

confidence: 89%

Section: Introductionmentioning

confidence: 74%

Section: Definition 31 (Weighted Topology Model)mentioning

confidence: 99%

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Target counting with Presburger constraints and its application in sensor networks

Linker

Sevegnani

2019

Proc. R. Soc. A.

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“…The key problems with multi-camera configurations are co-ordination and control of individual, heterogeneous cameras such that they perform collaboratively [56]. The set of cameras should in other words behave as a CAS in order to react to local and global contingencies, and to provide distributed global functions [57].…”

Section: Public Safety and Securitymentioning

confidence: 99%

On the Social Implications of Collective Adaptive Systems

Bucchiarone

D'Angelo

Pianini

et al. 2020

IEEE Technol. Soc. Mag.

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Many Collective Adaptive Systems (CASs) exist in nature: think of ant colonies, where large collectives of ants operate autonomously but interact with other ants and the environment to provide resilient global behaviours that sustain their colony. Following scientific studies that were aimed at understanding and predicting the evolution of these systems, and fueled by technological advances, research has started to investigate CAS engineering: the methods, tools, and techniques for building CASs. This naturally leads to a vision where collectives of humans and computational elements, situated both in the digital and physical worlds, collaborate to give rise to "intelligent" collective behaviour supporting novel kinds of applications and services. Humans can be involved in two ways: both as users and as components of the CAS, in the sense that human behaviours and limitations are often integral to the system description. This has significant social implications that need to be considered by CAS researchers: in this paper, we share a discussion that took place between some experts thinking about CAS engineering, focusing on the social implication of CASs and related open research challenges. We hope that this provides a useful context for future research projects, research grant proposals, and research directions.

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“…The techniques can also provide a substrate for exploring location-or topology-dependent processes that are specified as global functions and then decomposed onto the spatial structure (cf. [43]).…”

Section: ) Resilience Strategymentioning

confidence: 99%

Self-Organization and Resilience for Networked Systems: Design Principles and Open Research Issues

et al. 2019

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| Networked systems form the backbone of modern society, underpinning critical infrastructures such as electricity, water, transport and commerce, and other essential services (e.g., information, entertainment, and social networks).It is almost inconceivable to contemplate a future without even more dependence on them. Indeed, any unavailability of such critical systems is-even for short periods-a rather bleak prospect. However, due to their increasing size and complexity, they also require some means of autonomic formation and self-organization. This paper identifies the design principles and open research issues in the twin fields of self-organization and resilience for networked systems. In combination, they offer the prospect of combating threats and allowing essential services that run on networked systems to continue operating satisfactorily. This will be achieved, on the one hand, through the (self-)adaptation of networked systems and, on the other Manuscript hand, through structural and operational resilience techniques to ensure that they can detect, defend against, and ultimately withstand challenges.

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Self-Stabilising Target Counting in Wireless Sensor Networks Using Euler Integration

Cited by 10 publications

References 14 publications

Target counting with Presburger constraints and its application in sensor networks

Target counting with Presburger constraints and its application in sensor networks

On the Social Implications of Collective Adaptive Systems

Self-Organization and Resilience for Networked Systems: Design Principles and Open Research Issues

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