Adaptive mechanisms for failure detection and management in complex network topologies

• Grant number: 12/25058-9
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: August 01, 2013
• End date: November 30, 2016
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Carlos Henrique Costa Ribeiro
• Grantee: Cinara Guellner Ghedini
• Host Institution: Pró-Reitoria de Pós-Graduação e Pesquisa. Instituto Tecnológico de Aeronáutica (ITA). São José dos Campos , SP, Brazil
• Associated research grant: 11/17610-0 - Monitoring and control of dynamic systems subject to faults, AP.TEM
• Associated scholarship(s): 14/13800-8 - Adaptive mechanisms for vulnerability detection and management in mobile multi-robot systems, BE.EP.PD

Abstract

Complex networks emerge naturally or as a design decision, in computational solutions. In both cases, the resulting topologies points to networks with high efficiency with respect to information dissemination and robustness, both locally and under node failures. These characteristics are credited to a small relative distance between the network elements and to a high clustering coefficient - the likelihood of neighbors connected to each other is high. Fault tolerance means that although elements fail or disconnect from the network, it can keep its main topological properties. However, studies have shown that this does not apply to cases where central elements fail continuously and concurrently. In these cases, the network may move to a completely different state, compromising its operation. Therefore, it is necessary to develop mechanisms to detect topology configurations considered critical, and promote adjustments that would reverse these states. This task is non-trivial because the topology is a result of the dynamics of the (mobile) elements and/or environmental conditions and infrastructure, which may also change over time. Moreover, the size of these networks coupled to operational constraints make methods based on global information prohibitive. Thus, this research aims to propose local mechanisms for detecting and mitigating critical topological states. (AU)

Scientific publications

(4)

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

GHEDINI, CINARA; RIBEIRO, CARLOS; SABATTINI, LORENZO. Toward fault-tolerant multi-robot networks. NETWORKS, v. 70, n. 4, SI, p. 388-400, DEC 2017. (12/25058-9, 13/13447-3, 14/13800-8)

GHEDINI, CINARA; RIBEIRO, CARLOS; SABATTINI, LORENZO. Toward fault-tolerant multi-robot networks. NETWORKS, v. 70, n. 4, p. 13-pg., 2017-12-01. (12/25058-9, 13/13447-3, 14/13800-8)

GHEDINI, CINARA G.; RIBEIRO, CARLOS H. C.. IMPROVING RESILIENCE OF COMPLEX NETWORKS FACING ATTACKS AND FAILURES THROUGH ADAPTIVE MECHANISMS. Advances in Complex Systems, v. 17, n. 2, MAR 2014. (12/25058-9)

GHEDINI, CINARA; RIBEIRO, CARLOS H. C.; SABATTINI, LORENZO. Toward efficient adaptive ad-hoc multi-robot network topologies. Ad Hoc Networks, v. 74, p. 57-70, MAY 15 2018. (13/13447-3, 12/25058-9)