Directional Navigation Improves Opportunistic Communication for Emergencies

Kokuti, Andras; Gelenbe, Erol

doi:10.3390/s140815387

Cited by 8 publications

(6 citation statements)

References 25 publications

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“…Winter et al [21] instead consider the use of local communications among nodes, essentially oppcomms, in order to disseminate information on the area and the hazard for emergency evacuation. The work in [22] builds upon the work presented in this paper by using a directional navigation algorithm in order to improve evacuation directions.…”

Section: Related Workmentioning

confidence: 97%

No way out: Emergency evacuation with no internet access

Görbil

2015

2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)

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In urban emergencies and disasters, Internet connectivity is commonly unavailable to a large number of civilians in the affected area since the cellular network infrastructure and WiFi systems are either congested, or they have partially or completely failed. In this paper, we discuss how short-range wireless communications among mobile devices, e.g., smartphones, can be leveraged to construct an ad hoc and disruption tolerant evacuation support system in these typical emergency scenarios. Opportunistic communications among mobile devices are employed to gather and disseminate information on the emergency, such as hazard locations, and personalized evacuation directions are provided to each civilian using this partial information. We evaluate the performance of an opportunistic communications based evacuation support system in both indoor and outdoor evacuations of urban areas using simulation experiments, and show the improvement that can be offered. We also discuss how such a system can be protected against either malicious or inadvertent dissemination of false information, quantifying the effect of false information and the protection offered by our proposed method.

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Section: Related Workmentioning

confidence: 97%

No way out: Emergency evacuation with no internet access

Görbil

2015

2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops)

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“…The use of fast autonomic RNN-based routing of evacues using CPN (Bi, Desmet, and Gelenbe [13]) and directional navigation were also developed (Gelenbe and Bi [73], Kokuti and Gelenbe [166], Gelenbe, Akinwande, and Bi [172]). There have been several applications of this approach to emergency management (Gelenbe and Wu [146,148]), and routing algorithms specifically for this area are discussed in (Desmet and Gelenbe [23], Gelenbe, Gorbil, and Wu [88], Gelenbe and Wu [147]).…”

Section: Autonomic Systems and Cognitive Packet Network (Cpns)mentioning

confidence: 99%

“…Low-cost disruption-tolerant techniques for robust communications in emergencies (Filippoupolitis, Gorbil, and Gelenbe [28], Gorbil, Filippoupolitis, and Gelenbe [152], Gorbil and Gelenbe [154]), such as opportunistic communication systems were evaluated in (Gorbil and Gelenbe [153], Lent et al [167]). The use of fast autonomic RNN-based routing of evacues using CPN (Bi, Desmet, and Gelenbe [13]) and directional navigation were also developed (Gelenbe and Bi [73], Kokuti and Gelenbe [166], Gelenbe, Akinwande, and Bi [172]). There have been several applications of this approach to emergency management (Gelenbe and Wu [146,148]), and routing algorithms specifically for this area are discussed in (Desmet and Gelenbe [23], Gelenbe, Gorbil, and Wu [88], Gelenbe and Wu [147]).…”

Section: Autonomic Systems and Cognitive Packet Network (Cpns)mentioning

confidence: 99%

G-Networks and Their Applications to Machine Learning, Energy Packet Networks and Routing: Introduction to the Special Issue

Caglayan¹

2017

Prob. Eng. Inf. Sci.

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This paper introduces a special issue of this journal (Probability in the Engineering and Informational Sciences) that is devoted to G(elenbe)-Networks and their Applications. The special issue is based on revised versions of some of the papers that were presented at a workshop held in early January 2017 at the Séminaire Saint-Paul in Nice (France). It includes contributions in several research directions that followed from the introduction of the G-Network in the late 1980s. The papers present original theoretical developments, as well as applications of G-Networks to Machine Learning, to the performance optimization of energy systems via the novel Energy Packet Networks formalism for systems that operate with renewable and intermittent energy sources, and to packet network routing and Cloud management over the Internet. We introduce these contributions from the perspective of an overview of recent work based on G-Networks.

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“…More recent work has been devoted to autonomic routing techniques based on ideas derived from CPN or from directional techniques so that the management of evacuees can be carried out without the intervention of any centralized decision making agent [18][19][20]74,185]…”

Section: Emergency Management Systemsmentioning

confidence: 99%

Erol Gelenbe: A Career in Multi-Disciplinary Probability Models

Caglayan¹

2016

Prob. Eng. Inf. Sci.

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We focus on Erol Gelenbe's scientific and technical contributions to probability models in the computer and information sciences, but limit our survey to the last fifteen years. We start with a brief overview of his work as a single author, as well as his work in collaboration with over 200 co-authors. We discuss some of his recent and innovative work regarding a new probability model that represents Intermittent Energy Sources for Computing and Communications, introducing Energy Packet Networks which are a probabilistic representation of the flow, storage and consumption of electrical energy at the microscopic level (in electronic chips), and at the macroscopic level (e.g. in buildings or data centers) and for its routing and dynamic usage by consuming units (such as computer elements, chips or machines). We next discuss his work on designing computer and communication systems that parsimoniously use energy in order to achieve a satisfactory level of quality of service (QoS). Trade-offs between system QoS and energy consumption are also considered. Then we turn to Prof. Gelenbe's pioneering work on Autonomic Communications and the design and implementation of CPN, the Cognitive Packet Network, and we also briefly review his spiking random neural network that was used in CPN. This is followed by a brief review of work that he conducted since 1999 on human evacuation from dangerous or catastrophic environments, and the design of technology driven Emergency Management Systems. His research since the late 2000s on Gene Regulatory Networks is then covered together with its application to the detecting possible disease from microarray data. Finally, we briefly discuss some novel analytical models that he developed in this period with publications appearing in journals of physics and applied mathematics.

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Directional Navigation Improves Opportunistic Communication for Emergencies

Cited by 8 publications

References 25 publications

No way out: Emergency evacuation with no internet access

No way out: Emergency evacuation with no internet access

G-Networks and Their Applications to Machine Learning, Energy Packet Networks and Routing: Introduction to the Special Issue

Erol Gelenbe: A Career in Multi-Disciplinary Probability Models

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