Novel applications and contexts for the cognitive packet network

Autonomic communication, which is the development of self-configuring, self-adapting, self-optimising and self-healing communication systems, has gained much attention in the network research community. This can be explained by the increasing demand for more sophisticated networking technologies with physical realities that possess computation capabilities and can operate successfully with minimum human intervention. Such systems are driving innovative applications and services that improve the quality of life of citizens both socially and economically. Furthermore, autonomic communication, because of its decentralised approach to communication, is also being explored by the research community as an alternative to centralised control infrastructures for efficient management of large networks. This thesis studies one of the successful contributions in the autonomic communication research, the Cognitive Packet Network (CPN). CPN is a highly scalable adaptive routing protocol that allows for decentralised control in communication. Consequently, CPN has achieved significant successes, and because of the direction of research, we expect it to continue to find relevance. To investigate this hypothesis, we research new applications and contexts for CPN. This thesis first studies Information-Centric Networking (ICN), a future Internet architecture proposal. ICN adopts a data-centric approach such that contents are directly addressable at the network level and in-network caching is easily supported. An optimal caching strategy for an information-centric network is first analysed, and approximate solutions are developed and evaluated. Furthermore, a CPN inspired forwarding strategy for directing requests in such a way that exploits the in-network caching capability of ICN is proposed. The proposed strategy is evaluated via discrete event simulations and shown to be more effective in its search for local cache hits compared to the conventional methods. Finally, CPN is proposed to implement the routing system of an Emergency Cyber-Physical System for guiding evacuees in confined spaces in emergency situations. By exploiting CPN’s QoS capabilities, different paths are assigned to evacuees based on their ongoing health conditions using well-defined path metrics. The proposed system is evaluated via discrete-event simulations and shown to improve survival chances compared to a static system that treats evacuees in the same way.Open Acces

Routing Diverse Crowds in Emergency with Dynamic Grouping

Evacuee routing algorithms in emergency typically adopt one single criterion to compute desired paths and ignore the specific requirements of users caused by different physical strength, mobility and level of resistance to hazard. In this paper, we present a quality of service (QoS) driven multi-path routing algorithm to provide diverse paths for different categories of evacuees. This algorithm borrows the concept of Cognitive Packet Network (CPN), which is a flexible protocol that can rapidly solve optimal solution for any user-defined goal function. Spatial information regarding the location and spread of hazards is taken into consideration to avoid that evacuees be directed towards hazardous zones. Furthermore, since previous emergency navigation algorithms are normally insensitive to sudden changes in the hazard environment such as abrupt congestion or injury of civilians, evacuees are dynamically assigned to several groups to adapt their course of action with regard to their on-going physical condition and environments. Simulation results indicate that the proposed algorithm which is sensitive to the needs of evacuees produces better results than the use of a single metric. Simulations also show that the use of dynamic grouping to adjust the evacuees' category and routing algorithms with regard for their on-going health conditions and mobility, can achieve higher survival rates.Comment: Contains 6 pages, 5 pages. Accepted by PerNEM' 201

Emerging Trends in Crisis Management: Usability, Earth Observation and Disaster Management

Availability of Earth observation (EO) data and dissemination has been revolutionized with technological advancement in computation and use of mobile tools such as phones, tablets and laptops. This is further expanded with availability of affordable data/internet connections which no longer require Ethernet cables to get internet connection. The result is explosion of spatial data on various blogs and personal profiles such as Tweeter, Facebook, Instagram and other internet feeds. This has created explosion of information with a lot of integrity issues on data quality, lack of data source and lack of responsibility and authenticity. The problem is further compounded with advancement in search engines and data harvesting applications which collects similar archived information and makes them available to the user on the internet search engines. There should be a clear link detailing the nature of EO and the kind of relevant information that can be derived from them

Factors influencing experience in crowds – the participant perspective

Humans encounter crowd situations on a daily basis, resulting in both negative and positive experiences. Understanding how to optimise the participant experience of crowds is important. In the study presented in this paper, 5 focus groups were conducted (35 participants, age range: 21–71 years) and 55 crowd situations observed (e.g. transport hubs, sport events, retail situations). Influences on participant experience in crowds identified by the focus groups and observations included: physical design of crowd space and facilities (layout, queuing strategies), crowd movement (monitoring capacity, pedestrian flow), communication and information (signage, wayfinding), comfort and welfare (provision of facilities, environmental comfort), and public order. It was found that important aspects affecting participant experience are often not considered systematically in the planning of events or crowd situations. The findings point to human factors aspects of crowds being overlooked, with the experiences of participants often poor

Assessing the perceived realism of agent crowd behaviour within virtual urban environments using psychophysics

Inhabited virtual environments feature in a growing number of graphical applications. Simulated crowds are employed for different purposes; ranging from evaluation of evacuation procedures to driving interactable elements in video games. For many applications, it is important that the displayed crowd behaviour is perceptually plausible to the intended viewers. Crowd behaviour is inherently in flux, often depending upon many different variables such as location, situation and crowd composition. Researchers have, for a long time, attempted to understand and reason about crowd behaviour, going back as far as famous psychologists such as Gustave Le Bon and Sigmund Freud who applied theories of mob psychology with varying results. Since then, various other methods have been tried, from articial intelligence to simple heuristics, for crowd simulation. Even though the research into methods for simulating crowds has a long history, evaluating such simulations has received less attention and, as this thesis will show, increased complexity and high-delity recreation of recorded behaviours does not guarantee improvement in the plausibility for a human observer. Actual crowd data is not always perceived more real than simulation, making it dicult to identify gold standards, or a ground truth. This thesis presents new work on the use of psychophysics for perceptual evaluation of crowd simulation in order to develop methods and metrics for tailoring crowd behaviour for target applications. Psychophysics itself is branch of psychology dedicated to studying the relationship between a given stimuli and how it is perceived. A three-stage methodology of analysis, synthesis and perception is employed in which crowd data is gathered from the analysis of real instances of crowd behaviour and then used to synthesise behavioural features for simulation before being perceptually evaluated using psychophysics. Perceptual thresholds are calculated based on the psychometric function and key congurations are identied that appear the most perceptually plausible to human viewers. The method is shown to be useful for the initial application and it is expected that it will be applicable to a wide range of simulation problems in which human perception and acceptance is the ultimate measure of success

Managing egress of crowd during infrastructure disruption

National Research Foundation (NRF) Singapore under Corp Lab @ University schem

17 Human-Car confluence: “Socially-Inspired driving mechanisms”

With self-driving vehicles announced for the 2020s, today’s challenges in Intelligent Transportation Systems (ITS) lie in problems related to negotiation and decision making in (spontaneously formed) car collectives. Due to the close coupling and interconnectedness of the involved driver-vehicle entities, effects on the local level induced by cognitive capacities, behavioral patterns, and the social context of drivers, would directly cause changes on the macro scale. To illustrate, a driver’s fatigue or emotion can influence a local driver-vehicle feedback loop, which is directly translated into his or her driving style, and, in turn, can affect driving styles of all nearby drivers. These transitional, yet collective driver state and driving style changes raise global traffic phenomena like jams, collective aggressiveness, etc. To allow harmonic coexistence of autonomous and self-driven vehicles, we investigate in this chapter the effects of socially-inspired driving and discuss the potential and beneficial effects its application should have on collective traffic