While transparent optical networks become more and more popular as the basis of the Next Generation Internet (NGI) infrastructure, such networks raise many security issues, which do not exist in traditional optoelectronic networks. The existing protection schemes which rely heavily on fault detection due to the use of network monitoring performed by the use of optoelectronic conversion at the switching nodes, is not sufficient to provide security assurance for all optical networks which lack the massive use of optoelectronic monitoring and require timely protection from malicious sabotage as well as inadvertent faults. In order to increase the security of future networks, them will need to use reactive mechanisms and self-organize through multipath routing (MPR) to protect themselves from potential failures caused by malicious new attacks and ordinary reliability problems. If we make the analogy to the human immunization system's primary defense mechanism, MPR will act as the primary defense mechanism reacting timely to network problems and evolving based on network information. In this paper we are proposing the use MPR as an instinct immediate network reaction to failures and attacks in transparent networks; after the nodes transmit the data and causes of failure are classified, better self organized decisions can be used based on changing routing output priorities to reach destination. INTRODUCTIONTransparent all-optical networks (AON) are becoming more and more attractive due to their ability to reduce power consumption and cost based on the less use of transponders in the network, they can also avoid the bottleneck of optoelectronic conversion and switching at each node. However, transparency raises many security vulnerabilities as well as reliability issues which do not exist in traditional optoelectronic networks [1]. In WDM systems, multiple optical signals co-propagate in fiber and optical components, possibly affecting each other directly or indirectly. Then, the quality of a signal is sometimes dependent on or degraded by other signals. Moreover, in a transparent network, it is desired that signals are not regenerated between source and destination unless it is absolutely necessary [2]. It has been discussed in [3] how signals can be maliciously designed to pass through transparent components, causing undesirable effects at remote components and degrading other signals passing through the components. While there are many reliability studies to defeat physical layer impairment problems in AONs, these measures require human intervention to adapt the network to failures that are most likely to happen. Apart from component failures and accidental fiber cuts, networks are vulnerable to attackers capable of disrupting a network from the physical level up to the transport level. Usually, attackers are more interested in failures that can be repeated and controlled, especially if those created failures are rare. In addition, attackers may use automated software to repeatedly cause a fault far more often than i...

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Open access education has significantly grown in strength as a new way of fostering innovation in schools. Such is the case of massive open online courses (MOOCs), which have the added benefit of encouraging the democratisation of learning. In this sense, the Bi-National Laboratory on Smart Sustainable Energy Management and Technology Training between Mexico and the United States of America was launched with the purpose of trying MOOC technology and measuring its impact on the academic, business, and social sectors. Under this scenario, this study aimed to show the relationship between using gamification and level of performance in a MOOC on energy topics. The methodology was quantitative, using the course analytical data for socio-demographic information and predictive models. A total of 6246 participants enrolled in the MOOC and 1060 finished it. The results showed that participants aged between 20 and 50 had the highest completion rates in the gamified challenge; the higher academic degree, the more inclined participants were to solve the gamified challenge; and no such distinction exists by gender. Implications for practice or policy:• xMOOC participants' educational level determines the successful completion of challengebased gamification. • Challenge-based gamification is a useful strategy for xMOOC students' evaluation.• It is important to focus on the challenges design, if the planned challenges are not up to the students' skills, the learning results could be detrimental. • Gamification in xMOOCs promotes participants' engagement regardless of age, gender, or educational level.

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