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Quantitative Modeling of Trust
and Trust Management Protocols
in Next-Generation Social Networks-Based Wireless Mobile Ad Hoc Networks
--Yogesh Malhotra
Trust and trust management represent the very foundations of Computer and Network Security Protocols enabling all cyber activities. The recent spate of national and global high-impact cyber security compromises threats, vulnerabilities and exposures leads to fundamental questioning of trust as the key enabler of all cyber phenomena in the unfolding era of exponentially increasing distrust. It is, therefore, necessary to understand the current state of trust and trust management modeling and implementation in the most high security environments such as in defense and space. Such understanding can serve as a foundation for modeling, design and implementation of next-generation mobile wireless networks for other high security environments such as in banking and finance. This study attempts to understand how trust and trust management are being modeled for the next-generation wireless communication systems (NIST) such as autonomous self-discovering, self-organizing and self-adaptive mobile ad hoc networks. Within the context of Network-Centric Operations (NCO), the paper examines (i) the capabilities of next-generation wireless mobile ad hoc networks; (ii) how trust and trust management are modeled in such mobile ad hoc networks; and (iii) how trust and trust management are implemented in trust-based task assignment in tactical networks. US Army Research Laboratory (ARL) Computational and Information Sciences Directorate’s Network Science research program on wireless mobile ad hoc networks is the focus of the case study.
© 2017 IUP. All Rights Reserved.
An Investigation of List Heuristic Scheduling Algorithms for Multiprocessor System
--Sunita Kushwaha and Sanjay Kumar
The problem of obtaining an optimal scheduling of dependent tasks in homogeneous multiprocessor system is well known as an NP-hard problem. Heuristic is the best way to solve this problem. In a homogeneous multiprocessor system, task execution time is independent of the machine to which it is assigned. Recent research in scheduling has shown that list scheduling algorithms usually obtain more efficient and less complex schedules than other known algorithms. In this paper, some basic list scheduling algorithms, namely, LPT, SPT, ECT and EST are compared on the basis of performance parameter Makespan in two different environments. In the first environment, all the processes arrive at ‘zero’ time instantly, while in the second environment, all the processes arrive randomly. Simulation results show that the makespan of LPT is better than other algorithms in both environments.
© 2017 IUP. All Rights Reserved.
Artificial Intelligence: Boon or Bane?
--Amit Tyagi
Artificial Intelligence (AI) is transforming the nature of almost everything that is connected to human life, e.g., employment, economy, communication, warfare, privacy, security, ethics, healthcare, etc. However, we are yet to see its evolution in the long term—whether it is leading humanity towards making this planet a better place to live in or a place which is full of disaster. Every technology has its advantages and disadvantages, but advantages always outweigh disadvantages for the technology to survive in the market. Nonetheless, for AI, we are not yet sure whether in the long term positive effects will always keep outweighing the negative effects, and if that is not the case, then we are in serious trouble. If we look around us, on the one hand, we seem to embrace the change being brought by technology, be it smart home, smart healthcare, Industry 4.0 or autonomous cars. On the other hand, we often find ourselves protesting against the government in the context of unemployment, taxes, privacy, etc. As AI development is speeding up, more robots or autonomous systems are being born and replacing human labor. This is the current situation; however, in the long term, results seem to get more interesting. This paper focuses on the major domains where human life is significantly affected by AI in both positive and negative ways.
© 2017 IUP. All Rights Reserved.
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