Applications of Repeated Games in Wireless Networks: A Survey

A repeated game is an effective tool to model interactions and conflicts for players aiming to achieve their objectives in a long-term basis. Contrary to static noncooperative games that model an interaction among players in only one period, in repeated games, interactions of players repeat for multiple periods; and thus the players become aware of other players' past behaviors and their future benefits, and will adapt their behavior accordingly. In wireless networks, conflicts among wireless nodes can lead to selfish behaviors, resulting in poor network performances and detrimental individual payoffs. In this paper, we survey the applications of repeated games in different wireless networks. The main goal is to demonstrate the use of repeated games to encourage wireless nodes to cooperate, thereby improving network performances and avoiding network disruption due to selfish behaviors. Furthermore, various problems in wireless networks and variations of repeated game models together with the corresponding solutions are discussed in this survey. Finally, we outline some open issues and future research directions.Comment: 32 pages, 15 figures, 5 tables, 168 reference

Agent-based Vs Agent-less Sandbox for Dynamic Behavioral Analysis

Malicious software is detected and classified by either static analysis or dynamic analysis. In static analysis, malware samples are reverse engineered and analyzed so that signatures of malware can be constructed. These techniques can be easily thwarted through polymorphic, metamorphic malware, obfuscation and packing techniques, whereas in dynamic analysis malware samples are executed in a controlled environment using the sandboxing technique, in order to model the behavior of malware. In this paper, we have analyzed Petya, Spyeye, VolatileCedar, PAFISH etc. through Agent-based and Agentless dynamic sandbox systems in order to investigate and benchmark their efficiency in advanced malware detection

Agent-based Vs Agent-less Sandbox for Dynamic Behavioral Analysis

2018 Global Information Infrastructure and Networking Symposium (GIIS)Malicious software is detected and classified by either static analysis or dynamic analysis. In static analysis, malware samples are reverse engineered and analyzed so that signatures of malware can be constructed. These techniques can be easily thwarted through polymorphic, metamorphic malware, obfuscation and packing techniques, whereas in dynamic analysis malware samples are executed in a controlled environment using the sandboxing technique, in order to model the behavior of malware. In this paper, we have analyzed Petya, Spyeye, VolatileCedar, PAFISH etc. through Agent-based and Agentless dynamic sandbox systems in order to investigate and benchmark their efficiency in advanced malware detection

Optimal decision making in cognitive radio networks

Cognitive Radio Networks are being researched upon heavily in the various layers of the communication structure. The task of bringing software in the physical layer of communication system led to the concept of a smart radio being able to learn, adapt and make intelligent decisions in an autonomous manner by use of a Software Defined Radio. This work provides novel concepts in the areas of spectrum sensing, learning of ongoing transmissions through Reinforcment learning, use of a game theoretic concept such as Zero-sum game for resilience of authorized users in cases of jamming, and decision making of user transmissions through Markov Decision processes. This is highly applicable in dynamic radio environments such as emergency communications required during natural disasters, large scale events and in mobile wireless communications. Such applications come under the "Internet of Things"

Proactive Monitoring, Anomaly Detection, and Forecasting of Solar Photovoltaic Systems Using Artificial Neural Networks

The world of energy sustainability landscape is witnessing high proliferation of smartgrids and microgrids, it has become significant to use intelligent tools to design, operate and maintain such crucial systems in our lives. Solar energy is an intermittent source and purely Photovoltaic (PV) based, or PV and storage based smartgrids require characterization and modelling of PV resources for an effective planning and effective operations. This dissertation familiarizes briefly the existing tools for design, monitoring, forecasting and operation of a solar system in smart electric grids infrastructure and proposes a unique application-based infrastructure to monitor, operate, forecast and troubleshoot a working PV of a smartgrid. A resilient smartgrid communication is proposed which enables monitoring and control of different elements in any PV system. This communication architecture is used to facilitate a feedback-oriented monitoring of different elements in a microgrid ecosystem and investigated thoroughly. This integrated architecture which is a combination of sensors, network elements, database and computation elements is designed specifically for solar photovoltaic (PV) powered grids on modular basis. Apart from this, the network resilience and redundancy for smooth and loss less communication is another characteristic factor in this research work. Subsequently, a deep neural network algorithm is developed to diagnose the underperformance in the generation of a PV system connected to a smartgrid. As PV generation is predominantly dependent on climatic parameters, it is necessary to have a mechanism for understanding and diagnosing performance of the system at any given instance. To address this challenge, this deep neural network architecture is presented for instantaneous performance diagnosis. The proposed architecture enabled modeling and diagnose of soiling and partial shade conditions prevalent with an accuracy of 90+%. Features of monitoring and regulating the generation and demand side of the grid were integrated through network along with feedback-based measures for effective performance in the PV system of a smartgrid or microgrid using the same network. The novelty in this work lies in real-time calculation of ideal performance and comparison for diagnosing critical performance issues of solar power generation like soiling and partial shading. Furthermore, long-short term memory (LSTM), which is a recurrent neural network model, is created for forecasting the PV solar resources, in which can assist in quantifying PV generation in various time intervals (hourly, daily, weekly). PV based smartgrids often experience expensive or inaccurate resources planning due to the lack of accurate forecasting tools where the projected methodology would eliminate such losses. This research work in its whole provides a different proposition of vertical integration which can transform into a new concept called Internet of Microgrid (IoMG). Planning, monitoring and operation form the core of smartgrids administration and if intelligent tools intertwined with network are being used as integral part in each of these aspects, then it forms a holistic view of smartgrids

Modelling, Dimensioning and Optimization of 5G Communication Networks, Resources and Services

This reprint aims to collect state-of-the-art research contributions that address challenges in the emerging 5G networks design, dimensioning and optimization. Designing, dimensioning and optimization of communication networks resources and services have been an inseparable part of telecom network development. The latter must convey a large volume of traffic, providing service to traffic streams with highly differentiated requirements in terms of bit-rate and service time, required quality of service and quality of experience parameters. Such a communication infrastructure presents many important challenges, such as the study of necessary multi-layer cooperation, new protocols, performance evaluation of different network parts, low layer network design, network management and security issues, and new technologies in general, which will be discussed in this book

The burden of the future: an exploration of the aftermath of violent conflict in the Eastern Democratic Republic of Congo (1996-2007)

Doctoral Degree. University of KwaZulu-Natal, Durban.This study explores the aftermath of protracted social conflict in the eastern Democratic Republic of Congo (DRC) through a historical lense in the Kabare district, precisely in Mulungu, Lwiro and Katana where research centres are located. A qualitative research paradigm was used to determine the nature and extent of protracted violence on the economy and the society. The sampling area involved the three research centres along with their direct vicinities. One hundred in-depth interviews with three focus groups followed by participant observation were used in this study in order to generate rich data. Purposive sampling technique was used to identify relevant respondents to which a snowball sampling method was added to help reach more interviewees. The findings of this study reveal that the numerous crisis that the country has gone through from the Leopoldian era right to the present are explained by the pursuit of the 1885 Berlin Protocol. Here international powers agreed on using the Congo as a carrefour for international commerce to enlarge their markets as well as to advance their commercial agenda while simultaneously using it as a digging ground of raw material required to boost industries in the West at the cost of the blood, sweat and misery of the Congolese people. The state failures from the Congo Free State to the Democratic Republic of Congo, coupled with the protracted social conflict that seats the culture of violence within the structures, institutions as well as the Congolese social fabric; are the result of the application of the 1885 Berlin Protocol that set the Congo to be an ever-open market for world leaders rather than a modern nation-state. The study concludes in demonstrating that unless the 1885 Berlin Protocol is reviewed and changed completely to allow the Congo to organize itself as a modern nation-state that will deal at equal terms of trade with Western countries, peace will remain illusory in the DRC and the innocent Congolese will continue to die in the process

LIPIcs, Volume 251, ITCS 2023, Complete Volume

LIPIcs, Volume 251, ITCS 2023, Complete Volum