280 research outputs found
Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey
Wireless sensor networks (WSNs) consist of autonomous and resource-limited
devices. The devices cooperate to monitor one or more physical phenomena within
an area of interest. WSNs operate as stochastic systems because of randomness
in the monitored environments. For long service time and low maintenance cost,
WSNs require adaptive and robust methods to address data exchange, topology
formulation, resource and power optimization, sensing coverage and object
detection, and security challenges. In these problems, sensor nodes are to make
optimized decisions from a set of accessible strategies to achieve design
goals. This survey reviews numerous applications of the Markov decision process
(MDP) framework, a powerful decision-making tool to develop adaptive algorithms
and protocols for WSNs. Furthermore, various solution methods are discussed and
compared to serve as a guide for using MDPs in WSNs
Intelligent Reflecting Surface Assisted Anti-Jamming Communications Based on Reinforcement Learning
Malicious jamming launched by smart jammer, which attacks legitimate
transmissions has been regarded as one of the critical security challenges in
wireless communications. Thus, this paper exploits intelligent reflecting
surface (IRS) to enhance anti-jamming communication performance and mitigate
jamming interference by adjusting the surface reflecting elements at the IRS.
Aiming to enhance the communication performance against smart jammer, an
optimization problem for jointly optimizing power allocation at the base
station (BS) and reflecting beamforming at the IRS is formulated. As the
jamming model and jamming behavior are dynamic and unknown, a win or learn fast
policy hill-climbing (WoLF-PHC) learning approach is proposed to jointly
optimize the anti-jamming power allocation and reflecting beamforming strategy
without the knowledge of the jamming model. Simulation results demonstrate that
the proposed anti-jamming based-learning approach can efficiently improve both
the IRS-assisted system rate and transmission protection level compared with
existing solutions.Comment: This paper appears in the Proceedings of IEEE Global Communications
Conference (GLOBECOM) 2020. A full version appears in IEEE Transactions on
Wireless Communications. arXiv:2004.1253
A Comprehensive Survey on the Cyber-Security of Smart Grids: Cyber-Attacks, Detection, Countermeasure Techniques, and Future Directions
One of the significant challenges that smart grid networks face is
cyber-security. Several studies have been conducted to highlight those security
challenges. However, the majority of these surveys classify attacks based on
the security requirements, confidentiality, integrity, and availability,
without taking into consideration the accountability requirement. In addition,
some of these surveys focused on the Transmission Control Protocol/Internet
Protocol (TCP/IP) model, which does not differentiate between the application,
session, and presentation and the data link and physical layers of the Open
System Interconnection (OSI) model. In this survey paper, we provide a
classification of attacks based on the OSI model and discuss in more detail the
cyber-attacks that can target the different layers of smart grid networks
communication. We also propose new classifications for the detection and
countermeasure techniques and describe existing techniques under each category.
Finally, we discuss challenges and future research directions
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