448 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
Emerging Communications for Wireless Sensor Networks
Wireless sensor networks are deployed in a rapidly increasing number of arenas, with uses ranging from healthcare monitoring to industrial and environmental safety, as well as new ubiquitous computing devices that are becoming ever more pervasive in our interconnected society. This book presents a range of exciting developments in software communication technologies including some novel applications, such as in high altitude systems, ground heat exchangers and body sensor networks. Authors from leading institutions on four continents present their latest findings in the spirit of exchanging information and stimulating discussion in the WSN community worldwide
Dimmer: Self-Adaptive Network-Wide Flooding with Reinforcement Learning
The last decade saw an emergence of Synchronous Transmissions (ST) as an
effective communication paradigm in low-power wireless networks. Numerous ST
protocols provide high reliability and energy efficiency in normal wireless
conditions, for a large variety of traffic requirements. Recently, with the
EWSN dependability competitions, the community pushed ST to harsher and
highly-interfered environments, improving upon classical ST protocols through
the use of custom rules, hand-tailored parameters, and additional
retransmissions. The results are sophisticated protocols, that require prior
expert knowledge and extensive testing, often tuned for a specific deployment
and envisioned scenario. In this paper, we explore how ST protocols can benefit
from self-adaptivity; a self-adaptive ST protocol selects itself its best
parameters to (1) tackle external environment dynamics and (2) adapt to its
topology over time. We introduce Dimmer as a self-adaptive ST protocol. Dimmer
builds on LWB and uses Reinforcement Learning to tune its parameters and match
the current properties of the wireless medium. By learning how to behave from
an unlabeled dataset, Dimmer adapts to different interference types and
patterns, and is able to tackle previously unseen interference. With Dimmer, we
explore how to efficiently design AI-based systems for constrained devices, and
outline the benefits and downfalls of AI-based low-power networking. We
evaluate our protocol on two deployments of resource-constrained nodes
achieving 95.8% reliability against strong, unknown WiFi interference. Our
results outperform baselines such as non-adaptive ST protocols (27%) and PID
controllers, and show a performance close to hand-crafted and more
sophisticated solutions, such as Crystal (99%)
Game-theoretic Robustness of Many-to-one Networks
In this paper, we study the robustness of networks that are
characterized by many-to-one communications (e.g., access
networks and sensor networks) in a game-theoretic model. More
specifically, we model the interactions between a network
operator and an adversary as a two player zero-sum game, where
the network operator chooses a spanning tree in the network, the
adversary chooses an edge to be removed from the network, and
the adversary’s payoff is proportional to the number of nodes
that can no longer reach a designated node through the spanning
tree. We show that the payoff in every Nash equilibrium of the
game is equal to the reciprocal of the persistence of the
network. We describe optimal adversarial and operator strategies
and give efficient, polynomial-time algorithms to compute
optimal strategies. We also generalize our game model to include
varying node weights, as well as attacks against nodes
Location based services in wireless ad hoc networks
In this dissertation, we investigate location based services in wireless ad hoc networks from four different aspects - i) location privacy in wireless sensor networks (privacy), ii) end-to-end secure communication in randomly deployed wireless sensor networks (security), iii) quality versus latency trade-off in content retrieval under ad hoc node mobility (performance) and iv) location clustering based Sybil attack detection in vehicular ad hoc networks (trust). The first contribution of this dissertation is in addressing location privacy in wireless sensor networks. We propose a non-cooperative sensor localization algorithm showing how an external entity can stealthily invade into the location privacy of sensors in a network. We then design a location privacy preserving tracking algorithm for defending against such adversarial localization attacks. Next we investigate secure end-to-end communication in randomly deployed wireless sensor networks. Here, due to lack of control on sensors\u27 locations post deployment, pre-fixing pairwise keys between sensors is not feasible especially under larger scale random deployments. Towards this premise, we propose differentiated key pre-distribution for secure end-to-end secure communication, and show how it improves existing routing algorithms. Our next contribution is in addressing quality versus latency trade-off in content retrieval under ad hoc node mobility. We propose a two-tiered architecture for efficient content retrieval in such environment. Finally we investigate Sybil attack detection in vehicular ad hoc networks. A Sybil attacker can create and use multiple counterfeit identities risking trust of a vehicular ad hoc network, and then easily escape the location of the attack avoiding detection. We propose a location based clustering of nodes leveraging vehicle platoon dispersion for detection of Sybil attacks in vehicular ad hoc networks --Abstract, page iii
Robotic Wireless Sensor Networks
In this chapter, we present a literature survey of an emerging, cutting-edge,
and multi-disciplinary field of research at the intersection of Robotics and
Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor
Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system
that aims to achieve certain sensing goals while meeting and maintaining
certain communication performance requirements, through cooperative control,
learning and adaptation. While both of the component areas, i.e., Robotics and
WSN, are very well-known and well-explored, there exist a whole set of new
opportunities and research directions at the intersection of these two fields
which are relatively or even completely unexplored. One such example would be
the use of a set of robotic routers to set up a temporary communication path
between a sender and a receiver that uses the controlled mobility to the
advantage of packet routing. We find that there exist only a limited number of
articles to be directly categorized as RWSN related works whereas there exist a
range of articles in the robotics and the WSN literature that are also relevant
to this new field of research. To connect the dots, we first identify the core
problems and research trends related to RWSN such as connectivity,
localization, routing, and robust flow of information. Next, we classify the
existing research on RWSN as well as the relevant state-of-the-arts from
robotics and WSN community according to the problems and trends identified in
the first step. Lastly, we analyze what is missing in the existing literature,
and identify topics that require more research attention in the future
A Survey on Modality Characteristics, Performance Evaluation Metrics, and Security for Traditional and Wearable Biometric Systems
Biometric research is directed increasingly towards Wearable Biometric Systems (WBS) for user authentication and identification. However, prior to engaging in WBS research, how their operational dynamics and design considerations differ from those of Traditional Biometric Systems (TBS) must be understood. While the current literature is cognizant of those differences, there is no effective work that summarizes the factors where TBS and WBS differ, namely, their modality characteristics, performance, security and privacy. To bridge the gap, this paper accordingly reviews and compares the key characteristics of modalities, contrasts the metrics used to evaluate system performance, and highlights the divergence in critical vulnerabilities, attacks and defenses for TBS and WBS. It further discusses how these factors affect the design considerations for WBS, the open challenges and future directions of research in these areas. In doing so, the paper provides a big-picture overview of the important avenues of challenges and potential solutions that researchers entering the field should be aware of. Hence, this survey aims to be a starting point for researchers in comprehending the fundamental differences between TBS and WBS before understanding the core challenges associated with WBS and its design
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