920 research outputs found
Game Theory-Based Cooperation for Underwater Acoustic Sensor Networks: Taxonomy, Review, Research Challenges and Directions.
Exploring and monitoring the underwater world using underwater sensors is drawing a lot of attention these days. In this field cooperation between acoustic sensor nodes has been a critical problem due to the challenging features such as acoustic channel failure (sound signal), long propagation delay of acoustic signal, limited bandwidth and loss of connectivity. There are several proposed methods to improve cooperation between the nodes by incorporating information/game theory in the node's cooperation. However, there is a need to classify the existing works and demonstrate their performance in addressing the cooperation issue. In this paper, we have conducted a review to investigate various factors affecting cooperation in underwater acoustic sensor networks. We study various cooperation techniques used for underwater acoustic sensor networks from different perspectives, with a concentration on communication reliability, energy consumption, and security and present a taxonomy for underwater cooperation. Moreover, we further review how the game theory can be applied to make the nodes cooperate with each other. We further analyze different cooperative game methods, where their performance on different metrics is compared. Finally, open issues and future research direction in underwater acoustic sensor networks are highlighted
A Survey on Efficient Routing Strategies For The Internet of Underwater Things (IoUT)
The Internet of Underwater Things (IoUT) is an emerging technology that promised to connect the underwater world to the land internet. It is enabled via the usage of the Underwater Acoustic Sensor Network (UASN). Therefore, it is affected by the challenges faced by UASNs such as the high dynamics of the underwater environment, the high transmission delays, low bandwidth, high-power consumption, and high bit error ratio. Due to these challenges, designing an efficient routing protocol for the IoUT is still a trade-off issue. In this paper, we discuss the specific challenges imposed by using UASN for enabling IoUT, we list and explain the general requirements for routing in the IoUT and we discuss how these challenges and requirements are addressed in literature routing protocols. Thus, the presented information lays a foundation for further investigations and futuristic proposals for efficient routing approaches in the IoUT
MAC/Routing design for under water sensor networks
The huge advances in communication technologies and Micro Electrical and Mechanical Systems (MEMS) have triggered a revolution in sensor networks. One major application of sensor networks is in the investigation of complex and uninhabited under water surfaces; such sensor networks are called the Underwater Wireless Sensor Networks (UWSN). UWSN comprises of a number of sensors which are submerged in water and one or several surface stations or a sinks at which the sensed data is collected. In some underwater sensor applications, autonomous underwater vehicles (AUVs) could be used. The underwater sensor nodes communicate with each other using acoustic signals. Applications for this type of networks include oceanographic data collection, pollution monitoring, offshore exploration and tactical surveillance applications. The novel networking paradigm of UWSN is facing a totally different operating environment than the ground based wireless sensor networks. This introduces new challenges such as huge propagation delays, and limited acoustic link capacity with high attenuation factors. These new challenges have their own impact on the design of most of the networking layers preventing researchers from using the same layers used for other networks. The most affected layers are the Physical, Medium Access Control (MAC), Routing and Transport layers. This work will introduce novel routing and MAC layers’ protocols for UWSNs. The routing protocol will adopt the minimum spanning tree algorithm and focus on maximizing the connectivity of the network, which means maximizing the total number of nodes connected to the root or the sink in this case. The protocol will try also to provide a minimum hop connection for all the nodes in the network taking into account the residual energy, location information and number of children at the next hop node. The other contribution of this work is a MAC Protocol which will incorporate the topology information provided by the routing protocol to minimize the collisions and energy wastage in data transmission. The MAC Protocol will also try to shorten the queuing delays at the intermediate nodes for a message traveling from source to the sink. A comparison will be conducted with other existing routing and MAC protocols. The routing protocol will be tested and compared with the E-Span spanning tree algorithm for data aggregation. The MAC protocol will be compared with Park\u27s protocol proposed in [2] in terms of performance metrics like end-to-end delay and the number of collisions. We will also explore the ability of the proposed protocols to enhance the life span of the network
A Survey on UAV-Aided Maritime Communications: Deployment Considerations, Applications, and Future Challenges
Maritime activities represent a major domain of economic growth with several
emerging maritime Internet of Things use cases, such as smart ports, autonomous
navigation, and ocean monitoring systems. The major enabler for this exciting
ecosystem is the provision of broadband, low-delay, and reliable wireless
coverage to the ever-increasing number of vessels, buoys, platforms, sensors,
and actuators. Towards this end, the integration of unmanned aerial vehicles
(UAVs) in maritime communications introduces an aerial dimension to wireless
connectivity going above and beyond current deployments, which are mainly
relying on shore-based base stations with limited coverage and satellite links
with high latency. Considering the potential of UAV-aided wireless
communications, this survey presents the state-of-the-art in UAV-aided maritime
communications, which, in general, are based on both conventional optimization
and machine-learning-aided approaches. More specifically, relevant UAV-based
network architectures are discussed together with the role of their building
blocks. Then, physical-layer, resource management, and cloud/edge computing and
caching UAV-aided solutions in maritime environments are discussed and grouped
based on their performance targets. Moreover, as UAVs are characterized by
flexible deployment with high re-positioning capabilities, studies on UAV
trajectory optimization for maritime applications are thoroughly discussed. In
addition, aiming at shedding light on the current status of real-world
deployments, experimental studies on UAV-aided maritime communications are
presented and implementation details are given. Finally, several important open
issues in the area of UAV-aided maritime communications are given, related to
the integration of sixth generation (6G) advancements
Toward RIS-Enhanced Integrated Terrestrial/Non-Terrestrial Connectivity in 6G
The next generation of wireless systems will take the concept of
communications and networking to another level through the seamless integration
of terrestrial, aerial, satellite, maritime and underwater communication
systems. Reconfigurable intelligent surface (RIS) is an innovative technology
which, with its singular features and functionalities, can expedite the
realization of this everywhere connectivity. Motivated by the unparalleled
properties of this innovatory technology, this article provides a comprehensive
discussion on how RIS can contribute to the actualization and proper
functioning of future integrated terrestrial/non-terrestrial (INTENT) networks.
As a case study, we explore the integration of RIS into non-orthogonal multiple
access (NOMA)-based satellite communication networks and demonstrate the
performance enhancement achieved by the inclusion of RIS via numerical
simulations. Promising directions for future research in this area are set
forth at the end of this article.Comment: This work has been accepted for publication in IEEE Networ
Reconfigurable Intelligent Surfaces in Challenging Environments: Underwater, Underground, Industrial and Disaster
Reconfigurable intelligent surfaces (RISs) have been introduced to improve
the signal propagation characteristics by focusing the signal power in the
preferred direction, thus making the communication environment "smart". The
typical use cases and applications for the "smart" environment include beyond
5G communication networks, smart cities, etc. The main advantage of employing
RISs in such networks is a more efficient exploitation of spatial degrees of
freedom. This advantage manifests in better interference mitigation as well as
increased spectral and energy efficiency due to passive beam steering.
Challenging environments comprise a range of scenarios, which share the fact
that it is extremely difficult to establish a communication link using
conventional technology due to many impairments typically associated with the
propagation medium and increased signal scattering. Although the challenges for
the design of communication networks, and specifically the Internet of Things
(IoT), in such environments are known, there is no common enabler or solution
for all these applications. Interestingly, the use of RISs in such scenarios
can become such an enabler and a game changer technology. Surprisingly, the
benefits of RIS for wireless networking in underwater and underground medium as
well as in industrial and disaster environments have not been addressed yet. In
this paper, we aim at filling this gap by discussing potential use cases,
deployment strategies and design aspects for RIS devices in underwater IoT,
underground IoT as well as Industry 4.0 and emergency networks. In addition,
novel research challenges to be addressed in this context are described.Comment: 16 pages, 13 figures, submitted for publication in IEEE journa
Machine Learning in Wireless Sensor Networks: Algorithms, Strategies, and Applications
Wireless sensor networks monitor dynamic environments that change rapidly
over time. This dynamic behavior is either caused by external factors or
initiated by the system designers themselves. To adapt to such conditions,
sensor networks often adopt machine learning techniques to eliminate the need
for unnecessary redesign. Machine learning also inspires many practical
solutions that maximize resource utilization and prolong the lifespan of the
network. In this paper, we present an extensive literature review over the
period 2002-2013 of machine learning methods that were used to address common
issues in wireless sensor networks (WSNs). The advantages and disadvantages of
each proposed algorithm are evaluated against the corresponding problem. We
also provide a comparative guide to aid WSN designers in developing suitable
machine learning solutions for their specific application challenges.Comment: Accepted for publication in IEEE Communications Surveys and Tutorial
- …