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

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Controller Synthesis of Multi-Axial Robotic System Used for Wearable Devices

Wearable devices are commonly used in different fields to help improving performance of movements for different groups of users. The long-term goal of this study is to develop a low-cost assistive robotic device that allows patients to perform rehabilitation activities independently and reproduces natural movement to help stroke patients and elderly adults in their daily activities while moving their arms. In the past few decades, various types of wearable robotic devices have been developed to assist different physical movements. Among different types of actuators, the twisted-string actuation system is one of those that has advantages of light-weight, low cost, and great portability. In this study, a dual twisted-string actuator is used to drive the joints of the prototype assistive robotic device. To compensate the asynchronous movement caused by nonlinear factors, a hybrid controller that combines fuzzy logic rules and linear PID control algorithm was adopted to compensate for both tracking and synchronization of the two actuators.;In order to validate the performance of proposed controllers, the robotic device was driven by an xPC Target machine with additional embedded controllers for different data acquisition tasks. The controllers were fine tuned to eliminate the inaccuracy of tracking and synchronization caused by disturbance and asynchronous movements of both actuators. As a result, the synthesized controller can provide a high precision when tracking simple actual human movements

Discrete and Continuous Optimization Methods for Self-Organization in Small Cell Networks - Models and Algorithms

Self-organization is discussed in terms of distributed computational methods and algorithms for resource allocation in cellular networks. In order to develop algorithms for different self-organization problems pertinent to small cell networks (SCN), a number of concepts from discrete and continuous optimization theory are employed. Self-organized resource allocation problems such as physical cell identifier (PCI) assignment and primary component carrier selection are formulated as discrete optimization problems. Distributed graph coloring and constraint satisfaction algorithms are used to solve these problems. The PCI assignment is also discussed for multi-operator heterogeneous networks. Furthermore, different variants of simulated annealing are proposed for solving a graph coloring formulation of the orthogonal resource allocation problem. In the continuous optimization domain, a network utility maximization approach is considered for solving different resource allocation problems. Network synchronization is addressed using greedy and gradient search algorithms. Primal and dual decomposition are discussed for transmit power and scheduling weight optimizations, under a network-wide power constraint. Joint optimization over transmit powers and multi-user scheduling weights is considered in a multi-carrier SCN, for both maximum rate and proportional-fair rate utilities. This formulation is extended for multiple-input multiple-output (MIMO) SCNs, where apart from transmit powers and multi-user scheduling weights, the transmit precoders are also optimized, for a generic alpha-fair utility function. Optimization of network resources over multiple degrees of freedom is particularly effective in reducing mutual interference, leading to significant gains in network utility. Finally, an alternate formulation of transmit power allocation is considered, in which the network transmit power is minimized subject to the data rate constraints of users. Thus, network resource allocation algorithms inspired by optimization theory constitute an effective approach for self-organization in contemporary as well as future cellular networks

Digital Twin-Driven Network Architecture for Video Streaming

Digital twin (DT) is revolutionizing the emerging video streaming services through tailored network management. By integrating diverse advanced communication technologies, DTs are promised to construct a holistic virtualized network for better network management performance. To this end, we develop a DT-driven network architecture for video streaming (DTN4VS) to enable network virtualization and tailored network management. With the architecture, various types of DTs can characterize physical entities' status, separate the network management functions from the network controller, and empower the functions with emulated data and tailored strategies. To further enhance network management performance, three potential approaches are proposed, i.e., domain data exploitation, performance evaluation, and adaptive DT model update. We present a case study pertaining to DT-assisted network slicing for short video streaming, followed by some open research issues for DTN4VS.Comment: 8 pages, 5 figures, submitted to IEEE Network Magazin

Asynchronous and Multiprecision Linear Solvers - Scalable and Fault-Tolerant Numerics for Energy Efficient High Performance Computing

Asynchronous methods minimize idle times by removing synchronization barriers, and therefore allow the efficient usage of computer systems. The implied high tolerance with respect to communication latencies improves the fault tolerance. As asynchronous methods also enable the usage of the power and energy saving mechanisms provided by the hardware, they are suitable candidates for the highly parallel and heterogeneous hardware platforms that are expected for the near future