Multipath Routing over Wireless Mesh Networks

Master'sMASTER OF SCIENC

Exploiting the power of multiplicity: a holistic survey of network-layer multipath

The Internet is inherently a multipath network: For an underlying network with only a single path, connecting various nodes would have been debilitatingly fragile. Unfortunately, traditional Internet technologies have been designed around the restrictive assumption of a single working path between a source and a destination. The lack of native multipath support constrains network performance even as the underlying network is richly connected and has redundant multiple paths. Computer networks can exploit the power of multiplicity, through which a diverse collection of paths is resource pooled as a single resource, to unlock the inherent redundancy of the Internet. This opens up a new vista of opportunities, promising increased throughput (through concurrent usage of multiple paths) and increased reliability and fault tolerance (through the use of multiple paths in backup/redundant arrangements). There are many emerging trends in networking that signify that the Internet's future will be multipath, including the use of multipath technology in data center computing; the ready availability of multiple heterogeneous radio interfaces in wireless (such as Wi-Fi and cellular) in wireless devices; ubiquity of mobile devices that are multihomed with heterogeneous access networks; and the development and standardization of multipath transport protocols such as multipath TCP. The aim of this paper is to provide a comprehensive survey of the literature on network-layer multipath solutions. We will present a detailed investigation of two important design issues, namely, the control plane problem of how to compute and select the routes and the data plane problem of how to split the flow on the computed paths. The main contribution of this paper is a systematic articulation of the main design issues in network-layer multipath routing along with a broad-ranging survey of the vast literature on network-layer multipathing. We also highlight open issues and identify directions for future work

Quickest Detection of Denial-of-Service Attacks in Cognitive Wireless Networks

Abstract Many denial-of-service (DOS) attacks in wireless networks, such as jamming, will cause significant performance degradation to the network and thus need to be detected quickly. This becomes more important in a cognitive wireless network employing dynamic spectrum access (DSA), where it is easier for the attackers to launch DOS attacks. For instance, the attackers may pretend to be a licensed primary user, and carry out the primary user emulation (PUE) attacks. The attackers may also explore the spectrum themselves, and conduct smart jamming. These attacks usually happen at unknown time and are unpredictable due to the lack of prior knowledge of the attackers. It is also observed that the statistical property of the resulted paths from multipath routing will have abrupt change when the attack happens. Hence, in this paper, we formulate the detection of DOS attacks as a quickest detection problem, i.e., detect the abrupt changes in distributions of certain observables at the network layer with minimum detection delay, while maintaining a given low false alarm probability. Specifically, we propose a non-parametric version of the Pages cumulative sum (CUSUM) algorithm to minimize the detection delay so that a network manager may react to the event as soon as possible to mitigate the effect of the attacks. Simulation results using a Spectrum-Aware Split Multipath Routing with dynamic channel assignment as a baseline routing protocol demonstrate the effectiveness of the proposed approach

Review and Comparison of Routing Metrics in Cognitive Radio Networks

In this paper, cognitive radio network is briefly introduced as well as routing parameters in cognitive radio networks. Due to lack of Spectrum, using not efficient methods of allocating static spectrum, in cognitive radio networks dynamic accessing spectrum is functional. Utilizing opportunistic a Spectrum requires recognition of routing parameters and metrics in cognition radio networks, which means considering fulfilling the minimum requirements of quality of service (QOS) secondary users need to use the allowed range of primary (main) users. Since primary users are prior to use the spectrum, when primary and secondary users coexist, they need to monitor the bandwidth of the authorized spectrum. One of the most important stages to excess the dynamic spectrum is to explore it. Detection of the presence of the authorized users by unauthorized users is one of the things done in this stage, which is called spectroscopy. In the next stage, we used the analyzed information I was spectroscopy, to decide on accessing the spectrum. cognition radio is defined as a smart wireless communication system, which is aware of the environment and changes its job variables like power forward, type of modulation, carrier frequency etc. using environment learning. For further explaining routing metrics, we try to compare routing metrics in cognitive radio networks and wireless network and analyze its challenges in one-way routing and in multi-route routing

Cyber-Human Systems, Space Technologies, and Threats

CYBER-HUMAN SYSTEMS, SPACE TECHNOLOGIES, AND THREATS is our eighth textbook in a series covering the world of UASs / CUAS/ UUVs / SPACE. Other textbooks in our series are Space Systems Emerging Technologies and Operations; Drone Delivery of CBNRECy – DEW Weapons: Emerging Threats of Mini-Weapons of Mass Destruction and Disruption (WMDD); Disruptive Technologies with applications in Airline, Marine, Defense Industries; Unmanned Vehicle Systems & Operations On Air, Sea, Land; Counter Unmanned Aircraft Systems Technologies and Operations; Unmanned Aircraft Systems in the Cyber Domain: Protecting USA’s Advanced Air Assets, 2nd edition; and Unmanned Aircraft Systems (UAS) in the Cyber Domain Protecting USA’s Advanced Air Assets, 1st edition. Our previous seven titles have received considerable global recognition in the field. (Nichols & Carter, 2022) (Nichols, et al., 2021) (Nichols R. K., et al., 2020) (Nichols R. , et al., 2020) (Nichols R. , et al., 2019) (Nichols R. K., 2018) (Nichols R. K., et al., 2022)https://newprairiepress.org/ebooks/1052/thumbnail.jp

A pervasive body sensor network for monitoring post-operative recovery

Over the past decade, miniaturisation and cost reduction brought about by the semiconductor industry has led to computers smaller in size than a pin head, powerful enough to carry out the processing required, and affordable enough to be disposable. Similar technological advances in wireless communication, sensor design, and energy storage have resulted in the development of wireless “Body Sensor Network (BSN) platforms comprising of tiny integrated micro sensors with onboard processing and wireless data transfer capability, offering the prospect of pervasive and continuous home health monitoring. In surgery, the reduced trauma of minimally invasive interventions combined with initiatives to reduce length of hospital stay and a socioeconomic drive to reduce hospitalisation costs, have all resulted in a trend towards earlier discharge from hospital. There is now a real need for objective, pervasive, and continuous post-operative home recovery monitoring systems. Surgical recovery is a multi-faceted and dynamic process involving biological, physiological, functional, and psychological components. Functional recovery (physical independence, activities of daily living, and mobility) is recognised as a good global indicator of a patient’s post-operative course, but has traditionally been difficult to objectively quantify. This thesis outlines the development of a pervasive wireless BSN system to objectively monitor the functional recovery of post-operative patients at home. Biomechanical markers were identified as surrogate measures for activities of daily living and mobility impairment, and an ear-worn activity recognition (e-AR) sensor containing a three-axis accelerometer and a pulse oximeter was used to collect this data. A simulated home environment was created to test a Bayesian classifier framework with multivariate Gaussians to model activity classes. A real-time activity index was used to provide information on the intensity of activity being performed. Mobility impairment was simulated with bracing systems and a multiresolution wavelet analysis and margin-based feature selection framework was used to detect impaired mobility. The e-AR sensor was tested in a home environment before its clinical use in monitoring post-operative home recovery of real patients who have undergone surgery. Such a system may eventually form part of an objective pervasive home recovery monitoring system tailored to the needs of today’s post-operative patient.Open acces