342 research outputs found

    Rohc-Mpls Tunnel Architecture For Wireless Mesh

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    Natural or human-made disasters are sudden events that can cause significant damage, especially to the network communication infrastructure. In these events, a rapid deployment of network communication systems is required in order to relay or receive the communication among the people in the disaster areas to conduct relief and rescue efforts. Wireless mesh networks have emerged and has been recognised for its potential for rapid deployment and last mile coverage of network infrastructure, which is highly suitable for emergency response management. While wireless mesh networks have beneficial attributes, it also introduces some crucial problems. During data transmission, the path recovery time is significantly higher resulting in the loss of data if node and link failures occur

    Resource Allocation and Service Management in Next Generation 5G Wireless Networks

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    The accelerated evolution towards next generation networks is expected to dramatically increase mobile data traffic, posing challenging requirements for future radio cellular communications. User connections are multiplying, whilst data hungry content is dominating wireless services putting significant pressure on network's available spectrum. Ensuring energy-efficient and low latency transmissions, while maintaining advanced Quality of Service (QoS) and high standards of user experience are of profound importance in order to address diversifying user prerequisites and ensure superior and sustainable network performance. At the same time, the rise of 5G networks and the Internet of Things (IoT) evolution is transforming wireless infrastructure towards enhanced heterogeneity, multi-tier architectures and standards, as well as new disruptive telecommunication technologies. The above developments require a rethinking of how wireless networks are designed and operate, in conjunction with the need to understand more holistically how users interact with the network and with each other. In this dissertation, we tackle the problem of efficient resource allocation and service management in various network topologies under a user-centric approach. In the direction of ad-hoc and self-organizing networks where the decision making process lies at the user level, we develop a novel and generic enough framework capable of solving a wide array of problems with regards to resource distribution in an adaptable and multi-disciplinary manner. Aiming at maximizing user satisfaction and also achieve high performance - low power resource utilization, the theory of network utility maximization is adopted, with the examined problems being formulated as non-cooperative games. The considered games are solved via the principles of Game Theory and Optimization, while iterative and low complexity algorithms establish their convergence to steady operational outcomes, i.e., Nash Equilibrium points. This thesis consists a meaningful contribution to the current state of the art research in the field of wireless network optimization, by allowing users to control multiple degrees of freedom with regards to their transmission, considering mobile customers and their strategies as the key elements for the amelioration of network's performance, while also adopting novel technologies in the resource management problems. First, multi-variable resource allocation problems are studied for multi-tier architectures with the use of femtocells, addressing the topic of efficient power and/or rate control, while also the topic is examined in Visible Light Communication (VLC) networks under various access technologies. Next, the problem of customized resource pricing is considered as a separate and bounded resource to be optimized under distinct scenarios, which expresses users' willingness to pay instead of being commonly implemented by a central administrator in the form of penalties. The investigation is further expanded by examining the case of service provider selection in competitive telecommunication markets which aim to increase their market share by applying different pricing policies, while the users model the selection process by behaving as learning automata under a Machine Learning framework. Additionally, the problem of resource allocation is examined for heterogeneous services where users are enabled to dynamically pick the modules needed for their transmission based on their preferences, via the concept of Service Bundling. Moreover, in this thesis we examine the correlation of users' energy requirements with their transmission needs, by allowing the adaptive energy harvesting to reflect the consumed power in the subsequent information transmission in Wireless Powered Communication Networks (WPCNs). Furthermore, in this thesis a fresh perspective with respect to resource allocation is provided assuming real life conditions, by modeling user behavior under Prospect Theory. Subjectivity in decisions of users is introduced in situations of high uncertainty in a more pragmatic manner compared to the literature, where they behave as blind utility maximizers. In addition, network spectrum is considered as a fragile resource which might collapse if over-exploited under the principles of the Tragedy of the Commons, allowing hence users to sense risk and redefine their strategies accordingly. The above framework is applied in different cases where users have to select between a safe and a common pool of resources (CPR) i.e., licensed and unlicensed bands, different access technologies, etc., while also the impact of pricing in protecting resource fragility is studied. Additionally, the above resource allocation problems are expanded in Public Safety Networks (PSNs) assisted by Unmanned Aerial Vehicles (UAVs), while also aspects related to network security against malign user behaviors are examined. Finally, all the above problems are thoroughly evaluated and tested via a series of arithmetic simulations with regards to the main characteristics of their operation, as well as against other approaches from the literature. In each case, important performance gains are identified with respect to the overall energy savings and increased spectrum utilization, while also the advantages of the proposed framework are mirrored in the improvement of the satisfaction and the superior Quality of Service of each user within the network. Lastly, the flexibility and scalability of this work allow for interesting applications in other domains related to resource allocation in wireless networks and beyond

    Edu-Cloud: On-the-fly Employability Skills as a Service

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    21st Century global job market competition requires Science, Technology, Engineering and Mathematics (STEM) university curricula to support both state-of-the-art technical and soft skills learning to improve graduate employment. This necessitates the transformation of the current teaching and learning methodology powered by a social and col- laborative platform to provide a social co-learning environment. This social co-learning will provide students with opportunities for self-enrichment while supporting their technical skills and hands-on needs. The platform must also provide the required lab infrastructure for hands-on experimentation. This paper proposes the design and implementation of a cloud based platform called Edu-Cloud. The Edu-Cloud has been designed to provide automated resource provisioning and perform on-the-fly deployment of scalable virtual network functions to stream multimedia content closer to the global learners. This would help to meet the specific learning needs of a group of global interconnected students with similar learning skills and abilities. The benchmarking performance results show that the proposed framework works efficiently while reducing primary network traffic by deploying resources closer to the users and support scalability for a global deployment scenario

    Mobile Ad-Hoc Networks

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    Being infrastructure-less and without central administration control, wireless ad-hoc networking is playing a more and more important role in extending the coverage of traditional wireless infrastructure (cellular networks, wireless LAN, etc). This book includes state-of-the-art techniques and solutions for wireless ad-hoc networks. It focuses on the following topics in ad-hoc networks: quality-of-service and video communication, routing protocol and cross-layer design. A few interesting problems about security and delay-tolerant networks are also discussed. This book is targeted to provide network engineers and researchers with design guidelines for large scale wireless ad hoc networks

    Reliable Multicast in Mobile Ad Hoc Wireless Networks

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    A mobile wireless ad hoc network (MANET) consists of a group of mobile nodes communicating wirelessly with no fixed infrastructure. Each node acts as source or receiver, and all play a role in path discovery and packet routing. MANETs are growing in popularity due to multiple usage models, ease of deployment and recent advances in hardware with which to implement them. MANETs are a natural environment for multicasting, or group communication, where one source transmits data packets through the network to multiple receivers. Proposed applications for MANET group communication ranges from personal network apps, impromptu small scale business meetings and gatherings, to conference, academic or sports complex presentations for large crowds reflect the wide range of conditions such a protocol must handle. Other applications such as covert military operations, search and rescue, disaster recovery and emergency response operations reflect the mission critical nature of many ad hoc applications. Reliable data delivery is important for all categories, but vital for this last one. It is a feature that a MANET group communication protocol must provide. Routing protocols for MANETs are challenged with establishing and maintaining data routes through the network in the face of mobility, bandwidth constraints and power limitations. Multicast communication presents additional challenges to protocols. In this dissertation we study reliability in multicast MANET routing protocols. Several on-demand multicast protocols are discussed and their performance compared. Then a new reliability protocol, R-ODMRP is presented that runs on top of ODMRP, a well documented best effort protocol with high reliability. This protocol is evaluated against ODMRP in a standard network simulator, ns-2. Next, reliable multicast MANET protocols are discussed and compared. We then present a second new protocol, Reyes, also a reliable on-demand multicast communication protocol. Reyes is implemented in the ns-2 simulator and compared against the current standards for reliability, flooding and ODMRP. R-ODMRP is used as a comparison point as well. Performance results are comprehensively described for latency, bandwidth and reliable data delivery. The simulations show Reyes to greatly outperform the other protocols in terms of reliability, while also outperforming R-ODMRP in terms of latency and bandwidth overhead

    A framework for traffic flow survivability in wireless networks prone to multiple failures and attacks

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    Transmitting packets over a wireless network has always been challenging due to failures that have always occurred as a result of many types of wireless connectivity issues. These failures have caused significant outages, and the delayed discovery and diagnostic testing of these failures have exacerbated their impact on servicing, economic damage, and social elements such as technological trust. There has been research on wireless network failures, but little on multiple failures such as node-node, node-link, and link–link failures. The problem of capacity efficiency and fast recovery from multiple failures has also not received attention. This research develops a capacity efficient evolutionary swarm survivability framework, which encompasses enhanced genetic algorithm (EGA) and ant colony system (ACS) survivability models to swiftly resolve node-node, node-link, and link-link failures for improved service quality. The capacity efficient models were tested on such failures at different locations on both small and large wireless networks. The proposed models were able to generate optimal alternative paths, the bandwidth required for fast rerouting, minimized transmission delay, and ensured the rerouting path fitness and good transmission time for rerouting voice, video and multimedia messages. Increasing multiple link failures reveal that as failure increases, the bandwidth used for rerouting and transmission time also increases. This implies that, failure increases bandwidth usage which leads to transmission delay, which in turn slows down message rerouting. The suggested framework performs better than the popular Dijkstra algorithm, proactive, adaptive and reactive models, in terms of throughput, packet delivery ratio (PDR), speed of transmission, transmission delay and running time. According to the simulation results, the capacity efficient ACS has a PDR of 0.89, the Dijkstra model has a PDR of 0.86, the reactive model has a PDR of 0.83, the proactive model has a PDR of 0.83, and the adaptive model has a PDR of 0.81. Another performance evaluation was performed to compare the proposed model's running time to that of other evaluated routing models. The capacity efficient ACS model has a running time of 169.89ms on average, while the adaptive model has a running time of 1837ms and Dijkstra has a running time of 280.62ms. With these results, capacity efficient ACS outperforms other evaluated routing algorithms in terms of PDR and running time. According to the mean throughput determined to evaluate the performance of the following routing algorithms: capacity efficient EGA has a mean throughput of 621.6, Dijkstra has a mean throughput of 619.3, proactive (DSDV) has a mean throughput of 555.9, and reactive (AODV) has a mean throughput of 501.0. Since Dijkstra is more similar to proposed models in terms of performance, capacity efficient EGA was compared to Dijkstra as follows: Dijkstra has a running time of 3.8908ms and EGA has a running time of 3.6968ms. In terms of running time and mean throughput, the capacity efficient EGA also outperforms the other evaluated routing algorithms. The generated alternative paths from these investigations demonstrate that the proposed framework works well in preventing the problem of data loss in transit and ameliorating congestion issue resulting from multiple failures and server overload which manifests when the process hangs. The optimal solution paths will in turn improve business activities through quality data communications for wireless service providers.School of ComputingPh. D. (Computer Science
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