Game theory for collaboration in future networks

Cooperative strategies have the great potential of improving network performance and spectrum utilization in future networking environments. This new paradigm in terms of network management, however, requires a novel design and analysis framework targeting a highly flexible networking solution with a distributed architecture. Game Theory is very suitable for this task, since it is a comprehensive mathematical tool for modeling the highly complex interactions among distributed and intelligent decision makers. In this way, the more convenient management policies for the diverse players (e.g. content providers, cloud providers, home providers, brokers, network providers or users) should be found to optimize the performance of the overall network infrastructure. The authors discuss in this chapter several Game Theory models/concepts that are highly relevant for enabling collaboration among the diverse players, using different ways to incentivize it, namely through pricing or reputation. In addition, the authors highlight several related open problems, such as the lack of proper models for dynamic and incomplete information games in this area.info:eu-repo/semantics/acceptedVersio

Game theory for cooperation in multi-access edge computing

Cooperative strategies amongst network players can improve network performance and spectrum utilization in future networking environments. Game Theory is very suitable for these emerging scenarios, since it models high-complex interactions among distributed decision makers. It also finds the more convenient management policies for the diverse players (e.g., content providers, cloud providers, edge providers, brokers, network providers, or users). These management policies optimize the performance of the overall network infrastructure with a fair utilization of their resources. This chapter discusses relevant theoretical models that enable cooperation amongst the players in distinct ways through, namely, pricing or reputation. In addition, the authors highlight open problems, such as the lack of proper models for dynamic and incomplete information scenarios. These upcoming scenarios are associated to computing and storage at the network edge, as well as, the deployment of large-scale IoT systems. The chapter finalizes by discussing a business model for future networks.info:eu-repo/semantics/acceptedVersio

Game Theory for Multi-Access Edge Computing:Survey, Use Cases, and Future Trends

Game theory (GT) has been used with significant success to formulate, and either design or optimize, the operation of many representative communications and networking scenarios. The games in these scenarios involve, as usual, diverse players with conflicting goals. This paper primarily surveys the literature that has applied theoretical games to wireless networks, emphasizing use cases of upcoming multiaccess edge computing (MEC). MEC is relatively new and offers cloud services at the network periphery, aiming to reduce service latency backhaul load, and enhance relevant operational aspects such as quality of experience or security. Our presentation of GT is focused on the major challenges imposed by MEC services over the wireless resources. The survey is divided into classical and evolutionary games. Then, our discussion proceeds to more specific aspects which have a considerable impact on the game's usefulness, namely, rational versus evolving strategies, cooperation among players, available game information, the way the game is played (single turn, repeated), the game's model evaluation, and how the model results can be applied for both optimizing resource-constrained resources and balancing diverse tradeoffs in real edge networking scenarios. Finally, we reflect on lessons learned, highlighting future trends and research directions for applying theoretical model games in upcoming MEC services, considering both network design issues and usage scenarios

Traffic Scheduling in Software-defined Backhaul Network

In the past few years, severe challenges have arisen for network operators, as explosive growth and service differentiation in data demands require an increasing number of network capacity as well as dynamic traffic management. To adapt to the network densification, wireless backhaul solution is attracting more and more attentions due to its flexible deployment. Meanwhile, the software-defined network (SDN) proposes an promising architecture that can achieve dynamic control and management for various functionalities. In this case, by applying the SDN architecture to wireless backhaul networks, the traffic scheduling functionality may satisfy the ever-increasing and differentiated traffic demands. To tackle the traffic demand challenges, traffic scheduling for software-defined backhaul networks (SDBN) is investigated from three aspects in this thesis. In the first aspect, various virtual networks based on service types are embedded to the same wireless backhaul infrastructure. An algorithm, named VNE-SDBN, is proposed to solve the virtual network embedding (VNE) problem to improve the performance of the revenue of infrastructure providers and virtual network request acceptance ratio by exploiting the unique characteristics of SDBNs. In the second aspect, incoming traffic is scheduled online by joint routing and resource allocation approach in backhaul networks operated in low-frequency microwave (LFM) and those operated in millimetre wave (mmW). A digraph-based greedy algorithm (DBGA) is proposed considering the relationship between the degrees of vertices in the constructed interference digraph and system throughput with low complexity. In the third aspect, quality-of-service is provided in terms of delay and throughput with two proposed algorithms for backhaul networks with insufficient spectral resources. At last, as a trial research on E-band, a conceptual adaptive modulation system with channel estimation based on rain rate for E-band SDBN is proposed to exploit the rain attenuation feature of E-band. The results of the research works are mainly achieved through heuristic algorithms. Genetic algorithm, which is a meta-heuristic algorithm, is employed to obtain near-optimal solutions to the proposed NP-hard problems. Low complexity greedy algorithms are developed based on the specific problem analysis. Finally, the evaluation of proposed systems and algorithms are performed through numerical simulations. Simulations for backhaul networks with respect to VNE, routing and resource allocation are developed

Role of Wireless technology in mobile augmented reality system (MARS)

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Game Theoretic Energy Balanced Routing Protocols For Wireless Sensor Networks

A primary concern in the operation of Wireless Sensor Network (WSN) is the issue of balancing energy consumption and lifetime maximization. This dissertation addresses the problem of unbalanced energy consumption in WSNs by designing traffic load balancing geographical routing protocols. In order to provide energy balance; two decentralized, scalable and stable routing protocols are proposed: Game Theoretic Energy Balanced (GTEB) routing protocol for WSNs and three dimensional (3D) Game Theoretic Energy Balance (3D-GTEB) routing protocol for WSNs. GTEB were designed to fit with WSNs deployed in 2D space, while 3D-GTEB designed to work with WSNs deployed in 3D terrain. Both protocols are built based on balancing energy consumption into region level and node level using different game theory in each level. In the first level, evolutionary game theory was used to balance the energy consumption in various packet forwarding sub-regions, while in the second level classical game theory was used to balance the energy consumption in forwarding sub-region nodes. 3D-GTEB benefits from utilizing the third coordinate of nodes\u27 locations to achieve better and accurate routing decision with low network overhead. The protocols where evaluated analytically and experimentally under realistic simulation environment. Thus, the results show not only combining evolutionary and classical game theories are applicable to WSNs, but also they achieve significantly better performance in terms of energy usage, load spreading, and packet delivery ratio under different network scenarios when compared to the state-of-art protocols. Moreover, further investigation is made to evaluate the effectiveness of using game theories by comparing GTEB with three random test protocols. The results demonstrated that the GTEB and 3D-GTEB are prolonged the network lifetime from 33% to 85%, and provided better delivery ratio form 26% to 52% as compared with other three random test protocols and three similar state-of-art routing algorithms

Performance modelling and evaluation of heterogeneous wired / wireless networks under Bursty Traffic. Analytical models for performance analysis of communication networks in multi-computer systems, multi-cluster systems, and integrated wireless systems.

Computer networks can be classified into two broad categories: wired networks and wireless networks, according to the hardware and software technologies used to interconnect the individual devices. Wired interconnection networks are hardware fabrics supporting communications between individual processors in highperformance computing systems (e.g., multi-computer systems and cluster systems). On the other hand, due to the rapid development of wireless technologies, wireless networks have emerged and become an indispensable part for people¿s lives. The integration of different wireless technologies is an effective approach to accommodate the increasing demand of the users to communicate with each other and access the Internet. This thesis aims to investigate the performance of wired interconnection networks and integrated wireless networks under the realistic working conditions. Traffic patterns have a significant impact on network performance. A number of recent measurement studies have convincingly demonstrated that the traffic generated by many real-world applications in communication networks exhibits bursty arrival nature and the message destinations are non-uniformly distributed. Analytical models for the performance evaluation of wired interconnection networks and integrated wireless networks have been widely reported. However, most of these models are developed under the simplified assumption of non-bursty Poisson process with uniformly distributed message destinations. To fill this gap, this thesis first presents an analytical model to investigate the performance of wired interconnection networks in multi-computer systems. Secondly, the analytical models for wired interconnection networks in multi-cluster systems are developed. Finally, this thesis proposes analytical models to evaluate the end-to-end delay and throughput of integrated wireless local area networks and wireless mesh networks. These models are derived when the networks are subject to bursty traffic with non-uniformly distributed message destinations which can capture the burstiness of real-world network traffic in the both temporal domain and spatial domain. Extensive simulation experiments are conducted to validate the accuracy of the analytical models. The models are then used as practical and cost-effective tools to investigate the performance of heterogeneous wired or wireless networks under the traffic patterns exhibited by real-world applications

Optimized traffic scheduling and routing in smart home networks

Home networks are evolving rapidly to include heterogeneous physical access and a large number of smart devices that generate different types of traffic with different distributions and different Quality of Service (QoS) requirements. Due to their particular architectures, which are very dense and very dynamic, the traditional one-pair-node shortest path solution is no longer efficient to handle inter-smart home networks (inter-SHNs) routing constraints such as delay, packet loss, and bandwidth in all-pair node heterogenous links. In addition, Current QoS-aware scheduling methods consider only the conventional priority metrics based on the IP Type of Service (ToS) field to make decisions for bandwidth allocation. Such priority based scheduling methods are not optimal to provide both QoS and Quality of Experience (QoE), especially for smart home applications, since higher priority traffic does not necessarily require higher stringent delay than lower-priority traffic. Moreover, current QoS-aware scheduling methods in the intra-smart home network (intra-SHN) do not consider concurrent traffic caused by the fluctuation of intra-SH network traffic distributions. Thus, the goal of this dissertation is to build an efficient heterogenous multi-constrained routing mechanism and an optimized traffic scheduling tool in order to maintain a cost-effective communication between all wired-wireless connected devices in inter-SHNs and to effectively process concurrent and non-concurrent traffic in intra-SHN. This will help Internet service providers (ISPs) and home user to enhance the overall QoS and QoE of their applications while maintaining a relevant communication in both inter-SHNs and intra-SHN. In order to meet this goal, three key issues are required to be addressed in our framework and are summarized as follows: i) how to build a cost-effective routing mechanism in heterogonous inter-SHNs ? ii) how to efficiently schedule the multi-sourced intra-SHN traffic based on both QoS and QoE ? and iii) how to design an optimized queuing model for intra-SHN concurrent traffics while considering their QoS requirements? As part of our contributions to solve the first problem highlighted above, we present an analytical framework for dynamically optimizing data flows in inter-SHNs using Software-defined networking (SDN). We formulate a QoS-based routing optimization problem as a constrained shortest path problem and then propose an optimized solution (QASDN) to determine minimal cost between all pairs of nodes in the network taking into account the different types of physical accesses and the network utilization patterns. To address the second issue and to solve the gaps between QoS and QoE, we propose a new queuing model for QoS-level Pair traffic with mixed arrival distributions in Smart Home network (QP-SH) to make a dynamic QoS-aware scheduling decision meeting delay requirements of all traffic while preserving their degrees of criticality. A new metric combining the ToS field and the maximum number of packets that can be processed by the system's service during the maximum required delay, is defined. Finally, as part of our contribution to address the third issue, we present an analytic model for a QoS-aware scheduling optimization of concurrent intra-SHN traffics with mixed arrival distributions and using probabilistic queuing disciplines. We formulate a hybrid QoS-aware scheduling problem for concurrent traffics in intra-SHN, propose an innovative queuing model (QC-SH) based on the auction economic model of game theory to provide a fair multiple access over different communication channels/ports, and design an applicable model to implement auction game on both sides; traffic sources and the home gateway, without changing the structure of the IEEE 802.11 standard. The results of our work offer SHNs more effective data transfer between all heterogenous connected devices with optimal resource utilization, a dynamic QoS/QoE-aware traffic processing in SHN as well as an innovative model for optimizing concurrent SHN traffic scheduling with enhanced fairness strategy. Numerical results show an improvement up to 90% for network resource utilization, 77% for bandwidth, 40% for scheduling with QoS and QoE and 57% for concurrent traffic scheduling delay using our proposed solutions compared with Traditional methods