Enhancing cooperation in wireless networks using different concepts of game theory

PhDOptimizing radio resource within a network and across cooperating heterogeneous networks is the focus of this thesis. Cooperation in a multi-network environment is tackled by investigating network selection mechanisms. These play an important role in ensuring quality of service for users in a multi-network environment. Churning of mobile users from one service provider to another is already common when people change contracts and in a heterogeneous communication environment, where mobile users have freedom to choose the best wireless service-real time selection is expected to become common feature. This real time selection impacts both the technical and the economic aspects of wireless network operations. Next generation wireless networks will enable a dynamic environment whereby the nodes of the same or even different network operator can interact and cooperate to improve their performance. Cooperation has emerged as a novel communication paradigm that can yield tremendous performance gains from the physical layer all the way up to the application layer. Game theory and in particular coalitional game theory is a highly suited mathematical tool for modelling cooperation between wireless networks and is investigated in this thesis. In this thesis, the churning behaviour of wireless service users is modelled by using evolutionary game theory in the context of WLAN access points and WiMAX networks. This approach illustrates how to improve the user perceived QoS in heterogeneous networks using a two-layered optimization. The top layer views the problem of prediction of the network that would be chosen by a user where the criteria are offered bit rate, price, mobility support and reputation. At the second level, conditional on the strategies chosen by the users, the network provider hypothetically, reconfigures the network, subject to the network constraints of bandwidth and acceptable SNR and optimizes the network coverage to support users who would otherwise not be serviced adequately. This forms an iterative cycle until a solution that optimizes the user satisfaction subject to the adjustments that the network provider can make to mitigate the binding constraints, is found and applied to the real network. The evolutionary equilibrium, which is used to 3 compute the average number of users choosing each wireless service, is taken as the solution. This thesis also proposes a fair and practical cooperation framework in which the base stations belonging to the same network provider cooperate, to serve each other‘s customers. How this cooperation can potentially increase their aggregate payoffs through efficient utilization of resources is shown for the case of dynamic frequency allocation. This cooperation framework needs to intelligently determine the cooperating partner and provide a rational basis for sharing aggregate payoff between the cooperative partners for the stability of the coalition. The optimum cooperation strategy, which involves the allocations of the channels to mobile customers, can be obtained as solutions of linear programming optimizations

An Overview of Multi-Attribute Decision Making (MADM) Vertical Handover Using Systematic Mapping

The evolution of infotainment industries yet the advancement of cellular gadgets such as smartphones, tablets, and laptop had increased the request on cellular traffic demands. As a result, a Heterogeneous Wireless Network (HWN) has been introduced to fulfil users requests in having seamless mobility and better Quality of Services (QoS) for the users. A lot of research works have been done in order to provide a seamless connection to the users. Even though a lot of methods have been proposed, a Multi-Attribute Decision Making (MADM) has been seemed like a promising way due to its ability to evaluate many attributes simultaneously. Previously, many reviews based on MADM methods in a Heterogeneous Wireless Network provides a details review which required researchers time in order to determine the possible potential areas to be explored. Therefore, in this study, we present an overview of the MADM method in performing vertical handover via a systematic mapping method. This will enable future researchers to identify the trends and research opportunities within this area. This mapping study analysed 30 papers. Results from the study show eight main potential research issues can be explored by researchers, including normalisation, criteria weighting, ranking abnormality, network selection, and performance comparison between MADM algorithms, network selection for a group of calls, mobility patterns and handover triggering

Genetic Algorithm for Vertical Handover (GAfVH)in a Heterogeneous networks

The fifth generation (5G) wireless system will deal with the growing demand of new multimedia and broadband application. The 5G network architecture is based on heterogeneous Radio Access Technologies (RATs). In such implementation the Vertical handover is a key issue. Up till now, systems are using simple mechanisms to make handover decision, based on the evaluation of the Received Signal Strength (RSS). In some cases these mechanisms are not Efficient.This paper presents a new vertical handover algorithm based on Genetic Algorithm (GAfVH). It aims to reduce the number of unnecessary handovers, and optimizes the system performance. We compare our simulation results to the Received Signal Strength (RSS) based method. The results show that the number of handovers decreases. Moreover, we demonstrate that the network selection result can differ from an application to another

Employing Unmanned Aerial Vehicles for Improving Handoff using Cooperative Game Theory

Heterogeneous wireless networks that are used for seamless mobility are expected to face prominent problems in future 5G cellular networks. Due to their proper flexibility and adaptable preparation, remote-controlled Unmanned Aerial Vehicles (UAVs) could assist heterogeneous wireless communication. However, the key challenges of current UAV-assisted communications consist in having appropriate accessibility over wireless networks via mobile devices with an acceptable Quality of Service (QoS) grounded on the users' preferences. To this end, we propose a novel method based on cooperative game theory to select the best UAV during handover process and optimize handover among UAVs by decreasing the (i) end-to-end delay, (ii) handover latency and (iii) signaling overheads. Moreover, the standard design of Software Defined Network (SDN) with Media Independent Handover (MIH) is used as forwarding switches in order to obtain seamless mobility. Numerical results derived from the real data are provided to illustrate the effectiveness of the proposed approach in terms of number of handovers, cost and delay

Network Selection Problems - QoE vs QoS Who is the Winner?

In network selection problem (NSP), there are now two schools of thought. There are those who think using QoE (Quality of Experience) is the best yardstick to measure the suitability of a Candidate Network (CN) to handover to. On the other hand, Quality of Service (QoS) is also advocated as the solution for network selection problems. In this article, a comprehensive framework that supports effective and efficient network selection is presented. The framework   attempts to provide a holistic solution to network selection problem that is achieved by combining both of the QoS and QoE measures.   Using this hybrid solution the best qualities in both methods are combined to overcome issues of the network selection problem According to ITU-R (International Telecommunications Union – Radio Standardization Sector), a 4G network is defined as having peak data rates of 100Mb/s for mobile nodes with speed up to 250 km/hr and 1Gb/s for mobile nodes moving at pedestrian speed. Based on this definition, it is safe to say that mobile nodes that can go from pedestrian speed to speed of up to 250 km/hr will be the norm in future. This indicates that the MN’s mobility will be highly dynamic. In particular, this article addresses the issue of network selection for high speed Mobile Nodes (MN) in 4G networks. The framework presented in this article also discusses how the QoS value collected from CNs can be fine-tuned to better reflect an MN’s current mobility scenario

Context-aware multi-attribute decision multi - attribute decision making for radio access technology selection in ultra dense network

Ultra Dense Network (UDN) is the extreme densification of heterogeneous Radio Access Technology (RAT) that is deployed closely in coordinated or uncoordinated manner. The densification of RAT forms an overlapping zone of signal coverage leading to the frequent service handovers among the RAT, thus degrading overall system performance. The current RAT selection approach is biased towards network-centric criteria pertaining to signal strength. However, the paradigm shift from network-centric to user-centric approach necessitates a multi-criteria selection process, with methodology relating to both network and user preferences in the context of future generation networks. Hence, an effective selection approach is required to avoid unnecessary handovers in RAT. The main aim of this study is to propose the Context-aware Multiattribute decision making for RAT (CMRAT) selection for investigating the need to choose a new RAT and further determine the best amongst the available methods. The CMRAT consists of two mechanisms, namely the Context-aware Analytical Hierarchy Process (CAHP) and Context-aware Technique for Order Preference by Similarity to an Ideal Solution (CTOPSIS). The CAHP mechanism measures the need to switch from the current RAT, while CTOPSIS aids in decision making to choose the best target RAT. A series of experimental studies were conducted to validate the effectiveness of CMRAT for achieving improved system performance. The investigation utilises shopping mall and urban dense network scenarios to evaluate the performance of RAT selection through simulation. The findings demonstrated that the CMRAT approach reduces delay and the number of handovers leading to an improvement of throughput and packet delivery ratio when compared to that of the commonly used A2A4-RSRQ approach. The CMRAT approach is effective in the RAT selection within UDN environment, thus supporting heterogeneous RAT deployment in future 5G networks. With context-aware selection, the user-centric feature is also emphasized

A Genetic Algorithm-based Framework for Soft Handoff Optimization in Wireless Networks

In this paper, a genetic algorithm (GA)-based approach is used to evaluate the probability of successful handoff in heterogeneous wireless networks (HWNs) so as to increase capacity and network performance. The traditional handoff schemes are prone to ping pong and corner effects and developing an optimized handoff scheme for seamless, faster, and less power consuming handoff decision is challenging. The GA scheme can effectively optimize soft handoff decision by selecting the best fit network for the mobile terminal (MT) considering quality of service (QoS) requirements, network parameters and user’s preference in terms of cost of different attachment points for the MT. The robustness and ability to determine global optima for any function using crossover and mutation operations makes GA a promising solution. The developed optimization framework was simulated in Matrix Laboratory (MATLAB) software using MATLAB’s optima tool and results show that an optimal MT attachment point is the one with the highest handoff success probability value which determines direction for successful handoff in HWN environment. The system maintained a 90%  with 4 channels and more while a 75% was obtained even at high traffic intensity

An intelligent path management in heterogeneous vehicular networks

Achieving reliable connectivity in heterogeneous vehicular networks is a challenging task, owing to rapid topological changes and unpredictable vehicle speeds. As vehicular communication demands continue to evolve, multipath connectivity is emerging as an important tool, which promises to enhance network interoperability and reliability. Given the limited coverage area of serving access technologies, frequent disconnections are to be expected as the vehicle moves. To ensure seamless communication in dynamic vehicular environments, an intelligent path management algorithm for Multipath TCP (MPTCP) has been proposed. The algorithm utilizes a network selection mechanism based on Fuzzy Analytic Hierarchy Process (FAHP), which dynamically assigns the most appropriate underlying network for each running application. The selection process takes into account multiple factors, such as path quality, vehicle mobility, and service characteristics. In contrast to existing solutions, our proposed method offers a dynamic and comprehensive approach to network selection that is tailored to the specific needs of each service to ensure that it is always paired with the optimal access technology. The results of the evaluation demonstrate that the proposed method is highly effective in maintaining service continuity during vertical handover. By tailoring the network selection to the specific needs of each application, our path manager is able to ensure optimal connectivity and performance, even in challenging vehicular environments, delivering a better user experience, with more reliable connections, and smoother data transfers.FCT - Fundação para a Ciência e a Tecnologia(PD/BDE/150506/2019