Manzoor Ahmed Khan

Game Dynamics and Cost of Learning in Heterogeneous 4G Networks

In this paper, we study game dynamics and learning schemes for heterogeneous 4G networks. We introduce a novel learning scheme called cost-to-learn that incorporates the cost to switch, the switching delay, and the cost of changing to a new action and, captures the realistic behavior of the users that we have experimented on OPNET simulations. Considering a dynamic and uncertain environment where the users and operators have only a numerical value of their own payoffs as information, we construct various heterogeneous combined fully distributed payoff and strategy reinforcement learning (CODIPAS-RL): the users try to learn their own optimal payoff and their optimal strategy simultaneously. We establish the asymptotic pseudo-trajectories as solution of differential equations. Using evolutionary game dynamics, we prove the convergence and stability properties in specific classes of dynamic robust games. We provide various numerical examples and OPNET simulations in the context network selection in wireless local area networks (WLAN) and Long Term Evolution (LTE).

Evolutionary coalitional games: design and challenges in wireless networks

The current state of the art of evolutionary coalitional game theory in wireless networking and communications is captured in this article, where solutions are discussed under their related applications. Fully distributed algorithms for global optima in network selection games are examined. Then the problem of dynamic network formation and evolutionary coalitional games in wireless networks are investigated. This article also points out the open research issues, new interests, and developments in this interdisciplinary field.

Game-Theory Based User Centric Network Selection with Media Independent Handover Services and Flow Management

Future envisions universal and uninterrupted access to information owing to the widespread use of heterogeneous wireless technologies. The integration of heterogeneous wireless technologies and existence of multi-mode terminals enable users get associated to the best available networks according to user preferences over different application specific requirements, prices and network technologies. In this paper we present the user-centric network selection decision mechanism, where negotiation between users and network operators is carried out using game-theoretic approach. We model the utility functions of users and network operators in terms of offered prices and service quality. The proposed approach builds on IEEE 802.21standard. Session Initiation Protocol(SIP) and Mobile Internet Protocol (MIPv6) based flow management solutions are given, the later approach is implemented using OPNET modeller simulator. The performance of our approachis compared with Long-term contractual approach in termsof users throughput, users’ cost, operators’ revenue and call blocking probability.

Cooperative game theoretic approach to integrated bandwidth sharing and allocation

The current trend in wireless communication networks involves the integration of different wireless access technologies into a single operator network. The possible leveraging of high deployment costs, and the possibility to increase revenue have also introduced the concept of network sharing between different operators. The problem of optimal allocation of bandwidth to multimedia applications over different wireless access networks, is augmented with the possibility of using the bandwidth of other operators who are willing to share bandwidth.We formulate the allocation of bandwidth within the operator network and distribution of excess bandwidth among operators as cooperative bargaining games. We provide distribution and allocation rules based on the Kalai-Smorodinsky Solution, and provide bandwidth offer algorithms based on these rules. We compare this integrated approach with the service and capacity based approaches in the literature.

Network level cooperation for resource allocation in future wireless networks

The increasing number of radio access technologies and the availability of multi-radio devices boost the need for novel resource allocation schemes in cellular networks. This paper uses a cooperative game theoretic approach for resource allocation at the network level, while utilizing simultaneous use of available radio interfaces at the device level. We model resource allocation management using the well known bankruptcy model and apply Kalai-Smorodinsky bargaining solution method to find a distribution rule, based on which we propose resource allocation and call admission control schemes. Performance analysis of our allocation and control schemes demonstrates significant improvements over previous approaches in terms of utilization of the available bandwidth and the number of call drops.

Stochastic Routing in Wireless Sensor Networks

We propose a new location-based stochastic routing approach that is well-suited for wireless sensor networks deployed for public safety applications such as emergency evacuations or search and rescue operations. We first introduce a new modeling and evaluation framework based on Markov chains for randomized routing. Based on this evaluation framework, we study the load balancing and routing performance aspects of i) a near-optimal solution using the complete topology information, ii) a heuristic algorithm that uses only local neighborhood information. Numerical studies using the evaluation framework show that our heuristic routing approach scales well with both network size and density, considering the combined problem of routing and load balancing.

Cooperation-based resource allocation and call admission for wireless network operators

The increasing number of radio access technologies and the availability of multi-radio devices boost the need for novel resource allocation schemes in cellular networks. This paper uses a cooperative game theoretic approach for resource allocation at the network level, while utilizing simultaneous use of available radio interfaces at the device level. We model resource allocation management using the well known bankruptcy model and apply Kalai-Smorodinsky bargaining solution method to find a distribution rule, based on which we propose resource allocation and call admission control schemes. Performance analysis of our allocation and control schemes demonstrates significant improvements over previous approaches in terms of utilization of the available bandwidth and the number of call drops. We also study the performance of proposed approach for different operator policies.

Vehicles of the Future: A Survey of Research on Safety Issues

Information and communication technologies (ICTs) have a profound impact on the current state and envisioned future of automobiles. This paper presents an overview of research on ICT-based support and assistance services for the safety of future connected vehicles. A general classification and a brief description of the focus areas for research and development in this direction are given under the titles of vehicle detection, road detection, lane detection, pedestrian detection, drowsiness detection, and collision avoidance. Following an overview and taxonomy of the reviewed research articles, a categorized literature survey of safety critical applications is presented in detail. Future research directions are also highlighted.

User Satisfaction Based Resource Allocation in Future Heterogeneous Wireless Networks

The widespread use of heterogeneous wireless network technologies and their integration with multi-mode terminals enable users to be associated to the best available networks according to user preferences and application specific requirements. We study a user-centric quality of experience based resource allocation problem with several operators, several types of users and different classes of services. We propose a framework for future short term user-operator contractual vision. We also study the equilibrium solution for the mentioned problem using a game-theoretic approach. Based on experimental measurements, we formulate the utility functions for the users and the operators. Our results are validated through OPNET simulations for different service classes including FTP, VoIP and Video streaming over Long Term Evolution (LTE), and Wireless Local Area Networks (WLAN) technologies. We also implement the IPv6 based flow management for congestion avoidance at inter-operator level, and study the performance of various splitting and non-splitting approaches.

Dynamic spectrum trade and game-theory based network selection in LTE virtualization using uniform auctioning

It is expected that in future user-centric wireless network scenario the concept of dynamic spectrum trade will provide operators with opportunities to utilize the spectrum more efficiently. Wireless market players (both incumbent and new entrants) trade the spectrum chunks on the provide, when needed basis with the spectrum broker. In this paper, we model the interaction between different stake-holders such as users, operators and spectrum brokers at different hierarchical level and investigate the equilibria. We also model the utility functions of all the stake-holders. We propose and implement the realization framework for the proposed dynamic spectrum allocation approach using Long Term Evolution (LTE) virtualization.