606 research outputs found

    A Game-Theoretic Approach to Strategic Resource Allocation Mechanisms in Edge and Fog Computing

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    With the rapid growth of Internet of Things (IoT), cloud-centric application management raises questions related to quality of service for real-time applications. Fog and edge computing (FEC) provide a complement to the cloud by filling the gap between cloud and IoT. Resource management on multiple resources from distributed and administrative FEC nodes is a key challenge to ensure the quality of end-user’s experience. To improve resource utilisation and system performance, researchers have been proposed many fair allocation mechanisms for resource management. Dominant Resource Fairness (DRF), a resource allocation policy for multiple resource types, meets most of the required fair allocation characteristics. However, DRF is suitable for centralised resource allocation without considering the effects (or feedbacks) of large-scale distributed environments like multi-controller software defined networking (SDN). Nash bargaining from micro-economic theory or competitive equilibrium equal incomes (CEEI) are well suited to solving dynamic optimisation problems proposing to ‘proportionately’ share resources among distributed participants. Although CEEI’s decentralised policy guarantees load balancing for performance isolation, they are not faultproof for computation offloading. The thesis aims to propose a hybrid and fair allocation mechanism for rejuvenation of decentralised SDN controller deployment. We apply multi-agent reinforcement learning (MARL) with robustness against adversarial controllers to enable efficient priority scheduling for FEC. Motivated by software cybernetics and homeostasis, weighted DRF is generalised by applying the principles of feedback (positive or/and negative network effects) in reverse game theory (GT) to design hybrid scheduling schemes for joint multi-resource and multitask offloading/forwarding in FEC environments. In the first piece of study, monotonic scheduling for joint offloading at the federated edge is addressed by proposing truthful mechanism (algorithmic) to neutralise harmful negative and positive distributive bargain externalities respectively. The IP-DRF scheme is a MARL approach applying partition form game (PFG) to guarantee second-best Pareto optimality viii | P a g e (SBPO) in allocation of multi-resources from deterministic policy in both population and resource non-monotonicity settings. In the second study, we propose DFog-DRF scheme to address truthful fog scheduling with bottleneck fairness in fault-probable wireless hierarchical networks by applying constrained coalition formation (CCF) games to implement MARL. The multi-objective optimisation problem for fog throughput maximisation is solved via a constraint dimensionality reduction methodology using fairness constraints for efficient gateway and low-level controller’s placement. For evaluation, we develop an agent-based framework to implement fair allocation policies in distributed data centre environments. In empirical results, the deterministic policy of IP-DRF scheme provides SBPO and reduces the average execution and turnaround time by 19% and 11.52% as compared to the Nash bargaining or CEEI deterministic policy for 57,445 cloudlets in population non-monotonic settings. The processing cost of tasks shows significant improvement (6.89% and 9.03% for fixed and variable pricing) for the resource non-monotonic setting - using 38,000 cloudlets. The DFog-DRF scheme when benchmarked against asset fair (MIP) policy shows superior performance (less than 1% in time complexity) for up to 30 FEC nodes. Furthermore, empirical results using 210 mobiles and 420 applications prove the efficacy of our hybrid scheduling scheme for hierarchical clustering considering latency and network usage for throughput maximisation.Abubakar Tafawa Balewa University, Bauchi (Tetfund, Nigeria

    Conception des réseaux maillés sans fil à multiples-radios multiples-canaux

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    GĂ©nĂ©ralement, les problĂšmes de conception de rĂ©seaux consistent Ă  sĂ©lectionner les arcs et les sommets d’un graphe G de sorte que la fonction coĂ»t est optimisĂ©e et l’ensemble de contraintes impliquant les liens et les sommets dans G sont respectĂ©es. Une modification dans le critĂšre d’optimisation et/ou dans l’ensemble de contraintes mĂšne Ă  une nouvelle reprĂ©sentation d’un problĂšme diffĂ©rent. Dans cette thĂšse, nous nous intĂ©ressons au problĂšme de conception d’infrastructure de rĂ©seaux maillĂ©s sans fil (WMN- Wireless Mesh Network en Anglais) oĂč nous montrons que la conception de tels rĂ©seaux se transforme d’un problĂšme d’optimisation standard (la fonction coĂ»t est optimisĂ©e) Ă  un problĂšme d’optimisation Ă  plusieurs objectifs, pour tenir en compte de nombreux aspects, souvent contradictoires, mais nĂ©anmoins incontournables dans la rĂ©alitĂ©. Cette thĂšse, composĂ©e de trois volets, propose de nouveaux modĂšles et algorithmes pour la conception de WMNs oĂč rien n’est connu Ă  l’ avance. Le premiervolet est consacrĂ© Ă  l’optimisation simultanĂ©e de deux objectifs Ă©quitablement importants : le coĂ»t et la performance du rĂ©seau en termes de dĂ©bit. Trois modĂšles bi-objectifs qui se diffĂ©rent principalement par l’approche utilisĂ©e pour maximiser la performance du rĂ©seau sont proposĂ©s, rĂ©solus et comparĂ©s. Le deuxiĂšme volet traite le problĂšme de placement de passerelles vu son impact sur la performance et l’extensibilitĂ© du rĂ©seau. La notion de contraintes de sauts (hop constraints) est introduite dans la conception du rĂ©seau pour limiter le dĂ©lai de transmission. Un nouvel algorithme basĂ© sur une approche de groupage est proposĂ© afin de trouver les positions stratĂ©giques des passerelles qui favorisent l’extensibilitĂ© du rĂ©seau et augmentent sa performance sans augmenter considĂ©rablement le coĂ»t total de son installation. Le dernier volet adresse le problĂšme de fiabilitĂ© du rĂ©seau dans la prĂ©sence de pannes simples. PrĂ©voir l’installation des composants redondants lors de la phase de conception peut garantir des communications fiables, mais au dĂ©triment du coĂ»t et de la performance du rĂ©seau. Un nouvel algorithme, basĂ© sur l’approche thĂ©orique de dĂ©composition en oreilles afin d’installer le minimum nombre de routeurs additionnels pour tolĂ©rer les pannes simples, est dĂ©veloppĂ©. Afin de rĂ©soudre les modĂšles proposĂ©s pour des rĂ©seaux de taille rĂ©elle, un algorithme Ă©volutionnaire (mĂ©ta-heuristique), inspirĂ© de la nature, est dĂ©veloppĂ©. Finalement, les mĂ©thodes et modĂšles proposĂ©s on Ă©tĂ© Ă©valuĂ©s par des simulations empiriques et d’évĂ©nements discrets.Generally, network design problems consist of selecting links and vertices of a graph G so that a cost function is optimized and all constraints involving links and the vertices in G are met. A change in the criterion of optimization and/or the set of constraints leads to a new representation of a different problem. In this thesis, we consider the problem of designing infrastructure Wireless Mesh Networks (WMNs) where we show that the design of such networks becomes an optimization problem with multiple objectives instead of a standard optimization problem (a cost function is optimized) to take into account many aspects, often contradictory, but nevertheless essential in the reality. This thesis, composed of three parts, introduces new models and algorithms for designing WMNs from scratch. The first part is devoted to the simultaneous optimization of two equally important objectives: cost and network performance in terms of throughput. Three bi-objective models which differ mainly by the approach used to maximize network performance are proposed, solved and compared. The second part deals with the problem of gateways placement, given its impact on network performance and scalability. The concept of hop constraints is introduced into the network design to reduce the transmission delay. A novel algorithm based on a clustering approach is also proposed to find the strategic positions of gateways that support network scalability and increase its performance without significantly increasing the cost of installation. The final section addresses the problem of reliability in the presence of single failures. Allowing the installation of redundant components in the design phase can ensure reliable communications, but at the expense of cost and network performance. A new algorithm is developed based on the theoretical approach of "ear decomposition" to install the minimum number of additional routers to tolerate single failures. In order to solve the proposed models for real-size networks, an evolutionary algorithm (meta-heuristics), inspired from nature, is developed. Finally, the proposed models and methods have been evaluated through empirical and discrete events based simulations

    Gateway placement optimization in LEO satellite networks based on traffic estimation

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    ​© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Adopting satellite constellations to provide global Internet access services has recently drawn increasing attention. A Low Earth Orbit (LEO) satellite network with multiple satellites has global coverage ability, low latency and independent operation, so it can be an effective complement to terrestrial IP networks. Satellite gateways are placed on the ground and can serve as data exchange points between satellite networks and the Internet. As the placement scheme can affect the network performance, it is a fundamental problem to find appropriate sites for gateways. In this paper, a Gateway Placement Optimization (GPO) method in LEO satellite networks is proposed to solve the problem, which is modeled as a combination optimization problem. Our aim is to select the best places for gateways that can balance the traffic loads with as few gateways as possible. The constraints come from the physical links between gateways and satellites including the link interference, the satellite bandwidth and the number of satellite antennas. The gravity model is used to estimate the traffic matrix from/to gateways and satellites, and then the discrete Particle Swarm Optimization (PSO) algorithm is adopted and modified to solve this problem. Finally, the GPO method is applied to numerical tests involving real satellite constellation networks. Results indicate that our method has good performance and effectiveness.Objectius de Desenvolupament Sostenible::9 - IndĂșstria, InnovaciĂł i InfraestructuraObjectius de Desenvolupament Sostenible::9 - IndĂșstria, InnovaciĂł i Infraestructura::9.1 - Desenvolupar infraestructures fiables, sostenibles, resilients i de qualitat, incloent infraestructures regionals i transfrontereres, per tal de donar suport al desenvolupament econĂČmic i al benestar humĂ , amb especial atenciĂł a l’accĂ©s assequible i equitatiu per a totes les personesObjectius de Desenvolupament Sostenible::9 - IndĂșstria, InnovaciĂł i Infraestructura::9.c - Augmentar de forma significativa l’accĂ©s a les tecnologies de la informaciĂł i la comunicaciĂł i esforçar-se a proporcionar accĂ©s universal i assequible a Internet als paĂŻsos menys avançats a tot tardar el 2020Postprint (author's final draft

    Joint Satellite Gateway Placement and Routing for Integrated Satellite-Terrestrial Networks

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    With the increasing attention to the integrated satellite-terrestrial networks (ISTNs), the satellite gateway placement problem becomes of paramount importance. The resulting network performance may vary depending on the different design strategies. In this paper, a joint satellite gateway placement and routing strategy for the terrestrial network is proposed to minimize the overall cost of gateway deployment and traffic routing, while adhering to the average delay requirement for traffic demands. Although traffic routing and gateway placement can be solved independently, the dependence between the routing decisions for different demands makes it more realistic to solve an aggregated model instead. We develop a mixed-integer linear program (MILP) formulation for the problem. We relax the integrality constraints to achieve a linear program (LP) which reduces time-complexity at the expense of a sub-optimal solution. We further propose a variant of the proposed model to balance the load between the selected gateways.Comment: 6 pages, In Proceedings of IEEE ICC 2020. https://ieeexplore.ieee.org/document/9149175 N. Torkzaban, A. Gholami, J. S. Baras and C. Papagianni, "Joint Satellite Gateway Placement and Routing for Integrated Satellite-Terrestrial Networks," ICC 2020 - 2020 IEEE International Conference on Communications (ICC), Dublin, Ireland, 2020, pp. 1-6. doi: 10.1109/ICC40277.2020.914917

    QUALITY-OF-SERVICE PROVISIONING FOR SMART CITY APPLICATIONS USING SOFTWARE-DEFINED NETWORKING

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    In the current world, most cities have WiFi Access Points (AP) in every nook and corner. Hence upraising these cities to the status of a smart city is a more easily achievable task than before. Internet-of-Things (IoT) connections primarily use WiFi standards to form the veins of a smart city. Unfortunately, this vast potential of WiFi technology in the genesis of smart cities is somehow compromised due to its failure in meeting unique Quality-of-Service (QoS) demands of smart city applications. Out of the following QoS factors; transmission link bandwidth, packet transmission delay, jitter, and packet loss rate, not all applications call for the all of the factors at the same time. Since smart city is a pool of drastically unrelated services, this variable demand can actually be advantageous to optimize the network performance. This thesis work is an attempt to achieve one of those QoS demands, namely packet delivery latency. Three algorithms are developed to alleviate traffic load imbalance at APs so as to reduce packet forwarding delay. Software-Defined Networking (SDN) is making its way in the network world to be of great use and practicality. The algorithms make use of SDN features to control the connections to APs in order to achieve the delay requirements of smart city services. Real hardware devices are used to imitate a real-life scenario of citywide coverage consisting of WiFi devices and APs that are currently available in the market with neither of those having any additional requirements such as support for specific roaming protocol, running a software agent or sending probe packets. Extensive hardware experimentation proves the efficacy of the proposed algorithms

    Gateway Placement Optimization in Wireless Mesh Networks With QoS Constraints

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