A Game-Theoretic Based QoS-Aware Capacity Management for Real-Time EdgeIoT Applications

More and more real-time IoT applications such as smart cities or autonomous vehicles require big data analytics with reduced latencies. However, data streams produced from distributed sensing devices may not suffice to be processed traditionally in the remote cloud due to: (i) longer Wide Area Network (WAN) latencies and (ii) limited resources held by a single Cloud. To solve this problem, a novel Software-Defined Network (SDN) based InterCloud architecture is presented for mobile edge computing environments, known as EdgeIoT. An adaptive resource capacity management approach is proposed to employ a policy-based QoS control framework using principles in coalition games with externalities. To optimise resource capacity policy, the proposed QoS management technique solves, adaptively, a lexicographic ordering bi-criteria Coalition Structure Generation (CSG) problem. It is an onerous task to guarantee in a deterministic way that a real-time EdgeIoT application satisfies low latency requirement specified in Service Level Agreements (SLA). CloudSim 4.0 toolkit is used to simulate an SDN-based InterCloud scenario, and the empirical results suggest that the proposed approach can adapt, from an operational perspective, to ensure low latency QoS for real-time EdgeIoT application instances

QoS-Aware Resource Management in SDN-Based InterClouds: A Software Cybernetics Perspective

Software Defined Networking (SDN) paradigm is introducing novel approaches for many unresolved issues of networking. These new outlooks are imperative in emerging scenarios where user requirements keep growing, the required bandwidth keeps increasing, and so does the variety of applications (e.g. Big data analytics) that suggest the network plays a more prominent role. As such, our research aims to provide a novel adaptive (self-tuning) resource management technique in SDN-based InterCloud environments. A quality of service (QoS) policy control framework is presented by modelling QoS-aware resource management as an adaptive control problem, and using principles in coalition games with externalities or partition form games (PFGs) as control mechanism. This on-going work outlines a proposed dynamic programming and anytime approach (Integer partition based) to solve the multi-criteria optimisation problem of a Markov decision process (MDP) model for system dynamics in SDN-based InterClouds

Modern software cybernetics: new trends

Software cybernetics research is to apply a variety of techniques from cybernetics research to software engineering research. For more than fifteen years since 2001, there has been a dramatic increase in work relating to software cybernetics. From cybernetics viewpoint, the work is mainly on the first-order level, namely, the software under observation and control. Beyond the first-order cybernetics, the software, developers/users, and running environments influence each other and thus create feedback to form more complicated systems. We classify software cybernetics as Software Cybernetics I based on the first-order cybernetics, and as Software Cybernetics II based on the higher order cybernetics. This paper provides a review of the literature on software cybernetics, particularly focusing on the transition from Software Cybernetics I to Software Cybernetics II. The results of the survey indicate that some new research areas such as Internet of Things, big data, cloud computing, cyber-physical systems, and even creative computing are related to Software Cybernetics II. The paper identifies the relationships between the techniques of Software Cybernetics II applied and the new research areas to which they have been applied, formulates research problems and challenges of software cybernetics with the application of principles of Phase II of software cybernetics; identifies and highlights new research trends of software cybernetic for further research

Modern software cybernetics: New trends

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Software cybernetics research is to apply a variety of techniques from cybernetics research to software engineering research. For more than fifteen years since 2001, there has been a dramatic increase in work relating to software cybernetics. From cybernetics viewpoint, the work is mainly on the first-order level, namely, the software under observation and control. Beyond the first-order cybernetics, the software, developers/users, and running environments influence each other and thus create feedback to form more complicated systems. We classify software cybernetics as Software Cybernetics I based on the first-order cybernetics, and as Software Cybernetics II based on the higher order cybernetics. This paper provides a review of the literature on software cybernetics, particularly focusing on the transition from Software Cybernetics I to Software Cybernetics II. The results of the survey indicate that some new research areas such as Internet of Things, big data, cloud computing, cyber-physical systems, and even creative computing are related to Software Cybernetics II. The paper identifies the relationships between the techniques of Software Cybernetics II applied and the new research areas to which they have been applied, formulates research problems and challenges of software cybernetics with the application of principles of Phase II of software cybernetics; identifies and highlights new research trends of software cybernetic for further research

Coordination model for the self-regulated activity of software-defined networks

graficas, tablasEn esta tesis se estudian, adaptan y aplican dos prometedoras áreas de investigación influyentes en la automatización de Redes de Datos: las Redes definidas por software (Software Definid Network - SDN) y Procesamiento de señales en grafos (Graph Signal Processing -GSP). Este documento presenta un conjunto de estrategias, soportadas por la teoría de procesamiento de señales en grafos, para la autorregulación del comportamiento ante eventos de anormalidad en una red definida por software (SDN) y para la coordinación entre el conjunto de procesos que interactúan en la reprogramación de la Red Definida por Software para lograr un estado funcional acorde a parámetros de normalidad para la red. Las contribuciones y hallazgos más relevantes de esta tesis son los siguientes: 0) Se establece un puente referencial de aplicación entre las áreas de investigación SDN y GSP; 1) se propone e implementa un monitor multicapa, basado en la teoría de procesamiento de señales en grafos que explota las características inherentes a las Redes Definidas por Software (SDN); 2) se propone e implementa una estrategia de autorregulación del direccionamiento de tráfico en una SDN ante la presencia de anomalías, basado en la técnica de aprendizaje por refuerzo (Reinforcement Learning – RL) y en el procesamiento de señales en grafos (GSP); 3) Se propone e implementa una técnica de coordinación de las actividades inherentes a los procesos de adaptación sobre las SDN; 4) se presenta un esquema de conectividad de las herramientas de desarrollo de software que actualmente son utilizadas en procesos de automatización de redes de datos. (Texto tomado de la fuente)In this thesis, two promising research areas that are influential in the automation of Data Networks are studied, adapted and applied: Software Defined Networks (SDN) and Graph Signal Processing (GSP). This document presents a set of strategies, supported by the theory of signal processing in graphs, for the self-regulation of behavior in presence of abnormality events in a network and for the coordination between the set of processes that interact in the reprogramming of the Software Defined Network to achieve a functional state according to normality parameters for the network. The most relevant contributions and findings of this thesis are the following: 0) A referential application bridge is established between the SDN and GSP research areas 1) A multilayer monitor is proposed and implemented, based on the theory of signal processing in graphs that it exploits the characteristics inherent to Software Defined Networks (SDN); 2) a self-regulation strategy for traffic routing in an SDN in the presence of anomalies is proposed and implemented, based on the reinforcement learning technique (Reinforcement Learning - RL) and on graph signal processing (GSP). 3) A coordination technique for the activities inherent to the adaptation processes on SDN is proposed and implemented. 4) a connectivity scheme of the software development tools that are currently used in data network automation processes is presented.DoctoradoDoctor en IngenieríaAutoRedes de Datos y Redes IndustrialesEléctrica, Electrónica, Automatización Y Telecomunicacione

Delivery, distribution and prediction of multimedia contents in software-defined networks

Orientador: Varese Salvador TimoteoTese (doutorado) - Universidade Estadual de Campinas, Faculdade de TecnologiaResumo: Nos últimos anos, aplicações e serviços multimídia, tais como para o acesso e compartilhamento de conteúdos de áudio e vídeo ou para realização de jogos online, dentre outras, tornaram-se extremamente populares. Por outro lado, esses novos serviços e aplicações tornaram o fluxo de tráfego de rede, além de mais intenso, mais detalhado e complexo, exigindo abordagens específicas para comunicações multimídia. Diante desse cenário, este trabalho propõe e explora, enquanto recursos de um gateway multimídia no âmbito de Redes Definidas por Software (SDN) OpenFlow, algumas abordagens que objetivam aprimorar comunicações multimídia no que se refere ao encaminhamento, à distribuição e à predição de seus conteúdos ao longo de rede. Para esse propósito, no âmbito de um gateway multimídia em SDN, os seguintes aspectos são especialmente discutidos neste trabalho: (I) identificação, classificação e encaminhamento diferenciado de fluxos de tráfego multimídia; (II) encaminhamento por fluxos com suporte à Qualidade de Serviço (QoS); (III) cache de conteúdos multimídia; e, (IV) predição de conteúdos multimídia. Nesse contexto, para efeitos de experimentação e avaliação acerca das abordagens empregadas neste trabalho, um ambiente de emulação e um ambiente de simulação são utilizados para a obtenção de resultados experimentais. Em linhas gerais, os resultados obtidos mostram que tais abordagens, enquanto recursos de um gateway multimídia no âmbito de SDNs OpenFlow, são capazes de fornecer recursos para aprimorar comunicações multimídia ao longo da rede, nesse caso, com ênfase no encaminhamento, na distribuição e na predição de conteúdos multimídiaAbstract: In the last few years, multimedia applications and services, such as for multimedia sharing services for audio and video contents, and for online gaming, among others, are becoming more and more popular. On the other hand, these multimedia applications and services increase the network traffic load and make the traffic profiles more detailed and complex, requiring the use of specific approaches for multimedia communications. In this scenario, this work proposes and explores, as resources of a multimedia gateway in the context of OpenFlow Software-Defined Networks (SDN), some approaches and resources that aim to enhance multimedia communications over the network, with focus on multimedia routing, multimedia distribution and multimedia content prediction. For this purpose, in the context of a multimedia gateway in OpenFlow SDN, the following aspects are especially considered and discussed in this work: (I) identification, classification and differentiated routing of multimedia traffic flows; (II) per-flow routing with Quality of Service (QoS) support; (III) multimedia content caching; and, (IV) multimedia content prediction. In this context, for experimentation and evaluation purposes of the approaches proposed in this work, an emulation environment and a simulation environment are used to obtain experimental results. In summary, the obtained results show that the approaches proposed in this work, as resources of a multimedia gateway in OpenFlow SDN, are able to provide resources to enhance multimedia communications over the network, in this case, with emphasis on multimedia routing, multimedia distribution and multimedia content predictionDoutoradoSistemas de Informação e ComunicaçãoDoutor em TecnologiaCAPE

A network control application enabling Software-Defined Quality of Service

The constant growth in IT as well as the increase of users and services requirements are making communication networking more and more complex to manage. This is why there has been the need to look for new approaches. One very promising solution is Software Defined Networking (SDN) that decouples the data and control planes, having one centralized controller for the network. This gives chances to control and manage the network as desired, thus opening many new possibilities. In this work we chose to exploit SDN to enable QoS control, starting from existing tools (Floodlight) and making modifications in order to better exploit their potential. A new network control application for end-to-end QoS provisioning is built on top of Floodlight and validated in an emulated SDN environment

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

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