VirtFogSim: A parallel toolbox for dynamic energy-delay performance testing and optimization of 5G Mobile-Fog-Cloud virtualized platforms

It is expected that the pervasive deployment of multi-tier 5G-supported Mobile-Fog-Cloudtechnological computing platforms will constitute an effective means to support the real-time execution of future Internet applications by resource- and energy-limited mobile devices. Increasing interest in this emerging networking-computing technology demands the optimization and performance evaluation of several parts of the underlying infrastructures. However, field trials are challenging due to their operational costs, and in every case, the obtained results could be difficult to repeat and customize. These emergingMobile-Fog-Cloud ecosystems still lack, indeed, customizable software tools for the performance simulation of their computing-networking building blocks. Motivated by these considerations, in this contribution, we present VirtFogSim. It is aMATLAB-supported software toolbox that allows the dynamic joint optimization and tracking of the energy and delay performance of Mobile-Fog-Cloud systems for the execution of applications described by general Directed Application Graphs (DAGs). In a nutshell, the main peculiar features of the proposed VirtFogSim toolbox are that: (i) it allows the joint dynamic energy-aware optimization of the placement of the application tasks and the allocation of the needed computing-networking resources under hard constraints on acceptable overall execution times, (ii) it allows the repeatable and customizable simulation of the resulting energy-delay performance of the overall system; (iii) it allows the dynamic tracking of the performed resource allocation under time-varying operational environments, as those typically featuring mobile applications; (iv) it is equipped with a user-friendly Graphic User Interface (GUI) that supports a number of graphic formats for data rendering, and (v) itsMATLAB code is optimized for running atop multi-core parallel execution platforms. To check both the actual optimization and scalability capabilities of the VirtFogSim toolbox, a number of experimental setups featuring different use cases and operational environments are simulated, and their performances are compared

가상 네트워크의 자원 할당, 가격 결정 및 고장 관리

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2013. 8. 서승우.네트워크 가상화는 물리적 네트워크의 공유 자원들을 복수 개의 가상 네트워크들에 동적으로 할당할 수 있게 해주는 기술이다. 자원 할당의 유연성과 가상 네트워크들 사이의 독립성 때문에, 네트워크 가상화는 네트워크 테스트베드를 설계하기 위한 기반 기술로써 주로 활용되어 왔을 뿐만 아니라, 인터넷의 다양화를 지원하기 위한 비용 효율 높은 해결책으로써 여겨지기 시작했다. 서비스에 따라 계층화된 인터넷을 설계하기 위한 하나의 수단으로써, 네트워크 가상화는 여전히 해결해야 할 많은 도전 과제들을 가지고 있다. 이 학위 논문은 가상 네트워크 환경에서 중요한 몇 가지 새로운 연구 주제들을 제시하고, 그에 대한 효과적인 해법들을 제안한다. 첫 번째로, 가상 네트워크의 다양한 QoS 요구사항을 만족시킬 수 있는 네트워크 최적 분할 방법을 제안한다. QoS와 대역폭 제한 조건을 고려하여 가상 네트워크 분할 문제를 최적화 문제로 모형화하고, 문제의 구조적 복잡성을 해결하기 위해 최단 경로 라우팅에 기반한 휴리스틱을 제안한다. 실제 인터넷 환경을 고려한 대규모 실험을 통해, 제안한 휴리스틱의 효율성과 확장성을 입증한다. 다음으로, 가상 네트워크에서 차등 접속 서비스를 위한 경제성 분석 모델을 제시한다. 먼저 사용자 가입 변동 모형이 한 값으로 수렴하기 위한 충분 조건을 유도하고, 이러한 조건 하에서 인터넷 서비스 제공자의 수익을 최대화할 수 있는 최적의 가격 결정 방법 및 대역폭 분할 방법을 찾는다. 수치 실험을 통해, 적절한 가격 결정과 대역폭 분할이 이루어진다는 가정 하에서 차등화 서비스가 단일 서비스보다 더 높은 수익성을 나타낼 수 있음을 증명한다. 마지막으로, 가상 네트워크 간 트래픽 전환을 통한 빠르고 효과적인 고장 회복 기술을 개발한다. 가상 네트워크의 구조적 특성을 활용한 고장 회복 기술을 이용하면, 모든 링크에 대한 백업 경로가 항상 존재하도록 미리 토폴로지를 설계해야 할 필요가 없고, 각 라우터에서 그 경로들에 대한 계산을 미리 해 놓을 필요가 없다. 그럼에도 불구하고, 제안한 고장 회복 방법은 기존의 기술들과 같은 좋은 성능을 보인다. 이 학위 논문은 가상 네트워크를 기반으로 하는 인터넷 환경에서 발생할 수 있는 중요한 문제들을 다루고자 한다. 이 논문에서 제안하는 분석 모델 및 실험 결과들은 현재 인터넷의 한계를 극복하고, 미래 인터넷 아키텍처를 설계하기 위한 유용한 지침을 제공할 것이다.Network virtualization is an emerging technology that enables the dynamic partitioning of a shared physical network infrastructure into multiple virtual networks. Because of its flexibility in resource allocation and independency among virtual networks, the network virtualization technology has not only been mainly deployed to build a testbed network, but also has come to be regarded as a cost-effective solution for diversifying the Internet. As a means of building the multi-layered Internet, network virtualization still faces a number of challenging issues that need to be addressed. This dissertation deals with several important research topics and provides effective solutions in network virtualization environment. First, I focus on the optimal partitioning of finite substrate resources for satisfying the diverse QoS requirements of virtual networks. I formulate virtual network partitioning problem as a mixed integer multi-commodity flow problem. Then, to tackle the structural complexity of the problem, I propose a simple heuristic based on shortest path routing algorithm. By conducting large-scale network experiments, I verify the efficiency and scalability of the heuristic. Next, I propose an economic model for tiered access service in virtual networks in order to remedy the deficiency of the existing tiered service schemes. I first derive a sufficient condition for stability of user subscription dynamics, and find the optimal pricing and capacity partitioning by addressing the revenue maximization problem of the tiered access service in a network virtualization environment. Numerical results show that the tiered service can be more profitable than the non-tiered service under proper pricing and capacity partitioning conditions. Last, I develop a fast and effective failure recovery mechanism through inter-virtual network traffic switching in virtual networks. The proposed failure recovery mechanism neither has topological constraints for the existence of backup paths, nor requires the pre-computation of them, but nevertheless guarantees as fast recovery as the existing failure recovery methods. This dissertation aims to address important issues in the virtual network-based Internet. I believe that the analysis and results in this dissertation will provide useful guidelines to improve the Internet.1 Introduction 1.1 Background and Motivation 1.2 Contributions and Outline of the Dissertation 2 Effective Partitioning for Service Level Differentiation in Virtual Networks 2.1 Introduction 2.2 Related Work 2.3 Model and Assumption 2.3.1 Business Model 2.3.2 Network Model 2.3.3 Traffic Demands 2.3.4 QoS Metric 2.4 Formulation 2.4.1 Objective 2.4.2 Substrate Partitioning Problem 2.4.3 Decomposition 2.5 Heuristic 2.6 Evaluation 2.6.1 Small Network Experiment 2.6.2 Large Network Experiment 2.7 Summary 3 Optimal Pricing and Capacity Partitioning for Tiered Access Service in Virtual Networks 3.1 Introduction 3.2 Motivating Example 3.3 A Tiered Service Model 3.3.1 Network Virtualization Environment 3.3.2 Effective Access Rate 3.3.3 Valuation Parameter and User Utility 3.3.4 User Subscription and the ISP Revenue 3.4 Non-tiered Service Analysis 3.4.1 User Subscription Dynamics 3.4.2 Optimal Pricing for Maximizing the ISP Revenue 3.5 Tiered Service Analysis 3.5.1 User Subscription Dynamics 3.5.2 Convergence of the User Subscription Dynamics 3.5.3 Optimal Pricing for Maximizing the ISP Revenue 3.6 Numerical Results 3.6.1 Non-tiered Service Example 3.6.2 Tiered Service Example 3.7 Related Work and Discussion 3.8 Summary 4 Inter-Virtual Network Traffic Switching for Fast Failure Recovery 4.1 Introduction 4.2 Background 4.3 Preliminaries 4.3.1 Virtual Network Model 4.3.2 Design Goals 4.3.3 Business Models and Switching Policy Agreement 4.3.4 Other Considerations 4.4 Failure Recovery based on Traffic Switching 4.4.1 Inter-VN Traffic Switching 4.4.2 Failure Recovery Process 4.5 Numerical Analysis 4.5.1 Delay 4.5.2 Congestion probability 4.6 Summary 5 Conclusion A Proofs of Lemmas A.1 Proof of Lemma 2 A.2 Proof of Lemma 3Docto

Effects of a Trust Mechanism on Complex Adaptive Supply Networks: An Agent-Based Social Simulation Study

This paper models a supply network as a complex adaptive system (CAS), in which firms or agents interact with one another and adapt themselves. And it applies agent-based social simulation (ABSS), a research method of simulating social systems under the CAS paradigm, to observe emergent outcomes. The main purposes of this paper are to consider a social factor, trust, in modeling the agents\' behavioral decision-makings and, through the simulation studies, to examine the intermediate self-organizing processes and the resulting macro-level system behaviors. The simulations results reveal symmetrical trust levels between two trading agents, based on which the degree of trust relationship in each pair of trading agents as well as the resulting collaboration patterns in the entire supply network emerge. Also, it is shown that agents\' decision-making behavior based on the trust relationship can contribute to the reduction in the variability of inventory levels. This result can be explained by the fact that mutual trust relationship based on the past experiences of trading diminishes an agent\'s uncertainties about the trustworthiness of its trading partners and thereby tends to stabilize its inventory levels.Complex Adaptive System, Agent-Based Social Simulation, Supply Network, Trust

Efficient sharing mechanisms for virtualized multi-tenant heterogeneous networks

The explosion in data traffic, the physical resource constraints, and the insufficient financial incentives for deploying 5G networks, stress the need for a paradigm shift in network upgrades. Typically, operators are also the service providers, which charge the end users with low and flat tariffs, independently of the service enjoyed. A fine-scale management of the network resources is needed, both for optimizing costs and resource utilization, as well as for enabling new synergies among network owners and third-parties. In particular, operators could open their networks to third parties by means of fine-scale sharing agreements over customized networks for enhanced service provision, in exchange for an adequate return of investment for upgrading their infrastructures. The main objective of this thesis is to study the potential of fine-scale resource management and sharing mechanisms for enhancing service provision and for contributing to a sustainable road to 5G. More precisely, the state-of-the-art architectures and technologies for network programmability and scalability are studied, together with a novel paradigm for supporting service diversity and fine-scale sharing. We review the limits of conventional networks, we extend existing standardization efforts and define an enhanced architecture for enabling 5G networks' features (e.g., network-wide centralization and programmability). The potential of the proposed architecture is assessed in terms of flexible sharing and enhanced service provision, while the advantages of alternative business models are studied in terms of additional profits to the operators. We first study the data rate improvement achievable by means of spectrum and infrastructure sharing among operators and evaluate the profit increase justified by a better service provided. We present a scheme based on coalitional game theory for assessing the capability of accommodating more service requests when a cooperative approach is adopted, and for studying the conditions for beneficial sharing among coalitions of operators. Results show that: i) collaboration can be beneficial also in case of unbalanced cost redistribution within coalitions; ii) coalitions of equal-sized operators provide better profit opportunities and require lower tariffs. The second kind of sharing interaction that we consider is the one between operators and third-party service providers, in the form of fine-scale provision of customized portions of the network resources. We define a policy-based admission control mechanism, whose performance is compared with reference strategies. The proposed mechanism is based on auction theory and computes the optimal admission policy at a reduced complexity for different traffic loads and allocation frequencies. Because next-generation services include delay-critical services, we compare the admission control performances of conventional approaches with the proposed one, which proves to offer near real-time service provision and reduced complexity. Besides, it guarantees high revenues and low expenditures in exchange for negligible losses in terms of fairness towards service providers. To conclude, we study the case where adaptable timescales are adopted for the policy-based admission control, in order to promptly guarantee service requirements over traffic fluctuations. In order to reduce complexity, we consider the offline pre­computation of admission strategies with respect to reference network conditions, then we study the extension to unexplored conditions by means of computationally efficient methodologies. Performance is compared for different admission strategies by means of a proof of concept on real network traces. Results show that the proposed strategy provides a tradeoff in complexity and performance with respect to reference strategies, while reducing resource utilization and requirements on network awareness.La explosion del trafico de datos, los recursos limitados y la falta de incentivos para el desarrollo de 5G evidencian la necesidad de un cambio de paradigma en la gestion de las redes actuales. Los operadores de red suelen ser tambien proveedores de servicios, cobrando tarifas bajas y planas, independientemente del servicio ofrecido. Se necesita una gestion de recursos precisa para optimizar su utilizacion, y para permitir nuevas sinergias entre operadores y proveedores de servicios. Concretamente, los operadores podrian abrir sus redes a terceros compartiendolas de forma flexible y personalizada para mejorar la calidad de servicio a cambio de aumentar sus ganancias como incentivo para mejorar sus infraestructuras. El objetivo principal de esta tesis es estudiar el potencial de los mecanismos de gestion y comparticion de recursos a pequei\a escala para trazar un camino sostenible hacia el 5G. En concreto, se estudian las arquitecturas y tecnolog fas mas avanzadas de "programabilidad" y escalabilidad de las redes, junto a un nuevo paradigma para la diversificacion de servicios y la comparticion de recursos. Revisamos los limites de las redes convencionales, ampliamos los esfuerzos de estandarizacion existentes y definimos una arquitectura para habilitar la centralizacion y la programabilidad en toda la red. La arquitectura propuesta se evalua en terminos de flexibilidad en la comparticion de recursos, y de mejora en la prestacion de servicios, mientras que las ventajas de un modelo de negocio alternativo se estudian en terminos de ganancia para los operadores. En primer lugar, estudiamos el aumento en la tasa de datos gracias a un uso compartido del espectro y de las infraestructuras, y evaluamos la mejora en las ganancias de los operadores. Presentamos un esquema de admision basado en la teoria de juegos para acomodar mas solicitudes de servicio cuando se adopta un enfoque cooperativo, y para estudiar las condiciones para que la reparticion de recursos sea conveniente entre coaliciones de operadores. Los resultados ensei\an que: i) la colaboracion puede ser favorable tambien en caso de una redistribucion desigual de los costes en cada coalicion; ii) las coaliciones de operadores de igual tamai\o ofrecen mejores ganancias y requieren tarifas mas bajas. El segundo tipo de comparticion que consideramos se da entre operadores de red y proveedores de servicios, en forma de provision de recursos personalizada ya pequei\a escala. Definimos un mecanismo de control de trafico basado en polfticas de admision, cuyo rendimiento se compara con estrategias de referencia. El mecanismo propuesto se basa en la teoria de subastas y calcula la politica de admision optima con una complejidad reducida para diferentes cargas de trafico y tasa de asignacion. Con particular atencion a servicios 5G de baja latencia, comparamos las prestaciones de estrategias convencionales para el control de admision con las del metodo propuesto, que proporciona: i) un suministro de servicios casi en tiempo real; ii) una complejidad reducida; iii) unos ingresos elevados; y iv) unos gastos reducidos, a cambio de unas perdidas insignificantes en terminos de imparcialidad hacia los proveedores de servicios. Para concluir, estudiamos el caso en el que se adoptan escalas de tiempo adaptables para el control de admision, con el fin de garantizar puntualmente los requisitos de servicio bajo diferentes condiciones de trafico. Para reducir la complejidad, consideramos el calculo previo de las estrategias de admision con respecto a condiciones de red de referenda, adaptables a condiciones inexploradas por medio de metodologias computacionalmente eficientes. Se compara el rendimiento de diferentes estrategias de admision sobre trazas de trafico real. Los resultados muestran que la estrategia propuesta equilibra complejidad y ganancias, mientras se reduce la utilizacion de recursos y la necesidad de conocer el estado exacto de la red.Postprint (published version

Calidad de servicio en computación en la nube: técnicas de modelado y sus aplicaciones

Recent years have seen the massive migration of enterprise applications to the cloud. One of the challenges posed by cloud applications is Quality-of-Service (QoS) management, which is the problem of allocating resources to the application to guarantee a service level along dimensions such as performance, availability and reliability. This paper aims at supporting research in this area by providing a survey of the state of the art of QoS modeling approaches suitable for cloud systems. We also review and classify their early application to some decision-making problems arising in cloud QoS management

Cloud Workload Allocation Approaches for Quality of Service Guarantee and Cybersecurity Risk Management

It has become a dominant trend in industry to adopt cloud computing --thanks to its unique advantages in flexibility, scalability, elasticity and cost efficiency -- for providing online cloud services over the Internet using large-scale data centers. In the meantime, the relentless increase in demand for affordable and high-quality cloud-based services, for individuals and businesses, has led to tremendously high power consumption and operating expense and thus has posed pressing challenges on cloud service providers in finding efficient resource allocation policies. Allowing several services or Virtual Machines (VMs) to commonly share the cloud\u27s infrastructure enables cloud providers to optimize resource usage, power consumption, and operating expense. However, servers sharing among users and VMs causes performance degradation and results in cybersecurity risks. Consequently, how to develop efficient and effective resource management policies to make the appropriate decisions to optimize the trade-offs among resource usage, service quality, and cybersecurity loss plays a vital role in the sustainable future of cloud computing. In this dissertation, we focus on cloud workload allocation problems for resource optimization subject to Quality of Service (QoS) guarantee and cybersecurity risk constraints. To facilitate our research, we first develop a cloud computing prototype that we utilize to empirically validate the performance of different proposed cloud resource management schemes under a close to practical, but also isolated and well-controlled, environment. We then focus our research on the resource management policies for real-time cloud services with QoS guarantee. Based on queuing model with reneging, we establish and formally prove a series of fundamental principles, between service timing characteristics and their resource demands, and based on which we develop several novel resource management algorithms that statically guarantee the QoS requirements for cloud users. We then study the problem of mitigating cybersecurity risk and loss in cloud data centers via cloud resource management. We employ game theory to model the VM-to-VM interdependent cybersecurity risks in cloud clusters. We then conduct a thorough analysis based on our game-theory-based model and develop several algorithms for cybersecurity risk management. Specifically, we start our cybersecurity research from a simple case with only two types of VMs and next extend it to a more general case with an arbitrary number of VM types. Our intensive numerical and experimental results show that our proposed algorithms can significantly outperform the existing methodologies for large-scale cloud data centers in terms of resource usage, cybersecurity loss, and computational effectiveness