304 research outputs found

    Containerization in Cloud Computing: performance analysis of virtualization architectures

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    La crescente adozione del cloud è fortemente influenzata dall’emergere di tecnologie che mirano a migliorare i processi di sviluppo e deployment di applicazioni di livello enterprise. L’obiettivo di questa tesi è analizzare una di queste soluzioni, chiamata “containerization” e di valutare nel dettaglio come questa tecnologia possa essere adottata in infrastrutture cloud in alternativa a soluzioni complementari come le macchine virtuali. Fino ad oggi, il modello tradizionale “virtual machine” è stata la soluzione predominante nel mercato. L’importante differenza architetturale che i container offrono ha portato questa tecnologia ad una rapida adozione poichè migliora di molto la gestione delle risorse, la loro condivisione e garantisce significativi miglioramenti in termini di provisioning delle singole istanze. Nella tesi, verrà esaminata la “containerization” sia dal punto di vista infrastrutturale che applicativo. Per quanto riguarda il primo aspetto, verranno analizzate le performances confrontando LXD, Docker e KVM, come hypervisor dell’infrastruttura cloud OpenStack, mentre il secondo punto concerne lo sviluppo di applicazioni di livello enterprise che devono essere installate su un insieme di server distribuiti. In tal caso, abbiamo bisogno di servizi di alto livello, come l’orchestrazione. Pertanto, verranno confrontate le performances delle seguenti soluzioni: Kubernetes, Docker Swarm, Apache Mesos e Cattle

    Towards Runtime Verification via Event Stream Processing in Cloud Computing Infrastructures

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    Software bugs in cloud management systems often cause erratic behavior, hindering detection, and recovery of failures. As a consequence, the failures are not timely detected and notified, and can silently propagate through the system. To face these issues, we propose a lightweight approach to runtime verification, for monitoring and failure detection of cloud computing systems. We performed a preliminary evaluation of the proposed approach in the OpenStack cloud management platform, an “off-the-shelf” distributed system, showing that the approach can be applied with high failure detection coverage

    Design, Implementation and Experiments for Moving Target Defense Framework

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    The traditional defensive security strategy for distributed systems employs well-established defensive techniques such as; redundancy/replications, firewalls, and encryption to prevent attackers from taking control of the system. However, given sufficient time and resources, all these methods can be defeated, especially when dealing with sophisticated attacks from advanced adversaries that leverage zero-day exploits

    Enhancing Security and Robustness for SDN-Enabled Cloud Networks

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    Software-Defined Networking is an emerging network architecture which promises to solve the limitations associated with current cloud computing systems based on traditional network. The main idea behind SDN is to separate control plane from networking devices, thereby providing a centralized control layer integrable to cloud-based infrastructure. The integration of SDN and Cloud Computing brings an immense benefits to network deployment and management, however, this model still faces many critical challenges with regards to availability, scalability and security. In this study, we present a security and robustness SDN-Enabled Cloud model using OpenStack and OpenDaylight. In particular, we design and implement a security clustering-based SDN Controller for monitoring and managing cloud networking, and a hardware platform to accelerate packet processing in virtual switches. We evaluate our proposed model on a practical cloud testbed consisting of several physical and virtual nodes. The experiment results show that the SDN controller cluster significantly improve robustness for the network even in case of being attacked by abnormal network traffic; while the hardware-accelerated switches can be operated in highperformance and well-adapted to the cloud environment

    Dependability of the NFV Orchestrator: State of the Art and Research Challenges

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    © 2018 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.The introduction of network function virtualisation (NFV) represents a significant change in networking technology, which may create new opportunities in terms of cost efficiency, operations, and service provisioning. Although not explicitly stated as an objective, the dependability of the services provided using this technology should be at least as good as conventional solutions. Logical centralisation, off-the-shelf computing platforms, and increased system complexity represent new dependability challenges relative to the state of the art. The core function of the network, with respect to failure and service management, is orchestration. The failure and misoperation of the NFV orchestrator (NFVO) will have huge network-wide consequences. At the same time, NFVO is vulnerable to overload and design faults. Thus, the objective of this paper is to give a tutorial on the dependability challenges of the NFVO, and to give insight into the required future research. This paper provides necessary background information, reviews the available literature, outlines the proposed solutions, and identifies some design and research problems that must be addressed.acceptedVersio

    MACHS: Mitigating the Achilles Heel of the Cloud through High Availability and Performance-aware Solutions

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    Cloud computing is continuously growing as a business model for hosting information and communication technology applications. However, many concerns arise regarding the quality of service (QoS) offered by the cloud. One major challenge is the high availability (HA) of cloud-based applications. The key to achieving availability requirements is to develop an approach that is immune to cloud failures while minimizing the service level agreement (SLA) violations. To this end, this thesis addresses the HA of cloud-based applications from different perspectives. First, the thesis proposes a component’s HA-ware scheduler (CHASE) to manage the deployments of carrier-grade cloud applications while maximizing their HA and satisfying the QoS requirements. Second, a Stochastic Petri Net (SPN) model is proposed to capture the stochastic characteristics of cloud services and quantify the expected availability offered by an application deployment. The SPN model is then associated with an extensible policy-driven cloud scoring system that integrates other cloud challenges (i.e. green and cost concerns) with HA objectives. The proposed HA-aware solutions are extended to include a live virtual machine migration model that provides a trade-off between the migration time and the downtime while maintaining HA objective. Furthermore, the thesis proposes a generic input template for cloud simulators, GITS, to facilitate the creation of cloud scenarios while ensuring reusability, simplicity, and portability. Finally, an availability-aware CloudSim extension, ACE, is proposed. ACE extends CloudSim simulator with failure injection, computational paths, repair, failover, load balancing, and other availability-based modules

    Elastic Highly Available Cloud Computing

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    High availability and elasticity are two the cloud computing services technical features. Elasticity is a key feature of cloud computing where provisioning of resources is closely tied to the runtime demand. High availability assure that cloud applications are resilient to failures. Existing cloud solutions focus on providing both features at the level of the virtual resource through virtual machines by managing their restart, addition, and removal as needed. These existing solutions map applications to a specific design, which is not suitable for many applications especially virtualized telecommunication applications that are required to meet carrier grade standards. Carrier grade applications typically rely on the underlying platform to manage their availability by monitoring heartbeats, executing recoveries, and attempting repairs to bring the system back to normal. Migrating such applications to the cloud can be particularly challenging, especially if the elasticity policies target the application only, without considering the underlying platform contributing to its high availability (HA). In this thesis, a Network Function Virtualization (NFV) framework is introduced; the challenges and requirements of its use in mobile networks are discussed. In particular, an architecture for NFV framework entities in the virtual environment is proposed. In order to reduce signaling traffic congestion and achieve better performance, a criterion to bundle multiple functions of virtualized evolved packet-core in a single physical device or a group of adjacent devices is proposed. The analysis shows that the proposed grouping can reduce the network control traffic by 70 percent. Moreover, a comprehensive framework for the elasticity of highly available applications that considers the elastic deployment of the platform and the HA placement of the application’s components is proposed. The approach is applied to an internet protocol multimedia subsystem (IMS) application and demonstrate how, within a matter of seconds, the IMS application can be scaled up while maintaining its HA status

    CLOSURE: A cloud scientific workflow scheduling algorithm based on attack-defense game model

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    The multi-tenant coexistence service mode makes the cloud-based scientific workflow encounter the risks of being intruded. For this problem, we propose a CLoud scientific wOrkflow SchedUling algoRithm based on attack-defensE game model (CLOSURE). In the algorithm, attacks based on different operating system vulnerabilities are regarded as different “attack” strategies; and different operating system distributions in a virtual machine cluster executing the workflows are regarded as different “defense” strategies. The information of the attacker and defender is not balanced. In other words, the defender cannot obtain the information about the attacker’s strategies, while the attacker can acquire information about the defender’s strategies through a network scan. Therefore, we propose to dynamically switch the defense strategies during the workflow execution, which can weaken the network scan effects and transform the workflow security problem into an attack-defense game problem. Then, the probability distribution of the optimal mixed defense strategies can be achieved by calculating the Nash Equilibrium in the attack-defense game model. Based on this probability, diverse VMs are provisioned for workflow execution. Furthermore, a task-VM mapping algorithm based on dynamic Heterogeneous Earliest Finish Time (HEFT) is presented to accelerate the defense strategy switching and improve workflow efficiency. The experiments are conducted on both simulation and actual environment, experimental results demonstrate that compared with other algorithms, the proposed algorithm can reduce the attacker’s benefits by around 15.23%, and decrease the time costs of the algorithm by around 7.86%
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