1,721,285 research outputs found
Coupling energy efficiency and quality for consolidation of cloud workloads
No full textEfficient usage of IT equipment in Data Centers requires modulating their power-consumption according to the actual workload. The most effective strategy to this aim consists in consolidating as many applications as possible on the smallest number of servers, so that idle devices can be shut down or put in low-power states. Usually, this process is driven by computing and networking resources requested by each application (e.g., CPU and RAM) and applies a certain degree of overcommitment, assuming that such resources are not fully used continuously. However, this approach is critical with real workload patterns, which usually change over time; as a matter of fact, consolidation in real scenarios often leads to either low efficiency or violations of Quality of Service (QoS) constraints, depending on the level of overcommitment. In this paper, we investigate a novel consolidation strategy based on an enhanced system model for the Infrastructure-as-a-Service cloud paradigm, which targets a better trade-off between Energy Efficiency and Quality of Service. We explicitly target modular cloud applications, which design is split into multiple components deployed in Virtual Machine (VM)s or containers. Our consolidation strategy allows to “freeze” parts of the application which are not currently used, making them available when requested with minimal latency. This improves energy saving with respect to other approaches, especially when idle VMs are present for backup or redundancy purposes, without degrading the service level. We compare multiple heuristics available in Optaplanner to solve our consolidation problem, and investigate improvements with respect to a more traditional approach. Our evaluation includes both simulations and experimentation in a real test-bed. The comparison shows that the Late Acceptance algorithm on average finds better solutions than other alternatives and energy efficiency improves up to 40% with respect to more conventional strategies, with deterioration of QoS indexes below 1%
Cloud Applications Consolidation through Context Information and Heuristic Optimization
No full textResource consolidation has been proposed as an effective mechanism to save energy in data centers. Several algorithms have been developed for this purpose, which use the minimal number of servers and network switches, and power off unused equipment. Consolidation algorithms usually take into account static service constraints (Central Processing Unit CPU, Random Access Memory RAM, disk, bandwidth), but do not consider dynamic context information, as CPU utilization and the specific role of each Virtual Machines (VMs) in the running application (e.g., core component, backup replica, member of a pool of workers for load balancing).In this paper, we describe and evaluate a novel heuristic based consolidation strategy that explicitly considers context information. Our approach avoids running idle VMs that are pre-provisioned for availability and redundancy purposes, hence pursuing a better linear relationship between power consumption and actual computation than other existing algorithms. We demonstrate through simulations, by comparing different heuristics, the optimal trade-off between service level and energy efficiency achieved by our approach
Monitoring Network Flows in Containerized Environments
No full textWith the progressive implementation of digital services over virtualized infrastructures and smart devices, the inspection of network traffic becomes more challenging than ever, because of the difficulty to run legacy cybersecurity tools in novel cloud models and computing paradigms. The main issues concern i) the portability of the service across heterogeneous public and private infrastructures, that usually lack hardware and software acceleration for efficient packet processing, and ii) the difficulty to integrate monolithic appliances in modular and agile containerized environments. In this Chapter, we investigate the usage of the extended Berkeley Packet Filter (eBPF) for effective and efficient packet inspection in virtualized environments. Our preliminary implementation demonstrates that we can achieve the same performance as well-known packet inspection tools, but with far less resource consumption. This motivates further research work to extend the capability of our framework and to integrate it in Kubernetes
A novel cyber-security framework leveraging programmable capabilities in digital services
No full textThe introduction of new computing and networking paradigms, which leverage virtualization and service-oriented architectures, has brought far more agility than ever in the creation and concatenation of digital services. Yet it raises new security and privacy concerns that cannot be properly tackled by existing tools and models. In this paper, we briefly review the main characteristics of emerging digital services, point out open cyber-security challenges, and discuss the need to include cyber-security programmable capabilities in every digital component. We also describe a novel framework for managing such functions and implement multiple security services for complex business chains
An architecture to manage security operations for digital service chains
No full textEvolving business models are progressively pushing for increasing digitalization of existing and novel processes. The ICT industry is already addressing this need by massive introduction of virtualization paradigms and tight integration with the physical environment, which allow the creation of multi-domain and complex business service chains. Emerging technologies undoubtedly bring more agility in service deployment and operation but also break traditional security models, which have not been conceived for dynamic and multi-tenancy environments. In this paper, we briefly elaborate on existing gaps and research challenges towards advanced assurance and protection of trustworthy and reliable business chains spanning multiple administrative domains and heterogeneous infrastructures. We consolidate our analysis in a reference architecture, which includes all functional elements to effectively tackle the dynamic and agile nature of emerging ICT paradigms
Energy-Aware Consolidation Scheme for Data Center Cloud Applications
No full textThe consolidation of resources is one of the most efficient strategies to reduce the power consumption in data centers. Various algorithms have been proposed in order to reduce the total number of required servers and network devices. The practice developed in response to the problem of server sprawl, a situation in which multiple, under-utilized servers (and/or network devices) take up more space and consume more resources than the ones justified by their workload; with the effect to power off unused equipment. Generally, consolidation mechanisms consider different parameters related to the services neglecting the specific function of the Virtual Machines (VMs) in the application framework (e.g., core component, backup replica, member of a set of workers for load balancing). In this work, we develop a new consolidation algorithm that takes into account the particular function of each VM with the aim to apply power saving mechanisms without compromising the desired service level. The results of the simulations show that it is possible to obtain significant energy savings. In particular, we show, with different heuristics, the optimal trade-off between service level and power efficiency achieved by the proposed model
A network-centric architecture for building the cloud continuum
No full textThe growing interest in distributed, context-aware and data-sensitive applications is pushing the evolution of computing infrastructures from centralized to distributed models, which could effectively tackle the execution of complex software frameworks over geographical scale. The concept of cloud continuum that extends computing infrastructures beyond the data center boundary will require new architectural paradigms that overcome the evident limitations intrinsic in mere cloud federation and that enable effective and efficient interaction between the cloud and the physical environment. In this paper, we discuss why and how telecommunication networks could be the most effective infrastructure to create a distributed, pervasive, carrier-grade cloud continuum, by acting as the core federation paradigm for the dynamic and flexible composition of data centers, networks and IoT platforms
Exploiting novel software development paradigms to increase the sustainability of data centers
No full textThe application of effective energy management strategies in data centers is often hindered by the substantial conict between the interests of cloud users and infrastructure owners. As a matter of fact, cloud users require that the service level they are paying for is tightly met, whereas data center owners try to cut down their operational expenses. In this paper, we propose a novel consolidation algorithm that exploits emerging software development paradigms. Our approach enables cloud users to indicate their willingness to apply energy saving mechanisms to some of their virtual resources, hence giving infrastructure managers the ability to apply more efficient workload consolidation and to switch their hardware to very low-power states. The result is an optimal trade-off between energy consumption and performance
Green and Heuristics-Based Consolidation Scheme for Data Center Cloud Applications
No full textThe consolidation of resources is one of the most efficient strategies to reduce the power consumption in data centers. Various algorithms have been proposed in order to reduce the total number of required servers and network devices. The practice developed in response to the problem of server sprawl, a situation in which multiple, under-utilized servers (and/or network devices) take up more space and consume more resources than can be justified by their workload; with the effect to power off unused equipment. Generally, consolidation mechanisms consider different parameters related to the services neglecting the specific function of the Virtual Machines (VMs) in the application framework (e.g., core component, backup replica, member of a set of workers for load balancing). In this work, we developed a new consolidation algorithm that takes into account the particular function of each VM with the aim to apply power saving mechanisms without compromising the desired service level. The results of the simulations show that it is possible to obtain significant values of energy saving. In particular, we show, with different heuristics, the optimal trade-off between service level and power efficiency achieved by the proposed model
Data Log Management for Cyber-Security Programmability of Cloud Services and Applications
No full textIn last years, the security appliance is becoming a more important and critical challenge considering the growing complexity and diversification of cyber-attacks. The current solutions are often too cumbersome to be run in virtual services and Internet of Things (IoT) devices. Therefore, it is neces- sary to evolve to a more cooperative models, which collect security-related data from a large set of heterogeneous sources for centralized analysis and correlation.
In this paper, we outline a flexible abstraction layer for access to secu- rity context. It is conceived to program and gather data from lightweight inspection and enforcement hooks deployed in cloud applications and IoT devices. We provide a description of its implementation, by reviewing the main software components and their role.
Finally, we test this abstraction layer with a performance evaluation of a Proof of Concept (PoC) implementation with the aim to evaluate the effectiveness to collect data / logs from virtual services and IoT to enable a centralized security analysis
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