3,719 research outputs found
Understanding the Computational Requirements of Virtualized Baseband Units using a Programmable Cloud Radio Access Network Testbed
Cloud Radio Access Network (C-RAN) is emerging as a transformative
architecture for the next generation of mobile cellular networks. In C-RAN, the
Baseband Unit (BBU) is decoupled from the Base Station (BS) and consolidated in
a centralized processing center. While the potential benefits of C-RAN have
been studied extensively from the theoretical perspective, there are only a few
works that address the system implementation issues and characterize the
computational requirements of the virtualized BBU. In this paper, a
programmable C-RAN testbed is presented where the BBU is virtualized using the
OpenAirInterface (OAI) software platform, and the eNodeB and User Equipment
(UEs) are implemented using USRP boards. Extensive experiments have been
performed in a FDD downlink LTE emulation system to characterize the
performance and computing resource consumption of the BBU under various
conditions. It is shown that the processing time and CPU utilization of the BBU
increase with the channel resources and with the Modulation and Coding Scheme
(MCS) index, and that the CPU utilization percentage can be well approximated
as a linear increasing function of the maximum downlink data rate. These
results provide real-world insights into the characteristics of the BBU in
terms of computing resource and power consumption, which may serve as inputs
for the design of efficient resource-provisioning and allocation strategies in
C-RAN systems.Comment: In Proceedings of the IEEE International Conference on Autonomic
Computing (ICAC), July 201
Trusted Computing and Secure Virtualization in Cloud Computing
Large-scale deployment and use of cloud computing in industry
is accompanied and in the same time hampered by concerns regarding protection of
data handled by cloud computing providers. One of the consequences of moving
data processing and storage off company premises is that organizations have
less control over their infrastructure. As a result, cloud service (CS) clients
must trust that the CS provider is able to protect their data and
infrastructure from both external and internal attacks. Currently however, such
trust can only rely on organizational processes declared by the CS
provider and can not be remotely verified and validated by an external party.
Enabling the CS client to verify the integrity of the host where the
virtual machine instance will run, as well as to ensure that the virtual
machine image has not been tampered with, are some steps towards building
trust in the CS provider. Having the tools to perform such
verifications prior to the launch of the VM instance allows the CS
clients to decide in runtime whether certain data should be stored- or calculations
should be made on the VM instance offered by the CS provider.
This thesis combines three components -- trusted computing, virtualization technology
and cloud computing platforms -- to address issues of trust and
security in public cloud computing environments. Of the three components,
virtualization technology has had the longest evolution and is a cornerstone
for the realization of cloud computing. Trusted computing is a recent
industry initiative that aims to implement the root of trust in a hardware
component, the trusted platform module. The initiative has been formalized
in a set of specifications and is currently at version 1.2. Cloud computing
platforms pool virtualized computing, storage and network resources in
order to serve a large number of customers customers that use a multi-tenant
multiplexing model to offer on-demand self-service over broad network.
Open source cloud computing platforms are, similar to trusted computing, a
fairly recent technology in active development.
The issue of trust in public cloud environments is addressed
by examining the state of the art within cloud computing security and
subsequently addressing the issues of establishing trust in the launch of a
generic virtual machine in a public cloud environment. As a result, the thesis
proposes a trusted launch protocol that allows CS clients
to verify and ensure the integrity of the VM instance at launch time, as
well as the integrity of the host where the VM instance is launched. The protocol
relies on the use of Trusted Platform Module (TPM) for key generation and data protection.
The TPM also plays an essential part in the integrity attestation of the
VM instance host. Along with a theoretical, platform-agnostic protocol,
the thesis also describes a detailed implementation design of the protocol
using the OpenStack cloud computing platform.
In order the verify the implementability of the proposed protocol, a prototype
implementation has built using a distributed deployment of OpenStack.
While the protocol covers only the trusted launch procedure using generic
virtual machine images, it presents a step aimed to contribute towards
the creation of a secure and trusted public cloud computing environment
Grid Infrastructure for Domain Decomposition Methods in Computational ElectroMagnetics
The accurate and efficient solution of Maxwell's equation is the problem addressed by the scientific discipline called Computational ElectroMagnetics (CEM). Many macroscopic phenomena in a great number of fields are governed by this set of differential equations: electronic, geophysics, medical and biomedical technologies, virtual EM prototyping, besides the traditional antenna and propagation applications. Therefore, many efforts are focussed on the development of new and more efficient approach to solve Maxwell's equation. The interest in CEM applications is growing on. Several problems, hard to figure out few years ago, can now be easily addressed thanks to the reliability and flexibility of new technologies, together with the increased computational power. This technology evolution opens the possibility to address large and complex tasks. Many of these applications aim to simulate the electromagnetic behavior, for example in terms of input impedance and radiation pattern in antenna problems, or Radar Cross Section for scattering applications. Instead, problems, which solution requires high accuracy, need to implement full wave analysis techniques, e.g., virtual prototyping context, where the objective is to obtain reliable simulations in order to minimize measurement number, and as consequence their cost. Besides, other tasks require the analysis of complete structures (that include an high number of details) by directly simulating a CAD Model. This approach allows to relieve researcher of the burden of removing useless details, while maintaining the original complexity and taking into account all details. Unfortunately, this reduction implies: (a) high computational effort, due to the increased number of degrees of freedom, and (b) worsening of spectral properties of the linear system during complex analysis. The above considerations underline the needs to identify appropriate information technologies that ease solution achievement and fasten required elaborations. The authors analysis and expertise infer that Grid Computing techniques can be very useful to these purposes. Grids appear mainly in high performance computing environments. In this context, hundreds of off-the-shelf nodes are linked together and work in parallel to solve problems, that, previously, could be addressed sequentially or by using supercomputers. Grid Computing is a technique developed to elaborate enormous amounts of data and enables large-scale resource sharing to solve problem by exploiting distributed scenarios. The main advantage of Grid is due to parallel computing, indeed if a problem can be split in smaller tasks, that can be executed independently, its solution calculation fasten up considerably. To exploit this advantage, it is necessary to identify a technique able to split original electromagnetic task into a set of smaller subproblems. The Domain Decomposition (DD) technique, based on the block generation algorithm introduced in Matekovits et al. (2007) and Francavilla et al. (2011), perfectly addresses our requirements (see Section 3.4 for details). In this chapter, a Grid Computing infrastructure is presented. This architecture allows parallel block execution by distributing tasks to nodes that belong to the Grid. The set of nodes is composed by physical machines and virtualized ones. This feature enables great flexibility and increase available computational power. Furthermore, the presence of virtual nodes allows a full and efficient Grid usage, indeed the presented architecture can be used by different users that run different applications
Will SDN be part of 5G?
For many, this is no longer a valid question and the case is considered
settled with SDN/NFV (Software Defined Networking/Network Function
Virtualization) providing the inevitable innovation enablers solving many
outstanding management issues regarding 5G. However, given the monumental task
of softwarization of radio access network (RAN) while 5G is just around the
corner and some companies have started unveiling their 5G equipment already,
the concern is very realistic that we may only see some point solutions
involving SDN technology instead of a fully SDN-enabled RAN. This survey paper
identifies all important obstacles in the way and looks at the state of the art
of the relevant solutions. This survey is different from the previous surveys
on SDN-based RAN as it focuses on the salient problems and discusses solutions
proposed within and outside SDN literature. Our main focus is on fronthaul,
backward compatibility, supposedly disruptive nature of SDN deployment,
business cases and monetization of SDN related upgrades, latency of general
purpose processors (GPP), and additional security vulnerabilities,
softwarization brings along to the RAN. We have also provided a summary of the
architectural developments in SDN-based RAN landscape as not all work can be
covered under the focused issues. This paper provides a comprehensive survey on
the state of the art of SDN-based RAN and clearly points out the gaps in the
technology.Comment: 33 pages, 10 figure
Clustering Algorithms for Scale-free Networks and Applications to Cloud Resource Management
In this paper we introduce algorithms for the construction of scale-free
networks and for clustering around the nerve centers, nodes with a high
connectivity in a scale-free networks. We argue that such overlay networks
could support self-organization in a complex system like a cloud computing
infrastructure and allow the implementation of optimal resource management
policies.Comment: 14 pages, 8 Figurs, Journa
On Evaluating Commercial Cloud Services: A Systematic Review
Background: Cloud Computing is increasingly booming in industry with many
competing providers and services. Accordingly, evaluation of commercial Cloud
services is necessary. However, the existing evaluation studies are relatively
chaotic. There exists tremendous confusion and gap between practices and theory
about Cloud services evaluation. Aim: To facilitate relieving the
aforementioned chaos, this work aims to synthesize the existing evaluation
implementations to outline the state-of-the-practice and also identify research
opportunities in Cloud services evaluation. Method: Based on a conceptual
evaluation model comprising six steps, the Systematic Literature Review (SLR)
method was employed to collect relevant evidence to investigate the Cloud
services evaluation step by step. Results: This SLR identified 82 relevant
evaluation studies. The overall data collected from these studies essentially
represent the current practical landscape of implementing Cloud services
evaluation, and in turn can be reused to facilitate future evaluation work.
Conclusions: Evaluation of commercial Cloud services has become a world-wide
research topic. Some of the findings of this SLR identify several research gaps
in the area of Cloud services evaluation (e.g., the Elasticity and Security
evaluation of commercial Cloud services could be a long-term challenge), while
some other findings suggest the trend of applying commercial Cloud services
(e.g., compared with PaaS, IaaS seems more suitable for customers and is
particularly important in industry). This SLR study itself also confirms some
previous experiences and reveals new Evidence-Based Software Engineering (EBSE)
lessons
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