1. A
CLASSIFICATION AND COMPARISON FRAMEWORKFOR CLOUD SERVICE BROKERAGE
ARCHITECTURES
ABSTRACT: Cloud
service brokerage and related management and marketplace concepts have been
identified as key concerns for future cloud technology development and
research. Cloud service management is an important building block of cloud
architectures that can be extended to act as a broker service layer between
consumers and providers, and even to form marketplace services. We present a
3-pronged classification and comparison framework for broker platforms and
applications. A range of specific broker development concerns like
architecture, programming and quality are investigated. Based on this
framework, selected management, brokerage and marketplace solutions will be
compared, not only to demonstrate the utility of the framework, but also to
identify challenges and wider research objectives based on an identification of
cloud broker architecture concerns and technical requirements for service
brokerage solutions. Cloud architecture concerns such as commoditisation and
federation of integrated, vertical cloud stacks emerge.
2. ASSESSMENT
OF THE SUITABILITY OF FOG COMPUTING IN THE CONTEXT OF INTERNET OF THINGS
ABSTRACT: This
work performs a rigorous, comparative analysis of the fog computing paradigm
and the conventional cloud computing paradigm in the context of the Internet of
Things (IoT), by mathematically formulating the parameters and characteristics
of fog computing – one of the first attempts of its kind. With the rapid
increase in the number of Internetconnected devices, the increased demand of
real-time, low-latency services is proving to be challenging for the
traditional cloud computing framework. Also, our irreplaceable dependency on
cloud computing demands the cloud data centers (DCs) always to be up and
running which exhausts huge amount of power and yield tons of carbon dioxide
(CO2) gas. In this work, we assess the applicability of the newly proposed fog
computing paradigm to serve the demands of the latency-sensitive applications
in the context of IoT. We model the fog computing paradigm by mathematically
characterizing the fog computing network in terms of power consumption, service
latency, CO2 emission, and cost, and evaluating its performance for an
environment with high number of Internet-connected devices demanding realtime
service. A case study is performed with traffic generated from the 100 highest
populated cities being served by eight geographically distributed DCs. Results
show that as the number of applications demanding real-time service increases,
the fog computing paradigm outperforms traditional cloud computing. For an
environment with 50% applications requesting for instantaneous, real-time
services, the overall service latency for fog computing is noted to decrease by
50:09%. However, it is mentionworthy that for an environment with less percentage
of applications demanding for low-latency services, fog computing is observed
to be an overhead compared to the traditional cloud computing. Therefore, the
work shows that in the context of IoT, with high number of latency-sensitive
applications fog computing outperforms cloud computing.
3. ASSURANCE
OF SECURITY AND PRIVACY REQUIREMENTS FOR CLOUD DEPLOYMENT MODELS
ABSTRACT: Despite
of the several benefits of migrating enterprise critical assets to the Cloud,
there are challenges specifically related to security and privacy. It is
important that Cloud Users understand their security and privacy needs, based
on their specific context and select cloud model best fit to support these
needs. The literature provides works that focus on discussing security and
privacy issues for cloud systems but such works do not provide a detailed
methodological approach to elicit security and privacy requirements neither
methods to select cloud deployment models based on satisfaction of these
requirements by Cloud Service Providers. This work advances the current state
of the art towards this direction. In particular, we consider requirements engineering
concepts to elicit and analyze security and privacy requirements and their
associated mechanisms using a conceptual framework and a systematic process.
The work introduces assurance as evidence for satisfying the security and
privacy requirements in terms of completeness and reportable of security
incident through audit. This allows perspective cloud users to define their
assurance requirements so that appropriate cloud models can be selected for a
given context. To demonstrate our work, we present results from a real case
study based on the Greek National Gazette.
4. CLOUD
MESSAGE QUEUEING AND NOTIFICATION: CHALLENGES AND (BLOCKCHAIN) OPPORTUNITIES
ABSTRACT: The
current mobile app development practice, like other large-scale network-centric
software projects, is characterized by the use of event notification facilities
supporting the exchange of effective and efficient data flows between the
application’s front-end, usually located on customer’s terminal equipment, and
the back-end services available within the cloud. In order to avoid the need of
setting up the notification infrastructure from scratch for any new
application, many cloud service providers and mobile system manufacturing
companies provide cloud-based messaging solutions. Such solutions, however, are
often characterized by vulnerabilities that can be exploited to compromise the
mobile applications’ security by violating the privacy and integrity in their
operations. In this work, we analyze these issues and posit the potential for
the blockchain technology to mitigate such threats.
ABSTRACT: The
eHealth trend has spread globally. Internet of Things(IoT) devices for medical
service and pervasivePersonal Health Information (PHI) systemsplay important
roles inthe eHealth environment. A cloud-based PHIsystem appearspromising but
raises privacy and informationsecurity concerns. We propose a cloud-based
fine-grained health information access control framework for lightweight IoT
devices with data dynamics auditing and attribute revocation functions.
6. CONSISTENT
DISASTER RECOVERY FOR MICROSERVICES: THE BAC THEOREM
ABSTRACT: How
do you back up a microservice? You dump its database. But how do you back up an
entire application decomposed into microservices? In this article, we discuss
the tradeoff between the availability and consistency of a microservice-based
architecture when a backup of the entire application is being performed.
7. A
HOLISTIC APPROACH TO DISTRIBUTED DIMENSIONALITY REDUCTION OF BIG DATA
ABSTRACT: With
the exponential growth of data volume, big data have placed an unprecedented
burden on current computing infrastructure. Dimensionality reduction of big
data attracts a great deal of attention in recent years as an efficient method
to extract the core data which is smaller to store and faster to process. This
paper aims at addressing the three fundamental problems closely related to
distributed dimensionality reduction of big data, i.e. big data fusion,
dimensionality reduction algorithm and construction of distributed computing
platform. A chunk tensor method is presented to fuse the unstructured,
semi-structured and structured data as a unified model in which all
characteristics of the heterogeneous data are appropriately arranged along the
tensor orders. A Lanczos based High Order Singular Value Decomposition
algorithm is proposed to reduce dimensionality of the unified model.
Theoretical analyses of the algorithm are provided in terms of storage scheme,
convergence property and computation cost. To execute the dimensionality
reduction task, this paper employs the Transparent Computing paradigm to
construct a distributed computing platform as well as utilizes the linear
predictive model to partition the data blocks. Experimental results demonstrate
that the proposed holistic approach is efficient for distributed dimensionality
reduction of big data.
8. ARCHITECTURAL
PROTECTION OF APPLICATION PRIVACY AGAINST SOFTWARE AND PHYSICAL ATTACKS IN
UNTRUSTED CLOUD ENVIRONMENT
ABSTRACT: In
cloud computing, it is often assumed that cloud vendors are trusted; the guest
Operating System (OS) and the Virtual Machine Monitor (VMM, also called
Hypervisor) are secure. However, these assumptions are not always true in
practice and existing approaches cannot protect the data privacy of
applications when none of these parties are trusted. We investigate how to cope
with a strong threat model which is that the cloud vendors, the guest OS, or
the VMM, or both of them are malicious or untrusted, and can launch attacks
against privacy of trusted user applications. This model is relevant because
applications may be small enough to be formally verified, while the guest OS
and VMM are too complex to be formally verified. Specifically, we present the
design and analysis of an architectural solution which integrates a set of
components on-chip to protect the memory of trusted applications from potential
software and hardware based attacks from untrusted cloud providers, compromised
guest OS, or malicious VMM. Full-system performance evaluation results show
that the design only incurs 9% overhead
on average, which is a small performance price that is paid for the
substantial security gain.
9. SHAPLEY-VALUE MECHANISM FOR BANDWIDTH ON DEMAND BETWEEN DATACENTERS
ABSTRACT: Recent
studies in cloud resource allocation and pricing have focused on computing and
storage resources but not network bandwidth. Cloud users nowadays customarily
deploy services across multiple geo-distributed datacenters, with significant
interdatacenter traffic generated, paid by cloud providers to ISPs. An
effective bandwidth allocation and charging mechanism is needed between the
cloud provider and the cloud users. Existing volume based static charging
schemes lack market efficiency. This work presents the first dynamic pricing
mechanism for inter-datacenter on-demand bandwidth, via a Shapley value based
auction. Our auction is expressive enough to accept bids as a flat bandwidth
rate plus a time duration, or a data volume with a transfer deadline. We start
with an offline auction, design an optimal end-to-end traffic scheduling
approach, and exploit the Shapley value in computing payments. Our auction is
truthful, individual rational, budget balanced and approximately efficient in
social welfare. An online version of the auction follows, where decisions are
made instantly upon the arrival of each user’s realtime transmission demand. We
propose an efficient online traffic scheduling algorithm, and approximate the
offline Shapley value based payments on the fly. We validate our mechanism
design with solid theoretical analysis, as well as trace-driven simulation
studies.
