1,721,406 research outputs found
Mobile cloud networking: Lessons learnt, open research directions, and industrial innovation opportunities
No full textThis keynote speech has the ambition of overviewing some primary lessons learnt and most promising directions for future research/innovation activities in the area of Mobile Cloud Networking (MCN). In the following, the MCN term is specifically used to indicate the exploitation of cloud resources and infrastructures (possibly distributed and federated) to sustain and provision mobility-enabled services to mobile devices, with significant advantages in terms of both cost/investment reduction for mobile infrastructure providers and additional innovative (functional and non-functional) features generated by infrastructure virtualization. Let me note that this definition does not include other potential forms of «mobile clouds» that can combine the innovation directions of mobility and cloud, e.g., exploiting richer and richer mobile devices as cloud-like virtual resources, for instance in the so-called vehicular clouds [1]. The latter approaches are considered out of the scope of this paper and presentation
Cyber Physical Sensors and Actuators for Privacy- and Cost-Aware Optimization of User-Generated Content Provisioning
Full text linkNowadays there is growing interest in evolving the distributed sensors concept from the more traditional one of enabling technology to monitor the surrounding physical environment towards Cyber Physical Systems (CPS) sensors and actuators , that is, as a suitable tool to measure/influence the cyber activity of possibly worldwide communities of users (e.g., any geotagged operation leaving a cyber footprint and any cyber physical incentive to stimulate activity as in crowdsensing). To leverage this novel perspective, we propose a framework to integrate at best multilayer CPS sensors and actuators as the basis for autonomic management operations on both physical and cyber worlds. In this paper the specific application domain target is peer-to-peer content sharing based on social identities and relationships, but we claim that the proposed CPS framework is of general applicability. In particular, our original middleware solution adopts CPS actuators to move users' content temporarily from smart home environments to high-performance cloud resources to minimize the access time of a dynamically selected quota of contents. Then, based on social network sensors and connectivity/networking ones hosted at lightweight domestic Web servers, our CPS actuators can originally and dynamically move content back from the cloud to smart homes when appropriate, in order to both retain full ownership of user-generated content and reduce cloud hosting costs
Guest editorial for the PMC special section on selected papers from ICDCN 2017
No full textThe special section includes three extended versions of selected papers from the 18th edition of the International
Conference on Distributed Computing and Networking (ICDCN), held in Hyderabad, India during January 4–7, 2017. These
three articles are the result of the full and regular reviewing process of a selected set of ICDCN’17 papers that were invited
for possible fast-track publication in Pervasive and Mobile Computing based on strong positive reviews from the reviewers
and their relevance to the journal. During the process, the papers have undergone substantial changes from the conference
version, with additional technical details and results, and towards addressing the suggestions by the reviewers and guest
editors of the journal special section. We believe this revision process has substantially improved the completeness and the
quality of these works. We believe that these selected papers will interest a sizable section of the readers of this journal,
by providing a fresh and up-to-date overview of some recent research results about reliability and emerging applications of
mobile pervasive computing systems, from different layers (middleware and application perspectives) and from different
international viewpoints. Below, we briefly outline how they advance the state-of-the-art in topics that fall in the scope of
this journal
Cloud Continuum Digital Twins: Architectures of Solution, Open Technical Challenges, and Lessons Learned
No full textInteraction and Behaviour Evaluation for Smart Homes: Data Collection and Analytics in the ScaledHome Project
No full textThe smart home concept can significantly benefit from predictive models that take proactive management operations on home actuators, based on users’ behavior evaluation. In this paper, we use a small-scale physical model, the ScaledHome-2 testbed, to experiment with the evolution of measurements in a suburban home under different environmental scenarios. We start from the observation that, for a home to become smart, in addition to IoT sensors and actuators, we also need a predictive model of how actions taken by inhabitants and home actuators affect the internal environment of the home, reflected in the sensor readings. In this paper, we propose a technique to create such a predictive model through machine learning in various simulated weather scenarios. This paper also contributes to the literature in the field by quantitatively comparing several machine learning algorithms (K-nearest neighbor, regression trees, Support Vector Machine regression, and Long Short Term Memory deep neural networks) in their ability to create accurate and generalizable predictive models for smart homes
Middleware-Layer Quality-Aware Collaborative Re-casting of Live Multimedia in Multi-hop Spontaneous Networks
No full textThe growing availability of connectivity/computing/storage resources on smartphones and tablets together with the trend toward frequent and voluntary collaborations in user communities (such as in experience/status sharing and shopping recommending applications) are enabling novel scenarios of high relevance for the user mass market. In particular, we claim that the social-aware sharing of under-utilized resources in physical proximity will be of paramount importance in future heterogeneous wireless networks, i.e., spontaneous networks (SNs), where neighbors opportunistically and temporarily cooperate for service provisioning. In this paper we propose a novel middleware for multi-hop SNs, by specifically focusing on the hard technical challenges of supporting collaborative re-casting of live multimedia flows with dynamic quality adaptation. Our middleware prototype originally (1) adopts a middleware-level multimedia redistribution approach with cross-layer visibility of underlying SNs, (2) dynamically exploits collaborating nodes to monitor and tailor end-to-end streams by splitting them in sub-segments in a completely decentralized way, and (3) performs quality/resource-aware management decisions with limited resource consumption at collaborating peers. The reported experimental results demonstrate that, notwithstanding the middleware-layer approach and the challenging characteristics of multi-hop SNs, our solution effectively supports redistribution of tailored multimedia content with limited overhead
Decentralised Learning in Federated Deployment Environments
Full text linkDecentralised learning is attracting more and more interest because it embodies the principles of data minimisation and focused data collection, while favouring the transparency of purpose specification (i.e., the objective for which a model is built). Cloud-centric-only processing and deep learning are no longer strict necessities to train high-fidelity models; edge devices can actively participate in the decentralised learning process by exchanging meta-level information in place of raw data, thus paving the way for better privacy guarantees. In addition, these new possibilities can relieve the network backbone from unnecessary data transfer and allow it to meet strict low-latency requirements by leveraging on-device model inference. This survey provides a detailed and up-to-date overview of the most recent contributions available in the state-of-the-art decentralised learning literature. In particular, it originally provides the reader audience with a clear presentation of the peculiarities of federated settings, with a novel taxonomy of decentralised learning approaches, and with a detailed description of the most relevant and specific system-level contributions of the surveyed solutions for privacy, communication efficiency, non-IlDness, device heterogeneity, and poisoning defense
Federated Learning Algorithms with Heterogeneous Data Distributions: An Empirical Evaluation
No full textWelcome message from the IEEE mobile cloud 2015 TPC co-chairs
No full textOn behalf of the whole Technical Program Committee, it is our pleasure
to welcome you to the 3rd IEEE International Conference on Mobile
Cloud Computing, Services, and Engineering (IEEE Mobile Cloud
2015), held in San Francisco, CA, USA. We hope that you will fully enjoy
and benefit from the papers in this year's program, which we believe
represent a fresh and vivid overview of the different hot research subareas
associated with mobile cloud computing nowadays.
This year we received 53 paper submissions from 21 different countries.
We selected 15 as full papers and 10 as short papers. Due to timing
constraints for oral presentations, we accepted 10 high-quality papers as
short papers (with a shorter presentation time slot). Papers are distributed
over 8 sessions (plus a dedicated poster session), with no parallel presentation;
the sessions cover state-of-the-art topics and areas of strong
international relevance, spanning from mobile cloud computing infrastructures
and platforms to mobile cloud data services and security,
from efficient scalability and performance optimization of mobile cloud
to service models and practical experiences of application deployment.
We really hope that these sessions will provide good opportunity for the
IEEE Mobile Cloud 2015 attendees, especially students and young researchers,
to interact with one another in informative and informal settings,
with adequate and not too restricted time allocated for sessions in
order to promote in-depth technical interactions, exchange of opinions,
and networking
Special track on reliable software technologies and communication middleware (RST)
No full textGuest Editorial for this special track on reliable software technologies and communication middleware (RST)
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