AMCC 2016 - CALL FOR CHAPTER PROPOSALS Advances in Mobile Cloud Computing and Big Data under the 5G Era

CALL FOR CHAPTER PROPOSALS
Advances in Mobile Cloud Computing and Big Data under the 5G Era
A book edited by:
Constandinos X. Mavromoustakis, University of Nicosia, Cyprus
George Mastorakis, Technological Educational Institute of Crete, Greece
Ciprian Dobre, University Politehnica of Bucharest, Romania
Proposal Submission Deadline: May 30th, 2015
To be published in the "Studies in Big Data" book series, Springer (2016)
http://www.cs.unic.ac.cy/cmavrom/CFC_MobCloudBigDa...
Introduction
The ongoing growth of mobile communication networks, along with the launch of new mobile devices (e.g. smart phones and tablets) and the increased demand for additional data network traffic, pave the way to the need of a fully interconnected Information Society, supporting the ubiquitous provision of multiple services (e.g. multimedia and data services) to mobile users, located in urban and rural areas. In addition, the new trends of mobile networks that enable the interconnection of new types of devices along with their services (i.e. household appliances) rise the need for adopting new solutions and network architectures to support the provision of novel services and applications. Furthermore, the huge increase of the number of mobile devices with growing requirements for multiple services provision, open the way towards new communication standards that will be adopted by the year 2020 for the deployment of the future mobile networking systems. In this context, the fifth generation (5G) wireless communication systems are envisaged to lead to higher-level mobile users' experiences, significantly supporting increased connection rates (i.e. peak data rates of 10 Gb/s), while it will also contribute to host novel services and applications. With the emergence of ultra-fast 5G mobile networks and highly-featured smartphones, tablets, and wearable computing devices (e.g., with always growing sensing capabilities), the prerequisites will be met for bringing cloud computing to the mobile domain. While first commercial products are restricted to the sharing of files, contacts, etc. among different devices, more sophisticated applications still have to be developed. In addition, it is undoubtedly true that Big Data is as a result of the 2.5 quintillion bytes of data generated each day with pervasive, wearable as well as handheld devices composed by configurations such as machine-to-machine connectivity and the related applications hosting online/mobile social networks. The multi-source collection of data brings into the researchers attention issues that should be investigated like novel access mechanisms and multi-source Big Data Collecting techniques, as well as the distributed Big Data Storing methodologies and finally Intra/Inter Big Data processing.
Objective
This book aims to become a state-of-the-art reference, discussing progress made, as well as prompting future directions on the theories, practices, standards and strategies that are related to the Mobile Cloud computing (MCC) and Big Data and their association with the emerging 5G mobile networks. The book will target methodologies aiming to take Big Data to the Cloud and the Mobile Cloud (through opportunistically formed networks), and be able to process Real-Time Streaming Events on-the-move. The need of high velocity processing and low latency response will be one of the major characteristics of the aims and objectives of the sections related in the book. Another aim is to discuss methods and practices to improve multi-source Big Data collecting techniques as well as the integration of resources' availability through the 3As (Anywhere, Anything, Anytime) paradigm using the 5G access technologies comprising of distributed Big Data storing methodologies and processing.
Topics
Chapters should be written in a manner readable for both specialists and non-specialists.
Recommended topic areas include, but are not limited to:
Big Data and Internet of Things advances and challenges with impact on Cloud Computing
Analysis of the various aspects for Big Data storage services
Context-aware data intensive applications; Context modelling and context management
Event-driven architectures and services
Cloud data storage solutions for context-aware data intensive applications
Self-aware Internet of Things
Software engineering for self-adaptive Internet of things
Automated tools for development, deployment and supervision of IoT devices and services
Self-matchmaking of IoT & Internet of services; Modelling environmental context and user behaviour
Semantic IoT and self-adaptation to context; Autonomous IoT clouds. Self-provisioning of IoT services
Control theory in IoT, and decision making mechanisms
Event-Condition-Action rules and prediction models applied to the IoT
Performance monitoring, diagnostics and self-healing in IoT
Autonomic security and dependency management; Robust and trustable IoT systems
Self-organizing network protocols and ad-hoc routing mechanisms
Autonomic experience in IoT applications such as smart home, transport, healthcare, retailer
Autonomicity and self-management in M2M communication systems and networks
Modeling, measurement, and simulation of multi-networks of autonomic IoT applications, such as energy sensing and management, vehicle control, mobile devices, and emergency management
Internet of Things and the smart city vision
Spatial, temporal, and contextual city data representation, reasoning, search, exploration, services, analysis, and optimization
City data life cycles, including de-noising, cleansing, anonymization and privacy protection, fusion, interpretation, lifting, aggregation, and correlation; Ubiquitous and pervasive city systems
Scalable processing of distributed, networked, dynamic, or heterogeneous city data
Social aspects of information systems, such as citizens as sensors, urban dynamics, and citizen participation in public life and decision-making
Innovative applications in public safety, government, commerce, transportation, among others
Foundations and Principles of Technologies for Big Data and IoT (emphasis on smart environments):
Pervasive Computing and Computational Technologies for Big Data and IoT
Internet of Things, Architecture, Components, RFID, NFC, Sensors and Actuator Technologies
Inter-operability and Inter-cooperative Protocols, Standards and Technologies, Multi-agents
Concurrency and Synchronisation, Wireless and Mobile Communications, Protocols and Standards
Data/Text Mining, Data Clustering, Graph Partitioning, Collective Decision Making
Multi-objective Optimisation Techniques in Dynamic Computational Environments
Advanced Modelling of Emerging e-Infrastructures for Big Data and IoT (emphasis on smart environments):
Social Networks Analysis, Formal Concept Analysis, Temporal Analysis, Topic Maps
Ad-Hoc Networks, RF Modelling, Object and Context Representation, Ontology Management
Enabling Technologies; Service Architectures, Discovery, Retrieval, Scheduling, Allocation, Monitoring
Mobility Management, Traffic Models, Process Workflow, Resource and Device Management
Data Centres, Real-time and (Historical) Data Management, Data Growth, Storage, Implications
Context-Aware Infrastructures and Services, Smart Objects, Positioning Location-Based Services
Advanced Applications of Big Data and IoT (emphasis on smart environments):
Applications, Services and Business Models, Strategies, Interaction Paradigms i.e. Smart Cities
Middleware, Languages, Components, Programs and Portals
Performance, Scalability, Robustness, Reliability Verification, Validation, Benchmarking
Concepts and/or Frameworks of Applicable Future Technologies, Implications and Trends
Network functions virtualization for MCC paradigm in 5G mobile networks
Protocols and wireless network technologies for MCC applications and virtualization in 5G context
MCC models, novel network infrastructures and approaches in 5G context
Management of MCC resources in 5G mobile networks
Cognitive radio networks on MCC in 5G context
MCC models, services, and applications in 5G mobile networks
Virtualization techniques for MCC in 5G context
Content-aware solution for MCC in 5G mobile networks
Resource and service management, provision, and migration of MCC in 5G
Mobile context-aware services for clouds in 5G mobile networks
Collaboration, management and administration of MCC in 5G context
Mobile cloud sensing service and crowdsourcing in 5G
Mobile context-aware services and computing for clouds in 5G
MCC data centers and storage technologies in 5G mobile networks
Mobile-aware cloud databases and data retrievals in 5G
Energy-efficient schemes of MCC in 5G context
Location-based MCC applications in 5G context
Security and privacy issues for MCC in 5G context
Big data analytics on MCC in 5G context
Urban sensing and crowd-sensing, and smart sensor networks in 5G
Mobile social media and community services in 5G
Machine-to-Machine (M2M) Big Data Processing and Controlling Networking at the Edge (Sensing and sensor signal processing, sensor networking protocols, energy harvesting and energy management)
Middleware (System and network architectures, middleware for heterogeneous sensors, devices & protocols, QoS provisioning, security issues - data confidentiality, integrity, network resilience, etc.)
Applications and case studies of M2M communications and IoT ecosystems
Analytics and management (Data management and analytics: data-stream, sharing, mining etc, business intelligence from sensor data, social network analysis in IoT)
M2M Infrastructure (Big Data Storage and processing, management and analysis, back-end (cloud based) infrastructure, distributed processing)
Related applications (Novel application developments and case studies in energy, healthcare, logistics and transportation, manufacturing etc., test-beds and field trials etc.)
Submission information
Academics, researchers and practitioners are invited to submit by 30 April 2015, a 2-page manuscript proposal detailing the background, motivations and structure of their proposed chapter. Authors of accepted proposals will be notified by 10 May 2015 and will be given instructions and guidelines for chapter preparation. Full chapters will be due on 10 July 2015 and should be of around 8,000 words in length and/or 25 pages long. Please follow the manuscript formatting guidelines below and submit the original version (in Microsoft word) and or LaTex format as per the guidelines (URL: www.cs.unic.ac.cy/cmavrom/T1-book(MC_bigData).zip). All chapters will be reviewed on a double-blind basis. The book is to be published in the "Studies in Big Data" book series, Springer.
Submit the proposal of your chapter(s) via e-mail: cfcbooksp-AT-gmail.com and via Easychair. The submission Web site for IoT5GMob is https://easychair.org/conferences/?conf=bookmobclo.... Note that both (email and via EasyChair) submission methods should be used for cross confirmation.
This publication is anticipated to be released in 2016.
Important dates
30 May 2015: 2-page Proposal Submission Deadline
10 July 2015: Full Chapter Submission (in Word or PDF)
20 September 2015: Notification of Full Chapter Acceptance
30 October 2015: Revised Chapter Submission
15 January 2016: Final Notification of Acceptance
25 February 2016: Final Material Submission
Contact
Inquiries (e-mail) and submissions (in Word or PDF) can be forwarded electronically to:
Constandinos X. Mavromoustakis
Email: mavromoustakis.c-AT-unic.ac.cy
University of Nicosia, Cyrpus
George Mastorakis
Email: gmastorakis-AT-staff.teicrete.gr
Technological Educational Institute of Crete, Greece
Ciprian Dobre
Email: ciprian.dobre-AT-cs.pub.ro
University POLITEHNICA of Bucharest, Romania