PrestoCloud organised successfully the special session entitled “Intelligent systems and services for cloud accessible, data-intensive computing, ISS-CLOUD” in the 8th IEEE International Conference on Information, Intelligence, Systems and Applications, in Larnaca, Cyprus, 28-30 August 2017.
The special session focused on the integration of cloud computing with mobile services, which enables the development of systems that provide resources and services on an on-demand basis, process big data collected from mobile sensors, and support Internet of things (IoT) with massive cloud-based backend. Such systems may employ computational intelligence methods, utilise artificial intelligence approaches as well as decision making techniques for enhancing the effectiveness and efficiency of computing infrastructures, increasing security and data privacy while making infrastructure configuration, deployment and maintenance easier.
The following papers were accepted and presented in the special session:
- Fraud Threats Disclosure through Cloud Information Security Framework, Theodoros Mavroeidakos and Dimitrios Vergados
- Seamless task offloading on multi-clouds and edge resources: An experiment, Andreas Tsagkaropoulos, Yiannis Verginadis, Dimitris Apostolou and Gregoris Mentzas
- A Network Selection Scheme for Healthcare Vehicular Cloud Computing Systems, Emmanouil Skondras, Angelos Michalas, Nikolaos Tsolis, Aggeliki Sgora and Dimitrios D. Vergados
- Genomic Analysis by Pipelined Bioinformatics Softwares in Cloud, Jitao Yang
- Evaluation of Cloud Platforms for Managing IoT Devices, M.Carmen Ruiz, Teresa Olivares and Jaime Lopez
- Wide Area Video Surveillance Based on Edge and Fog Computing Concept, Georgios Kioumourtzis, Michalis Skitsas, Nikolaos Zotos and Anargyros Sideris
PrestoCloud partners ICCS and ADITESS participated with papers which described early work on managing the seamless offloading of computation effort between cloud and egde resources (paper #2) as well as the requirements stemming from the use of cloud and edge computing resources for wide area video surveillance (paper#6), respectively.