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Modern applications span multiple clouds to reduce costs, avoid vendor lock-in, and leverage low-availability resources in another cloud. However, standard object stores operate within a single cloud, forcing users to manually manage data…
Cloud applications are increasingly distributing data across multiple regions and cloud providers. Unfortunately, wide-area bulk data transfers are often slow, bottlenecking applications. We demonstrate that it is possible to significantly…
Fast, reliable, and efficient data transmission across wide-area networks is a predominant bottleneck for data-intensive cloud applications. This paper introduces OneDataShare, which is designed to eliminate the issues plaguing effective…
Advances in networks, accelerators, and cloud services encourage programmers to reconsider where to compute -- such as when fast networks make it cost-effective to compute on remote accelerators despite added latency. Workflow and…
Using multiple datacenters allows for higher availability, load balancing and reduced latency to customers of cloud services. To distribute multiple copies of data, cloud providers depend on inter-datacenter WANs that ought to be used…
Modern science and engineering computing environments often feature storage systems of different types, from parallel file systems in high-performance computing centers to object stores operated by cloud providers. To enable easy, reliable,…
The Internet of Things (IoT) is offering unprecedented observational data that are used for managing Smart City utilities. Edge and Fog gateway devices are an integral part of IoT deployments to acquire real-time data and enact controls.…
Data distribution across different facilities offers benefits such as enhanced resource utilization, increased resilience through replication, and improved performance by processing data near its source. However, managing such data is…
One of the main challenges in building a large scale publish-subscribe infrastructure in an enterprise network, is to provide the subscribers with the required information, while minimizing the consumed host and network resources.…
This paper proposes using file system custom metadata as a bidirectional communication channel between applications and the storage system. This channel can be used to pass hints that enable cross-layer optimizations, an option hindered…
Structural Health Monitoring (SHM) is crucial for the safety and maintenance of various infrastructures. Due to the large amount of data generated by numerous sensors and the high real-time requirements of many applications, SHM poses…
The proliferation of GPS-enabled devices has led to the development of numerous location-based services. These services need to process massive amounts of spatial data in real-time. The current scale of spatial data cannot be handled using…
Development of cloud computing enables to move Big Data in the hybrid cloud services. This requires research of all processing systems and data structures for provide QoS. Due to the fact that there are many bottlenecks requires monitoring…
This paper presents a case for exploiting the synergy of dedicated and opportunistic network resources in a distributed hosting platform for data stream processing applications. Our previous studies have demonstrated the benefits of…
Emerging distributed cloud architectures, e.g., fog and mobile edge computing, are playing an increasingly important role in the efficient delivery of real-time stream-processing applications (also referred to as augmented information…
Cloud storage plays an important role in social computing. This paper aims to develop a cloud storage management system for mobile devices to support an extended set of file operations. Because of the limit of storage, bandwidth, power…
The explosive increase in volume, velocity, variety, and veracity of data generated by distributed and heterogeneous nodes such as IoT and other devices, continuously challenge the state of art in big data processing platforms and mining…
Data stream processing is an increasingly important topic due to the prevalence of smart devices and the demand for real-time analytics. Geo-distributed streaming systems, where cloud-based queries utilize data streams from multiple…
Orchestrating service-oriented workflows is typically based on a design model that routes both data and control through a single point - the centralised workflow engine. This causes scalability problems that include the unnecessary…
Robots have inherently limited onboard processing, storage, and power capabilities. Cloud computing resources have the potential to provide significant advantages for robots in many applications. However, to make use of these resources,…