Related papers: Efficient Inter-Datacenter Bulk Transfers with Mix…
Several organizations have built multiple datacenters connected via dedicated wide area networks over which large inter-datacenter transfers take place. This includes tremendous volumes of bulk multicast traffic generated as a result of…
Large inter-datacenter transfers are crucial for cloud service efficiency and are increasingly used by organizations that have dedicated wide area networks between datacenters. A recent work uses multicast forwarding trees to reduce the…
As applications become more distributed to improve user experience and offer higher availability, businesses rely on geographically dispersed datacenters that host such applications more than ever. Dedicated inter-datacenter networks have…
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…
Large cloud companies manage dozens of datacenters across the globe connected using dedicated inter-datacenter networks. An important application of these networks is data replication which is done for purposes such as increased resiliency…
Multicast allows sending a message to multiple recipients without having to create and send a separate message for each recipient. This preserves network bandwidth, which is particularly important in time-sensitive networks. These networks…
The conventional wireless schedulers of Unicast and Multicast either fulfill multiuser diversity or broadcast gain, but not both together. To achieve optimal system throughput we need a scheduler that exploits both the multiuser diversity…
Results from and progress on the development of a Data Intensive and Network Aware (DIANA) Scheduling engine, primarily for data intensive sciences such as physics analysis, are described. Scientific analysis tasks can involve thousands of…
Multicast data transfers occur in many distributed systems and applications (e.g. IPTV, Grids, content delivery networks). Because of this, efficient multicast data distribution optimization techniques are required. In the first part of…
Inter-datacenter networks connect dozens of geographically dispersed datacenters and carry traffic flows with highly variable sizes and different classes. Adaptive flow routing can improve efficiency and performance by assigning paths to…
Scheduling is an important task allowing parallel systems to perform efficiently and reliably. For modern computation systems, divisible load is a special type of data which can be divided into arbitrary sizes and independently processed in…
Datacenters provide the infrastructure for cloud computing services used by millions of users everyday. Many such services are distributed over multiple datacenters at geographically distant locations possibly in different continents. These…
In grid networks, distributed resources are interconnected by wide area network to support compute and data-intensive applications, which require reliable and efficient transfer of gigabits (even terabits) of data. Different from…
We study real time periodic query scheduling for data collection in multihop Wireless Sensor Networks (WSNs). Given a set of heterogenous data collection queries in WSNs, each query requires the data from the source sensor nodes to be…
Motivated by modern parallel computing applications, we consider the problem of scheduling parallel-task jobs with heterogeneous resource requirements in a cluster of machines. Each job consists of a set of tasks that can be processed in…
The containerized services allocated in the mobile edge clouds bring up the opportunity for large-scale and real-time applications to have low latency responses. Meanwhile, live container migration is introduced to support dynamic resource…
This paper addresses the data transfer scheduling problem for Grid environments, presenting a centralized scheduler developed with dynamic and adaptive features. The algorithm offers a reservation system for user transfer requests that…
Results from the research and development of a Data Intensive and Network Aware (DIANA) scheduling engine, to be used primarily for data intensive sciences such as physics analysis, are described. In Grid analyses, tasks can involve…
With the ever-growing need of data in HPC applications, the congestion at the I/O level becomes critical in super-computers. Architectural enhancement such as burst-buffers and pre-fetching are added to machines, but are not sufficient to…
The impact of transformer networks is booming, yet, they come with significant computational complexity. It is therefore essential to understand how to optimally map and execute these networks on modern neural processor hardware. So far,…