In the era of digitization, Data Center Networks (DCN) have emerged as a critical component
supporting infrastructure for cloud computing, big data analytics, online services, and more …

In data center networks, existing control plane-and end host-based load-balancing methods
are encumbered by excessively large decision delays during rapid reactions to microbursts …

In next generation Internet of Things (NG-IoT) networks, numerous pieces of information are
aggregated from the user devices and sensor nodes to the local computing units for further …

In distributed machine learning training, bulk synchronous parallel (BSP) and asynchronous
parallel (ASP) are two main synchronization methods to help achieve gradient aggregation …

Existing load-balancing methods used in data center networks involve some shortcomings
such as excessively large decision delays during reactions to microbursts and large …

Mobile edge computing (MEC) is a promising computing paradigm that enables offloading
tasks to edge servers to decrease the load on user equipment (UE) and the latency of …

Summary Software Defined‐DCN (SD‐DCN) is a layered topology with logically centralized
control which provides intelligence thro‐ugh programmability. The controller in SD‐DCN …

In recent decades, the exponential growth of applications has intensified traffic demands,
posing challenges in ensuring optimal user experiences within modern networks. Traditional …

In an SDN-based Data Center Network (SD-DCN) environment, network traffic is highly
vulnerable to handle the dynamic requirements of the users. It creates difficulty for network …

In the data center network, mixed flows which have contradictory service requirements are
transmitted simultaneously. Switches usually aggregate similar flows to the same queue …