相关论文: vSDNEmul: A Software-Defined Network Emulator Base…

Non-volatile memory (NVM) is a promising technology for low-energy and high-capacity main memory of computers. The characteristics of NVM devices, however, tend to be fundamentally different from those of DRAM (i.e., the memory device…

The accurate modeling of semiconductor devices plays a critical role in the development of new technology nodes and next-generation devices. Semiconductor device designers largely rely on advanced simulation software to solve the…

Traditionally, applications that are used in large and small enterprises were deployed on "bare metal" servers installed with operating systems. Recently, the use of multiple virtual machines (VMs) on the same physical server was adopted…

A Vehicular Ad-hoc Network (VANET) is a collection of wireless vehicle nodes forming a temporary network without using any centralized Road Side Unit (RSU). VANET protocols have to face high challenges due to dynamically changing topologies…

Ethernet Virtual Private Network (EVPN) is an emerging technology that addresses the networking challenges presented by geo-distributed Data Centers (DCs). One of the major advantages of EVPN over legacy layer 2 VPN solutions is providing…

Plug-and-play information technology (IT) infrastructure has been expanding very rapidly in recent years. With the advent of cloud computing, many ecosystem and business paradigms are encountering potential changes and may be able to…

Full system "end-to-end" measurements in physical testbeds are the gold standard for network systems evaluation but are often not feasible. When physical testbeds are not available we frequently turn to simulation for evaluation.…

IoT devices based on microcontroller units (MCU) provide ultra-low power consumption and ubiquitous computation for near-sensor deep learning models (DNN). However, the memory of MCU is usually 2-3 orders of magnitude smaller than mobile…

Containerization is the mainstream of current software development, which enables software to be used across platforms without additional configuration of running environment. However, many images created by developers are redundant and…

Due to the limited and varying availability of cheap infrastructure and resources, cloud network systems and applications are tested in simulation and emulation environments prior to physical deployments, at different stages of development.…

Network protocols have historically been developed on an ad-hoc basis, and cloud computing is no exception. A fundamental management protocol, not yet standardized, that cloud providers need to run to support wide-area virtual network…

There is a growing body of research on developing testing techniques for Deep Neural Networks (DNN). We distinguish two general modes of testing for DNNs: Offline testing where DNNs are tested as individual units based on test datasets…

Deep networks consume a large amount of memory by their nature. A natural question arises can we reduce that memory requirement whilst maintaining performance. In particular, in this work we address the problem of memory efficient learning…

Software Defined Networking (SDN) offers a flexible and scalable architecture that abstracts decision making away from individual devices and provides a programmable network platform. However, implementing a centralized SDN architecture…

In-memory computing technology is used extensively in artificial intelligence devices due to lower power consumption and fast calculation of matrix-based functions. The development of such a device and its integration in a system takes a…

The rapidly growing computational demands of deep neural networks require novel hardware designs. Recently, tunable nanoelectronic devices were developed based on hopping electrons through a network of dopant atoms in silicon. These "Dopant…

The advent of SDN has brought a plethora of new architectures and controller designs for many use-cases and scenarios. Existing SDN deployments focus on campus, datacenter and WAN networks. However, little research efforts have been devoted…

Computing-in-memory with emerging non-volatile memory (nvCiM) is shown to be a promising candidate for accelerating deep neural networks (DNNs) with high energy efficiency. However, most non-volatile memory (NVM) devices suffer from…

Deep Neural Networks (DNNs) have revolutionized numerous applications, but the demand for ever more performance remains unabated. Scaling DNN computations to larger clusters is generally done by distributing tasks in batch mode using…

Software-Defined Networking (SDN) allows to control the available network resources by an intelligent and centralized authority in order to optimize traffic flows in a flexible manner. However, centralized control may face scalability…