SDN-controlled and Orchestrated OPSquare DCN Enabling Automatic Network Slicing with Differentiated QoS Provisioning

In this work, we propose and experimentally assess the automatic and flexible NSs configurations of optical OPSquare DCN controlled and orchestrated by an extended SDN control plane for multi-tenant applications with differentiated QoS provisioning. Optical Flow Control (OFC) protocol has been developed to prevent packet losses at switch sides caused by packet contentions.Based on the collected resource topology of data plane, the optical network slices can be dynamically provisioned and automatically reconfigured by the SDN control plane. Meanwhile, experimental results validate that the priority assignment of application flows supplies dynamic QoS performance to various slices running applications with specific requirements in terms of packet loss and transmission latency. In addition, the capability of exposing traffic statistics information of data plane to SDN control plane enables the implementation of load balancing algorithms further improving the network performance with high QoS. No packet loss and less than 4.8 us server-to-server latency can be guaranteed for the sliced network with highest priority at a load of 0.5

Caladan: a distributed meta-OS for data center disaggregation

Data center resource disaggregation promises cost savings by pool-ing compute, storage and memory resources into separate, net-worked nodes. The benefits of this model are clear, but a closer lookshows that its full performance and efficiency potential cannot beeasily realized. Existing systems use CPUs pervasively to interface ar-bitrary devices with the network and to orchestrate communicationamong them, reducing the benefits of disaggregation.In this paper we presentCaladan, a novel system with a trusteduni-versal resource fabricthat interconnects all resources and efficientlyoffloads the system and application control planes to SmartNICs,freeing server CPUs to execute application logic. Caladan offersthree core services: capability-driven distributed name space, virtualdevices, and direct inter-device communications. These servicesare implemented in a trustedmeta-kernelthat executes in per-nodeSmartNICs. Low-level device drivers running on the commodity hostOS are used for setting up accelerators and I/O devices, and exposingthem to Caladan. Applications run in a distributed fashion acrossCPUs and multiple accelerators, which in turn can directly performI/O, i.e., access files, other accelerators or host services. Our dis-tributed dataflow runtime runs on top of this substrate. It orchestratesthe distributed execution, connecting disaggregated resources usingdata transfers and inter-device communication, while eliminatingthe performance bottlenecks of the traditional CPU-centric design

On the benefits of resource disaggregation for virtual data centre provisioning in optical data centres

Virtual Data Centre (VDC) allocation requires the provisioning of both computing and network resources. Their joint provisioning allows for an optimal utilization of the physical Data Centre (DC) infrastructure resources. However, traditional DCs can suffer from computing resource underutilization due to the rigid capacity configurations of the server units, resulting in high computing resource fragmentation across the DC servers. To overcome these limitations, the disaggregated DC paradigm has been recently introduced. Thanks to resource disaggregation, it is possible to allocate the exact amount of resources needed to provision a VDC instance. In this paper, we focus on the static planning of a shared optically interconnected disaggregated DC infrastructure to support a known set of VDC instances to be deployed on top. To this end, we provide optimal and sub-optimal techniques to determine the necessary capacity (both in terms of computing and network resources) required to support the expected set of VDC demands. Next, we quantitatively evaluate the benefits yielded by the disaggregated DC paradigm in front of traditional DC architectures, considering various VDC profiles and Data Centre Network (DCN) topologies.Peer ReviewedPostprint (author's final draft

Design and Implementation of High QoS 3D-NoC using Modified Double Particle Swarm Optimization on FPGA

One technique to overcome the exponential growth bottleneck is to increase the number of cores on a processor, although having too many cores might cause issues including chip overheating and communication blockage. The problem of the communication bottleneck on the chip is presently effectively resolved by networks-on-chip (NoC). A 3D stack of chips is now possible, thanks to recent developments in IC manufacturing techniques, enabling to reduce of chip area while increasing chip throughput and reducing power consumption. The automated process associated with mapping applications to form three-dimensional NoC architectures is a significant new path in 3D NoC research. This work proposes a 3D NoC partitioning approach that can identify the 3D NoC region that has to be mapped. A double particle swarm optimization (DPSO) inspired algorithmic technique, which may combine the characteristics having neighbourhood search and genetic architectures, also addresses the challenge of a particle swarm algorithm descending into local optimal solutions. Experimental evidence supports the claim that this hybrid optimization algorithm based on Double Particle Swarm Optimisation outperforms the conventional heuristic technique in terms of output rate and loss in energy. The findings demonstrate that in a network of the same size, the newly introduced router delivers the lowest loss on the longest path.  Three factors, namely energy, latency or delay, and throughput, are compared between the suggested 3D mesh ONoC and its 2D version. When comparing power consumption between 3D ONoC and its electronic and 2D equivalents, which both have 512 IP cores, it may save roughly 79.9% of the energy used by the electronic counterpart and 24.3% of the energy used by the latter. The network efficiency of the 3D mesh ONoC is simulated by DPSO in a variety of configurations. The outcomes also demonstrate an increase in performance over the 2D ONoC. As a flexible communication solution, Network-On-Chips (NoCs) have been frequently employed in the development of multiprocessor system-on-chips (MPSoCs). By outsourcing their communication activities, NoCs permit on-chip Intellectual Property (IP) cores to communicate with one another and function at a better level. The important components in assigning application duties, distributing the work to the IPs, and coordinating communication among them are mapping and scheduling methods. This study aims to present an entirely advanced form of research in the area of 3D NoC mapping and scheduling applications, grouping the results according to various parameters and offering several suggestions for further research

Advances in wireless community networks with the community-lab testbed

Beyond traditional telecom providers, citizens and organizations pool their own resources and coordinate in order to build local network infrastructures to address the digital divide in many parts of the world. These crowdsourced network infrastructures can be self-organized and shared by a community for the collective benefit of its members. Several of these networks have developed open, free, and neutral agreements, and are governed as a common-pool resource: community networks. These are built using a variety of commodity wireless hardware (e.g., Wi-Fi long-range point-to-point links, Wi-Fi and GSM access points, and mesh networks), sometimes optical fiber links, heterogeneous nodes, routing protocols, and applications. A group of researchers, developers, and community networks developed the Community-Lab testbed, and for the last five years have worked together to overcome obstacles, improve the technologies, tools, and operational models being used, as well as model best practices for more effective and sustainable community networks. This article presents the challenges for experimentation, the testbeds built, results, lessons learned, and the impact of that work to place wireless community networks as one sustainable way toward an Internet accessible to all.Peer ReviewedPostprint (author's final draft

End-to-end slices to orchestrate resources and services in the cloud-to-edge continuum

Fog computing, combined with traditional cloud computing, offers an inherently distributed infrastructure – referred to as the cloud-to-edge continuum – that can be used for the execution of low-latency and location-aware IoT services. The management of such an infrastructure is complex: resources in multiple domains need to be accessed by several tenants, while an adequate level of isolation and performance has to be guaranteed. This paper proposes the dynamic allocation of end-to-end slices to perform the orchestration of resources and services in such a scenario. These end-to-end slices require a unified resource management approach that encompasses both data centre and network resources. Currently, fog orchestration is mainly focused on the management of compute resources, likewise, the slicing domain is specifically centred solely on the creation of isolated network partitions. A unified resource orchestration strategy, able to integrate the selection, configuration and management of compute and network resources, as part of a single abstracted object, is missing. This work aims to minimise the silo-effect, and proposes end-to-end slices as the foundation for the comprehensive orchestration of compute resources, network resources, and services in the cloud-to-edge continuum, as well acting as the basis for a system implementation. The concept of the end-to-end slice is formally described via a graph-based model that allows for dynamic resource discovery, selection and mapping via different algorithms and optimisation goals; and a working system is presented as the way to build slices across multiple domains dynamically, based on that model. These are independently accessible objects that abstract resources of various providers – traded via a Marketplace – with compute slices, allocated using the bare-metal cloud approach, being interconnected to each other via the connectivity of network slices. Experiments, carried out on a real testbed, demonstrate three features of the end-to-end slices: resources can be selected, allocated and controlled in a softwarised fashion; tenants can instantiate distributed IoT services on those resources transparently; the performance of a service is absolutely not affected by the status of other slices that share the same resource infrastructure