Experimental Evaluation of a Coarse-Grained Switch Scheduler

Modern high performance routers rely on sophisticated interconnection networks to meet ever increasing demands on capacity. Regulating the flow of packets through these interconnects is critical to providing good performance, particularly in the presence of extreme traffic patterns that result in sustained overload at output ports. Previous studies have used a combination of analysis and idealized simulations to show that coarse-grained scheduling of traffic flows can be effective in preventing congestion, while ensuring high utilization. In this paper, we study the performance of a coarse-grained scheduler in a real router with a scalable architecture similar to those found in high performance commercial systems. Our results are obtained by taking fine-grained measurements of an operating router that provide a detailed picture of how the scheduling algorithm behaves under a variety of conditions, giving a more complete and realistic understanding of the short time-scale dynamics than previous studies could provide. We also examine computation and communication overheads of our scheduler implementation to assess its resource usage and to provide the basis for an analysis of how the resource usage scales with system size

Towards delay-aware container-based Service Function Chaining in Fog Computing

Recently, the fifth-generation mobile network (5G) is getting significant attention. Empowered by Network Function Virtualization (NFV), 5G networks aim to support diverse services coming from different business verticals (e.g. Smart Cities, Automotive, etc). To fully leverage on NFV, services must be connected in a specific order forming a Service Function Chain (SFC). SFCs allow mobile operators to benefit from the high flexibility and low operational costs introduced by network softwarization. Additionally, Cloud computing is evolving towards a distributed paradigm called Fog Computing, which aims to provide a distributed cloud infrastructure by placing computational resources close to end-users. However, most SFC research only focuses on Multi-access Edge Computing (MEC) use cases where mobile operators aim to deploy services close to end-users. Bi-directional communication between Edges and Cloud are not considered in MEC, which in contrast is highly important in a Fog environment as in distributed anomaly detection services. Therefore, in this paper, we propose an SFC controller to optimize the placement of service chains in Fog environments, specifically tailored for Smart City use cases. Our approach has been validated on the Kubernetes platform, an open-source orchestrator for the automatic deployment of micro-services. Our SFC controller has been implemented as an extension to the scheduling features available in Kubernetes, enabling the efficient provisioning of container-based SFCs while optimizing resource allocation and reducing the end-to-end (E2E) latency. Results show that the proposed approach can lower the network latency up to 18% for the studied use case while conserving bandwidth when compared to the default scheduling mechanism

Enhancing end-to-end quality of service provisioning in wireless ad hoc networks using service vectors

A cross-layer architecture that achieves significant power savings, while enhancing the end-to-end QoS provisioning and granularity in wireless ad hoc networks is proposed in this thesis. Recently, a new concept called service vector has been introduced, which enables an end host to choose different service classes along its data path. This scheme enhances the user benefits from the network services and network resource utilization, while maintaining the simplicity and scalability of the current Differentiated Services (DiffServ) network architecture. This thesis explores the application of this concept on wireless ad hoc networks and provides a cross-layer architecture based on the combination of delay-bounded wireless link level scheduling and the network layer service vector concept, which enables a wireless ad hoc network to achieve significant power savings and finer end-to-end QoS granularity. The impact of various traffic arrival distributions and flows with different QoS requirements on the performance of this cross-layer architecture is also investigated and evaluated

Scalable parallel communications

Coarse-grain parallelism in networking (that is, the use of multiple protocol processors running replicated software sending over several physical channels) can be used to provide gigabit communications for a single application. Since parallel network performance is highly dependent on real issues such as hardware properties (e.g., memory speeds and cache hit rates), operating system overhead (e.g., interrupt handling), and protocol performance (e.g., effect of timeouts), we have performed detailed simulations studies of both a bus-based multiprocessor workstation node (based on the Sun Galaxy MP multiprocessor) and a distributed-memory parallel computer node (based on the Touchstone DELTA) to evaluate the behavior of coarse-grain parallelism. Our results indicate: (1) coarse-grain parallelism can deliver multiple 100 Mbps with currently available hardware platforms and existing networking protocols (such as Transmission Control Protocol/Internet Protocol (TCP/IP) and parallel Fiber Distributed Data Interface (FDDI) rings); (2) scale-up is near linear in n, the number of protocol processors, and channels (for small n and up to a few hundred Mbps); and (3) since these results are based on existing hardware without specialized devices (except perhaps for some simple modifications of the FDDI boards), this is a low cost solution to providing multiple 100 Mbps on current machines. In addition, from both the performance analysis and the properties of these architectures, we conclude: (1) multiple processors providing identical services and the use of space division multiplexing for the physical channels can provide better reliability than monolithic approaches (it also provides graceful degradation and low-cost load balancing); (2) coarse-grain parallelism supports running several transport protocols in parallel to provide different types of service (for example, one TCP handles small messages for many users, other TCP's running in parallel provide high bandwidth service to a single application); and (3) coarse grain parallelism will be able to incorporate many future improvements from related work (e.g., reduced data movement, fast TCP, fine-grain parallelism) also with near linear speed-ups