Delivering Consistent Network Performance in Multi-tenant Data Centers

Data centers are growing rapidly in size and have recently begun acquiring a new role as cloud hosting platforms, allowing outside developers to deploy their own applications on large scales. As a result, today\u27s data centers are multi-tenant environments that host an increasingly diverse set of applications, many of which have very demanding networking requirements. This has prompted research into new data center architectures that offer increased capacity by using topologies that introduce multiple paths between servers. To achieve consistent network performance in these networks, traffic must be effectively load balanced among the available paths. In addition, some form of system-wide traffic regulation is necessary to provide performance guarantees to tenants. To address these issues, this thesis introduces several software-based mechanisms that were inspired by techniques used to regulate traffic in the interconnects of scalable Internet routers. In particular, we borrow two key concepts that serve as the basis for our approach. First, we investigate packet-level routing techniques that are similar to those used to balance load effectively in routers. This work is novel in the data center context because most existing approaches route traffic at the level of flows to prevent their packets from arriving out-of-order. We show that routing at the packet-level allows for far more efficient use of the network\u27s resources and we provide a novel resequencing scheme to deal with out-of-order arrivals. Secondly, we introduce distributed scheduling as a means to engineer traffic in data centers. In routers, distributed scheduling controls the rates between ports on different line cards enabling traffic to move efficiently through the interconnect. We apply the same basic idea to schedule rates between servers in the data center. We show that scheduling can prevent congestion from occurring and can be used as a flexible mechanism to support network performance guarantees for tenants. In contrast to previous work, which relied on centralized controllers to schedule traffic, our approach is fully distributed and we provide a novel distributed algorithm to control rates. In addition, we introduce an optimization problem called backlog scheduling to study scheduling strategies that facilitate more efficient application execution

Scheduling soft real-time jobs over dual non-real-time servers

In this paper, we consider soft real-time systems with redundant off-the-shelf processing components (e.g., CPU, disk, network), and show how applications can exploit the redundancy to improve the system's ability of meeting response time goals (soft deadlines). We consider two scheduling policies, one that evenly distributes load (Balance), and one that partitions load according to job slackness (Chop). We evaluate the effectiveness of these policies through analysis and simulation. Our results show that by intelligently distributing jobs by their slackness amount the servers, Chop can significantly improve real-time performance. ©1996 IEEE.published_or_final_versio

Multistage Packet-Switching Fabrics for Data Center Networks

Recent applications have imposed stringent requirements within the Data Center Network (DCN) switches in terms of scalability, throughput and latency. In this thesis, the architectural design of the packet-switches is tackled in different ways to enable the expansion in both the number of connected endpoints and traffic volume. A cost-effective Clos-network switch with partially buffered units is proposed and two packet scheduling algorithms are described. The first algorithm adopts many simple and distributed arbiters, while the second approach relies on a central arbiter to guarantee an ordered packet delivery. For an improved scalability, the Clos switch is build using a Network-on-Chip (NoC) fabric instead of the common crossbar units. The Clos-UDN architecture made with Input-Queued (IQ) Uni-Directional NoC modules (UDNs) simplifies the input line cards and obviates the need for the costly Virtual Output Queues (VOQs). It also avoids the need for complex, and synchronized scheduling processes, and offers speedup, load balancing, and good path diversity. Under skewed traffic, a reliable micro load-balancing contributes to boosting the overall network performance. Taking advantage of the NoC paradigm, a wrapped-around multistage switch with fully interconnected Central Modules (CMs) is proposed. The architecture operates with a congestion-aware routing algorithm that proactively distributes the traffic load across the switching modules, and enhances the switch performance under critical packet arrivals. The implementation of small on-chip buffers has been made perfectly feasible using the current technology. This motivated the implementation of a large switching architecture with an Output-Queued (OQ) NoC fabric. The design merges assets of the output queuing, and NoCs to provide high throughput, and smooth latency variations. An approximate analytical model of the switch performance is also proposed. To further exploit the potential of the NoC fabrics and their modularity features, a high capacity Clos switch with Multi-Directional NoC (MDN) modules is presented. The Clos-MDN switching architecture exhibits a more compact layout than the Clos-UDN switch. It scales better and faster in port count and traffic load. Results achieved in this thesis demonstrate the high performance, expandability and programmability features of the proposed packet-switches which makes them promising candidates for the next-generation data center networking infrastructure

Design and implementation of multiple address parallel transmission architecture for storage area network

Master'sMASTER OF ENGINEERIN

Packet delay and sequence number space in the radio link protocol layer

Thesis (S.B. and M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.Includes bibliographical references (leaf 85).by Euree Y. Kim.S.B.and M.Eng

Methods in intelligent transportation systems exploiting vehicle connectivity, autonomy and roadway data

Intelligent transportation systems involve a variety of information and control systems methodologies, from cooperative systems which aim at traffic flow optimization by means of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication, to information fusion from multiple traffic sensing modalities. This thesis aims to address three problems in intelligent transportation systems, one in optimal control of connected automated vehicles, one in discrete-event and hybrid traffic simulation model, and one in sensing and classifying roadway obstacles in smart cities. The first set of problems addressed relates to optimally controlling connected automated vehicles (CAVs) crossing an urban intersection without any explicit traffic signaling. A decentralized optimal control framework is established whereby, under proper coordination among CAVs, each CAV can jointly minimize its energy consumption and travel time subject to hard safety constraints. A closed-form analytical solution is derived while taking speed, control, and safety constraints into consideration. The analytical solution of each such problem, when it exists, yields the optimal CAV acceleration/deceleration. The framework is capable of accommodating for turns and ensures the absence of collisions. In the meantime, a measurement of passenger comfort is taken into account while the vehicles make turns. In addition to the first-in-first-out (FIFO) ordering structure, the concept of dynamic resequencing is introduced which aims at further increasing the traffic throughput. This thesis also studies the impact of CAVs and shows the benefit that can be achieved by incorporating CAVs to conventional traffic. To validate the effectiveness of the proposed solution, a discrete-event and hybrid simulation framework based on SimEvents is proposed, which facilitates safety and performance evaluation of an intelligent transportation system. The traffic simulation model enables traffic study at the microscopic level, including new control algorithms for CAVs under different traffic scenarios, the event-driven aspects of transportation systems, and the effects of communication delays. The framework spans multiple toolboxes including MATLAB, Simulink, and SimEvents. In another direction, an unsupervised anomaly detection system is developed based on data collected through the Street Bump smartphone application. The system, which is built based on signal processing techniques and the concept of information entropy, is capable of generating a prioritized list of roadway obstacles, such that the higher-ranked entries are most likely to be actionable bumps (e.g., potholes) requiring immediate attention, while those lower-ranked are most likely to be nonactionable bumps(e.g., flat castings, cobblestone streets, speed bumps) for which no immediate action is needed. This system enables the City to efficiently prioritize repairs. Results on an actual data set provided by the City of Boston illustrate the feasibility and effectiveness of the system in practice

JTIT

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