Datacenter Traffic Control: Understanding Techniques and Trade-offs

Datacenters provide cost-effective and flexible access to scalable compute and storage resources necessary for today's cloud computing needs. A typical datacenter is made up of thousands of servers connected with a large network and usually managed by one operator. To provide quality access to the variety of applications and services hosted on datacenters and maximize performance, it deems necessary to use datacenter networks effectively and efficiently. Datacenter traffic is often a mix of several classes with different priorities and requirements. This includes user-generated interactive traffic, traffic with deadlines, and long-running traffic. To this end, custom transport protocols and traffic management techniques have been developed to improve datacenter network performance. In this tutorial paper, we review the general architecture of datacenter networks, various topologies proposed for them, their traffic properties, general traffic control challenges in datacenters and general traffic control objectives. The purpose of this paper is to bring out the important characteristics of traffic control in datacenters and not to survey all existing solutions (as it is virtually impossible due to massive body of existing research). We hope to provide readers with a wide range of options and factors while considering a variety of traffic control mechanisms. We discuss various characteristics of datacenter traffic control including management schemes, transmission control, traffic shaping, prioritization, load balancing, multipathing, and traffic scheduling. Next, we point to several open challenges as well as new and interesting networking paradigms. At the end of this paper, we briefly review inter-datacenter networks that connect geographically dispersed datacenters which have been receiving increasing attention recently and pose interesting and novel research problems.Comment: Accepted for Publication in IEEE Communications Surveys and Tutorial

MODELS AND SOLUTION ALGORITHMS FOR EQUITABLE RESOURCE ALLOCATION IN AIR TRAFFIC FLOW MANAGEMENT

Population growth and economic development lead to increasing demand for travel and pose mobility challenges on capacity-limited air traffic networks. The U.S. National Airspace System (NAS) has been operated near the capacity, and air traffic congestion is expected to remain as a top concern for the related system operators, passengers and airlines. This dissertation develops a number of model reformulations and efficient solution algorithms to address resource allocation problems in air traffic flow management, while explicitly accounting for equitable objectives in order to encourage further collaborations by different stakeholders. This dissertation first develops a bi-criteria optimization model to offload excess demand from different competing airlines in the congested airspace when the predicted traffic demand is higher than available capacity. Computationally efficient network flow models with side constraints are developed and extensively tested using datasets obtained from the Enhanced Traffic Management System (ETMS) database (now known as the Traffic Flow Management System). Representative Pareto-optimal tradeoff frontiers are consequently generated to allow decision-makers to identify best-compromising solutions based on relative weights and systematical considerations of both efficiency and equity. This dissertation further models and solves an integrated flight re-routing problem on an airspace network. Given a network of airspace sectors with a set of waypoint entries and a set of flights belonging to different air carriers, the optimization model aims to minimize the total flight travel time subject to a set of flight routing equity, operational and safety requirements. A time-dependent network flow programming formulation is proposed with stochastic sector capacities and rerouting equity for each air carrier as side constraints. A Lagrangian relaxation based method is used to dualize these constraints and decompose the original complex problem into a sequence of single flight rerouting/scheduling problems. Finally, within a multi-objective utility maximization framework, the dissertation proposes several practically useful heuristic algorithms for the long-term airport slot assignment problem. Alternative models are constructed to decompose the complex model into a series of hourly assignment sub-problems. A new paired assignment heuristic algorithm is developed to adapt the round robin scheduling principle for improving fairness measures across different airlines. Computational results are presented to show the strength of each proposed modeling approach

Review and analysis of networking challenges in cloud computing

Cloud Computing offers virtualized computing, storage, and networking resources, over the Internet, to organizations and individual users in a completely dynamic way. These cloud resources are cheaper, easier to manage, and more elastic than sets of local, physical, ones. This encourages customers to outsource their applications and services to the cloud. The migration of both data and applications outside the administrative domain of customers into a shared environment imposes transversal, functional problems across distinct platforms and technologies. This article provides a contemporary discussion of the most relevant functional problems associated with the current evolution of Cloud Computing, mainly from the network perspective. The paper also gives a concise description of Cloud Computing concepts and technologies. It starts with a brief history about cloud computing, tracing its roots. Then, architectural models of cloud services are described, and the most relevant products for Cloud Computing are briefly discussed along with a comprehensive literature review. The paper highlights and analyzes the most pertinent and practical network issues of relevance to the provision of high-assurance cloud services through the Internet, including security. Finally, trends and future research directions are also presented

Design issues in quality of service routing

The range of applications and services which can be successfully deployed in packet-switched networks such as the Internet is limited when the network does nor provide Quality of Service (QoS). This is the typical situation in today's Internet. A key aspect in providing QoS support is the requirement for an optimised and intelligent mapping of customer traffic flows onto a physical network topology. The problem of selecting such paths is the task of QoS routing QoS routing algorithms are intrinsically complex and need careful study before being implemented in real networks. Our aim is to address some of the challenges present m the deployment of QoS routing methods. This thesis considers a number of practical limitations of existing QoS routing algorithms and presents solutions to the problems identified. Many QoS routing algorithms are inherently unstable and induce traffic fluctuations in the network. We describe two new routing algorithms which address this problem The first method - ALCFRA (Adaptive Link Cost Function Routing Algorithm) - can be used in networks with sparse connectivity, while the second algorithm - CAR (Connectivity Aware Routing) - is designed to work well in other network topologies. We also describe how to ensure co-operative interaction of the routing algorithms in multiple domains when hierarchial routing is used and also present a solution to the problems of how to provide QoS support m a network where not all nodes are QoS-aware. Our solutions are supported by extensive simulations over a wide range of network topologies and their performance is compared to existing algorithms. It is shown that our solutions advance the state of the art in QoS routing and facilitate the deployment of QoS support in tomorrow's Internet

Design, Implementation and Evaluation of an In-House Controller for Software Defined Networking with Applications

Over the past several decades, there has been a dramatic improvement in net- working technologies. Network devices and protocols are becoming more powerful and complex. The vertical structure of the network protocol layers also leads to a coupled control plane and data plane in data frames. To solve this issue from a structural level, researchers introduced a new architecture of networking, the Software Defined Networking (SDN). By decoupling the control plane and data plane from a frame level and aggregating the protocols into software run in a centralized controller dynamically, engineers obtained a new way to build and control a network dynamically in real time. Meanwhile, with the development of Internet of Things (IoT), data volume from mobile devices and low power terminals are dramatically increasing. However, the traditional cloud computing is still in a relatively centralized architecture, which causes huge traffic volume of IoT applications in the network. To this end, researchers proposed the concept of Edge Computing, which utilizes the capacity of the edge nodes in the network to process data and aggregate data from terminals. This research introduces In-House Controller of SDN which has a distributed characteristic and deployed within SDN nodes to minimize the costs in control plane communication. The In-House controller also enables data processing and aggregation capacity in access points which host these functionalities as SDN applications. To research the system performance of the In-House controller in different application scenarios, in this work, following applications were studied: Data flow aggregation of Message Queue Telemetry Transport (MQTT) protocol in Internet of Things, an MQTT proxy in edge switch which is aggregating short MQTT flows from multiple clients into a long MQTT flow to reduce the control plane traffic overhead in TCP. A novel delay tolerant network architecture and a new convergence layer over MQTT protocol in opportunistic networking. Using in-house controller as host and event scheduler for Delay Tolerant Network (DTN) modules and convergence layers which run as applications guest applications in the controller. With the study of applications, this research also proposed a generalized framework named as SDN Docker which support dynamically docking and un-docking applications in network devices with the help of the In-House controller