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

Service-level based response by assignment and order processing for warehouse automation

Along with tremendous growth of online sales in this Internet era, unprecedented intensive competition in shortening the delivery time of orders has been occurring among several major online retailers. On the other hand, the idea of customer-oriented service creates a trend of diversified pricing strategy. Different price options are offered to cater to diversified needs of customers. It has become an urgent need for online sales industries to provide the differentiated service levels for different classes of customers with different priorities based on the charging prices and resource constraints of the supply network. In response to the challenges mentioned above, this thesis focuses on providing differentiated service levels to different customers within the warehouse automation system, which is the key point of the supply network. To concentrate on the research topic, the process of a user’s order in warehouse automation system is broken down into the waiting process and retrieving process, which is related to order processing policy and storage assignment method respectively. Priority Based Turn-over Rate (PBTR) storage assignment method, Priority Based Weighted Queuing (PBWQ) policy and joint optimization of storage assignment and PBWQ policy are proposed, developed, explored and validated in this thesis. Utility function of charging price and order processing time is developed to measure the performances of the proposed methods. Compared with the classical turn over rate assignment method, PBTR has 23.21% of improvement under the measurement of utility function, when different classes of customers have different needs for products. PBWQ improves the system performance by 18.15% compared with First-Come-First-Serve (FCFS) policy under baseline setting of experiments. Joint optimization of storage assignment and PBWQ policy has the improvement of 19.64% in system performance compared with the baseline system which applies both classical storage assignment method and FCFS order processing policy

Exploration of Erasure-Coded Storage Systems for High Performance, Reliability, and Inter-operability

With the unprecedented growth of data and the use of low commodity drives in local disk-based storage systems and remote cloud-based servers has increased the risk of data loss and an overall increase in the user perceived system latency. To guarantee high reliability, replication has been the most popular choice for decades, because of simplicity in data management. With the high volume of data being generated every day, the storage cost of replication is very high and is no longer a viable approach. Erasure coding is another approach of adding redundancy in storage systems, which provides high reliability at a fraction of the cost of replication. However, the choice of erasure codes being used affects the storage efficiency, reliability, and overall system performance. At the same time, the performance and interoperability are adversely affected by the slower device components and complex central management systems and operations. To address the problems encountered in various layers of the erasure coded storage system, in this dissertation, we explore the different aspects of storage and design several techniques to improve the reliability, performance, and interoperability. These techniques range from the comprehensive evaluation of erasure codes, application of erasure codes for highly reliable and high-performance SSD system, to the design of new erasure coding and caching schemes for Hadoop Distributed File System, which is one of the central management systems for distributed storage. Detailed evaluation and results are also provided in this dissertation

Reducing Internet Latency : A Survey of Techniques and their Merit

Bob Briscoe, Anna Brunstrom, Andreas Petlund, David Hayes, David Ros, Ing-Jyh Tsang, Stein Gjessing, Gorry Fairhurst, Carsten Griwodz, Michael WelzlPeer reviewedPreprin