Ashok Anand

MicroTE: fine grained traffic engineering for data centers

The effects of data center traffic characteristics on data center traffic engineering is not well understood. In particular, it is unclear how existing traffic engineering techniques perform under various traffic patterns, namely how do the computed routes differ from the optimal routes. Our study reveals that existing traffic engineering techniques perform 15% to 20% worse than the optimal solution. We find that these techniques suffer mainly due to their inability to utilize global knowledge about flow characteristics and make coordinated decision for scheduling flows. To this end, we have developed MicroTE, a system that adapts to traffic variations by leveraging the short term and partial predictability of the traffic matrix. We implement MicroTE within the OpenFlow framework and with minor modification to the end hosts. In our evaluations, we show that our system performs close to the optimal solution and imposes minimal overhead on the network making it appropriate for current and future data centers.

Redundancy in network traffic: findings and implications

A large amount of popular content is transferred repeatedly across network links in the Internet. In recent years, protocol-independent redundancy elimination, which can remove duplicate strings from within arbitrary network flows, has emerged as a powerful technique to improve the efficiency of network links in the face of repeated data. Many vendors offer such redundancy elimination middleboxes to improve the effective bandwidth of enterprise, data center and ISP links alike. In this paper, we conduct a large scale trace-driven study of protocol independent redundancy elimination mechanisms, driven by several terabytes of packet payload traces collected at 12 distinct network locations, including the access link of a large US-based university and of 11 enterprise networks of different sizes. Based on extensive analysis, we present a number of findings on the benefits and fundamental design issues in redundancy elimination systems. Two of our key findings are (1) A new redundancy elimination algorithm based on Winnowing that outperforms the widely-used Rabin fingerprint-based algorithm by 5-10% on most traces and by as much as 35% in some traces. (2) A surprising finding that 75-90% of middleboxs bandwidth savings in our enterprise traces is due to redundant byte-strings from within each clients traffic, implying that pushing redundancy elimination capability to the end hosts, i.e. an end-to-end redundancy elimination solution, could obtain most of the middleboxs bandwidth savings.

SmartRE: an architecture for coordinated network-wide redundancy elimination

Application-independent Redundancy Elimination (RE), or identifying and removing repeated content from network transfers, has been used with great success for improving network performance on enterprise access links. Recently, there is growing interest for supporting RE as a network-wide service. Such a network-wide RE service benefits ISPs by reducing link loads and increasing the effective network capacity to better accommodate the increasing number of bandwidth-intensive applications. Further, a networkwide RE service democratizes the benefits of RE to all end-to-end traffic and improves application performance by increasing throughput and reducing latencies. While the vision of a network-wide RE service is appealing, realizing it in practice is challenging. In particular, extending single vantage-point RE solutions designed for enterprise access links to the network-wide case is inefficient and/or requires modifying routing policies. We present SmartRE, a practical and efficient architecture for network-wide RE. We show that SmartRE can enable more effective utilization of the available resources at network devices, and thus can magnify the overall benefits of network-wide RE. We prototype our algorithms using Click and test our framework extensively using several real and synthetic traces.

Understanding data center traffic characteristics

As data centers become more and more central in Internet communications, both research and operations communities have begun to explore how to better design and manage them. In this paper, we present a preliminary empirical study of end-to-end traffic patterns in data center networks that can inform and help evaluate research and operational approaches. We analyze SNMP logs collected at 19 data centers to examine temporal and spatial variations in link loads and losses. We find that while links in the core are heavily utilized the ones closer to the edge observe a greater degree of loss. We then study packet traces collected at a small number of switches in one data center and find evidence of ON-OFF traffic behavior. Finally, we develop a framework that derives ON-OFF traffic parameters for data center traffic sources that best explain the SNMP data collected for the data center. We show that the framework can be used to evaluate data center traffic engineering approaches. We are also applying the framework to design network-level traffic generators for data centers.

A comparative study of handheld and non-handheld traffic in campus Wi-Fi networks

Handheld devices such as smartphones have become a major platform for accessing Internet services. The small, mobile nature of these devices results in a unique mix of network usage. Other studies have used Wi-Fi and 3G wireless traces to analyze session, mobility, and performance characteristics for handheld devices.We complement these studies through our unique study of the differences in the content and flow characteristics of handheld versus non-handheld traffic. We analyze packet traces from two separate campus wireless networks, with 3 days of traffic for 32, 278 unique devices. Trends for handhelds include low UDP usage, high volumes of HTTP traffic, and a greater proportion of video traffic. Our observations can inform network management and mobile system design.

REfactor-ing content overhearing to improve wireless performance

Many systems have leveraged the broadcast nature of wireless radios to improve wireless capacity and performance. While conventional approaches have focused on overhearing entire packets, recent designs have argued that focusing on overheard content may be more effective. Unfortunately, key design choices in these approaches limit them from fully leveraging the benefits of overhearing content. We propose a cleaner refactoring of functionality where-in overhearing is realized at the sub-packet payload level through the use of IP-layer redundancy elimination. We show that this dramatically improves the effectiveness of prior overhearing based approaches and enables new designs, e.g., enhanced network coding, where content overhearing can be more effectively integrated to improve performance. Realizing the benefits of IP-layer content overhearing requires us to overcome challenges arising from the probabilistic nature of wireless reception (which could lead to inconsistent state) and the limited resources on wireless devices. We overcome these challenges through careful data structure and wireless redundancy elimination designs. We evaluate the effectiveness of our system using experimentation on real traces. We find that our design is highly effective: e.g., it can improve goodput by nearly 25% and air time utilization by nearly 20%.

On Store Placement for Response Time Minimization in Parallel Disks

We investigate the placement of N enterprise data-stores (e.g., database tables, application data) across an array of disks with the aim of minimizing the response time averaged over all served requests, while balancing the load evenly across all the disks in the parallel disk array. Incorporating the non-FCFS serving discipline and non work-conserving nature of disk drives in formulation of the placement problem is difficult and current placement strategies do not take them into account. We present a novel formulation of the placement problem to incorporate these crucial features and identify the runlength of requests accessing a store as the most important criterion for placing the stores. We use these insights to design a fast (running time of N logN) placement algorithm that is optimal under the assumption that transfer times are small. Comprehensive experimental studies establish the efficacy of the proposed algorithm under a wide variety of workloads with the proposed algorithm reducing the response time for real storage traces by more than a factor of 2 under heterogeneous workload scenarios.

A case for information-bound referencing

Links and content references form the foundation of the way that users interact today. Unfortunately, the links used today (URLs) are fragile since they tightly specify a protocol, host, and filename. Some past efforts have decoupled this binding to a certain degree; e.g., creating links that bind to byte-level data. We argue that these systems do not go far enough. Our key observation is that users really care about the intent of the referenced link and are relatively agnostic to the byte-level representation. Based on this observation, we argue that references should be bound to the underlying information associated with the referenced content. We call such references Information-Bound References (IBR). In this paper, we focus on the challenges of creating IBRs for multimedia data, since these form a dominant fraction of Internet traffic today. We explore the trade-offs of various alternatives for generating and using IBRs. We identify that it is possible to adapt multimedia fingerprinting algorithms in the literature to generate IBRs.

An open framework for federating integrated management model of distributed it environment

Heterogeneity has been the curse of the IT industry and systems management is no exception. As organizations are expanding their global business, and new technology and platforms are being introduced, the complexity of systems management is increasing rapidly due to heterogeneity and getting unified view of IT environments is becoming more difficult. To simplify and expedite information integration, this paper brings best practices of model-driven system and information integration to the problems of information integration in systems management. Specifically, we present an open framework for describing meta-model of a new component in isolation using UML and relating it with meta-models of other components through semantic relationships. The resulting integrated meta-model together with querying mechanisms for various sources can federate automatically and on-demand, integrated model of IT environment without relying on a central database repository.

General store placement for response time minimization in parallel disks

We investigate the placement of N enterprise data-stores (e.g., database tables, application data) across an array of disks with the aim of minimizing the response time averaged over all served requests, while balancing the load evenly across all the disks in the parallel disk array. Incorporating the non-FCFS serving discipline and non-work-conserving nature of disk drives in formulation of the placement problem is difficult and current placement strategies do not take them into account. We present a novel formulation of the placement problem to incorporate these crucial features and identify the runlength of requests accessing a store as the most important criterion for placing the stores. We use these insights to design a fast (running time of NlogN) placement algorithm that is optimal under the assumption that transfer times are small. Further, we develop polynomial-time extensions of the algorithm that minimize response time even if transfer times are large, while balancing the loads across the disks. Comprehensive experimental studies establish the efficacy of the proposed algorithm under a wide variety of workloads with the proposed algorithm reducing the response time for real storage traces by more than a factor of 2 under heterogeneous workload scenarios.