Users are often frustrated when they cannot view video links shared via blogs, social networks, and shared bookmark sites on their devices or suffer performance and usability problems when doing so. While other versions of the same content better suited to their device and network constraints may be available on other third-party hosting sites, these remain unusable because users cannot efficiently discover these and verify that these variants match the content publisher's original intent. Our vision is to enable consumers to leverage verifiable alternatives from different hosting sites that are best suited to their constraints to deliver a high quality of experience and enable content publishers to reach a wide audience with diverse operating conditions with minimal upfront costs. To this end, we make a case for information-bound references or IBRs that bind references to video content to the underlying information that a publisher wants to convey, decoupled from details such as protocols, hosts, file names, or the underlying bits. This paper addresses key challenges in the design and implementation of IBR generation and resolution mechanisms, and presents an evaluation of the benefits IBRs offer.

Mobile web usage has significantly increased in last few years. There has been a lot of emphasis on providing good web page performance for mobile devices. Client-side caching can play a significant role in providing good web page performance, but unfortunately, traditional browser caches lack in various aspects leading to sub-optimal performance. More specifically, web applications do not have control on caching, e.g., which resources to cache, how to cache, etc., leading to ineffective cache utilization. Recently, HTML5 has introduced number of persistent storage APIs, that can provide required control for web applications. We evaluate these HTML5 storage options on various devices, and find that they can also meet the performance criteria of caching; in fact, some of the HTML5 storage APIs, e.g., localStorage, can provide even better performance than browser cache. Based on these insights, we make a case for application-managed hierarchical client-side cache, called HCache, that leverages these storage options as backends. We propose a novel API that allows web application developers to intelligently control the caching behavior and the usage of these storage options transparently. Our experiments with a prototype show that HCache can improve web page performance by up to 60%.

A number of data-intensive systems require using random hash-based indexes of various forms, e.g., hash tables, Bloom filters, and locality sensitive hash tables. In this paper, we present general SSD optimization techniques that can be used to design a variety of such indexes while ensuring higher performance and easier tunability than specialized state-of-the-art approaches. We leverage two key SSD innovations: a) rearranging the data layout on the SSD to combine multiple read requests into one page read, and b) intelligently reordering requests to exploit inherent parallelism in the architecture of SSDs. We build three different indexes using these techniques, and we conduct extensive studies showing their superior performance, lower CPU/memory footprint, and tunability compared to state-of-the-art systems.

The current IaaS model has several shortcomings. First, several IaaS providers only offers VM (virtual machine) with predefined sizes, thus enterprise tenants must judiciously determine the VM size that best fit their application. This is challenging as overprovisioning VMs can lead to waste of resources while underprovisioned VMs can lead to poor performance. Second, when an application requires more resources than a VM can provide, tenants are currently limited to either scaling-out or scaling-up their applications. However, in both situations the granularity is at the level of VMs which leads to sizing issues discussed earlier. Third, scaling-up is ineffective as it incurs a significant amount of downtime/poor performance while the new VM is being provisioned and not all applications support scaling-out. For example while, Web servers can be easily scaled-out other legacy applications can not [1], thus limiting its applicability.

The progress of a big data job is often a function of storage, networking and processing. Hence, for efficient job execution, it is important to collectively optimize all three components. Prior proposals [1], in contrast, have focused on mainly on one or two of the three components. This narrow focus constraints the extent to which these proposals can support efficient operation of big data applications.

Users are often frustrated when they cannot view video links shared via blogs, social networks, and shared bookmark sites on their devices or suffer performance and usability problems when doing so. While other versions of the same content better suited to their device and network constraints may be available on other third-party hosting sites, these remain unusable because users cannot efficiently discover these and verify that these variants match the content publisher's original intent. Our vision is to enable consumers to leverage verifiable alternatives from different hosting sites that are best suited to their constraints to deliver a high quality of experience and enable content publishers to reach a wide audience with diverse operating conditions with minimal upfront costs. To this end, we make a case for information-bound references or IBRs that bind references to video content to the underlying information that a publisher wants to convey, decoupled from details such as protocols, hosts, file names, or the underlying bits. This paper addresses key challenges in the design and implementation of IBR generation and resolution mechanisms, and presents an evaluation of the benefits IBRs offer.

Data centers provide resources for a broad range of services, such as web search, email, web sites, etc., each with different delay requirements. For example, web search should cater to users' requests quickly, while data backup has no special requirement on completion time. Different applications also introduce flows with very different properties (e.g., size and duration). The default method of transport in data centers, namely TCP, treats flows equally, forcing equal share of the bottleneck network bandwidth. This fairness property leads to poor outcomes for time-sensitive applications. A better solution is to allocate more bandwidth to time-sensitive applications. However, the state-of-the-art approaches that do this all require forklift changes to data center networking gear. In some cases, substantial changes need to be made to end-system stacks and applications as well. In this paper, we argue that a simple modification to TCP can help better meet the requirements of latency-sensitive applications in the data center. No modification to end-systems, applications or networking gear is necessary. We motivate our Adaptive TCP (ATCP) design using measurements of real data center traffic. We analytically derive the parameters to use in our proposed modification to TCP. Finally, we use extensive simulations in NS2 to show the benefits of ATCP.

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.

Motivated by limitations in today's host-based IP network architecture, recent studies have proposed clean-slate network architectures centered around alternative first-class principals, such as content, services, or users. However, much like the host-centric IP design, elevating one principal type above others hinders communication between other principals and inhibits the network's capability to evolve. Our work presents the eXpressive Internet Architecture (XIA), an architecture with native support for multiple principals and the ability to evolve its functionality to accommodate new, as yet unforeseen, principals over time. XIA also provides intrinsic security: communicating entities validate that their underlying intent was satisfied correctly without relying on external databases or configuration.

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%.

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.

Multimedia content is a dominant fraction of Internet usage today. At the same time, there is significant heterogeneity in video presentation modes and operating conditions of Internet-enabled devices that access such content. Users are often interested in the content, rather than the specific sources or the formats. The host-centric format of the current Internet does not support these requirements naturally. Neither do the recent data-centric naming proposals, since they rely on naming content based on raw byte-level hashing schemes. We argue that to meet these requirements, enabling content retrieval mechanisms to name and query directly for the underlying information is a good way forward. In addition to decoupling content from available sources and transfer protocols, these "information-aware names" or InfoNames explicitly decouple the information from content presentation factors as well. We envision an InfoName Resolution System (IRS) to resolve location based on InfoNames, while taking into account the operating conditions of devices. In this demo, we present an application to show how InfoNames can serve as presentation-invariant and portable names to fetch video content independent of device capabilities and resource constraints.

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.

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.

Many past systems have explored how to eliminate redundant transfers from network links and improve network efficiency. Several of these systems operate at the application layer, while the more recent systems operate on individual packets. A common aspect of these systems is that they apply to localized settings, e.g. at stub network access links. In this paper, we explore the benefits of deploying packet-level redundant content elimination as a universal primitive on all Internet routers. Such a universal deployment would immediately reduce link loads everywhere. However, we argue that far more significant network-wide benefits can be derived by redesigning network routing protocols to leverage the universal deployment. We develop "redundancy-aware" intra- and inter-domain routing algorithms and show that they enable better traffic engineering, reduce link usage costs, and enhance ISPs' responsiveness to traffic variations. In particular, employing redundancy elimination approaches across redundancy-aware routes can lower intra and inter-domain link loads by 10-50%. We also address key challenges that may hinder implementation of redundancy elimination on fast routers. Our current software router implementation can run at OC48 speeds.

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.

We present a framework and tool for porting assessment and code remediation in commercial porting projects, primarily targeting interplatform C/C++ porting. Our framework has a modular architecture for handling real-world code bases, a key part of which is an extensible knowledge base of porting issue types. Porting issue detection and remediation are achieved through dynamically-linked detector and remediation "plug-ins" which can be augmented over time. Analysis and remediation can be performed over multiple intermediate forms, such as the AST or error logs. Analysis and remediation results can be presented as a single assessment report, or the changes can be incorporated into the original code base. Furthermore our framework has been integrated into Eclipse, providing a user interface and allowing further capability for integration with other Eclipse extensions. A subset of our tool has been prototyped and benchmarked against real-world customer code.