ROAR: increasing the flexibility and performance of distributed search

Search engines are a fundamental building block of the web. Be they general purpose web search engines, product search engines for online catalogues or people search in online networks, search engines provide easy access to a huge amount of information. To cope with large amounts of information, search engines use many distributed servers to perform their functionality. For instance, to search the web quickly, search engines partition the web index over many machines, and consult every partition when answering a query. To increase throughput, replicas are added for each of these machines. The key parameter of these search algorithms is the trade-off between replication and partitioning: increasing the partitioning level typically improves query completion time since more servers handle the query. However, partitioning too much also has drawbacks: startup costs for each sub-query are not negligible, and will decrease total throughput. Finding the right operating point and adapting to it can significantly improve performance and reduce costs. In this thesis we propose that the tradeoff between partitioning and replication should be easily configurable. To this end we introduce Rendezvous On a Ring (ROAR), a novel distributed algorithm that enables on-the-fly re-configuration of the partitioning level. ROAR can add and remove servers without stopping the system, cope with server failures, and provide good load-balancing even with a heterogeneous server pool. We experimentally show that it is possible to dynamically adjust the partitioning level to cope with different loads while meeting target query delays, and in doing so the system can reduce its power consumption significantly. To test ROAR we introduce Privacy Preserving Search: a particular search application that allows users to store encrypted data online while being able to easily search that data. Our contributions include novel protocols that allow PPS for numeric values, as well as a proof of concept implementation of PPS running on top of ROAR and allowing users to match as many as 5 million files in well under 1s

An edge-queued datagram service for all datacenter traffic

Modern datacenters support a wide range of protocols and in-network switch enhancements aimed at improving performance. Unfortunately, the resulting protocols often do not coexist gracefully because they inevitably interact via queuing in the network. In this paper we describe EQDS, a new datagram service for datacenters that moves almost all of the queuing out of the core network and into the sending host. This enables it to support multiple (conflicting) higher layer protocols, while only sending packets into the network according to any receiver-driven credit scheme. EQDS can transparently speed up legacy TCP and RDMA stacks, and enables transport protocol evolution, while benefiting from future switch enhancements without needing to modify higher layer stacks. We show through simulation and multiple implementations that EQDS can reduce FCT of legacy TCP by 2x, improve the NVMeOF-RDMA throughput by 30%, and safely run TCP alongside RDMA on the same network

Boosting mobility performance with multi-path TCP

Proceeding of: Future Network & Mobile Summit 2010, 16 - 18 June 2010, Florence, ItalyFourth Generation mobile devices incorporate multiple interfaces with diverse access technologies. The current Mobile IP protocol fails to support the enhanced fault tolerance capabilities that are enabled by the availability of multiple interfaces. In particular, established Mobile IP communications cannot be preserved through outages affecting the Home Address. In this paper we describe an architecture for mobile host multihoming that enables transport layer survivability through multiple failure modes. The proposed approach relies on the cooperation between Mobile IP and Multi-Path TCP and aims to fully support multihoming and extend roaming capabilities of mobile devices.This research was supported by Trilogy (http://www.trilogy-project.org), a research project (ICT-216372) partially funded by the European Community under its Seventh Framework Programme.European Community's Seventh Framework ProgramNo publicad

Choreo: network-aware task placement for cloud applications

Cloud computing infrastructures are increasingly being used by network-intensive applications that transfer significant amounts of data between the nodes on which they run. This paper shows that tenants can do a better job placing applications by understanding the underlying cloud network as well as the demands of the applications. To do so, tenants must be able to quickly and accurately measure the cloud network and profile their applications, and then use a network-aware placement method to place applications. This paper describes Choreo, a system that solves these problems. Our experiments measure Amazon's EC2 and Rackspace networks and use three weeks of network data from applications running on the HP Cloud network. We find that Choreo reduces application completion time by an average of 8%-14% (max improvement: 61%) when applications are placed all at once, and 22%-43% (max improvement: 79%) when they arrive in real-time, compared to alternative placement schemes.National Science Foundation (U.S.) (Grant 0645960)National Science Foundation (U.S.) (Grant 1065219)National Science Foundation (U.S.) (Grant 1040072

How Hard Can It Be? Designing and Implementing a Deployable Multipath TCP

Networks have become multipath: mobile devices have multiple radio interfaces, datacenters have redundant paths and multihoming is the norm for big server farms. Mean- while, TCP is still only single-path. Is it possible to extend TCP to enable it to support multiple paths for current applications on today’s Internet? The answer is positive. We carefully review the constraints—partly due to various types of middleboxes— that influenced the design of Multipath TCP and show how we handled them to achieve its deployability goals. We report our experience in implementing Multipath TCP in the Linux kernel and we evaluate its performance. Our measurements focus on the algorithms needed to efficiently use paths with different characteristics, notably send and receive buffer tuning and segment reordering. We also compare the performance of our implementation with regular TCP on web servers. Finally, we discuss the lessons learned from designing MPTCP

WhiteHaul: An Efficient Spectrum Aggregation System for Low-Cost and High Capacity Backhaul over White Spaces

We address the challenge of backhaul connectivity for rural and developing regions, which is essential for universal fixed/mobile Internet access. To this end, we propose to exploit the TV white space (TVWS) spectrum for its attractive properties: low cost, abundance in under-served regions and favorable propagation characteristics. Specifically, we propose a system called WhiteHaul for the efficient aggregation of the TVWS spectrum tailored for the backhaul use case. At the core of WhiteHaul are two key innovations: (i) a TVWS conversion substrate that can efficiently handle multiple non-contiguous chunks of TVWS spectrum using multiple low cost 802.11n/ac cards but with a single antenna; (ii) novel use of MPTCP as a link-level tunnel abstraction and its use for efficiently aggregating multiple chunks of the TVWS spectrum via a novel uncoupled, cross-layer congestion control algorithm. Through extensive evaluations using a prototype implementation of WhiteHaul, we show that: (a) WhiteHaul can aggregate almost the whole of TV band with 3 interfaces and achieve nearly 600Mbps TCP throughput; (b) the WhiteHaul MPTCP congestion control algorithm provides an order of magnitude improvement over state of the art algorithms for typical TVWS backhaul links. We also present additional measurement and simulation based results to evaluate other aspects of the WhiteHaul design