Vatche Ishakian

Angels in the Cloud: A Peer-Assisted Bulk-Synchronous Content Distribution Service

Leveraging client upload capacity through peer assisted content distribution was shown to decrease the load on content providers, while also improving average distribution times. These benefits, however, are limited by the disparity between client upload and download speeds, especially in scenarios requiring a minimum distribution time (MDT) of a fresh piece of content to a set of clients. Achieving MDT is crucial for bulk-synchronous applications, when every client in a set must wait for all other clients in the set to finish their downloads before being able to make use of the downloaded content. In this paper, we propose the use of dedicated servers, which we call angels to accelerate peer-assisted content distribution in general, and to minimize MDT in particular. An angel is not itself the content origin, nor is it interested in fully downloading the content, its only purpose is to enable a peer assisted content distribution scheme to approach the theoretical lower-bound for MDT. To overcome scalability issues inherent in an optimal MDT construction, we propose and evaluate a content exchange strategy involving angels, which we call Group Tree. In addition to simulation results that demonstrate the near optimal performance of our proposed approach, we present the architecture and implementation of CLOUDANGELS -- a service that allows the elastic, on-the-fly deployment of angels (in the cloud) to assist a content provider (off the cloud) in realizing its MDT objective.

Building a Chatbot with Serverless Computing

Chatbots are emerging as the newest platform used by millions of consumers worldwide due in part to the commoditization of natural language services, which provide provide developers with many building blocks to create chatbots inexpensively. However, it is still difficult to build and deploy chatbots. Developers need to handle the coordination of the cognitive services to build the chatbot interface, integrate the chatbot with external services, and worry about extensibility, scalability, and maintenance. In this work, we present the architecture and prototype of a chatbot using a serverless platform, where developers compose stateless functions together to perform useful actions. We describe our serverless architecture based on function sequences, and how we used these functions to coordinate the cognitive microservices in the Watson Developer Cloud to allow the chatbot to interact with external services. The serverless model improves the extensibility of our chatbot, which currently supports 6 abilities: location based weather reports, jokes, date, reminders, and a simple music tutor.

Serverless Computing: Current Trends and Open Problems

Serverless computing has emerged as a new compelling paradigm for the deployment of applications and services. It represents an evolution of cloud programming models, abstractions, and platforms, and is a testament to the maturity and wide adoption of cloud technologies. In this chapter, we survey existing serverless platforms from industry, academia, and open-source projects, identify key characteristics and use cases, and describe technical challenges and open problems.

Colocation as a Service: Strategic and Operational Services for Cloud Colocation

By colocating with other tenants of an Infrastructure as a Service (IaaS) offering, IaaS users could reap significant cost savings by judiciously sharing their use of the fixed-size instances offered by IaaS providers. This paper presents the blueprints of a Colocation as a Service (CaaS) framework. CaaS strategic services identify coalitions of self-interested users that would benefit from colocation on shared instances. CaaS operational services provide the information necessary for, and carry out the reconfigurations mandated by strategic services. CaaS could be incorporated into an IaaS offering by providers; it could be implemented as a value-added proposition by IaaS resellers; or it could be directly leveraged in a peer-to-peer fashion by IaaS users. To establish the practicality of such offerings, this paper presents XCS – a prototype implementation of CaaS on top of the Xen hypervisor. XCS makes specific choices with respect to the various elements of the CaaS framework: it implements strategic services based on a game-theoretic formulation of colocation; it features novel concurrent migration heuristics which are shown to be efficient; and it offers monitoring and accounting services at both the hypervisor and VM layers. Extensive experimental results obtained by running PlanetLab trace-driven workloads on the XCS prototype confirm the premise of CaaS – by demonstrating the efficiency and scalability of XCS, and by quantifying the potential cost savings accrued through the use of XCS.

On supporting mobility and multihoming in recursive internet architectures

As the Internet has evolved and grown, an increasing number of nodes (hosts or autonomous systems) have become multihomed, i.e., a node is connected to more than one network. Mobility can be viewed as a special case of multihoming-as a node moves, it unsubscribes from one network and subscribes to another, which is akin to one interface becoming inactive and another active. The current Internet architecture has been facing significant challenges in effectively dealing with multihoming (and consequently mobility), which has led to the emergence of several custom point-solutions. The Recursive InterNetwork Architecture (RINA) was recently proposed as a clean-slate solution to the current problems of the Internet. In this paper, we present a specification of the process of ROuting in Recursive Architectures (RORA). We also perform an average-case cost analysis to compare the multihoming/mobility support of RINA, against that of other approaches such as LISP and Mobile-IP. Extensive experimental results confirm the premise that the RINA architecture and its RORA routing approach are inherently better suited for supporting mobility and multihoming.

A Divide-and-Conquer Algorithm for Betweenness Centrality

Given a set of target nodes S in a graph G we dene the betweenness centrality of a node v with respect to S as the fraction of shortest paths among nodes in S that contain v. For this setting we describe Brandes++, a divide-and-conquer algorithm that can eciently compute the exact values of betweenness scores. Brandes++ uses Brandes{ the most widelyused algorithm for betweenness computation { as its subroutine. It achieves the notable faster running times by applying Brandes on signicantly smaller networks than the input graph, and many of its computations can be done in parallel. The degree of speedup achieved by Brandes++ depends on the community structure of the input network as well as the size of S. Our experiments with real-life networks reveal Brandes++ achieves an average of 10-fold speedup over Brandes, while there are networks where this speedup is 75-fold. We have made our code public to benet the research community.

The filter-placement problem and its application to minimizing information multiplicity

In many information networks, data items -- such as updates in social networks, news flowing through interconnected RSS feeds and blogs, measurements in sensor networks, route updates in ad-hoc networks -- propagate in an uncoordinated manner: nodes often relay information they receive to neighbors, independent of whether or not these neighbors received the same information from other sources. This uncoordinated data dissemination may result in significant, yet unnecessary communication and processing overheads, ultimately reducing the utility of information networks. To alleviate the negative impacts of this information multiplicity phenomenon, we propose that a subset of nodes (selected at key positions in the network) carry out additional information filtering functionality. Thus, nodes are responsible for the removal (or significant reduction) of the redundant data items relayed through them. We refer to such nodes as filters. We formally define the Filter Placement problem as a combinatorial optimization problem, and study its computational complexity for different types of graphs. We also present polynomial-time approximation algorithms and scalable heuristics for the problem. Our experimental results, which we obtained through extensive simulations on synthetic and real-world information flow networks, suggest that in many settings a relatively small number of filters are fairly effective in removing a large fraction of redundant information.

MORPHOSYS: Efficient Colocation of QoS-Constrained Workloads in the Cloud

In hosting environments such as IaaS clouds, desirable application performance is usually guaranteed through the use of Service Level Agreements (SLAs), which specify minimal fractions of resource capacities that must be allocated for unencumbered use for proper operation. Arbitrary colocation of applications with different SLAs on a single host may result in inefficient utilization of the hosts resources. In this paper, we propose that periodic resource allocation and consumption models -- often used to characterize real-time workloads -- be used for a more granular expression of SLAs. Our proposed SLA model has the salient feature that it exposes flexibilities that enable the infrastructure provider to safely transform SLAs from one form to another for the purpose of achieving more efficient colocation. Towards that goal, we present MORPHOSYS: a framework for a service that allows the manipulation of SLAs to enable efficient colocation of arbitrary workloads in a dynamic setting. We present results from extensive trace-driven simulations of colocated Video-on-Demand servers in a cloud setting. These results show that potentially-significant reduction in wasted resources (by as much as 60%) are possible using MORPHOSYS.

On the cost of supporting mobility and multihoming

As the Internet has evolved and grown, an increasing number of nodes (hosts or autonomous systems) have become multihomed, i.e., a node is connected to more than one network. Multihoming can be viewed as a special case of mobility-as a node moves, it unsubscribes from one network and subscribes to another, which is akin to one interface becoming inactive and another active. The current Internet architecture has been facing significant challenges in effectively dealing with mobility (and consequently multihoming). The Recursive InterNetwork Architecture (RINA) [1] was recently proposed as a clean-slate solution to the current problems of the Internet. In this paper, we perform an average-case cost analysis to compare the mobility / multihoming support of RINA, against that of other approaches such as LISP and Mobile-IP. We also validate our analysis using simulation.

A Type-Theoretic Framework for Efficient and Safe Colocation of Periodic Real-Time Systems

Desirable application performance is typically guaranteed through the use of Service Level Agreements (SLAs) that specify fixed fractions of resource capacities that must be allocated for unencumbered use by the application. The mapping between what constitutes desirable performance and SLAs is not unique: multiple SLA expressions might be functionally equivalent. Having the flexibility to transform SLAs from one form to another in a manner that is provably safe would enable hosting solutions to achieve significant efficiencies. This paper demonstrates the promise of such an approach by proposing a type-theoretic framework for the representation and safe transformation of SLAs. Based on that framework, the paper describes a methodical approach for the inference of efficient and safe mappings of periodic, real-time tasks to the physical and virtual hosts that constitute a hierarchical scheduler. Extensive experimental results support the conclusion that the flexibility afforded by safe SLA transformations has the potential to yield significant savings.