Iqbal Mohomed

WhereStore: location-based data storage for mobile devices interacting with the cloud

In recent years, two major trends have changed the way mobile phones are used: smartphones have become a platform for applications, and 3G connectivity has turned them into ubiquitous Internet clients. Increasingly, applications on smartphones (such as document sharing, media players and map browsers) interact with the cloud as a backend for data storage and computation. We observe that, for many mobile applications, the specific data that is accessed depends on the current location of the user. For example, a restaurant recommendation application is often used to get information about nearby restaurants. In this paper, we present WhereStore, a location-based data store for smart-phones interacting with the cloud. It uses filtered replication along with each devices location history to distribute items between smartphones and the cloud. We discuss the challenges of designing such a system, relevant applications, and a specific design and prototype implementation.

Where's that phone?: geolocating IP addresses on 3G networks

Cell phones connected to high-speed 3G networks constitute an increasingly important class of clients on the Internet. From the viewpoint of the servers they connect to, such devices are virtually indistinguishable from conventional end-hosts. In this study, we examine the IP addresses seen by Internet servers for cell phone clients and make two observations. First, individual cell phones can expose different IP addresses to servers within time spans of a few minutes, rendering IP-based user identification and blocking inadequate. Second, cell phone IP addresses do not embed geographical information at reasonable fidelity, reducing the effectiveness of commercial geolocation tools used by websites for fraud detection, server selection and content customization. In addition to these two observations, we show that application-level latencies between cell phones and Internet servers can differ greatly depending on the location of the cell phone, but do not vary much at a given location over short time spans; as a result, they provide fine-grained location information that IPs do not.

StarTrack: a framework for enabling track-based applications

Mobile devices are increasingly equipped with hardware and software services allowing them to determine their locations, but support for building location-aware applications remains rudimentary. This paper proposes tracks of location coordinates as a high-level abstraction for a new class of mobile applications including ride sharing, location-based collaboration, and health monitoring. Each track is a sequence of entries recording a persons time, location, and application-specific data. StarTrack provides applications with a comprehensive set of operations for recording, comparing, clustering and querying tracks. StarTrack can efficiently operate on thousands of tracks.

Performance Evaluation of Microservices Architectures Using Containers

Micro services architecture has started a new trend for application development for a number of reasons: (1) to reduce complexity by using tiny services, (2) to scale, remove and deploy parts of the system easily, (3) to improve flexibility to use different frameworks and tools, (4) to increase the overall scalability, and (5) to improve the resilience of the system. Containers have empowered the usage of micro services architectures by being lightweight, providing fast start-up times, and having a low overhead. Containers can be used to develop applications based on monolithic architectures where the whole system runs inside a single container or inside a micro services architecture where one or few processes run inside the containers. Two models can be used to implement a micro services architecture using containers: master-slave, or nested-container. The goal of this work is to compare the performance of CPU and network running benchmarks in the two aforementioned models of micro services architecture hence provide a benchmark analysis guidance for system designers.

Analysis of Data from a Taxi Cab Participatory Sensor Network

Mobile participatory sensing applications are becoming quite popular, where individuals with mobile sensing devices such as smartphones, music players, and in-car GPS devices collect sensor data and share it with an external entity to compute statistics of mutual interest or map common phenomena. In this paper, we present an analysis of the data from a real-world city-scale mobile participatory sensor network comprised of about two thousand taxi cabs. Our analysis spans data collected from the taxi cab sensor network over the course of a year and we use it to make inferences about life in the city. The large scale data collection (size and time) from these taxi cabs allows us to examine various aspects about life in a city such as busy “party” times in the city, peak taxi usage (space and time), most traveled streets, and travel patterns on holidays. We also provide a summary of lessons learned from our analysis that can aid similar city-scale deployments and their analyses in the future.

THE Age of DIY and Dawn of the Maker Movement

HELLO, WORLD! We live in interesting times. While people have been “making” things for quite a while, the last few years has seen the emergence of a distinctive maker and DIY (“do-it-yourself ”) culture all around the world. One interesting facet of the maker culture is its pervasiveness. One does not need a PhD or professional license to be a part of this culture. It is pop culture at its finest! The cost of building a small, interesting robot today is really only a few hundred US dollars. A decent 3D printer can be built for under five hundred (not including ink). There are reasonable digital oscilloscopes that fit inside a watch or plug inside your PC. The precipitous drop in cost of materials and equipment, along with the widespread dissemination of knowledge via low barrier mediums like online videos and the web have all had a hand in making “DIY” easier than ever before. At the heart of the maker world is a collaborative community spirit, whether it is about sharing designs, working collaboratively in a shared space (a.k.a. “hackerspaces”), raising funds from a broad community of interest, or showing off your cool project at venues such as Makerfaire. The community of makers utilizes traditional manufacturing techniques (e.g., woodand metal-working). The special twist is that one does not need to go through an apprenticeship process and commit to years of study along with a vocation. Rather, one can simply find the closest hackerspace and join up or organize a course on PCB (“Printed Circuit Board”) design, soldering, or forging pendants by melting discarded coke cans. In addition, there are some enabling technologies – single board microcontrollers and 3D printers that became popular among the hobbyist communities over the last few years. These are distinct faces of the maker community. Finally, there are a plethora of applications that the maker community is interested in. This changes over time but recently, there is great interest in small robots, flying drones and quantifying one’s daily routines and habits. In this piece, we’ll be exploring some of these broad trends.

Enabling mobile application mashups with Merlion

We present Merlion, a system that enables end-users to build custom mobile applications by creating mashups from existing desktop applications. The original application executes on a machine running remote desktop software (such as VNC server) without any modifications. Users can utilize the Merlion Designer to select relevant visual regions of the original application and create an alternate layout that is more suitable to their circumstances (e.g. taking the screen real-estate of their mobile device into account). Once the custom application has been designed, the user can utilize the Merlion Runtime (running on the users mobile device) to interact with their custom application. Merlion can improve user productivity by simplifying user interfaces, automate repetitive actions, make applications available across different mobile form factors, and can allow applications that work on different OS platforms to operate in concert. In this paper, we describe the design of the Merlion system, details of our initial prototype, and discussion of the benefits and challenges of our approach.

COLD: Cloud Optimized Workload Deployer

We demonstrate a prototype system called COLD that we are developing at IBM Research which provides optimized deployment of workload in the cloud. A workload refers to an application, consisting of virtual entities (e.g. VM, volume), to be deployed in a cloud infrastructure, consisting of physical entities (e.g. PM, storage). The resource requirements of the virtual entities, as well as metadata describing relations among virtual entities (e.g. location proximity requirement), are described using a declarative workload definition language, namely using a HOT template. COLD provides a clean separation between the underlying mechanisms offered by a given cloud environment for lifecycle management of virtual resources and policies that influence optimal placement. The current implementation of COLD is tied to Open Stack, though we have plans in the future to make it cloud agnostic. It is designed to be fault-tolerant. In a software defined environment of an Open Stack cloud with various hyper visors, we show the operation of COLD to place various Heat stacks that contain specific policies such as rack-level antic location.