Indrajeet Singh

Computing while charging: building a distributed computing infrastructure using smartphones

Every night, a large number of idle smartphones are plugged into a power source for recharging the battery. Given the increasing computing capabilities of smartphones, these idle phones constitute a sizeable computing infrastructure. Therefore, for an enterprise which supplies its employees with smartphones, we argue that a computing infrastructure that leverages idle smartphones being charged overnight is an energy-efficient and cost-effective alternative to running tasks on traditional server infrastructure. While parallel execution and scheduling models exist for servers (e.g., MapReduce), smartphones present a unique set of technical challenges due to the heterogeneity in CPU clock speed, variability in network bandwidth, and lower availability compared to servers. In this paper, we address many of these challenges to develop CWC---a distributed computing infrastructure using smartphones. Specifically, our contributions are: (i) we profile the charging behaviors of real phone owners to show the viability of our approach, (ii) we enable programmers to execute parallelizable tasks on smartphones with little effort, (iii) we develop a simple task migration model to resume interrupted task executions, and (iv) we implement and evaluate a prototype of CWC (with 18 Android smartphones) that employs an underlying novel scheduling algorithm to minimize the makespan of a set of tasks. Our extensive evaluations demonstrate that the performance of our approach makes our vision viable. Further, we explicitly evaluate the performance of CWCs scheduling component to demonstrate its efficacy compared to other possible approaches.

CWC: A Distributed Computing Infrastructure Using Smartphones

Every night, many smartphones are plugged into a power source for recharging the battery. Given the increasing computing capabilities of smartphones, these idle phones constitute a sizeable computing infrastructure. Therefore, for an enterprise which supplies its employees with smartphones, we argue that a computing infrastructure that leverages idle smartphones being charged overnight is an energy-efficient and cost-effective alternative to running certain tasks on traditional servers. While parallel execution models and schedulers exist for servers, smartphones face a unique set of technical challenges due to the heterogeneity in CPU clock speed, variability in network bandwidth, and lower availability than servers. In this paper, we address many of these challenges to develop CWC-a distributed computing infrastructure using smartphones. We implement and evaluate a prototype of CWC that employs a novel scheduling algorithm to minimize the makespan of a set of computing tasks. Our evaluations using a testbed of 18 Android phones show that CWCs scheduler yields a makespan that is 1.6× faster than other simpler approaches.

Secret message sharing using online social media

Recently, there have been proposals to evade censors by using steganography to embed secret messages in images shared on public photo-sharing sites. However, establishing a covert channel in this manner is not straightforward. First, photo-sharing sites often process uploaded images, thus destroying any embedded message. Second, prior work assumes the existence of an out-of-band channel, using which the communicating users can exchange metadata or secret keys a priori; establishing such out-of-band channels, not monitored by censors, is difficult. In this paper, we address these issues to facilitate private communications on photo-sharing sites. In doing so, first, we conduct an in-depth measurement study of the feasibility of hiding data on four popular photo-sharing sites. Second, based on the understanding derived, we propose a novel approach for embedding secret messages in uploaded photos while preserving the integrity of such messages. We demonstrate that, despite the processing on photo-sharing sites, our approach ensures reliable covert communication, without increasing the likelihood of being detected via steganalysis. Lastly, we design and implement a scheme for bootstrapping private communications without an out-of-band channel, i.e., by exchanging keys via uploaded images.

TIDE: A User-centric Tool for Identifying Energy Hungry Applications on Smartphones

Today, many smartphone users are unaware of what applications (apps) they should stop using to prevent their battery from running out quickly. The problem is identifying such apps is hard due to the fact that there exist hundreds of thousands of apps and their impact on the battery is not well understood. We show via extensive measurement studies that the impact of an app on battery consumption depends on both environmental (wireless) factors and usage patterns. Based on this, we argue that there exists a critical need for a tool that allows a user to (a) identify apps that are energy hungry, and (b) understand why an app is consuming energy, on her phone. Towards addressing this need, we present TIDE, a tool to detect high energy apps on any particular smartphone. TIDEs key characteristic is that it accounts for usage-centric information while identifying energy hungry apps from among a multitude of apps that run simultaneously on a users phone. Our evaluation of TIDE on a testbed of Android-based smartphones, using weeklong smartphone usage traces from 17 real users, shows that TIDE correctly identifies over 94% of energy-hungry apps and has a false positive rate of < 6%.

Enabling private conversations on Twitter

User privacy has been an increasingly growing concern in online social networks (OSNs). While most OSNs today provide some form of privacy controls so that their users can protect their shared content from other users, these controls are typically not sufficiently expressive and/or do not provide fine-grained protection of information. In this paper, we consider the introduction of a new privacy control---group messaging on Twitter, with users having fine-grained control over who can see their messages. Specifically, we demonstrate that such a privacy control can be offered to users of Twitter today without having to wait for Twitter to make changes to its system. We do so by designing and implementing Twitsper, a wrapper around Twitter that enables private group communication among existing Twitter users while preserving Twitters commercial interests. Our design preserves the privacy of group information (i.e., who communicates with whom) both from the Twitsper server as well as from undesired Twitsper users. Furthermore, our evaluation shows that our implementation of Twitsper imposes minimal server-side bandwidth requirements and incurs low client-side energy consumption. Our Twitsper client for Android-based devices has been downloaded by over 1000 users and its utility has been noted by several media articles.

TIDE: A User-Centric Tool for Identifying Energy Hungry Applications on Smartphones

Today, many smartphone users are unaware of what applications (apps) they should stop using to prevent their battery from running out quickly. The problem is identifying such apps is hard due to the fact that there exist hundreds of thousands of apps and their impact on the battery is not well understood. We show via extensive measurement studies that the impact of an app on battery consumption depends on both environmental (wireless) factors and usage patterns. Based on this, we argue that there exists a critical need for a tool that allows a user to (a) identify apps that are energy hungry, and (b) understand why an app is consuming energy, on her phone. Towards addressing this need, we present TIDE, a tool to detect high energy apps on any particular smartphone. TIDEs key characteristic is that it accounts for usage-centric information while identifying energy hungry apps from among a multitude of apps that run simultaneously on a users phone. Our evaluation of TIDE on a testbed of Android-based smartphones, using weeklong smartphone usage traces from 17 real users, shows that TIDE correctly identifies over 94% of energy-hungry apps and has a false positive rate of <; 6%.

Resource Efficient Privacy Preservation of Online Social Media Conversations

On today’s online social networks (OSNs), users need to reveal their content and their sharing patterns to a central provider. Though there are proposals for decentralized OSNs to protect user privacy, they have paid scant attention to optimizing the cost borne by users or hiding their sharing patterns. In this paper, we present Hermes, a decentralized OSN architecture, designed explicitly with the goal of hiding sharing patterns while minimizing users’ costs. In doing so, Hermes tackles three key challenges: 1) it enables timely and consistent sharing of content, 2) it guarantees the confidentiality of posted private content, and 3) it hides sharing patterns from untrusted cloud service providers and users outside a private group. With extensive analyses of Hermes using traces of shared content on Facebook, we estimate that the cost borne per user will be less than

Twitsper: Tweeting privately

5 per month for over 90% of users. Our prototype implementation of Hermes demonstrates that it only adds minimal overhead to content sharing.