Nafize Paiker

Moitree: A Middleware for Cloud-Assisted Mobile Distributed Apps

This paper presents Moitree, the middleware of our Avatar platform for mobile cloud computing. Av... more This paper presents Moitree, the middleware of our Avatar platform for mobile cloud computing. Avatar leverages cloud resources to support fast, scalable, reliable, and energy efficient distributed computing over mobile devices. Each mobile device is augmented by an avatar, a per-user always-on software entity that resides in the cloud and acts as the surrogate of the mobile device, to the extent possible, thus reducing the workload and the demand for storage, bandwidth, and energy on the mobiles. Moitree provides: (1) a novel middleware which allows unmodified apps to execute seamlessly over mobile/avatar pairs with the provision of offloading computation and communication, and (2) a new programming framework to simplify mobile collaborative app development. The programming framework has two key features: (1) user collaborations are modeled using natural group semantics-groups are created dynamically based on context and are hierarchical. (2) data communication is offloaded to the cloud through high-level communication channels. A prototype of Moitree, along with several apps, has been implemented and evaluated on Android devices and on an OpenStack-based cloud running Android x86 avatars.

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Design and Implementation of an Overlay File System for Cloud-Assisted Mobile Apps

IEEE Transactions on Cloud Computing, 2020

With cloud assistance, mobile apps can offload their resource-demanding computation tasks to the ... more With cloud assistance, mobile apps can offload their resource-demanding computation tasks to the cloud. This leads to a scenario where computation tasks in the same program run concurrently on both the mobile device and the cloud. An important challenge is to ensure that the tasks are able to access and share the files on both the mobile and the cloud in a manner that is efficient, consistent, and transparent to locations. Existing distributed file systems and network file systems do not satisfy these requirements. Current systems for offloading tasks either do not support file access for offloaded tasks or do not offload tasks with file access. The paper addresses this issue by designing and implementing an application-level file system called Overlay File System (OFS). To improve efficiency, OFS maintains and buffers local copies of data sets on both the cloud and the mobile device. OFS ensures consistency and guarantees that all the reads get the latest data. It combines write-invalidate and write-update policies to effectively reduce the network traffic incurred by invalidating/updating stale data copies and to reduce the execution delay when the latest data cannot be accessed locally. To guarantee location transparency, OFS creates a unified view of the data that is location independent and is accessible as local storage. We overcome the challenges caused by the special features of mobile systems on an application-level file system, like the lack of root privilege and state loss when application is killed due to the shortage of resource and implement an easy to deploy prototype of OFS. The paper tests the OFS prototype on Android OS with a real mobile app and real mobile user traces. Extensive experiments show that OFS can effectively support consistent file accesses from computation tasks, no matter whether they are on a mobile device or offloaded to the cloud. In addition, OFS reduce both file access latency and network traffic incurred by file accesses.

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Context-Aware File Discovery System for Distributed Mobile-Cloud Apps

Recent research has proposed middleware to enable efficient distributed apps over mobile-cloud pl... more Recent research has proposed middleware to enable efficient distributed apps over mobile-cloud platforms. This paper presents a Context-Aware File Discovery Service (CAFDS) that allows distributed mobile-cloud applications to find and access files of interest shared by collaborating users. CAFDS enables programmers to search for files defined by context and content features, such as location, creation time, or the presence of certain object types within an image file. CAFDS provides low-latency through a cloud-based metadata server, which uses a decision tree to locate the nearest files that satisfy the context and content features requested by applications. We implemented CAFDS in Android and Linux. Experimental results show CAFDS achieves substantially lower latency than peer-to-peer solutions that cannot leverage context information.

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Storage systems for mobile-cloud applications

Mobile devices have become the major computing platform in todays world. However, some applicatio... more Mobile devices have become the major computing platform in todays world. However, some applications on mobile devices still suffer from insufficient computing and energy resources. A key solution is to offload resource-demanding computing tasks from mobile devices to the cloud. This leads to a scenario where computing tasks in the same application run concurrently on both the mobile device and the cloud. This dissertation aims to ensure that the tasks in a mobile application that employs offloading can access and share files concurrently on the mobile and the cloud in a manner that is efficient, consistent, and transparent to locations. Existing distributed file systems and network file systems do not satisfy these requirements. Furthermore, current offloading platforms either do not support efficient file access for offloaded tasks or do not offload tasks with file accesses.

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MEFS: Mobile Edge File System for Edge-Assisted Mobile Apps

Computation offloading is employed by mobile apps running over resource-constrained devices to le... more Computation offloading is employed by mobile apps running over resource-constrained devices to leverage the cloud in overcoming their resource limits. The advent of the Multi-access Edge Computing (MEC) paradigm further extends the potential opportunities of mobile-cloud offloading, allowing new service provisioning scenarios, such as mobile gaming and multimedia, where responsiveness of mobile devices at the network edge significantly benefits from low latency interactions. However, state-of-the-art offloading platforms for MEC architectures have not addressed the technical challenge of supporting specific file systems for this MEC-enabled class of applications, with components running at three hosting environments, i.e., mobile, edge, and cloud. This paper proposes the Mobile Edge File System (MEFS), an application-level distributed file system designed to be highly resilient and able to efficiently maintain consistency among the mobile, edge, and cloud entities. MEFS supports application handoff through live migration as end devices move between edges. The cloud transparently helps with recovery from faulty edge nodes or in the case of unavailability of edges in the user's proximity. We implemented a MEFS prototype in Android along with MEFSbased MEC-enabled mobile apps. The experimental results show how MEFS can achieve low latency and low overhead.

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An Overlay File System for cloud-assisted mobile applications

With cloud assistance, a mobile application can offload its resource-demanding computation tasks ... more With cloud assistance, a mobile application can offload its resource-demanding computation tasks to the cloud (public cloud, cloudlet, or personal cloud, etc). This leads to a scenario where computation tasks in the same application run concurrently on both the mobile device and the cloud. These tasks need to save, read, and write files on both the mobile device and the cloud. An important challenge is to ensure that the tasks are able to access and share the files in a manner that is efficient, consistent, and transparent to locations. The paper addresses this issue by designing an application-level file system called Overlay File System (OFS). To improve efficiency, OFS maintains and buffers local copies of data sets on both the cloud and the mobile device. OFS ensures consistency and guarantees that all the reads get the latest data. It combines write-invalidate and writeupdate policies to effectively reduce the network traffic incurred by invalidating/updating stale data copies and to reduce the application delay when the latest data cannot be accessed locally. To guarantee location transparency, OFS creates an unified view of the data that is location independent and is accessible as local storage. Our experiments show that OFS can effectively support task offloading and efficient execution of offloaded tasks by significantly decreasing both file access latency and network traffic incurred by file accesses.

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Context-Aware File Discovery System for Distributed Mobile-Cloud Apps

2018 IEEE International Conference on Cloud Computing Technology and Science (CloudCom), 2018

Recent research has proposed middleware to enable efficient distributed apps over mobile-cloud pl... more Recent research has proposed middleware to enable efficient distributed apps over mobile-cloud platforms. This paper presents a Context-Aware File Discovery Service (CAFDS) that allows distributed mobile-cloud applications to find and access files of interest shared by collaborating users. CAFDS enables programmers to search for files defined by context and content features, such as location, creation time, or the presence of certain object types within an image file. CAFDS provides low-latency through a cloud-based metadata server, which uses a decision tree to locate the nearest files that satisfy the context and content features requested by applications. We implemented CAFDS in Android and Linux. Experimental results show CAFDS achieves substantially lower latency than peer-to-peer solutions that cannot leverage context information.

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Storage systems for mobile-cloud applications

Mobile devices have become the major computing platform in todays world. However, some applicatio... more Mobile devices have become the major computing platform in todays world. However, some applications on mobile devices still suffer from insufficient computing and energy resources. A key solution is to offload resource-demanding computing tasks from mobile devices to the cloud. This leads to a scenario where computing tasks in the same application run concurrently on both the mobile device and the cloud. This dissertation aims to ensure that the tasks in a mobile application that employs offloading can access and share files concurrently on the mobile and the cloud in a manner that is efficient, consistent, and transparent to locations. Existing distributed file systems and network file systems do not satisfy these requirements. Furthermore, current offloading platforms either do not support efficient file access for offloaded tasks or do not offload tasks with file accesses.

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MEFS: Mobile Edge File System for Edge-Assisted Mobile Apps

2019 IEEE 20th International Symposium on "A World of Wireless, Mobile and Multimedia Networks" (WoWMoM), 2019

Computation offloading is employed by mobile apps running over resource-constrained devices to le... more Computation offloading is employed by mobile apps running over resource-constrained devices to leverage the cloud in overcoming their resource limits. The advent of the Multi-access Edge Computing (MEC) paradigm further extends the potential opportunities of mobile-cloud offloading, allowing new service provisioning scenarios, such as mobile gaming and multimedia, where responsiveness of mobile devices at the network edge significantly benefits from low latency interactions. However, state-of-the-art offloading platforms for MEC architectures have not addressed the technical challenge of supporting specific file systems for this MEC-enabled class of applications, with components running at three hosting environments, i.e., mobile, edge, and cloud. This paper proposes the Mobile Edge File System (MEFS), an application-level distributed file system designed to be highly resilient and able to efficiently maintain consistency among the mobile, edge, and cloud entities. MEFS supports application handoff through live migration as end devices move between edges. The cloud transparently helps with recovery from faulty edge nodes or in the case of unavailability of edges in the user's proximity. We implemented a MEFS prototype in Android along with MEFSbased MEC-enabled mobile apps. The experimental results show how MEFS can achieve low latency and low overhead.

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FaceDate: A Mobile Cloud Computing App for People Matching

Proceedings of the 11th International Conference on Body Area Networks, 2017

is paper presents FaceDate, a novel mobile app that matches persons based on their facial looks. ... more is paper presents FaceDate, a novel mobile app that matches persons based on their facial looks. Each FaceDate user uploads their pro le face photo and trains the app with photos of faces they like. Upon user request, FaceDate detects other users located in the proximity of the requester and performs face matching in real-time. If a mutual match is found, the two users are noti ed and given the option to start communicating. FaceDate is implemented over our Moitree middleware for mobile distributed computing assisted by the cloud. e app is designed to scale with the number of users, as face recognition is done in parallel at di erent users. FaceDate can be con gured for (i) higher performance, in which case the face recognition is done in the cloud or (ii) higher privacy, in which case the face recognition is done on the mobiles. e experimental results with Android-based phones demonstrate that FaceDate achieves promising performance. CCS Concepts •Human-centered computing →Mobile computing; •Computer systems organization →Cloud computing; •So ware and its engineering →Middleware;

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Design and Implementation of an Overlay File System for Cloud-Assisted Mobile Apps

IEEE Transactions on Cloud Computing, 2017

With cloud assistance, mobile apps can offload their resource-demanding computation tasks to the ... more With cloud assistance, mobile apps can offload their resource-demanding computation tasks to the cloud. This leads to a scenario where computation tasks in the same program run concurrently on both the mobile device and the cloud. An important challenge is to ensure that the tasks are able to access and share the files on both the mobile and the cloud in a manner that is efficient, consistent, and transparent to locations. Existing distributed file systems and network file systems do not satisfy these requirements. Current systems for offloading tasks either do not support file access for offloaded tasks or do not offload tasks with file access. The paper addresses this issue by designing and implementing an application-level file system called Overlay File System (OFS). To improve efficiency, OFS maintains and buffers local copies of data sets on both the cloud and the mobile device. OFS ensures consistency and guarantees that all the reads get the latest data. It combines write-invalidate and write-update policies to effectively reduce the network traffic incurred by invalidating/updating stale data copies and to reduce the execution delay when the latest data cannot be accessed locally. To guarantee location transparency, OFS creates a unified view of the data that is location independent and is accessible as local storage. We overcome the challenges caused by the special features of mobile systems on an application-level file system, like the lack of root privilege and state loss when application is killed due to the shortage of resource and implement an easy to deploy prototype of OFS. The paper tests the OFS prototype on Android OS with a real mobile app and real mobile user traces. Extensive experiments show that OFS can effectively support consistent file accesses from computation tasks, no matter whether they are on a mobile device or offloaded to the cloud. In addition, OFS reduce both file access latency and network traffic incurred by file accesses.

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An Overlay File System for cloud-assisted mobile applications

2016 32nd Symposium on Mass Storage Systems and Technologies (MSST), 2016

With cloud assistance, a mobile application can offload its resource-demanding computation tasks ... more With cloud assistance, a mobile application can offload its resource-demanding computation tasks to the cloud (public cloud, cloudlet, or personal cloud, etc). This leads to a scenario where computation tasks in the same application run concurrently on both the mobile device and the cloud. These tasks need to save, read, and write files on both the mobile device and the cloud. An important challenge is to ensure that the tasks are able to access and share the files in a manner that is efficient, consistent, and transparent to locations. The paper addresses this issue by designing an application-level file system called Overlay File System (OFS). To improve efficiency, OFS maintains and buffers local copies of data sets on both the cloud and the mobile device. OFS ensures consistency and guarantees that all the reads get the latest data. It combines write-invalidate and writeupdate policies to effectively reduce the network traffic incurred by invalidating/updating stale data copies and to reduce the application delay when the latest data cannot be accessed locally. To guarantee location transparency, OFS creates an unified view of the data that is location independent and is accessible as local storage. Our experiments show that OFS can effectively support task offloading and efficient execution of offloaded tasks by significantly decreasing both file access latency and network traffic incurred by file accesses.

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The Moitree Middleware for Distributed Mobile-Cloud Computing

Journal of Systems and Software, 2019

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The Moitree Middleware for Distributed Mobile-Cloud Computing

Journal of Systems and Software, 2019

Commonly, mobile cloud computing assumes that each mobile device of a user is paired with a user-... more Commonly, mobile cloud computing assumes that each mobile device of a user is paired with a user-controlled surrogate in the cloud to overcome resource limitations on mobiles. Our Avatar platform leverages this model to support efficient distributed computing over mobile devices. An avatar is a per-user, always-on software entity that resides in the cloud and acts as the surrogate of the mobile. Mobile-avatar pairs participate in distributed computing as a unified computing entity in such a way that the workload and the demand for resources on the mobiles remain low. This paper presents Moitree, the middleware of the Avatar platform, which provides a common programming and execution framework for mobile distributed apps. Moitree allows the components of a distributed app to execute seamlessly over a set of mobile-avatar pairs, with the provision of offloading computation and communication to the cloud. The programming framework has two key features: user collaborations are modeled using context-aware group semantics-groups are created dynamically based on context; data communication among group members is offloaded to the cloud through high-level communication channels. A prototype of Moitree, along with several apps, has been implemented and evaluated on Android devices and on a cloud running Android x86 avatars.

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Moitree: A Middleware for Cloud-Assisted Mobile Distributed Apps

by Hillol Debnath and Nafize Paiker

This paper presents Moitree, the middleware of our Avatar platform for mobile cloud computing. Av... more This paper presents Moitree, the middleware of our Avatar platform for mobile cloud computing. Avatar leverages cloud resources to support fast, scalable, reliable, and energy efficient distributed computing over mobile devices. Each mobile device is augmented by an avatar, a per-user always-on software entity that resides in the cloud and acts as the surrogate of the mobile device, to the extent possible, thus reducing the workload and the demand for storage, bandwidth, and energy on the mobiles. Moitree provides: (1) a novel middleware which allows unmodified apps to execute seamlessly over mobile/avatar pairs with the provision of offloading computation and communication, and (2) a new programming framework to simplify mobile collaborative app development. The programming framework has two key features: (1) user collaborations are modeled using natural group semantics-groups are created dynamically based on context and are hierarchical. (2) data communication is offloaded to the cloud through high-level communication channels. A prototype of Moitree, along with several apps, has been implemented and evaluated on Android devices and on an OpenStack-based cloud running Android x86 avatars.

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Moitree: A Middleware for Cloud-Assisted Mobile Distributed Apps

by Nafize Paiker and C. Borcea

2016 4th IEEE International Conference on Mobile Cloud Computing, Services, and Engineering (MobileCloud), 2016

This paper presents Moitree, the middleware of our Avatar platform for mobile cloud computing. Av... more This paper presents Moitree, the middleware of our Avatar platform for mobile cloud computing. Avatar leverages cloud resources to support fast, scalable, reliable, and energy efficient distributed computing over mobile devices. Each mobile device is augmented by an avatar, a per-user always-on software entity that resides in the cloud and acts as the surrogate of the mobile device, to the extent possible, thus reducing the workload and the demand for storage, bandwidth, and energy on the mobiles. Moitree provides: (1) a novel middleware which allows unmodified apps to execute seamlessly over mobile/avatar pairs with the provision of offloading computation and communication, and (2) a new programming framework to simplify mobile collaborative app development. The programming framework has two key features: (1) user collaborations are modeled using natural group semantics-groups are created dynamically based on context and are hierarchical. (2) data communication is offloaded to the cloud through high-level communication channels. A prototype of Moitree, along with several apps, has been implemented and evaluated on Android devices and on an OpenStack-based cloud running Android x86 avatars.

Robust customer satisfaction model using QFD

International Journal of Productivity and Quality Management, 2010

... Ameer Ali completed his BSc in Computer Science and Engineering in 2001 from Bangladesh Unive... more

Pattern based object segmentation using split and merge

2009 IEEE International Conference on Fuzzy Systems, 2009

Page 1. Pattern Based Object Segmentation using Split and Merge Ziaul Karim1, Nafize Rabbani Paik... more

Object segmentation based on split and merge algorithm

TENCON 2008 - 2008 IEEE Region 10 Conference, 2008

Image segmentation is a feverish issue as it is a challenging job and most digital imaging applic... more

Robust Object Segmentation using Split-and-Merge

International Journal of Signal and Imaging Systems Engineering, 2009

In spite of simplicity and effectiveness in segmenting homogeneous regions in an image, Split-and... more In spite of simplicity and effectiveness in segmenting homogeneous regions in an image, Split-and-Merge (SM) algorithm is unable to segment all types of objects due to huge number of objects with myriad variations among them and due to high dependability on the threshold values used in splitting and merging techniques. Addressing these issues, a novel Robust Object Segmentation using Split-and-Merge

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