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Publications

Publications by Joaquim Magalhães Silva

2016

Benchmarking Wireless Protocols for Feasibility in Supporting Crowdsourced Mobile Computing

Authors
Rodrigues, J; Silva, J; Martins, R; Lopes, L; Drolia, U; Narasimhan, P; Silva, F;

Publication
DISTRIBUTED APPLICATIONS AND INTEROPERABLE SYSTEMS, DAIS 2016

Abstract
Recent advances in mobile device technology have triggered research on using their aggregate computational and/or storage resources to form edge-clouds. Whilst traditionally viewed as simple clients, smart-phones and tablets today have hardware resources that allow more sophisticated software to be installed, and can be used as thick clients or even thin servers. Simultaneously, new standards and protocols, such as Wi-Fi Direct and Wi-Fi TDLS (Tunneled Direct Link Setup), have been established that allow mobile devices to talk directly with each other, as opposed to over the Internet or across Wi-Fi access points. This can, potentially, lead to ubiquitous, low-latency, device-to-device (D2D) communication. In this paper, we study whether D2D protocols can support mobile-edge clouds by benchmarking different protocols and configurations for a specific application. The results show that decentralized device-to-device techniques can be used to efficiently disseminate multimedia contents while diminishing contention in the wireless infrastructure, allowing for up to 65% traffic reduction at the access points.

2017

P3-Mobile: Parallel Computing for Mobile Edge-Clouds

Authors
Silva, J; Silva, D; Marques, ERB; Lopes, LMB; Silva, FMA;

Publication
Proceedings of the 4th Workshop on CrossCloud Infrastructures & Platforms, CrossCloud@EuroSys 2017, Belgrade, Serbia, April 23 - 26, 2017

Abstract
We address the problem of whether networks of mobile devices such as smart-phones or tablets can be used to perform opportunistic, best-effort, parallel computations. We designed and implemented P3-Mobile, a parallel programming system for edge-clouds of Android devices to test the feasibility of this idea. P3-Mobile comes with a programming model that supports parallel computations over peer-to-peer overlays mapped onto mobile networks. The system performs automatic load-balancing by using the overlay to discover work. We present preliminary performance results for a parallel benchmark, using up to 16 devices, and discuss their implications towards future work. Copyright © 2017 ACM.

2017

Using Edge-Clouds to Reduce Load on Traditional WiFi Infrastructures and Improve Quality of Experience

Authors
Pinto Silva, PMP; Rodrigues, J; Silva, J; Martins, R; Lopes, L; Silva, F;

Publication
2017 IEEE 1ST INTERNATIONAL CONFERENCE ON FOG AND EDGE COMPUTING (ICFEC)

Abstract
Crowd-sourcing the resources of mobile devices is a hot topic of research given the game-changing applications it may enable. In this paper we study the feasibility of using edge-clouds of mobile devices to reduce the load in traditional WiFi infrastructures for video dissemination applications. For this purpose, we designed and implemented a mobile application for video dissemination in sport venues that retrieves replays from a central server, through the access points in the WiFi infrastructure, into a smartphone. The fan's smartphones organize themselves into WiFi-Direct groups and exchange video replays whenever possible, bypassing the central server and access points. We performed a real-world experiment using the live TV feed for the Champions League game Benfica-Besiktas with the help of a group of volunteers using the application at the student's union lounge. The analysis of the logs strongly suggests that edge-clouds can significantly reduce the load in the access points at such large venues and improve quality of experience. Indeed, the edge-clouds formed were able to serve up to 80% of connected users and provide 56% of all downloads requested from within.

2018

Video Dissemination in Untethered Edge-Clouds: A Case Study

Authors
Rodrigues, J; Marques, ERB; Silva, J; Lopes, LMB; Silva, F;

Publication
DISTRIBUTED APPLICATIONS AND INTEROPERABLE SYSTEMS (DAIS 2018)

Abstract
We describe a case study application for untethered video dissemination using a hybrid edge-cloud architecture featuring Android devices, possibly organised in WiFi-Direct groups, and Raspberry Pi-based cloudlets, structured in a mesh and also working as access points. The application was tested in the real-world scenario of a Portuguese volleyball league game. During the game, users of the application recorded videos and injected them in the edge-cloud. The cloudlet servers continuously synchronised their cached video contents over the mesh network, allowing users on different locations to share their videos, without resorting to any other network infrastructure. An analysis of the logs gathered during the experiment shows that such portable setups can easily disseminate videos to tens of users through the edge-cloud with low latencies. We observe that the edge-cloud may be naturally resilient to faulty cloudlets or devices, taking advantage of video caching within devices and WiFi-Direct groups, and of device churn to opportunistically disseminate videos.

2020

RAMBLE: Opportunistic Crowdsourcing of User-Generated Data using Mobile Edge Clouds

Authors
Garcia, M; Rodrigues, J; Silva, J; Marques, ERB; Lopes, LMB;

Publication
2020 FIFTH INTERNATIONAL CONFERENCE ON FOG AND MOBILE EDGE COMPUTING (FMEC)

Abstract
We present RAMBLE(1), a framework for georeferenced content-sharing in environments that have limited infrastructural communications, as is the case for rescue operations in the aftermath of natural disasters. RAMBLE makes use of mobile edge-clouds, networks formed by mobile devices in close proximity, and lightweight cloudlets that serve a small geographical area. Using an Android app, users ramble whilst generating geo-referenced content (e.g., text messages, sensor readings, photos, or videos), and disseminate that content opportunistically to nearby devices, cloudlets, or even cloud servers, as allowed by intermittent wireless connections. Each RAMBLE-enabled device can both produce information; consume information for which it expresses interest to neighboors, and; serve as an opportunistic cache for other devices. We describe the architecture of the framework and a case-study application scenario we designed to evaluate its behavior and performance. The results obtained reinforce our view that kits of RAMBLE-enabled mobile devices and modest cloudlets can constitute lightweight and flexible untethered intelligence gathering platforms for first responders in the aftermath of natural disasters, paving the way for the deployment of humanitary assistance and technical staff at large.

2020

JAY: Adaptive Computation Offloading for Hybrid Cloud Environments

Authors
Silva, J; Marques, ERB; Lopes, LMB; Silva, F;

Publication
2020 FIFTH INTERNATIONAL CONFERENCE ON FOG AND MOBILE EDGE COMPUTING (FMEC)

Abstract
Edge computing is a hot research topic given the ever-increasing requirements of mobile applications in terms of computation and communication and the emerging Internet-of-Things with billions of devices. While ubiquitous and with considerable computational resources, devices at the edge may not be able to handle processing tasks on their own and thus resort to offloading to cloudlets, when available, or traditional cloud infrastructures. In this paper, we present JAY, a modular and extensible platform for mobile devices, cloudlets, and clouds that can manage computational tasks spawned by devices and make informed decisions about offloading to neighboring devices, cloudlets, or traditional clouds. JAY is parametric on the scheduling strategy and metrics used to make offloading decisions, providing a useful tool to study the impact of distinct offloading strategies. We illustrate the use of JAY with an evaluation of several offloading strategies in distinct cloud configurations using a real-world machine learning application, firing tasks can be dynamically executed on or offloaded to Android devices, cloudlet servers, or Google Cloud servers. The results obtained show that edge-clouds form competent computing platforms on their own and that they can effectively be meshed with cloudlets and traditional clouds when more demanding processing tasks are considered. In particular, edge computing is competitive with infrastructure clouds in scenarios where data is generated at the edge, high bandwidth is required, and a pool of computationally competent devices or an edge-server is available. The results also highlight JAY's ability of exposing the performance compromises in applications when they are deployed over distinct hybrid cloud configurations using distinct offloading strategies.

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