Optimizing Information Credibility in Social Swarming Applications

Liu, Bin; Terlecky, Peter; Bar-Noy, Amotz; Govindan, Ramesh; Neely, Michael J.; Rawitz, Dror

doi:10.1109/tpds.2011.281

Cited by 28 publications

(26 citation statements)

References 13 publications

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“…On the other hand, mobile devices are ultimately constrained by the limited battery supply and a computing-intensive application can quickly exhaust the limited battery power. Such a situation is worsened by the industrial trend to equip more sensors on mobile devices for a wider scope of non-traditional applications, such as environment monitoring [17], health monitoring [4,7], social applications [23,22], which are often more computing intensive.…”

Section: Introductionmentioning

confidence: 99%

Mobile MapReduce: Minimizing Response Time of Computing Intensive Mobile Applications

Hassan

Chen

2012

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Abstract. The increasing popularity of mobile devices calls for effective execution of mobile applications. A lot of research has been conducted on properly splitting and outsourcing computing intensive tasks to external resources (e.g., public clouds) by considering insufficient computing resources on mobile devices. However, little attention has been paid to the overall users' response time, where the network may dominate. In this study, we set to investigate how to effectively minimize users' response time for mobile applications. We consider both the impact of the network and the computing itself. We first show that outsourcing to nearby residential computers may be more advantageous than public clouds for mobile applications due to network impact. Furthermore, to speed up computing, we leverage parallel processing techniques. Accordingly, we propose to build Mobile MapReduce (MMR) to effectively execute outsource computing intensive mobile applications. Based on the original MapReduce framework, a new scheduling model is built in MMR that can always leverage the best computing resources to conduct computation with appropriate parallel processing. To demonstrate the performance of MMR, we run several real-world applications, such as text searching, face detection, and image processing, on the prototype. The results show great potentials of MMR in minimizing the response time of the outsourced mobile applications.

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Section: Introductionmentioning

confidence: 99%

Mobile MapReduce: Minimizing Response Time of Computing Intensive Mobile Applications

Hassan

Chen

2012

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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“…Methods to characterize credibility and maximize total credibility gained from a network have been presented in [2], [3]. In particular, authors consider a scenario where reporters send information they obtain about an event of interest to a central director.…”

Section: Introductionmentioning

confidence: 99%

“…In particular, authors consider a scenario where reporters send information they obtain about an event of interest to a central director. The credibility of information from each user depends on both the type/modality of information and the proximity of the reporter to the event [3].…”

Section: Introductionmentioning

confidence: 99%

“…For credibility of information, we utilize the model in reference [3]. The credibility of information depends on two factors.…”

Section: Introductionmentioning

confidence: 99%

“…A reporter who is closer to the event of interest will be able to make observations with higher detail and resolution. Overall, the credibility of reporter i using mode m, represented by c i,m is expressed as [3]:…”

Section: Introductionmentioning

confidence: 99%

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Maximizing credibility-based network utility via power allocation

Ciftcioglu

Yener

2012

2012 IEEE International Conference on Pervasive Computing and Communications Workshops

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Abstract-We consider Quality-of-Information (QoI)-based resource allocation in a scenario where multiple reporter nodes send information on an event of interest to a sink node. We express credibility of each reporter, an attribute of quality of information, as a function of both the proximity to the event and the type of information gathered. While a reporter close to the event using an advanced format as video may have high credibility, it might also need excessive network resources to transmit the information if it is far from the sink. To address this trade-off, we consider a network utility which depends on both information credibility and timeliness, and yields the timely and credible operational information content capacity (OICC) of this setting. We consider a network with a fixed transmission cost budget per event. Optimal power allocation among reporters is found that maximizes the utility. The constraint on network cost budget results in coupling among resources allocated to reporters. We demonstrate that power allocated to each reporter balances contrasting parameters associated with reporter location and type of information used. Overall, this work produces design insight bringing us one step closer to information quality aware wireless networking.

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