Towards Enabling Mobile Social Crowd-Sensing for Unstructured Transport Information Management: Performance Evaluation of Large-Scale End-to-End Publish/Subscribe Interaction

Abstract

Developing countries are characterised of chaotic large-scale traffic, especially in major cities. Robust mobile systems for information concerning transport services are of critical importance. Additionally, although most of the people have mobile phones, even smartphones, a large part of the population rely on SMS data access only. The situation of Senegal reflects the above. In this paper, we take a first step towards enabling an application platform for citywide and countrywide transport information management relying on mobile social crowd-sensing. To inform the stakeholders of expected loads and costs, we model a large-scale mobile publish or subscribe system as a queueing network. We introduce additional timing constraints such as (i) mobile user’s intermittent connectivity period; and (ii) data validity lifetime period (e.g. that of sensor data). Using our MobileJINQS simulator, we parameterize our model with realistic input loads derived from the D4D dataset and varied lifetime periods in order to analyze the effect on response time. This work provides system designers a coarse grain design time information when setting realistic loads and time constraints.

Publication
In D4D Challenge special session (NetMob 2015)

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