Abstract
In Delay-Tolerant Networks (DTNs), humans are the main carriers of mobile devices, signifying that human mobility can be exploited by extracting nodes’ interests, social behavior, and spatiotemporal features for the performance evaluation of DTNs protocols. This paper presents a new mobility model that describes students’ daily activities in a campus environment. Unlike the conventional random walk models, which use a free space environment, our model includes a collision-avoidance technique that generates an escape path upon encountering obstacles of different shapes and sizes that obstruct pedestrian movement. We evaluate the model’s usefulness by comparing the distributions of its synthetic traces with realistic traces in terms of spatial, temporal, and connectivity features of human mobility. Similarly, we analyze the concept of dynamic movement clusters observed on the location-based trajectories of the studied real traces. The model synthetically generates traces with the distribution of the intercluster travel distance, intracluster travel distance, direction of movement, contact duration, intercontact time, and pause time similar to the distribution of real traces.
Highlights
Mobility patterns play an essential role in the performance of wireless networks with intermittent connections such as Delay-Tolerant Networks (DTNs)
Humans are the main carriers of mobile devices. erefore, there is a need to understand the underlying behavior of pedestrian mobility, the driving forces that influence its motivation to move, and the repulsive forces that describe its interaction with environmental constraints. ese are essential for designing a realistic mobility model to be used as a tool for wireless network protocol evaluation, the need for a model based on the empirical study of pedestrians’ mobility and interaction with other objects in the environment to pave the way for better event management, emergency rescue operation, and congestion prediction in a narrow bottleneck
Our goal is to show that our conceptual model (EPOM) is generic enough to be fine-tuned with a few parameters to show matching characteristics with the NCSU Global Positioning System (GPS) traces [36], in terms of the spatial features: intracluster travel distance and intracluster direction of movement as well as the temporal feature
Summary
Mobility patterns play an essential role in the performance of wireless networks with intermittent connections such as Delay-Tolerant Networks (DTNs). (3) We propose an Escape Path Obstacle-based Mobility Model (EPOM) for the campus DTNs. We show that the model is generic enough to be fine-tuned with a few parameters to show matching characteristics with the spatiotemporal and connectivity features observed in the real traces. Synthetic models that capture intentional human behavior are more realistic than the conventional models, the trace-based models [22, 27] appear to be more realistic because they are mostly generated for a specific scenario and only for a few nodes. Movements and developed a software model that generates realistic user mobility tracks but the mobility trajectory granularity of the studied trace depends on the wireless Local Area Network (WLAN) access point locations and may not be applicable to higher mobility DTN. Symbol X indicates that the existing work studied the mobility feature while symbol x indicates the opposite
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