Cluster Aware Mobility Encounter Dataset Enlargement

From Encounters to Plausible Mobility

Inferring plausible node mobility based only on information from wireless contact traces is a difficult problem. Working with mobility information allows richer protocol simulations, particularly in dense networks, but requires complex set-ups to measure. On the other hand, contact information is easier to measure but only allows for simplistic simulation models. In a contact trace a lot of node movement information is irretrievably lost so the original positions and velocities are in general out of reach. In this paper, we propose a fast heuristic algorithm, inspired by dynamic force-based gr…

On the Relation Between Mobile Encounters and Web Traffic Patterns: A Data-driven Study

Mobility and network traffic have been traditionally studied separately. Their interaction is vital for generations of future mobile services and effective caching, but has not been studied in depth with real-world big data. In this paper, we characterize mobility encounters and study the correlation between encounters and web traffic profiles using large-scale datasets (30TB in size) of WiFi and NetFlow traces. The analysis quantifies these correlations for the first time, across spatio-temporal dimensions, for device types grouped into on-the-go Flutes and sit-to-use Cellos. The results cons…

Analysis of Spatio-Temporal Preferences and Encounter Statistics for DTN Performance

Spatio-temporal preferences and encounter statistics provide realistic measures to understand mobile user's behavioral preferences and transfer opportunities in Delay Tolerant Networks (DTNs). The time dependent behavior and periodic reappearances at specific locations can approximate future online presence while encounter statistics can aid to forward the routing decisions. It is theoretically shown that such characteristics heavily affect the performance of routing protocols. Therefore, mobility models demonstrating such characteristics are also expected to show identical routing performance…

Understanding periodicity and regularity of nodal encounters in mobile networks: A spectral analysis

Study on human mobility is gaining increasing attention from the research community with its multiple applications to use in mobile networks, particularly for the purpose of message delivery in the Delay Tolerant Networks. To better understand the potential of mobile nodes as message relays, our study investigates the encounter pattern of mobile devices. Specifically, we examine the extensive network traces that reflect mobility of communication devices. We analyze the periodicity in encounter pattern by using power spectral analysis. Strong periodicity was observed among rarely encountering m…

Characterizing and Evaluation :Temporal properties of real and synthetic datasets for DTN

Nodes movements play a significant role in disseminating messages in the sparse mobile ad-hoc network. In the network scenarios, where traditional end-to-end paths do not exist, mobility creates opportunities for nodes to connect and communicate when they are encountered. A series of encountering opportunities spread a message among many nodes and eventually deliver to the destination. Further improvements to the performance of message delivery can come from exploiting temporal mobility properties. It is modeled as time varying graph, where, moving nodes are considered as vertices and contact …

多跳可重构智能表面辅助的城市空中交通学习模型共享

Multi-hop RIS-aided Learning Model Sharing for Urban Air Mobility

针对城市空中交通中飞行汽车因环境多变导致的数据收集与训练成本高的问题，提出利用多跳可重构智能表面和知识蒸馏改进深度学习模型共享，仿真显示总奖励提升85%。