Efficient Quality-of-Service (QoS) Support in Mobile Opportunistic Networks

• Published in: IEEE transactions on vehicular technology Vol. 63; no. 9; pp. 4574 - 4584
• Main Authors: Liu, Yang, Yang, Zhipeng, Ning, Ting, Wu, Hongyi
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-11-2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Budgeting; Computer simulation; Data transmission; Delay; Delays; Mobile communication; Mobile computing; Networks; Provisioning; Quality of service; Quality of service architectures; Redundancy; Routing; Sensors; Mobile opportunistic networks; quality-of-service (QoS)
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2014.2311450

This paper aims to support quality-of-service (QoS) provisioning, particularly the guarantee for end-to-end data delivery delay, in mobile opportunistic networks. The QoS-aware delivery probability (QDP) is introduced to reflect the capability of a node to deliver data to a destination within a given delay budget. Each node maintains a set of QDPs to make autonomous decisions for QoS-aware data transmission. At the same time, a prioritized queue is employed by each mobile node. To support efficient prioritization and redundancy control, the priority is determined by a function of traffic class and data redundancy. The former is predetermined by the corresponding application, whereas the latter is dynamically estimated during data delivery. Two experiments are carried out to demonstrate and evaluate the proposed QoS-aware data delivery scheme. The first experiment involves multiple clusters of static Crossbow sensors that are connected by air and ground mobile nodes with controlled mobility. The second experiment is under a mobile social network setting, where 23 Dell Streak Android tablets are carried by volunteers with arbitrary and diverse mobility patterns over a period of two weeks. Moreover, simulation results are obtained under DieselNet trace and power-law mobility model to study scalability and performance trends. Our experiments and simulations demonstrate that the proposed scheme achieves efficient resource allocation according to the desired delay budget and, thus, supports effective QoS provisioning.