Accurate and generic sender selection for bulk data dissemination in low-power wireless networks
IEEE/ACM Transactions on Networking
Institute of Electrical and Electronics Engineers (IEEE) / Association for Computing Machinery (ACM)
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Data dissemination is a fundamental service offered by low-power wireless networks. Sender selection is the key to the dissemination performance and has been extensively studied. Sender impact metric plays a significant role in sender selection, since it determines which senders are selected for transmission. Recent studies have shown that spatial link diversity has a significant impact on the efficiency of broadcast. However, the existing metrics overlook such impact. Besides, they consider only gains but ignore the costs of sender candidates. As a result, existing works cannot achieve accurate estimation of the sender impact. Moreover, they cannot well support data dissemination with network coding, which is commonly used for lossy environments. In this paper, we first propose a novel sender impact metric, namely, ɣ, which jointly exploits link quality and spatial link diversity to calculate the gain/cost ratio of the sender candidates. Then, we develop a generic sender selection scheme based on the ɣ metric (called ɣ-component) that can generally support both types of dissemination using native packets and network coding. Extensive evaluations are conducted through real testbed experiments and large-scale simulations. The performance results and analysis show that ɣ achieves far more accurate impact estimation than the existing works. In addition, the dissemination protocols based on ɣ-component outperform the existing protocols in terms of completion time and transmissions (by 20.5% and 23.1%, respectively).
This work was supported by the Fundamental Research Funds for the Central Universities (No. ZYGX2016KYQD098 and No. 2016FZA5010), the National Science Foundation of China (No. 61602095 and No. 61472360), National Key Technology R&D Program (Grant No. 2014BAK15B02), CCFIntel Young Faculty Researcher Program, CCF-Tencent Open Research Fund, China Ministry of EducationChina Mobile Joint Project under Grant No. MCM20150401 and the EU FP7 CLIMBER project under Grant Agreement No. PIRSES-GA-2012-318939.
This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.