Accurate and generic sender selection for bulk data dissemination in low-power wireless networks

Abstract

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).