Affiliation:
1. Department of Computer Science, University of Illinois, Springfield, IL 62703, USA
2. Department of Electrical and Computer Engineering, Southern Illinois University, Carbondale, IL 62901, USA
Abstract
Focusing on a user's quality-of-experience (QoE) has become important, because of the growing space of sensor-dependent applications and low-cost sensor design. QoE is typically affected by two quantities: the quality-of-information (QoI) received and the lifetime-of-service. Therefore, QoE is defined as a sensor network's ability to consistently offer assured QoI for an expected lifetime when operating on a limited energy resource, such as a battery. However, dynamic factors, such as varying user requirements, unpredictable sensor environment, unreliable network conditions, and limited energy resource, affecting both QoI and lifetime-of-service, make it challenging to achieve a good QoE. In our previous work, we presented a SNR-based QoI metric which addresses the impact of several of these factors on QoI. In this paper, we design a QoE metric that quantifies the relationship between energy conservation, QoI received by a user, and an application's quality expectation. Further, we develop an adaptive sleep schedule mechanism to demonstrate the usefulness of this metric. Finally, simulation results presented show the effectiveness of our mechanism in achieving QoE improvement.
Subject
Computer Networks and Communications,General Engineering
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献