Abstract
Recent advances in the Internet of Things (IoT) technologies have enabled ubiquitous smart devices to sense and process various kinds of data. However, these innovations also raise the concern of efficient data transmission. Tackling the above issue is nontrivial since the resource constraints and environmental randomness in IoT require a lightweight transmission scheme while guaranteeing system stability. In this paper, we formulate the transmission scheduling problem of multi-interface IoT devices as a concave optimization, aimed at accommodating the randomness of the IoT environment within the network capacity. By applying the Lyapunov optimization technique, we divide the stochastic problem into a series of low-complex subproblems, which can be individually solved per time slot, and develop a dynamical control algorithm that does not require a priori knowledge such as link states. Theoretical analysis shows that our algorithms nicely bound the average queue length and are asymptotically optimal. Finally, extensive simulation results verify the theoretical conclusions and validate the effectiveness of the proposed algorithm.
Highlights
With the ubiquitously deployed smart devices, the Internet of Things (IoT) technology has been facilitating the intelligence of residential daily activities by providing advanced services for transportation, agriculture, industrial manufacturing, etc. [1,2,3]
An IoT device equipped with multiple interfaces can use multiple channels simultaneously in the physical link layer [9] and deliver packets through Multipath TCP (MPTCP) in the network layer [10]
We investigate the transmission scheduling in IoT
Summary
With the ubiquitously deployed smart devices, the Internet of Things (IoT) technology has been facilitating the intelligence of residential daily activities by providing advanced services for transportation, agriculture, industrial manufacturing, etc. [1,2,3]. According to related report [5], the global IoT cellular traffic is expected to grow to 1.7 exabytes per month by 2022, a twofold increase over 2020 This huge amount of data traffic poses a critical challenge to the current networks [6, 7], making it impractical to provide transmission guarantees. The IoT devices with multiple data flows can be treated as a transmission scheduler with a many-to-many traffic pattern. How many packets of different flows should be transmitted through which link, and how to adjust transmission rates for each flow with system stability guaranteed These concerns are Wireless Communications and Mobile Computing further complicated with IoT devices’ mobility, as it brings dynamical communication environments and stochastic link conditions.
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