2018/11/30 by Abubakr O. Al-Abbasi, Alabbasi, Abubakr, Vaneet Aggarwal +1 · 2 citations
Computer Science · Engineering · #Age of Information Optimization #IoT Networks and Protocols #IoT and Edge/Fog Computing
paper · pdf · doi:10.48550/arxiv.1811.12924
The demand for real-time cloud applications has seen an unprecedented growth\nover the past decade. These applications require rapidly data transfer and fast\ncomputations. This paper considers a scenario where multiple IoT devices update\ninformation on the cloud, and request a computation from the cloud at certain\ntimes. The time required to complete the request for computation includes the\ntime to wait for computation to start on busy virtual machines, performing the\ncomputation, waiting and service in the networking stage for delivering the\noutput to the end user. In this context, the freshness of the information is an\nimportant concern and is different from the completion time. This paper\nproposes novel scheduling strategies for both computation and networking\nstages. Based on these strategies, the age-of-information (AoI) metric and the\ncompletion time are characterized. A convex combination of the two metrics is\noptimized over the scheduling parameters. The problem is shown to be convex and\nthus can be solved optimally. Moreover, based on the offline policy, an online\nalgorithm for job scheduling is developed. Numerical results demonstrate\nsignificant improvement as compared to the considered baselines.\n