A predictive resource allocation algorithm in the LTE uplink for event based M2M applications
Article
Article Title | A predictive resource allocation algorithm in the LTE uplink for event based M2M applications |
---|---|
ERA Journal ID | 5073 |
Article Category | Article |
Authors | Brown, Jason (Author) and Khan, Jamil (Author) |
Journal Title | IEEE Transactions on Mobile Computing |
Journal Citation | 14 (12), pp. 2433-2446 |
Number of Pages | 14 |
Year | 2015 |
Place of Publication | Los Alamitos, Calif, United States |
ISSN | 1536-1233 |
1558-0660 | |
Digital Object Identifier (DOI) | https://doi.org/10.1109/TMC.2015.2398447 |
Web Address (URL) | https://ieeexplore.ieee.org/document/7035042 |
Abstract | Some M2M applications such as event monitoring involve a group of devices in a vicinity that act in a co-ordinated manner. An LTE network can exploit the correlated traffic characteristics of such devices by proactively assigning resources to devices based upon the activity of neighboring devices in the same group. This can reduce latency compared to waiting for each device in the group to request resources reactively per the standard LTE protocol. In this paper, we specify a new low complexity predictive resource allocation algorithm, known as the one way algorithm, for use with delay sensitive event based M2M applications in the LTE uplink. This algorithm requires minimal incremental processing power and memory resources at the eNodeB, yet can reduce the mean uplink latency below the minimum possible value for a non-predictive resource allocation algorithm. We develop mathematical models for the probability of a prediction, the probability of a successful prediction, the probability of an unsuccessful prediction, resource usage/wastage probabilities and mean uplink latency. The validity of these models is demonstrated by comparison with the results from a simulation. The models can be used offline by network operators or online in real time by the eNodeB scheduler to optimize performance. |
Keywords | LTE, M2M, predictive scheduling, proactive scheduling, OPNET |
ANZSRC Field of Research 2020 | 400604. Network engineering |
400608. Wireless communication systems and technologies (incl. microwave and millimetrewave) | |
Public Notes | © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Byline Affiliations | University of Newcastle |
Institution of Origin | University of Southern Queensland |
https://research.usq.edu.au/item/q4z35/a-predictive-resource-allocation-algorithm-in-the-lte-uplink-for-event-based-m2m-applications
Download files
217
total views277
total downloads1
views this month1
downloads this month