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Published January 2018 | public
Journal Article

Distributed Hybrid Scheduling in Multi-Cloud Networks using Conflict Graphs

Abstract

Recent studies on cloud-radio access networks assume either signal-level or scheduling-level coordination. This paper considers a hybrid coordinated scheme as a means to benefit from both policies. Consider the downlink of a multi-cloud radio access network, where each cloud is connected to several base-stations (BSs) via high capacity links, and, therefore, allows for joint signal processing within the cloud transmission. Across the multiple clouds, however, only scheduling-level coordination is permitted, as low levels of backhaul communication are feasible. The frame structure of every BS is composed of various time/frequency blocks, called power-zones (PZs), which are maintained at a fixed power level. The paper addresses the problem of maximizing a network-wide utility by associating users to clouds and scheduling them to the PZs, under the practical constraints that each user is scheduled to a single cloud at most, but possibly to many BSs within the cloud, and can be served by one or more distinct PZs within the BSs' frame. The paper solves the problem using graph theory techniques by constructing the conflict graph. The considered scheduling problem is, then, shown to be equivalent to a maximum-weight independent set problem in the constructed graph, which can be solved using efficient techniques. The paper then proposes solving the problem using both optimal and heuristic algorithms that can be implemented in a distributed fashion across the network. The proposed distributed algorithms rely on the well-chosen structure of the constructed conflict graph utilized to solve the maximum-weight independent set problem. Simulation results suggest that the proposed optimal and heuristic hybrid scheduling strategies provide appreciable gain as compared to the scheduling-level coordinated networks, with a negligible degradation to signal-level coordination.

Additional Information

© 2017 IEEE. A part of this paper [1] is published in IEEE Global Telecommunications Conference (GLOBECOM' 2015), San Diego, CA, USA., for funding the research reported in this paper through the Research and Consultancy Institute. Manuscript received October 17, 2016, revised March 14, 2017 and July 27, 2017; accepted August 24, 2017. Date of publication September 7, 2017; date of current version January 13, 2018. This paper was presented at the IEEE Global Telecommunications Conference (GLOBECOM' 2015), San Diego, CA, USA. H. Dahrouj would like to thank Effat University, Jeddah, Saudi Arabia, for funding the research reported in this paper through the Research and Consultancy Institute. The associate editor coordinating the review of this paper and approving it for publication was D. Wu. (Corresponding author: Ahmed Douik.)

Additional details

Created:
August 19, 2023
Modified:
October 17, 2023