Token Bucket-based Throughput Constraining in Cross-layer Schedulers

In this paper we consider upper and lower constraining users' service rates in a slotted, cross-layer scheduler context. Such schedulers often cannot guarantee these bounds, despite the usefulness in adhering to Quality of Service (QoS) requirements, aiding the admission control system or providing different levels of service to users. We approach this problem with a low-complexity algorithm that is easily integrated in any utility function-based cross-layer scheduler. The algorithm modifies the weights of the associated Network Utility Maximization problem, rather than for example applying a token bucket to the scheduler's output or adding constraints in the physical layer. We study the efficacy of the algorithm through simulations with various schedulers from literature and mixes of traffic. The metrics we consider show that we can bound the average service rate within about five slots, for most schedulers. Schedulers whose weight is very volatile are more difficult to constrain.Comment: 11 pages, 10 figures. Presented at 6th International Conference on Computer Science, Engineering and Information. Published in AIRCC http://airccse.org/csit/V9N13.htm

Network utility maximization for adaptive resource allocation in dsl systems

© EURASIP 2018. When signal coordination techniques can not eliminate all crosstalk in a digital subscriber line (DSL) system, competition for data rate among different users is strong. In such scenarios, employing a static resource allocation fails to capitalize on the time dependent nature of the traffic carried by the DSL network. An alternative approach is adaptive resource allocation, consisting of dividing time into slots of short duration and using a different resource allocation in each slot. A cross-layer scheduler then decides on the resource allocation for each time slot by solving a network utility maximization (NUM) problem. For many DSL systems however, this NUM problem is non-convex and solving it is NP-hard. This paper presents a fast algorithm for finding a local solution to the NUM problem, which is referred to as NUM-DSB. The algorithm is able to handle many DSL deployment scenarios, and is applicable regardless of the utility function's properties.status: publishe