Bounded Delay Scheduling with Packet Dependencies

A common situation occurring when dealing with multimedia traffic is having large data frames fragmented into smaller IP packets, and having these packets sent independently through the network. For real-time multimedia traffic, dropping even few packets of a frame may render the entire frame useless. Such traffic is usually modeled as having {\em inter-packet dependencies}. We study the problem of scheduling traffic with such dependencies, where each packet has a deadline by which it should arrive at its destination. Such deadlines are common for real-time multimedia applications, and are derived from stringent delay constraints posed by the application. The figure of merit in such environments is maximizing the system's {\em goodput}, namely, the number of frames successfully delivered. We study online algorithms for the problem of maximizing goodput of delay-bounded traffic with inter-packet dependencies, and use competitive analysis to evaluate their performance. We present competitive algorithms for the problem, as well as matching lower bounds that are tight up to a constant factor. We further present the results of a simulation study which further validates our algorithmic approach and shows that insights arising from our analysis are indeed manifested in practice

Enhanced PF Scheduling Algorithm for LTE Networks

Scheduling Algorithm is a key Radio ResourceManagement (RRM) mechanism to achieve Quality of Service(QoS) requirements and to optimize system performance of LongTerm Evolution (LTE) network. The LTE standard does notspecify a scheduling algorithm and some schedules have beenproposed in the literature. Most of them consider the channelstate or some QoS metric, however, they do not consider thePF characteristics and the delay required by the user. Then, anenhanced scheduling algorithm was proposed based on Latency-Rate (LR) server theory and system characteristics specifiedby the LTE standard. Properties of this proposal have beeninvestigated theoretically and through simulations. A simulationis presented with video traffic and also performance comparisonswith Proportional Fairness (PF) and Modified Largest WeightedDelay First (MLWDF) schedulers. The results show that theproposed schedule has a better performance compared with theabove schedulers

Application of learning algorithms to traffic management in integrated services networks.

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