This paper presents methodology of provisioning QoS (Quality of Service) in DiffServ based IP network. DiffServ is scalable IP based technology which can efficiently provide QoS in networks of DiffServ supporting rout...
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ISBN:
(纸本)9781424457939
This paper presents methodology of provisioning QoS (Quality of Service) in DiffServ based IP network. DiffServ is scalable IP based technology which can efficiently provide QoS in networks of DiffServ supporting routers. We evaluated performances of our proposed scheme for QoS provisioning of real-time traffic, using WFQ (Weighted Fair Queuing) scheduler to schedule the transmissions. Simulations are performed using network simulator ns~2, while EXP and CBR traffic generators are used as real-time traffic sources for voice and video applications. Through the simulation study we show the effect on queuing delays and jitter of both traffic types when their WFQ weights vary and derive and optimal weights that provide the best overall delay and jitter for real-time traffic.
This paper considers the problem of designing scheduling algorithms for multi-channel (e.g., OFDM) wireless downlink networks with n users/OFDM sub-channels. For this system, while the classical MaxWeight algorithm is...
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ISBN:
(纸本)9781424458363
This paper considers the problem of designing scheduling algorithms for multi-channel (e.g., OFDM) wireless downlink networks with n users/OFDM sub-channels. For this system, while the classical MaxWeight algorithm is known to be throughput-optimal, its buffer-overflow performance is very poor (formally, we show it has zero rate function in our setting). To address this, we propose a class of algorithms called iHLQF (iterated Heaviest matching with Longest Queues First) that is shown to be throughput optimal for a general class of arrival/channel processes, and also rate-function optimal (i.e., exponentially small buffer overflow probability) for certain arrival/channel processes. iHLQF however has higher complexity than MaxWeight (n~(4) vs. n~(2) respectively). To overcome this issue, we propose a new algorithm called SSG (Server-Side Greedy). We show that SSG is throughput optimal, results in a much better per-user buffer overflow performance than the MaxWeight algorithm (positive rate function for certain arrival/channel processes), and has a computational complexity (n~(2)) that is comparable to the MaxWeight algorithm. Thus, it provides a nice trade-off between buffer-overflow performance and computational complexity. These results are validated by both analysis and simulations.
In Polyamorous scheduling, we are given an edge-weighted graph and must find a periodic schedule of matchings in this graph which minimizes the maximal weighted waiting time between consecutive occurrences of the same...
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The scheduling of final exams at a university is a problem which can be improved with artificial intelligence techniques. In this paper we explain and compare two algorithms used to solve the exam scheduling problem a...
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In this paper, we study how to optimize the resource allocation and scheduling in art data recognition task by AI algorithm to improve the recognition efficiency and accuracy. This study first analyzes the main challe...
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The makespan scheduling problem is an extensively studied NP-hard problem, and its simplest version is to find an allocation approach for a set of jobs with deterministic processing time to two identical machines such...
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This paper studies the bicriteria problem of scheduling n jobs on a serial-batch machine to minimize makespan and maximum cost simultaneously. A serial-batch machine can process up to b jobs as a batch, where b is kno...
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Efficient scheduling optimization is a critical component of resource management in civil engineering projects, which often involve dynamic and complex environments. Traditional scheduling approaches face challenges i...
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A major trend in energy economics is the rise of solar energy production, that allows a same player to simultaneously behave as a producer and a consumer of energy, implementing this way self-consumption. Self-consump...
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As an emerging communication technology, time-sensitive networking (TSN) holds the potential to enable real-time and deterministic interactions for streams within the Industrial Internet of Things. However, effectivel...
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As an emerging communication technology, time-sensitive networking (TSN) holds the potential to enable real-time and deterministic interactions for streams within the Industrial Internet of Things. However, effectively and promptly scheduling large-scale streams in the TSN network poses a significant challenge due to high computational complexity. In this article, we conduct a schedulability analysis to preprocess the stream set with given routing paths, avoiding invalid searches and providing optimized guidance for stream routing. To accelerate the feasibility validation of potential solutions, an efficient stream conflict detection approach is proposed leveraging stream grouping with correlation analysis to compress the detection space. Integrating the above preprocess and efficient conflict detection, we develop a scalable scheduling algorithm with an incremental schedule synthesis to enhance scalability while ensuring low slot occupancy for all links. Evaluation results demonstrate that the proposed algorithm significantly reduces synthesis time and achieves low slot occupancy of all links compared to existing scheduling methods.
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