We propose a token-bucket based rate control algorithm that satisfies both maximum and minimum rate constraints with computational complexity of O(1). The proposed algorithm allocates the remaining bandwidth in a strict priority queuing manner to the flows with different priorities and in a weighted fair queuing manner to the flows within the same priority. key words: token bucket, rate control...

Among the various existing models for the warehousing management, the simultaneous use of private and public warehouses is as the most well-known one. The purpose of this article is to develop a queuing theory-based model for determining the optimal capacity of private warehouse in order to minimize the total corresponding costs. In the proposed model, the available space and budget to create a...

This paper exemplifies a framework for development of multi-objective genetic algorithm based job sequencing method by taking account of multiple resource constraints. Along this, Theory of Constraints based Drum-Buffer-Rope methodology has been combined with genetic algorithm to exploit the system constraints. This paper introduces the Drum-Buffer-Rope to exploit the system constraints, which ...

An approach, based on queuing modeling and simulation, to resource allocation for a distributed production system is examined in the paper. The problem is formulated as an objective function minimization for a queuing network. The optimization is based on the combination of analytical modeling and simulation. The analytical model is used for primary evaluation and branching for the optimization...

We analyze a simple linear triggering model of the T-cell receptor (TCR) within the framework of queuing theory, in which TCRs enter the queue upon full activation and exit by downregulation. We fit our model to four experimentally characterized threshold activation criteria and analyze their specificity and sensitivity: the initial calcium spike, cytotoxicity, immunological synapse formation, ...

Efficient traffic signal control is an important means to alleviate urban congestion. Reinforcement learning (RL) has shown great potentials in devising optimal plans that can adapt dynamic However, several challenges still need be overcome. Firstly, a paradigm of state, action, and reward design needed, especially for optimality-guaranteed function. Secondly, the generalization RL algorithms h...

Dong-Yong Kwak et al. 475 In this paper, we propose an efficient and simple fair queuing algorithm, called new starting potential fair queuing (NSPFQ), which has O(1) complexity for virtual time computation and also has good delay and fairness properties. NSPFQ introduces a simpler virtual time recalibration method as it follows a rate-proportional property. The NSPFQ algorithm recalibrates the...

To better utilize air-conditioning load in terms of demand side response potential and improve precision speed, a control strategy traditional temperature-control air conditioning, determining frequency as the research object, conditioning determined with theory model Monte Carlo method, were used to construct power aggregation model. This was combined user feedback study thermal comfort latera...

the advent of e-commerce has prompted many manufacturers to redesign their traditional channel structure by engaging in direct sales. in this paper, we present a dual channel inventory model based on queuing theory in a manufacturer-retailer supply chain, consisting of a traditional retail channel and a direct channel which stocks are kept in both upper and lower echelon. the system receives st...