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Green data centers have become more and more popular recently due to their sustainability. The resource management module within a green data center, which is in charge of dispatching jobs and scheduling energy, becomes especially critical since it directly affects a center's profit and sustainability. The thrust of managing a green data center's machine and energy resources lies at the uncertainty...
Motivated by providing quality-of-service for next generation IP-based networks, we design algorithms to schedule packets with values and deadlines. Packets arrive over time; each packet has a non-negative value and an integer deadline. In each time step, at most one packet can be sent. Packets can be dropped at any time before they are sent. The objective is to maximize the total value gained by...
By providing a detailed analysis of the particle swarm optimization (PSO) principle and job-shop scheduling problems, this paper presents a new hybrid discrete GAPSO combining the genetic strategy. Adjusting factors are introduced to regulate the generation of convergence; the proposed algorithm is tested by a set of benchmark problems. The results obtained show good convergence of the algorithm....
We study scheduling unit-length packets with soft deadlines. In our setting, packets arrive over time and a packet may have different values contributed to the objective when it is delivered at different time. In one time step, at most one packet is allowed to be sent. Our goal is to maximize the total value achieved by delivering packets. Based on various application requirements, we propose two...
In this paper, we study energy management algorithms for job scheduling. In our model, each job has a release time, a processing time, a reward, and a deadline. The objective is to maximize net profit, defined as the difference between the total reward achieved by completing jobs by their deadlines and the total energy consumption accrued during this course. The net profit model generalizes the well-studied...
In this paper, we undertake the competitive analysis of the online real-time scheduling problems under a given hard energy constraint. Specifically, we derive worst-case performance bounds that apply to any online algorithm, when compared to an optimal algorithm that has the knowledge of the input sequence in advance. First, by focusing on uniform value-density settings, we prove that no online algorithm...
We consider online scheduling weighted packets with time constraints over a fading channel. Packets arrive at the transmitter in an online manner. Each packet has a value and a deadline by which it should be sent. The fade state of the channel determines the throughput obtained per unit of time and the channel's quality may change over time. In this paper, we design online algorithms to maximize weighted...
Motivated by the quality-of-service (QoS) buffer management problem, we consider online scheduling of packets with hard deadlines in a finite capacity queue. At any time, a queue can store at most b isin Z+ packets. Packets arrive over time. Each packet is associated with a non-negative value and an integer deadline. In each time step, only one packet is allowed to be sent. Our objective is to maximize...
We consider scheduling weighted packets with time constraints over a fading channel. Packets arrive in an online manner. Each packet has a value and a hard deadline by which it should be sent. The fade state of the channel determines the throughput obtained per unit of time and the channel's quality may change over time. In this paper, we design both offline and online algorithms to maximize weighted...
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