We study the throughput and delay scaling laws of the mobile cognitive network. There are n primary users and m secondary users in the primary network and the secondary network, respectively. They are distributed unif...
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We study the throughput and delay scaling laws of the mobile cognitive network. There are n primary users and m secondary users in the primary network and the secondary network, respectively. They are distributed uniformly and independently on the surface of a unit torus, moving according to the random way-point mobility model (RWMM). The primary users have priority to access the spectrum, and do not alter their protocol in the presence of the secondary network. The secondary users opportunistically use the licensed spectrum when it remains unused. Under the improved 2-hop relay policy, we derive the constant throughput of Θ ( 1 ) per primary source–destination (S–D) pair when the radius of the preservation region r p = Θ ( 1 / m ) . The expected delay scales as Θ ( n / v ( n ) ) , where v ( n ) is the average speed of the primary nodes. Moreover, if the secondary network is denser than the primary network, i.e., m = n γ with γ > 1 , the constant throughput of Θ ( 1 ) per secondary S–D pair and the expected delay of Θ ( m / v ( m ) ) can be derived surprisingly when the radius of the avoidance region r s = Θ ( 1 / n ) and r p = Θ ( 1 / m ) , where v ( m ) is the average speed of the secondary nodes.
Optimal assignment of a meta-task in heterogeneous computingsystems is NP-complete in the general case. Therefore, heuristic approaches must be employed to find good solutions within a reasonable time. We propose a n...
Optimal assignment of a meta-task in heterogeneous computingsystems is NP-complete in the general case. Therefore, heuristic approaches must be employed to find good solutions within a reasonable time. We propose a novel discrete particle swarm optimization (DPSO) algorithm for this problem. Firstly, to make particle swarm optimization algorithm more suitable for solving task assignment problems, particles are represented as integer vectors and a new position update method is developed based on discrete domain. Secondly, an effective variable neighborhood descent algorithm is applied to emphasize exploitation. In addition, migration mechanism is introduced with the hope to escape from possible local optimum and to balance the exploration and exploitation. Computational simulations and comparisons based on a set of benchmark instances indicate that the proposed DPSO algorithm is a viable approach for the task assignment problem.
Vehicle detection in SAR image is attractive field. High moments included numerous information is proposed to exploit in the field. It not only restrains Gaussian noise automatically, but also suppresses non-gaussian ...
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Vehicle detection in SAR image is attractive field. High moments included numerous information is proposed to exploit in the field. It not only restrains Gaussian noise automatically, but also suppresses non-gaussian noise. Man-made targets in are different from the background clutter. Moreover, the influence of the shadow about man-made targets is reduced in the algorithm of high moments. We utilize high moments to avoid to analyst the complex scatter theory. By analyzing the relevent theory and practical calculated method of high order moments, we compare the difference of probability of detection between the target chip and clutter chip to achieve the goal of detection. Through processing lots of actual SAR data which is added different kinds of noise, we compare the performance between high order moments and low-order moments method.
A short-term scheduling problem for crude oil operations is highly challenging. There lack efficient techniques and software tools for its solution. Our prior research shows that it may be solved in a hierarchical way...
A short-term scheduling problem for crude oil operations is highly challenging. There lack efficient techniques and software tools for its solution. Our prior research shows that it may be solved in a hierarchical way. At the upper level, we find a realizable refining schedule to optimize concerned objectives. At the lower level, a detailed schedule is obtained to realize it. This work attempts to present a three-stage method to solve the the upper level problem from a control perspective. The first stage solves a linear programming problem to determine the maximal production rate. The second one solves a transportation problem to optimally assign crude oil types and volume to the distillers. The last one adjusts and sequences oil parcels. Consequently, the proposed method is computationally efficient. An industrial case study is presented to show the result.
Some wafer fabrication processes are repeated processes, e.g. atomic layer deposition (ALD) process. For such processes, the wafers need to visit some processing modules for a number of times, which complicates the cy...
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Atomic layer deposition (ALD) is a typical process with wafer revisiting that should be performed by cluster tools. This paper discusses the scheduling problem of single-arm cluster tools for the ALD process. In sched...
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Atomic layer deposition (ALD) is a typical process with wafer revisiting that should be performed by cluster tools. This paper discusses the scheduling problem of single-arm cluster tools for the ALD process. In scheduling such system, the most difficult part is to schedule the revisiting process and obtain its optimal cycle time. This paper studies the revisiting process of ALD with revisiting times k = 3, 4, and 5. Analytical expressions are obtained to calculate the cycle time for the k possible schedules with k = 3, 4, and 5, respectively, so as to obtain the optimal one. In this way, the scheduling problem of such a revisiting process becomes simple and this is a significant improvement in scheduling cluster tools with wafer revisiting.
This paper proposes a novel adaptive interpolation filter (AIF) to reduce computational complexity and bit-rate of video coding. In the proposed AIF, the filter coefficients of B frames, which are predicted from those...
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ISBN:
(纸本)9781612847719
This paper proposes a novel adaptive interpolation filter (AIF) to reduce computational complexity and bit-rate of video coding. In the proposed AIF, the filter coefficients of B frames, which are predicted from those of adjacent P frames with a novel parabolic model, are unnecessary to transmit. Experimental results show that the coding complexity is reduced by 40.22% with no penalty on coding efficiency and 1.59% bit rate reduction is achieved at low bit-rate against conventional AIF.
Considering time hopping impulse radio ultra wide band (TH-IR UWB) sensor networks composed n sensor nodes which are placed according to a Poisson point process on a square and a Sink. The results demonstrate that the...
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Considering time hopping impulse radio ultra wide band (TH-IR UWB) sensor networks composed n sensor nodes which are placed according to a Poisson point process on a square and a Sink. The results demonstrate that the bounds on the lifetime of dense network increase with the increase of the number of nodes n, and that of extended network decrease with the increase of the number of nodes n. The results also indicate the bounds on the lifetime of clustering sensor networks is far more than that of non-clustering network, thus clustering can evidently improve network lifetime. Furthermore, the bounds on the lifetime of clustering TH-IR UWB sensor network which the nodes are distributed according to a Poisson point process are different from that of clustering network which the nodes are placed according to uniform distribution, thus the behavior of nodes deploying can remarkably affect the lifetime bound.
A Social network graph shows social interactions and relationships between individuals in a specific social environment, which is very helpful for analyzing social relationships, activities, structures, etc. The autho...
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The causes of stress and how it affects our behaviors are generally not well understood. The stress research usually requires a large amount of data to analyze possible stress-related factors. The data collection proc...
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ISBN:
(纸本)9781450309820
The causes of stress and how it affects our behaviors are generally not well understood. The stress research usually requires a large amount of data to analyze possible stress-related factors. The data collection process traditionally is time-consuming and cost-ineffective. To help medical researchers collect the stress information, we propose a tool named StressBar utilizing the powerful data collection capacity of smart phones. In this paper, we will show our design and implementation considerations of StressBar. Copyright 2011 ACM.
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