The mentioned dynamic network routing system is a method where the routers are dynamically controlled to reduce congestion. A counting algorithm counts the number of data packets in the network. The count of the numbe...
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The mentioned dynamic network routing system is a method where the routers are dynamically controlled to reduce congestion. A counting algorithm counts the number of data packets in the network. The count of the number of data packets is analyzed and is saved in a text file. Parallel processing logic is used to achieve the scheduling process at various routers where the network traffic is frequently subjected to congestion and time delays. The present scenario is then linked with parallel architecture. The basic of parallel processing architectures and different MPI commands were studied. scheduling algorithm is used to dynamically allocate time and different MPI functions are applied to synchronize the routers. Synchronization of the required routers is done with the help of MPI functions.
Desktop grids utilize idle computational resources within a research organization. Task scheduling is a very important issue for a desktop grid due to its significant impact on computational performance. In the paper ...
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ISBN:
(纸本)9781479952915
Desktop grids utilize idle computational resources within a research organization. Task scheduling is a very important issue for a desktop grid due to its significant impact on computational performance. In the paper we propose a game-theoretical model of task scheduling in a desktop grid. The model allows to consider the trade-off between the server load and the total time of computations. The numerical results based on a virtual drug screening project are presented, and the Nash equilibrium is found.
Load demand scheduling of electricity consumers is an effective way to alleviate the peak power demand on the electricity grid and to combat the mismatch between generation and consumption. In this paper, we consider ...
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ISBN:
(纸本)9781479964154
Load demand scheduling of electricity consumers is an effective way to alleviate the peak power demand on the electricity grid and to combat the mismatch between generation and consumption. In this paper, we consider a scenario where multiple users cooperate to perform load demand scheduling in order to minimize the electricity generation cost. With the help of a central controller in the grid, a globally optimal solution can be achieved. However, this centralized solution may not always be feasible since it requires a huge amount of communication and the grid may not be equipped with such a central controller at all. Therefore, we propose a distributed load demand scheduling algorithm where each end user schedules its own tasks based on the partial information provided by other users. Simulation results show that this distributed load demand scheduling is able to achieve near-optimal solutions that has very little performance degradation compared to the centralized method.
Cloud computing is continuously growing as a business model for hosting information and communication technology applications. Although on-demand resource consumption and faster deployment time make this model appeali...
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ISBN:
(纸本)9781467364300
Cloud computing is continuously growing as a business model for hosting information and communication technology applications. Although on-demand resource consumption and faster deployment time make this model appealing for the enterprise, other concerns arise regarding the quality of service offered by the cloud. One major concern is the high availability of applications hosted in the cloud. This paper demonstrates the tremendous effect that the placement strategy for virtual machines hosting applications has on the high availability of the services provided by these applications. In addition, a novel scheduling technique is presented that takes into consideration the interdependencies between applications components and other constraints such as communication delay tolerance and resource utilization. The problem is formulated as a linear programming multi-constraint optimization model. The evaluation results demonstrate that the proposed solution improves the availability of the scheduled components compared to OpenStack Nova scheduler.
With the help of simulation tools, users can evaluate new proposals in cluster environment efficiently. However, current cloud simulators cannot meet the needs of application-driven simulation scenarios. In this paper...
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ISBN:
(纸本)9781467365994
With the help of simulation tools, users can evaluate new proposals in cluster environment efficiently. However, current cloud simulators cannot meet the needs of application-driven simulation scenarios. In this paper, we propose Pallas, a task and network simulation framework that supports various cloud applications. Task-aware network scheduling and network-perceived task placement algorithms can be easily implemented in Pallas. We present the architecture and main components of Pallas and evaluate its effectiveness by comparing algorithm improvements to the actual results.
With the development of network communicationtechnology, combination between network and automotiveelectronics industry has more and more extensively. The mainpoints on performance evaluation for this kind of multi-fu...
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With the development of network communicationtechnology, combination between network and automotiveelectronics industry has more and more extensively. The mainpoints on performance evaluation for this kind of multi-functionnetwork are bandwidth, resource utilization, security andreliability. Through the analysis of automotive electronicsnetwork topology and characteristic information transmissionpattern, we found that it will encounter many problems withtraditional network combination. One of them is the multi-nodesproblem. When multi nodes start at the same time, the networkwill cause congestion in the start-up period during the operationprocess. It will lead to the stagnation of network and reduce thesystem stability and security and reliability. In this paper, inorder to solve above problem, we propose a node-basedresolution strategy ETBAC (Embedding Task-based AccessControl) Model. This is an access control policy modeling byusing the top priority method HLF (Highest-level-First) toschedule the nodes in the media-oriented system network. Weuse CANoe 2640N to establish our network environment, andour implementation experiences connect it with other nodes, and through its real-time monitoring to record the network boottime. Experiments in our test demonstrate that this strategy canavoid network congestion problems effectively and accelerateset-up time during network booting.
In order to support the rapid increase of mobile traffic, network densification in addition to utilization of high frequency spectrum such as millimeter-wave frequency bands are envisioned as key enablers. In such sit...
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In order to support the rapid increase of mobile traffic, network densification in addition to utilization of high frequency spectrum such as millimeter-wave frequency bands are envisioned as key enablers. In such situations, the amount of resources available to users increases. This paper investigates the resource selection scheme based on the proportional fair (PF) criteria. It is proved that two resources are selected for at most two users, and only one of the resources is selected for other users, which is determined by the average achievable data rate of three resources, when the number of resources M = 3. This indicates that only one out of three resources is assigned to most users to achieve PF criteria. Therefore, the proposed scheme can effectively reduce the amount of channel quality indicator (CQI) feedback required at the subsequent PF-based packet scheduling, since CQI in the one out of three resource is only required. Although the algorithm and its proof is only limited to M = 3, the proposed algorithm can be easily extended to general number of resources.
Massive machine-to-machine (M2M) communication terminals can cause great challenges in cellular network. One of the critical challenges is to reduce network congestion and control signaling overhead. Most of data type...
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ISBN:
(纸本)9781479973392
Massive machine-to-machine (M2M) communication terminals can cause great challenges in cellular network. One of the critical challenges is to reduce network congestion and control signaling overhead. Most of data types in M2M communication is periodic data, which enables M2M user repetitively access networks, and inevitably lead to network congestion and large control signaling overhead. In this paper, a novel radio resource scheduling scheme which relies on the novel resource multiplexing condition tree (MCT) structure is presented for the periodic cellular M2M communications. Also the resource planning and traffic shaping aspects of this scheduling algorithm are studied. Compared with several different resource scheduling schemes, numerical results show that the proposed MCT based resource scheduling scheme not only can greatly reduce the network access conflict and control signaling overhead, but also yield significantly more efficient time-frequency resource utilization.
Multipath routing gains clear network performance advantages for data streaming. The level of packet reordering, however, becomes higher: distant packets are reordered, the application performance is reduced due to he...
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ISBN:
(纸本)9781509002078
Multipath routing gains clear network performance advantages for data streaming. The level of packet reordering, however, becomes higher: distant packets are reordered, the application performance is reduced due to head-of-line blocking at the destination, and a large resequencing buffer is needed for sorting incoming packets. In this paper, we study the stochastic compensation effect to reduce packet reordering. If a source randomizes packet scheduling into multiple paths of random transmission delays, then these two sides of randomness "quench" each other. We perform simulation experiments to test this hypothesis in various multipath configurations and compare deterministic vs. Randomized scheduling. The experiments show the existence of the stochastic compensation effect and its considerable influence on the application performance.
The deep penetration of Online Social Networks (OSNs) has made them as major portals for video information sharing. Propagated through chains of friends, the coverage of OSN-shared videos can be much broader with stro...
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The deep penetration of Online Social Networks (OSNs) has made them as major portals for video information sharing. Propagated through chains of friends, the coverage of OSN-shared videos can be much broader with stronger micro- and macro-dynamics. Given that the contents are still hosted by external Video Sharing Sites (VSSes), such distinct access patterns from OSN users have created significant new challenges to VSSes. In this paper, we present SNACS, a cost-effective social network-aware cloud assistance for video sharing. The SNACS module sits between VSSes and an OSN, and is managed by the OSN to improve its users' video access experience using both centralized cloud resources and edge servers. Given the strong dynamics of the access patterns, we are particularly interested in the content management and update strategies in the SNACS' implementation. Motivated by real world data traces, we show that conventional cache replacement can be quite inefficient in this context. We then develop optimal offline algorithms with minimized cache misses and replacements, which also motivate an online solution that makes effective use of the video sharing patterns in the OSN. Our design has been extensively evaluated and its superiority has been validated under diverse network and user configurations.
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