Road traffic simulation is a useful tool for studying road traffic and evaluating solutions to traffic problems. Large-scale agent-based road traffic simulation is computationally intensive, which triggers the need fo...
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Road traffic simulation is a useful tool for studying road traffic and evaluating solutions to traffic problems. Large-scale agent-based road traffic simulation is computationally intensive, which triggers the need for conducting parallel simulation. This paper deals with the synchronization problem in parallel agent-based road traffic simulation to reduce the overall simulation execution time. We aim to reduce synchronization operations by introducing some redundant computation to the simulation. There is a trade-off between the benefit of reduced synchronization operations and the overhead of redundant computation. The challenge is to minimize the total overhead of redundant computation and synchronization. First, to determine the amount of redundant computation, we proposed a way to define extended layers of partitions in the road network. The sizes of extended layers are determined by the behavior of agents and the topology of road networks. Second, due to the dynamic nature of road traffic, a heuristic was proposed to adjust the amount of redundant computation according to traffic conditions during simulation run-time to minimize the overall simulation execution time. The efficiency of the proposed method was investigated in a parallel agent-based road traffic simulator using real-world network and trip data. Results have shown that the method can reduce synchronization overhead and improve the overall performance of the parallel simulation significantly.
Existing works on task offloading in mobile edge computing (MEC) networks often assume a task is executed once at a single edge node (EN). Downloading the computed result from the EN back to the mobile user may suffer...
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Existing works on task offloading in mobile edge computing (MEC) networks often assume a task is executed once at a single edge node (EN). Downloading the computed result from the EN back to the mobile user may suffer long delay if the downlink channel experiences strong interference or deep fading. This paper exploits the idea of computation replication in MEC networks to speed up the downloading phase. computation replication allows each user to offload its task to multiple ENs for repetitive execution so as to create multiple copies of the computed result at different ENs which can then enable transmission cooperation and hence reduce the communication latency for result downloading. Yet, computation replication may also increase the communication latency for task uploading, despite the obvious increase in computation load. The main contribution of this work is to characterize asymptotically an order-optimal upload-download communication latency pair for a given computation load in a multi-user multi-server MEC network. Analysis shows when the computation load increases within a certain range, the downloading time decreases in an inversely proportional way if it is binary offloading or decreases linearly if it is partial offloading, both at the expense of linear increase in the uploading time.
With the development of wireless computing devices, extending distributed computing to wireless networks deserves a closer look. This paper considers distributed computing over unreliable and insecure device-to-device...
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With the development of wireless computing devices, extending distributed computing to wireless networks deserves a closer look. This paper considers distributed computing over unreliable and insecure device-to-device (D2D) networks, in which each device is not always available to perform computation. The process of distributed devices exchanging calculated results with each other is vulnerable to eavesdropping in wireless environments. To handle the unreliable devices, we adopt repetition codes to build a novel system that supports general computations, called rho-replication system, where each device has rho -1 replicas with duplicate data. A coded computation scheme for the $\rho $ -replication system is proposed, which not only achieves the minimum communication load of the system but also ensures weak security of wireless transmissions during data exchange. Furthermore, the replication nature of the system can be exploited for beamforming transmissions, naturally leading to the idea of energy optimization. Simulation results show that increasing rho does not necessarily improve energy efficiency, as the benefit of increased beamforming gain may be outweighed by the drawback of heavier communication load.
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