No Arabic abstract
We propose a simple channel-allocation method based on tug-of-war (TOW) dynamics, combined with the time scheduling based on nonlinear oscillator synchronization to efficiently use of the space (channel) and time resources in wireless communications. This study demonstrates that synchronization groups, where each node selects a different channel, are non-uniformly distributed in phase space such that every distance between groups is larger than the area of influence. New type of self-organized spatiotemporal patterns can be formed for resource allocation according to channel rewards.
P2P clusters like the Grid and PlanetLab enable in principle the same statistical multiplexing efficiency gains for computing as the Internet provides for networking. The key unsolved problem is resource allocation. Existing solutions are not economically efficient and require high latency to acquire resources. We designed and implemented Tycoon, a market based distributed resource allocation system based on an Auction Share scheduling algorithm. Preliminary results show that Tycoon achieves low latency and high fairness while providing incentives for truth-telling on the part of strategic users.
Artificial intelligence is one of the important technologies for industrial applications, but it requires a lot of computing resources and sensor data to support it. With the development of edge computing and the Internet of Things, artificial intelligence are playing an increasingly important role in the field of edge services. Therefore, how to make intelligent algorithms provide better services and the development of the Internet of Things has become an increasingly important topic. This paper focuses on the application of edge service distribution strategy, and proposes an edge service distribution strategy based on intelligent prediction, which reduces the bandwidth consumption of edge service providers and minimizes the cost of edge service providers. In addition, this article uses the real data provided by the Wangsu Technology Company and an improved long and short term memory prediction method to dynamically change the bandwidth, and achieves better optimization of resources allocation comparing with actual industrial applications.The simulation results show that our intelligent prediction can achieve good results, and the mechanism can achieve higher resource utilization.
Distributed clusters like the Grid and PlanetLab enable the same statistical multiplexing efficiency gains for computing as the Internet provides for networking. One major challenge is allocating resources in an economically efficient and low-latency way. A common solution is proportional share, where users each get resources in proportion to their pre-defined weight. However, this does not allow users to differentiate the value of their jobs. This leads to economic inefficiency. In contrast, systems that require reservations impose a high latency (typically minutes to hours) to acquire resources. We present Tycoon, a market based distributed resource allocation system based on proportional share. The key advantages of Tycoon are that it allows users to differentiate the value of their jobs, its resource acquisition latency is limited only by communication delays, and it imposes no manual bidding overhead on users. We present experimental results using a prototype implementation of our design.
We simulate a tug-of-war (TOW) scenario for a model double-stranded DNA threading through a double nanopore (DNP) system. The DNA, simultaneously captured at both pores is subject to two equal and opposite forces $-vec{f}_L= vec{f}_R$ (TOW), where $vec{f}_L$ and $vec{f}_R$ are the forces applied to the left and the right pore respectively. Even though the net force on the DNA polymer $Delta vec{f}_{LR}=vec{f}_L+ vec{f}_R=0$, the mean first passage time (MFPT) $langle tau rangle$ depends on the magnitude of the TOW forces $ left | f_L right | = left |f_R right | = f_{LR}$. We qualitatively explain this dependence of $langle tau rangle$ on $f_{LR}$ from the known results for the single-pore translocation of a triblock copolymer. We demonstrate that the time of flight (TOF) of a monomer with index $m$ ($langle tau_{LR}(m) rangle$) from one pore to the other exhibits quasi-periodic structure commensurate with the distance between the pores $d_{LR}$. Finally, we study the case $Delta vec{f}_{LR}=vec{f}_L+ vec{f}_R e 0$, and qualitatively reproduce the experimental result of the dependence of the MFPT on $Deltavec{f}_{LR}$. For a moderate bias, the MFPT for the DNP system for a chain length $N$ follows the same scaling ansatz as that of for the single nanopore, $langle tau rangle = left( AN^{1+ u} + eta_{pore}N right) left(Delta f_{LR}right)^{-1}$, where $eta_{pore}$ is the pore friction, which enables us to estimate $langle tau rangle $ for a long chain. Our Brownian dynamics simulation studies provide fundamental insights and valuable information about the details of the translocation speed obtained from $langle tau_{LR}(m) rangle$, and accuracy of the translation of the data obtained in the time-domain to units of genomic distances.
Web applications frequently leverage resources made available by remote web servers. As resources are created, updated, deleted, or moved, these applications face challenges to remain in lockstep with the servers change dynamics. Several approaches exist to help meet this challenge for use cases where good enough synchronization is acceptable. But when strict resource coverage or low synchronization latency is required, commonly accepted Web-based solutions remain elusive. This paper details characteristics of an approach that aims at decreasing synchronization latency while maintaining desired levels of accuracy. The approach builds on pushing change notifications and pulling changed resources and it is explored with an experiment based on a DBpedia Live instance.