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Proportional Fair Resource Allocation on an Energy Harvesting Downlink

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2013年第4期12卷 1699-1711页

作者： Tekbiyik, Neyre Girici, Tolga Uysal-Biyikoglu, Elif Leblebicioglu, Kemal Middle E Tech Univ Dept Elect & Elect Engn TR-06800 Ankara Turkey TOBB Econ & Technol Univ Dept Elect & Elect Engn TR-06560 Ankara Turkey

This paper considers the allocation of time slots in a frame, as well as power and rate to multiple receivers on an energy harvesting downlink. Energy arrival times that will occur within the frame are known at the beginning of the frame. The goal is to optimize throughput in a proportionally fair way, taking into account the inherent differences of channel quality among users. Analysis of structural characteristics of the problem reveals that it can be formulated as a biconvex optimization problem, and that it has multiple optima. Due to the biconvex nature of the problem, a Block Coordinate Descent (BCD) based optimization algorithm that converges to an optimal solution is presented. However, finding the optimal allocation with BCD entails a computational complexity that increases sharply in terms of the number of users or slots. Therefore, certain structural characteristics of the optimal power-time allocation policy are derived. Building on those, two simple and computationally scalable heuristics, PTF and ProNTO are proposed. Simulation results suggest that PTF and ProNTO can closely track the performance of BCD which achieves a good balance between total throughput and fairness.

关键词： Broadcast channel energy harvesting offline algorithms optimization block coordinate descent biconvex proportional fairness time sharing

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Optimal sensor scheduling for state estimation over lossy channel

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IET CONTROL THEORY AND APPLICATIONS 2015年第16期9卷 2458-2465页

作者： Sui, Tianju You, Keyou Fu, Minyue Zhejiang Univ Dept Control Sci & Engn Hangzhou 310013 Zhejiang Peoples R China Tsinghua Univ Dept Automat Beijing 100084 Peoples R China Univ Newcastle Sch Elect Engn & Comp Sci Callaghan NSW 2308 Australia

This study studies a sensor scheduling problem for the state estimation of a stochastic discrete-time system where the measurements are to be sent from multiple sensors to a centralised estimator through a lossy channel. By adopting a carrier sense multiple access/collision avoidance (CSMA/CA) protocol, the packet loss rate of the channel increases with the number of competing sensors for data communication. To increase the channel utilisation, it requires to smartly select informative sensors to transmit their measurements. Depending on the availability of the acknowledgment (ACK) messages from the estimator, both online and offline algorithms for scheduling sensor communication are proposed to optimise the expected performance of minimum mean-square error state estimator. Particularly, the online scheduling uses the ACK to trigger the sensor communication while the offline version adopts a random transmission framework and only decides the probability of sending measurements for each sensor in an offline manner. The optimal online scheduler is given by the solution of an integer programming, which is approximated by a practically solvable optimisation. Simulations are included to demonstrate the effectiveness of the proposed algorithms.

关键词： state estimation sensor fusion channel estimation stochastic systems discrete time systems carrier sense multiple access telecommunication scheduling least mean squares methods integer programming optimal sensor scheduling problem lossy channel estimation stochastic discrete-time system centralised estimator CSMA CA protocol packet loss rate data communication availability of the acknowledge messages ACK messages offline algorithms online algorithm sensor communication scheduling minimum mean-square error state estimator random transmission framework optimal online scheduler integer programming

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Deadline Scheduling in Energy Harvesting Networks: Competitive and Learning algorithms

Deadline Scheduling in Energy Harvesting Networks: Competiti...

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IEEE Global Communications Conference (IEEE GLOBECOM)

作者： Mlika, Zoubeir Driouch, Elmahdi Ajib, Wessam Univ Quebec Montreal Dept Comp Sci Montreal PQ Canada Univ Moncton Dept Comp Sci New Brunswick NB Canada

ISBN: (纸本)9781728109626

This paper considers the problem of maximizing the number of scheduled users that request to download data with deadlines from an energy-harvesting base station. This problem is solved based on two frameworks: online computation and online learning. In the first framework, an optimal offline and a deterministic competitive algorithms are designed. In the online learning framework, the multi-armed bandit approach is used to design a learning algorithm based on the well-known exponential-weight algorithm for exploration and exploitation. We bound its regret and show that it grows sub-linearly with time. Finally, we supplement our theoretical results by simulations to illustrate the performance of the proposed algorithms.

关键词： Scheduling offline algorithms competitive algorithms learning

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A Graph Theoretic Approach to Cache-Conscious Placement of Data for Direct Mapped Caches 10

A Graph Theoretic Approach to Cache-Conscious Placement of D...

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2010 International Symposium on Memory Management

作者： Beg, Mirza van Beek, Peter Univ Waterloo David R Cheriton Sch Comp Sci Waterloo ON N2L 3G1 Canada

ISBN: (纸本)9781450300544

Caches were designed to amortize the cost of memory accesses by moving copies of frequently accessed data closer to the processor. Over the years the increasing gap between processor speed and memory access latency has made the cache a bottleneck for program performance. Enhancing cache performance has been instrumental in speeding up programs. For this reason several hardware and software techniques have been proposed by researchers to optimize the cache for minimizing the number of misses. Among these are compile-time data placement techniques in memory which improve cache performance. For the purpose of this work, we concern ourselves with the problem of laying out data in memory given the sequence of accesses on a finite set of data objects such that cache-misses are minimized. The problem has been shown to be hard to solve optimally even if the sequence of data accesses is known at compile time. In this paper we show that given a direct-mapped cache, its size, and the data access sequence, it is possible to identify the instances where there are no conflict misses. We describe an algorithm that can assign the data to cache for minimal number of misses if there exists a way in which conflict misses can be avoided altogether. We also describe the implementation of a heuristic for assigning data to cache for instances where the size of the cache forces conflict misses. Experiments show that our technique results in a 30% reduction in the number of cache misses compared to the original assignment.

关键词： algorithms Measurement Performance offline algorithms Memory Management Cache Consciousness Cache Optimization Data Placement in Cache

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Data Sharing-Aware algorithms for Task Allocation in Edge Computing Systems 24

Data Sharing-Aware Algorithms for Task Allocation in Edge Co...

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24th IEEE/ACM International Symposium on Cluster, Cloud, and Internet Computing (CCGrid)

作者： Rabinia, Sanaz Grosu, Daniel Wayne State Univ Dept Comp Sci Detroit MI 48202 USA

ISBN: (纸本)9798350395679;9798350395662

Edge computing allows end-user devices to offload heavy computation to nearby edge servers for reduced latency, maximized profit, and/or minimized energy consumption. Data dependent tasks that analyze locally acquired sensing data are one of the most common candidates for task offloading in edge computing. Thus, the total latency and network load are affected by the total amount of data transferred from end-user devices to the selected edge servers. Most existing solutions for task allocation in edge computing do not consider that some user tasks may operate on the same data items. Making the task allocation algorithm aware of the existing data sharing characteristics of tasks can help reduce network load at a negligible profit loss by allocating more tasks sharing data on the same server. In this PhD thesis, we formulate the data sharing-aware task allocation problem that makes decisions on task allocation for maximized profit and minimized network load by considering the data-sharing characteristics of tasks. In addition, because the problem is NP-hard, we design and implement an offline algorithm, which finds a good feasible solution to the problem in polynomial time. We also design and implement online algorithms for task allocation in edge computing that take into account the sharing of data among the tasks offloaded to the same server. We analyze the performance of our offline algorithm against a state-of-the-art baseline that only maximizes profit. We also perform an extensive performance analysis by comparing our online algorithms with their sharing-oblivious counterparts.

关键词： Edge computing task allocation online algorithms offline algorithms data sharing

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Energy-Efficient algorithms for Flow Time Minimization

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ACM TRANSACTIONS ON algorithms 2007年第4期3卷 49–es页

作者： Albers, Susanne Fujiwara, Hiroshi Univ Freiburg Dept Comp Sci Georges Kohler Allee 79 D-79110 Freiburg Germany Kwansei Gakuin Univ Sch Sci & Technol Dept Informat Sanda 6691337 Japan

We study scheduling problems in battery-operated computing devices, aiming at schedules with low total energy consumption. While most of the previous work has focused on finding feasible schedules in deadline-based settings, in this article we are interested in schedules that guarantee good response times. More specifically, our goal is to schedule a sequence of jobs on a variable-speed processor so as to minimize the total cost consisting of the energy consumption and the total flow time of all jobs. We first show that when the amount of work, for any job, may take an arbitrary value, then no online algorithm can achieve a constant competitive ratio. Therefore, most of the article is concerned with unit-size jobs. We devise a deterministic constant competitive online algorithm and show that the offline problem can be solved in polynomial time.

关键词： Variable-speed processor flow time online algorithms competitive analysis offline algorithms dynamic programming

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